sha256 stringlengths 64 64 | language stringclasses 28
values | size int32 1 491k | lines int32 1 23.2k | content stringlengths 1 200k |
|---|---|---|---|---|
c755b3accfe155c6da2c6ec896f144a95fc2bfe0ff74db01e1557132fbb03779 | Python | 5,769 | 162 | # 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... |
f1af240169a0249894000b875574a20764d3f3f7251965fc74d6a025b6462e1c | Python | 5,769 | 117 | # * currently consider directly read the CG original files (organized as the original generation form from MARTINI) *
import os
import logging
import warnings
from tqdm import tqdm
from torchdrug import data, utils
from torchdrug.core import Registry as R
from cg_steps import cg_protein
logger = logging.getLo... |
2d08b3abc198f3f5d6373629ebd9f275e154a22af4659ea433596a3f3669886a | Python | 5,770 | 162 | from collections.abc import Iterator
from typing import Generic, TypeVar
from .graph import Graph
T = TypeVar("T")
TP = TypeVar("TP")
class State(Generic[T, TP]):
def __init__(self, graph: Graph[T]) -> None:
self.order: dict[T, int] = {n: i for i, n in enumerate(graph.successors.keys())}
self.or... |
a094404ff83ed59970a9d4848f174f587db0ef2468c57664cbfce5e9f7bcd951 | Python | 5,771 | 177 | """
Script for drawing GraphMCF instances as graphs
Input: - File with a GraphMCF (.pkl)
Output: - Output view (interactive window or .pdf file)
"""
__author__ = 'Antonio Martinez-Sanchez'
# ################ Package import
import sys
import time
import getopt
from graph import GraphGT
from globals ... |
770a8fa00ae75bbe8443244ed3aa5b783131d58fb6322f6128e54a20a4b43562 | Python | 5,772 | 144 | import matplotlib.pyplot as plt
import os
from constants import ABSOLUTE_ERROR
from src.analyze.utils import init_mpl
from src.dataloaders.semantic_transforms_dataset import TF_BRIGHTNESS, TF_PERSPECTIVE, TF_CONTRAST, TF_ROTATION
colors = init_mpl(sns_style='ticks', colorpalette='muted')
_CSV_PATTERN_ROT = "rotatio... |
74d13861c4c6d57b56cb2110183ad5011470b7e68c0549809b8046e9818b30ab | Python | 5,773 | 158 | #!/usr/bin/env python2
from __future__ import print_function
import sys
import os
import json
import stat
import argparse
import subprocess
import datetime
import re
import glob
import csv
import warnings
def main():
epilogstr = 'Examples:\n.../runpostproc.py /path/to/rootdir --prmfiles prmfile1.mat#prmfile2.mat... |
a1c7a4f1fc9f800c6a7ce8dd25308ad3afa80f68fb3da0cf39d3a79fe004de15 | Python | 5,773 | 162 | """
Pre-process PyTo segmentation of the pre-synaptic vesicle.
Each vesicle is cropped in a sub-volume, also membrane segmentations for PySeg application are generated
Input: - Reference tomogram
- Segmentation tomogram
Output: - A set of subvolumes with the original density map, segment... |
d15c085988d797408c48b4d29681eb4a22381afb8411bf7bd37c68b71a60d311 | Python | 5,775 | 149 | #
# 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,... |
ca9813aaa2b02d3746bbf518f748c92806615fdf150ce52e100df27de2017f7e | Python | 5,776 | 198 | from collections import namedtuple
import logging
import warnings
from typing import List, Sequence
import numpy as np
import pytorch_lightning as pl
import rich.syntax
import rich.tree
from omegaconf import DictConfig, OmegaConf
from pytorch_lightning.utilities import rank_zero_only
from pytorch_lightning.loggers.l... |
80c68b7be555c02de459940437032d8583315e8d615ea8800c45092b661ca531 | Python | 5,777 | 170 | import bct
import numpy as np
from tqdm import tqdm
from sklearn.utils import check_random_state
def strength_preserving_rand_sa_reheat_trajectory(A, rewiring_iter = 10,
nstage = 100, niter = 10000,
temp = 1000, frac ... |
65aa9295c70ec87bc5bcae86be7a57add6895567d43df77732576864343409aa | Python | 5,778 | 154 | """Interface class for dimensions."""
from __future__ import annotations
from dataclasses import asdict, dataclass, field
from typing import TYPE_CHECKING, Any
if TYPE_CHECKING:
from collections.abc import Callable, Iterable
from typing import Self
def _dict_factory(items: Iterable[tuple[str, Any]]) -> dict[... |
8ef4edea22a6bfe66a963dd3c95d129c3bc8fd7b074fa20857da40ef720a5ded | Python | 5,779 | 215 | #!/usr/bin/env python
# coding: utf-8
# ### Neural network hidden layer size experiments, per gene
#
# We want to see whether smaller models (i.e. models with smaller hidden layer sizes) tend to generalize to new cancer types better than larger ones; this script compares/visualizes those results.
# In[1]:
import o... |
d8f2907e8d1bb2a44bcd56addff2c286b1e9c1a320ebc9c147e6018e2b4848e6 | Python | 5,780 | 98 | #! /usr/bin/env python
# -*- coding: utf-8 -*-
from downward import suites
from lab.reports import Attribute, gm
from downward.reports.compare import CompareConfigsReport
from common_setup import IssueConfig, IssueExperiment
import os
def main(revisions=None):
suite = suites.suite_optimal_with_ipc11()
conf... |
3524962b44524b2cfac2f78213f22417914a59729baf52ca7f5aa38f433e99e7 | Python | 5,782 | 180 | # Node-group asset "Periodic Box" (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_CHECKING
... |
3c7572261737093d47530e7c497270de7132c02b0d3dc1e60959a1588cef8d2d | Python | 5,783 | 190 | # Node-group asset "Nucleic Dihedral" (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_CHECK... |
76ed6d29c26e8eae34dc072df7b71060e843881895cbdcb97f222b5dcefaa078 | Python | 5,784 | 197 | #!/usr/bin/env python
"""
Reads a labels file containing discs and writes another labels file with the
discs extending to balls having same centers and radii as the discs.
This script may be placed anywhere in the directory tree.
ToDo:
- see about excentricity
$Id$
Author: Vladan Lucic (Max Planck Institute for Bi... |
dadfbaff4d2b55765ecef9031a25abe622fa97f72552ee7ab248a7acc92a01ae | Python | 5,785 | 152 | from dreamcoder.program import *
class TowerState:
def __init__(self, hand=0, orientation=1, history=None):
# List of (State|Block)
self.history = history
self.hand = hand
self.orientation = orientation
def __str__(self): return f"S(h={self.hand},o={self.orientation})"
def ... |
303d95564910bea37a98412712533bf5e733b92abdffc37232118374e0796e94 | Python | 5,786 | 170 | import numpy as np
from elasticai.creator.file_generation.savable import Path
from elasticai.creator.file_generation.template import (
InProjectTemplate,
module_to_package,
)
from elasticai.creator.nn.integer.math_operations import get_padded_count
from elasticai.creator.nn.integer.ram.design import Ram
from e... |
8742ae4117993d4a25ba8bd78f074b6ecd9dd1c7d6c4b38820622097ddcfe898 | Python | 5,786 | 138 | """Cell points land on the anatomy in the input pane, for every 2D-ish input type.
Two defects this pins:
1. Scale. ``load_preview_array`` strides the section down to <= 256 px in-plane,
but the tab handed the panel point coords at ORIGINAL resolution - so on a
6000x8000 section (stride 32) nearly every ... |
18e6c113cd62ffa20200f50d6201d3a7e8f84a79195c17fdeef83c66cef34e8d | Python | 5,787 | 101 | """Steering diagnostics: numerics, step alignment and zero effect on inference (tiny random weights)."""
import json
import math
from threading import Event
import numpy as np
import pytest
import torch
from conftest import assert_no_hooks
from liquidaion_fly.observatory_engine import ChatSession
from liquidaion_fly.... |
33c89baff8613620102420bd89fa031d11fc1249848990d1519f7421283abdf0 | Python | 5,788 | 187 | # 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... |
9647390c470946f99b3b0741d1bb951eaef6a6b6970a778c7b46521c331681a8 | Python | 5,788 | 118 | # * currently consider directly read the CG original files (organized as the original generation form from MARTINI) *
import os
import logging
import warnings
from tqdm import tqdm
from torchdrug import data, utils
from torchdrug.core import Registry as R
from cg_steps_energy_injection import cg_protein
log... |
2aa9a954cabac9fbea2c6190502a15bdb9fac03d998b28c56709238bbf14a7f5 | Python | 5,789 | 134 | import numpy as np
import pytest
from SurvivalEVAL.nonparametric_estimator.competing_risks import (
AalenJohansenCompetingRisks,
)
from SurvivalEVAL.nonparametric_estimator.multi_state import AalenJohansenMultiState
def test_multistate_product_with_return_transitions():
transitions = np.zeros((2, 3, 3))
... |
7f950212cc97b704ef7fcdf8408949c210df87aff9311ff3edd3f350603bd6f7 | Python | 5,789 | 132 | import os
import numpy as np
import cv2
import pandas as pd
from annotation_module import process_video_folder # Import the function from the previous script
def read_last_annotations(csv_path, image_shape):
df = pd.read_csv(csv_path)
print("Column names in the CSV file:", df.columns) # Print column ... |
bdabd4c5d46124d328c9b983a488125e173ddbce3d4bbb0345cc55e138bec272 | Python | 5,790 | 196 | #
# Configuration dataclasses for ACME
#
# Copyright © 2026 Ernst Strüngmann Institute (ESI) of the Max Planck Society
#
# SPDX-License-Identifier: BSD-3-Clause
#
# Builtin/3rd party package imports
import logging
from dask.distributed import Client
from dataclasses import dataclass, field
from typing import Optional,... |
0185dcd11fd474f87235cd91c8403b6c2136076c1bea9ea87f4994051349aa33 | Python | 5,791 | 126 | ##########################################################################################
# This Script
# 1) imports the blocks based on the condition name in EEGLAB form from the BIDS directory
# 2) removes the stimulus artifact iv: -1.5 to 6 ms, for ESG use -7 to 7ms - linear interpolat... |
b4209b31ebb8eb1c83704fbef701cf6159649aa6e0051d1524501fdbae429dd7 | Python | 5,792 | 157 | from __future__ import annotations
import threading
import time
from concurrent.futures import ThreadPoolExecutor
from functools import partial
from typing import TYPE_CHECKING, Literal
import pandas as pd
from pertpy._types import cast_frame
from ._look_up import LookUp
from ._metadata import MetaData
if TYPE_CHE... |
503c9afe89efb9e3db29077968134448b634bebc18013b198591e211c07e8c33 | Python | 5,793 | 135 | #! /usr/bin/python
import argparse
import os
def _read_one_mod_freq_file(freqfile):
freqinfo = {}
with open(freqfile, "r") as rf:
for line in rf:
words = line.strip().split("\t")
m_key = (words[0], int(words[1]), words[2])
pos_in_strand = int(words[3])
... |
6a057179e11f5bd448365b389b7a74a820c1a974f8b34521840fa0596b886513 | Python | 5,793 | 192 | # 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... |
bcc1029b163340406074e0f64da3c0e9c151816187c4eb7d1f2480a3cb769647 | Python | 5,793 | 199 | # 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... |
5245387cf0afbf39299c544ad7bef5b670a0b717a8eb8408702b1d798b93e1c8 | Python | 5,794 | 229 | #! /usr/bin/python
# -*- coding: utf-8 -*-
import tensorflow as tf
from tensorflow.python.util.deprecation import deprecated
__all__ = [
'identity',
'ramp',
'leaky_relu',
'swish',
'sign',
'pixel_wise_softmax',
'linear',
'lrelu',
]
@deprecated("2018-06-30", "This API will be deprecate... |
b63637893bac0504f809ad8dfe5e243b0cfc9158b764fe658551633113a68a85 | Python | 5,794 | 122 | """
HEMIBRAIN_CONF_CONFOUND.py
Open item 4 in NOW.md section 7:
"The hemibrain conf column. Is the undetermined set just low-confidence T-bars?"
hemibrain-v1.2-tbar-neurotransmitters.feather carries a per-T-bar detection
confidence `conf`. If the within-neuron transmitter heterogeneity that drives the
effective-sam... |
bad3aa63bdfce45f83e2c6c09d99ba13d9620477445b63122f35eaf324d16115 | Python | 5,794 | 168 | ''' Modified by Mayank Kabra
From LEAP https://github.com/talmo/leap by Talmo Pereira
'''
import cv2
import numpy as np
import keras
from keras.utils import Sequence
import PoseTools
import easydict
def transform_imgs(X, theta=(-180,180), scale=1.0):
""" Transforms sets of images with the same random transformatio... |
334ef22943abac13f5e380550db58d2d69629931cd13bb35b7cb097213df4dcb | Python | 5,795 | 172 | import argparse
import pickle
from collections import Counter
class TorchVocab(object):
"""
:property freqs: collections.Counter
:property stoi: collections.defaultdict, string → id
:property itos: collections.defaultdict, id → string
"""
def __init__(self, counter, max_size=None, min_freq=1, ... |
3058d35161456905504df19ae0e946f701a46f28ee1887b22c150c6778d1fc52 | Python | 5,796 | 130 | import sys
import unittest
from unittest.mock import patch
import pandas as pd
import os
import sys
sys.path.append(os.path.dirname(os.path.realpath(__file__)) + "/../../src")
sys.path.append(os.path.dirname(os.path.realpath(__file__)) + "/../../scripts")
from predict import args, predict
class TestPredict(unittest.Te... |
ed0926d82150c9fa98522f97e6367313cd38761481beb229581db3c9c5febf5c | Python | 5,796 | 166 | # Write the benchmarking functions here.
# See "Writing benchmarks" in the asv docs for more information.
# http://asv.readthedocs.io/en/latest/writing_benchmarks.html
import autograd.numpy as np
from autograd import grad
class RNNSuite:
"""
Checking speed on a vanilla RNN.
"""
# NOTE: this is run ea... |
04b3e9abd1f6e4404713a2f408f1a891ee61fa8d6bd6f105314c4a1c3159ced1 | Python | 5,797 | 166 | #!/usr/bin/env python
# Copyright (c) 2020 Intel Corporation
#
# This work is licensed under the terms of the MIT license.
# For a copy, see <https://opensource.org/licenses/MIT>.
"""
This module provides a weather class and py_trees behavior
to simulate weather in CARLA according to the astronomic
behavior of the su... |
4e70d699fffe218a3b9eb88ecdfe92febee3a5aef86a675b2a21f0174b7da0b5 | Python | 5,797 | 203 | #
# 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,... |
d7e50bbb5f69a2beb562449b1c7ac56c2924bd308a079828f721f0478eaa1364 | Python | 5,797 | 162 | import json
import os
from glob import glob
from lxml import etree as ET
import cv2
from stitcher import stitch_slide, compute_overlap_percent
import sys
def get_pixel_size(slide_path, default_pixel_size=1.85, default_tube_lens_mm=50.0, default_objective_tube_lens_mm=180.0, default_magnification=20.0):
parameter_p... |
03371a4aef17d16129d962617ed5da506e1fa0ff03738438974bd82a3dcab460 | Python | 5,799 | 163 | #!/usr/bin/env python3
# -*- coding: utf-8 -*-
''' Script to do stats on ROI data '''
# Append path
proj_name = 'MINDLAB2020_MEG-AuditoryPatternRecognition'
wdir = '/projects/' + proj_name + '/scratch/working_memory/'
scripts_dir = '/projects/' + proj_name + '/scripts/working_memory/'
import sys
sys.path.append(scrip... |
79d64a193493624b48c61eccdbb872cf769aff856a3195525e0b3a32e68880bf | Python | 5,799 | 174 | # 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... |
ab3d431529c522f0fdb60e10669e5877493287b9f8a26ed10831e76d2efa54b8 | Python | 5,799 | 136 | # set QT_API environment variable
import os
os.environ["QT_API"] = "pyqt5"
import qtpy
from pathlib import Path
# qt libraries
from qtpy.QtCore import *
from qtpy.QtWidgets import *
from qtpy.QtGui import *
# app specific libraries
import control.widgets as widgets
import control.camera as camera
import control.core... |
d9ae41c2e51ded2ab8e617c0930709d5e6c456215fb7d7d6e3f91764a7761601 | Python | 5,799 | 148 | """Tests for the TissueCyte base-reorientation option in the 2D registration path.
Covers: the CLI flag round-trip, the param threading across the three layers,
and the behavioural effect (the transpose swaps the moving's H<->W) in
_load_and_orient_2d. GUI dialog wiring is checked under a QApplication.
"""
imp... |
53db0efb5b9b7ce56e824ecdc44539f19b1d293f5e8ece4b32fedf2396875872 | Python | 5,802 | 163 | # Manuel A. Morales (mmoraleq@bidmc.harvard.edu)
# Beth Israel Deaconess Medical Center
# Harvard Medical School
import time
import matplotlib.pyplot as plt
import torch.nn.parallel
import torch.optim
import torch.utils.data
import torch.utils.data.distributed
import torch.fft
import numpy as np
from Config import *... |
7fdf4812becb36ae1cf21da087a5e7f9407100d02e880c27e265d430cf390e85 | Python | 5,803 | 165 | ###
# This file will:
# 1. Generate and save Alexnet features in a given folder
# 2. preprocess Alexnet features using PCA and save them in another folder
###
import glob
import torch
import InternVideo
import numpy as np
import urllib
import torch
import cv2
import argparse
import time
import random
fro... |
2ca62ac25d0b733d88eb98f1f6d12d9d47965adf00c708cb0b134c74ca1927ce | Python | 5,804 | 156 | # 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... |
be307aeec7a0dd24bc8daf04e3780ce31996a309164fd6af57adbb5feb92b73a | Python | 5,804 | 133 | import sys
import traceback
from joblib import Parallel, delayed
import pandas as pd
import csv
import os
import ray
ray.init(num_cpus=16)
from src.utils import logger, parse_config, SegmentationVideo, Canvas, contain_substr
def plot_appear_features(args, run, tag):
# FPS is used to visualize, should be inferre... |
2370b1280c961abaa5cd5417a5626d40b87884e9e0da47c9b736d1fea537aedb | Python | 5,805 | 178 | from __future__ import annotations
from functools import cached_property
import pandas as pd
from cuppa.misc.utils import check_required_columns
from cuppa.logger import LoggerMixin
class SampleMetadata(pd.DataFrame, LoggerMixin):
def __init__(self, df: pd.DataFrame, *args, **kwargs):
super().__init__(... |
b1ac2fac8498b44f3d465fc0120ecf5d7419a83644166df7cb99e5931611ecfa | Python | 5,807 | 146 | # Code adapted from the appyter-catalog github repository (https://github.com/MaayanLab/appyter-catalog/tree/main),
# distributed under an Attribution-NonCommercial-ShareAlike 4.0 International license.
# Librairies
import os
import sys
code_path = os.path.split(os.path.split(os.getcwd())[0])[0]
sys.path.append(code_p... |
fbe7274c5578b251d9d7a78be02dfb592c1e865f2942784d29be6632f52250b9 | Python | 5,808 | 118 | """The foreground the 2D pipeline initialises from must not depend on working resolution.
``foreground_init`` reduces a mask to two scalars - foreground area and centroid - and applies
them as ANTs spacing and origin, so a mask that changes with the sampling grid corrupts the
initialisation rather than merely look... |
b061ed35ea9ab511a23cf48f9add6955fb3512d99907de1b78a77f69a66ec904 | Python | 5,809 | 193 | """Module to show video, if the file format supports it.
"""
from logging import getLogger
from platform import system
from PyQt5.QtCore import QTimer
from PyQt5.QtWidgets import (QFrame,
QGroupBox,
QPushButton,
QVBoxLayout,
... |
0bda4eaeed454150d23db93d6bb29c54a8dd7d55db715212b2e34df7fd2b2c2c | Python | 5,811 | 110 | from typing import List
import torch
import torch.nn as nn
from .mmd_like import _MMDLikeTrainer
def _maximum_mean_discrepancy_linear(x_source, x_target):
delta = x_source - x_target
loss = torch.mean(torch.mm(delta, torch.transpose(delta, 0, 1)))
return loss
class DDCTrainer(_MMDLikeTrainer):
r''... |
6f83f3f15f7733a3ffe58487e5f919e243e5995f5f3ca36d4982b6cc9a66223e | Python | 5,811 | 189 | from numpy import arange
from numpy.random import seed
from numpy.testing import assert_array_equal, assert_array_almost_equal
from pytest import approx, raises
from wonambi import Dataset
from wonambi.attr import Annotations
from wonambi.utils import create_data
from wonambi.trans import select, resample, frequency, ... |
c2112adf88f98b1480bf255f21361d21680c962bc6c82943694548de2d9fa965 | Python | 5,811 | 199 | from collections.abc import Callable, Iterator
from typing import Protocol, cast, overload
import pytest
from elasticai.creator.function_dispatch import (
KeyedDispatcherDescriptor,
KeyedDispatcherWithRegistrars,
create_keyed_dispatch,
dispatch_method,
registrar_method,
)
def test_can_register_n... |
dc56d79b64827074a9835ffd6680a555d44759de7c78989fb7362f10018bf474 | Python | 5,811 | 210 | import numpy as np
import graph_tool.all as gt
from scipy.sparse.linalg import spsolve
def get_sorted_label(u, msfa):
fu = u.copy()
mfas_filter = fu.new_edge_property('bool')
mfas_filter.a = msfa
fu.set_edge_filter(mfas_filter)
sort = gt.topological_sort(fu)
return sort
def get_sort... |
9ffdc92fe23a253624eb63e4d30db83a3994f751142011dfab33b6546de81d5b | Python | 5,812 | 167 | from torch import nn
from torch.nn import functional as F
from torchdrug import layers
class ProteinResNetBlock(nn.Module):
"""
Convolutional block with residual connection from `Deep Residual Learning for Image Recognition`_.
.. _Deep Residual Learning for Image Recognition:
https://arxiv.org/p... |
f034031e5f706fd11683034e669456fa408d340e8e0553b197a9ced6f8c69a10 | Python | 5,812 | 183 | from __future__ import annotations
import os
from pathlib import Path
import pytest
from ase.build import bulk
from ase.calculators.emt import EMT
from quacc import change_settings, get_settings
from quacc.runners.prep import calc_cleanup, calc_setup, terminate
def make_files():
with open("file1.txt", "w") as ... |
fd6704966dc30df9a44b6765f9bc6684302fbf83b528a1e80083a902fc0676d8 | Python | 5,812 | 197 | # 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... |
5a95a5a605e131b9c826e18c7206e81c6cfefbb61ec9b961b443529e6812764a | Python | 5,815 | 138 | import math
import numpy as np
import torch
import torch.nn as nn
import torch.optim as optim
from typing import Any, Dict, Optional
from models.model import Model
class M2DCNN_Net(nn.Module):
@staticmethod
def weight_init(m):
# [All the trainable parameters in our CNN should be initialized to
... |
a161cf84b76cabeb279590cc6b0d9db25702033e6ddb14818d5f02e27fca4bec | Python | 5,816 | 110 | """Shared threshold helpers for tissue/background masking.
Two consumers derive a tissue threshold from intensity and must not drift apart: the 2D
registration foreground (``registration_2d._clean_foreground_mask``) and the standalone
tissue-masking tool (``tissue_masking.core.masking.compute_tissue_mask``). They ... |
1e5e86f1253c1fe7ea62ec0aebe97c76eccddcc2f69111ea6bc684453cf3f647 | Python | 5,817 | 118 | '''
Script to create a table of results
'''
import pandas as pd
import db
import os
from scipy import stats
from sklearn.metrics import mean_squared_error
from collections import defaultdict
DATABASE = db.setup('PATH_TO_DATABASE')
ROOT = 'PATH_TO_ROOT'
VARIATIONS = ['random', 'compounds', 'kinases']
for VARIATION in... |
84a6a48f157192400ee7e391be3c22b7b7d4c94ce2564fb8e6fbdb24660447e0 | Python | 5,817 | 179 | import numpy as np
from numba import njit
@njit(nogil=True)
def _calc_mean_shrunken_residuals(
data_chrom,
indices_chrom,
indptr_chrom,
start,
end,
smoothed_vals,
n_cells,
chrom_len,
shrinkage_factor=1,
):
shrunken_resid = np.full(n_cells, np.nan)
if start > chrom_len:
... |
15b04d9a350463d0ae9041331563b71a6436f3714638067c131ff220d6a1ad5d | Python | 5,819 | 136 | import numpy as np
import pandas as pd
import vireoSNP
def load_ground_truth(n_mut, af_pct, size=None, tree=None):
if size is None and tree is None:
ground = pd.read_csv('data/' + str(n_mut) + '_clonal_variants_fixedAF' + str(af_pct) + 'pct/clonal_var.csv')
elif tree is not None:
ground = pd.re... |
501df7551beaafb576a143c3f521b47fa3664d7f362ee9b4364fa4c9110bfa0a | Python | 5,820 | 164 | import torch
import torch.nn as nn
import torch.nn.functional as F
from ..initializer import create_initializer
class BottleneckBlock(nn.Module):
expansion = 4
def __init__(self, in_channels, out_channels, stride, stage_index,
base_channels, cardinality):
super().__init__()
... |
d69ba8cb6a7330abab1dd8a0c65a7a937bd1551f624a255c21c3b325c4ea45aa | Python | 5,820 | 191 | """
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 os
import pathlib
from argparse import ArgumentParser
import pytorch_lightning as pl
from fastmri.data.mri_data import fetch_dir
fro... |
fac90ed9f81807ca772a0fff1b6d1e1386a41e5ee27f5919b243a9a358b1c723 | Python | 5,820 | 180 | """Column name constants for the DataFrame representation of HED schemas."""
from hed.schema.hed_schema_constants import HedSectionKey
KEY_COLUMN_NAME = "rdfs.label"
# Known tsv format suffixes
STRUCT_KEY = "Structure"
TAG_KEY = "Tag"
UNIT_KEY = "Unit"
UNIT_CLASS_KEY = "UnitClass"
UNIT_MODIFIER_KEY = "UnitModifier"
... |
6c34e822d42e288c94a9e2446412bb7f06ef72f7c4c64500eef958d0f3100db9 | Python | 5,821 | 137 | #!/usr/bin/env python
# -*- coding: utf-8 -*-
"""
"""
import os
import warnings
import numpy as np
import SFC_backprop
def restore_weights(datadir=os.path.join(".", "saved_weights"), index=0):
files = os.listdir(datadir)
files = [f for f in files if 'final_weights' in f]
files = np.flip(np.sort(files)... |
8d4aedf9718c40135620d9e6631ef284887a231fc2360936044d9b94e28bb8ad | Python | 5,821 | 166 | import numpy as np
from scipy.ndimage.interpolation import map_coordinates
from scipy.ndimage.filters import gaussian_filter
from cv2 import imwrite
import csv
from cv2 import imread
import os
from imutils import rotate_bound
from skimage import transform, filters
from helpers import *
import time
from config import DA... |
3f14b53591c8bb2420ba427302e4c06b37851eb4750a10eae608b4e6858a2ad4 | Python | 5,822 | 144 | """First-launch welcome dialog for the CCF Boundary Editor.
The editor used to present a blank canvas on first launch with no
guidance, leaving the user to discover the Atlas picker, region
activation, brush controls, multi-region delete, and shortcut overlay
on their own. :class:`WelcomeDialog` is a single-scree... |
5aaa8c8c356eb652820acd8ad2cab499dbffed3dc3a30e151489f7bc13377b43 | Python | 5,822 | 170 | #!/usr/bin/env python
#
# Copyright 2009, Google Inc.
# All rights reserved.
#
# Redistribution and use in source and binary forms, with or without
# modification, are permitted provided that the following conditions are
# met:
#
# * Redistributions of source code must retain the above copyright
# notice, this list... |
bfd01a19dbe56778c9f54c80db7f673185e57370c2f4128409c606308119134a | Python | 5,822 | 141 | # 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... |
f7de006bfb32639f134aa616350d74792b75c56a13ffbf9e1f6bf5461f251d8e | Python | 5,822 | 166 | from __future__ import annotations
# module use /cm/shared/ex3-modules/202309a/defq/modulefiles
# module load python-fenics-dolfin-2019.2.0.dev0
# . ~/local/src/smart-comp-sci/venv/bin/activate
from pathlib import Path
import pandas as pd
import json
from typing import NamedTuple, Any
from itertools import cycle
import... |
fa7dc7c3758d2e7ed405ea951071bfdc08be7f6e1ee8f5627c9a5f7cad1e07aa | Python | 5,822 | 114 | """
Python implementation of EPI registration
"""
import os
import sys
import numpy as np
import fsl.wrappers as fsl
from oxasl import struc
def epi_reg(wsp, epi_img, use_fmap=False, **kwargs):
"""
Do EPI registration
"""
struc.segment(wsp)
wmseg = wsp.structural.wm_seg
bbr_sch = os.path.joi... |
18bd69beb0c04372f3b48d74607a10928c1bb44a32c4b133f262a0d2f1feae77 | Python | 5,823 | 139 | """Per-section tissue masks for the tissue-masked vignetting-correction mode.
A section's raw tiles are laid on a clean, non-overlapping grid (a "montage")
and segmented once with the project's seeded Multi-Otsu-4 GrabCut. Because the
montage is non-overlapping and warp-free, each tile's mask block crops straight... |
0f74f88c4ac714c534ae68ac7ba4533c099ae3063a9e99eb622d5422cd56137f | Python | 5,824 | 136 | import argparse
from splitters import random_split, species_split
from loader import BioDataset
from dataloader import DataLoaderFinetune
# from torch_geometric.data import DataLoader
import torch
import torch.nn as nn
import torch.nn.functional as F
import torch.optim as optim
from tqdm import tqdm
import numpy as ... |
8460a2fadf9ab097ae2377c8ecae65668484ca608380bc94b8dbd7e2c34987dc | Python | 5,824 | 175 | """Prepration for runners."""
from __future__ import annotations
import logging
import os
from pathlib import Path
from shutil import move, rmtree
from typing import TYPE_CHECKING
from monty.shutil import gzip_dir
from quacc import get_settings
from quacc.utils.files import copy_decompress_files, make_unique_dir
i... |
d201ad6f449bf4a42d3884f7ebfe55d478bb8f0e079b36e489a6ba172d860f3b | Python | 5,824 | 149 | import numpy as np
import torch
class Normalizer(object):
def __init__(self,params=[],method = '-11',dim=None):
self.params = params
self.method = method
self.dim = dim
def fit_normalize(self,data):
raise NotImplementedError
def normalize(self, new_data):
rais... |
c3980d7a9041720634da8035fa0c12dc010299ffc6a238ef3e0c7e4098618fcd | Python | 5,825 | 153 | # 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... |
fb6237c3abf14bba6ddb9bd3fdc34ec07ff89c3cb3e0ed9efd3d34b4180e91a4 | Python | 5,825 | 198 | # 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... |
168838cac479da228fcfcc6fafa827eff1b085925632fe3f07d1e766850f611c | Python | 5,827 | 141 |
import pandas as pd
import os
def wrapper_table(f,pd, caption):
f.write('\\begin{table}\n')
f.write(pd.to_latex())
f.write('\\caption{'+caption+'}\n')
f.write('\\end{table}\n\n')
if not os.path.exists('stats'):
print("Error: Please run firs the script 'combine_tables.py'")
else:
p... |
21106392abce9062214c97257a128a9b5e6e169f9c8a1256eaa2c1a0a71e9115 | Python | 5,827 | 209 | # LIBRARIES
from argparse import ArgumentParser
from pytorch_lightning.callbacks import ModelCheckpoint
# Pytorch
import pytorch_lightning as pl
from pytorch_lightning.loggers import TensorBoardLogger
from datamodules import ImagePairsDataModule
import torchvision.transforms as T
# Extras
from pl_bolts.models.self_su... |
511188f140eabee25c52f88d96d270d95f63691f737f28f582a19f7d1b71c537 | Python | 5,828 | 178 |
# implementation independent network parameters
from model.network_params import ComputationBackendType, NetworkParams
# warn about usage of some method
from model.dev_utils import internal
class LagrangeNetwork:
"""
Wrapper over all implementations to make it easier to switch between them.
"""
de... |
744a16145f04e714094c817a41503905b17f32b42fe73a0f07a0bd104b77ba94 | Python | 5,828 | 131 | import matplotlib.pyplot as plt
import networkx as nx
from eworm.network import *
from eworm.utils import *
import _pickle as pkl
import os
import os.path as path
import sys
import matplotlib.patches as ptc
import numpy as np
import numpy.random as nr
import scipy
def spectral_layout(A):
c = (A + n... |
b45e4e89ff6590e99dfd8c120b915ccf3d29b1904661e54735d583021c67f93a | Python | 5,829 | 161 | """Unit tests for UndoHistory.
These are pure-Python - NO QApplication, no Qt - which is the whole
point of extracting the class out of the viewer: the stack invariants
can be verified at unit-test speed (~0.01s per test) regardless of GUI
state.
"""
import pytest
@pytest.fixture
def history():
fro... |
2b54aa488d3990354f0702c071201c41236a66ff88e74ce1a88e7149c658403d | Python | 5,830 | 171 | import bct
import numpy as np
from tqdm import tqdm
from sklearn.utils import check_random_state
from utils import cpl_func
def strength_preserving_rand_sa_trajectory(A, rewiring_iter = 10,
nstage = 100, niter = 10000,
temp = 1000, f... |
57544b5a85569f40425cdeb6f3440012468c5dabe60ac9029fecc9928df84694 | Python | 5,830 | 122 | # -*- coding: utf-8 -*-
"""
Created on Thu Oct 21 15:16:19 2021
@author: CY
"""
from typing import Callable
import time
from tqdm import tqdm
import copy
import torch
from nnunet.training.ssl.base import Model
from nnunet.training.data_augmentation.data_augmentation_batch import get_batch_augmentation
d... |
0741642c1b18c071204674a1f366c5a88b4d6f353570fdb2df6a7f1e7743664c | Python | 5,831 | 218 | import numpy as np
from moabb.datasets import (
Zhou2016,
BNCI2014004,
BNCI2014001,
MunichMI,
Weibo2014,
Cho2017,
)
from sklearn.discriminant_analysis import LinearDiscriminantAnalysis as LDA
from mne.decoding import CSP
from pyriemann.classification import MDM
from pyriemann.tangentspace impo... |
8cc8025eed396302871fb9d51964fd4fae537741d1f0874c0c85d1c5cd988116 | Python | 5,831 | 132 | """The batch masking pipeline's reference-free quality check.
Every mask failure measured in this project moves when the working resolution moves, so
re-segmenting at half scale and comparing detects a bad mask without ground truth. That is
the only kind of check available on real sections, and a batch run is exac... |
25bda7c668505d58c4cd6c412996cf843a7cdda78d6ab1cdaa62ce057b83dc76 | Python | 5,832 | 192 | """Utility functions for dealing with defects."""
from __future__ import annotations
from importlib.util import find_spec
from typing import TYPE_CHECKING
from monty.dev import requires
from pymatgen.core.periodic_table import DummySpecies
from pymatgen.entries.computed_entries import ComputedStructureEntry
from pym... |
562b5ca6c7f39958c6c283c10aeb24c98132711df2f5174d36d1993546f36cdc | Python | 5,833 | 135 | import math
import numpy as np
import torch
import torch.nn as nn
import torch.optim as optim
from typing import Any, Dict, Optional
from models.model import Model
from models.kan_layers import KAN, FastKANConv2DLayer
class M2DCNN_Net(nn.Module):
@staticmethod
def weight_init(m):
# [All the trainabl... |
0a2dfff5203881ccbce56391a565eea945d537f699ca5a46d7243426aed6dce7 | Python | 5,834 | 148 | import math
from abc import abstractmethod
from collections import defaultdict
from typing import Protocol
from elasticai.creator.arithmetic import FxpConverter, FxpParams
from elasticai.creator.file_generation.savable import Path
from elasticai.creator.file_generation.template import (
InProjectTemplate,
modu... |
3e5c1da734b6a298c69db893cd2644d7e5c1604bf80c291ad90f2082706253d3 | Python | 5,834 | 188 | import argparse
import datetime
import os
import numpy as np
import torch
import torch.nn as nn
import torch.nn.functional as F
from config import Raviv1
from learning_experiment import LearningExp
from modeling import MLP, RelaxedLinear, TiedRnnGS
from training import Trainer
try:
import wandb
except ImportErro... |
a1996f770df139b6d1c61bb0709fb89d46fe790083f169f584c10210ef778f61 | Python | 5,836 | 151 | ##### MODEL AND DATA LOADING
import time
start = time.time()
import torch
# torch.cuda.empty_cache()
import torch.utils.data
import torchvision.transforms as transforms
from torch.autograd import Variable
import numpy as np
from PIL import Image
import re
import os
from helpers import makedir
import train_and_test a... |
e2ab9a38a2a4c4d1d61f2988c965bae481ff92156a44b07001b10f7f674e970e | Python | 5,836 | 119 | from typing import Tuple
import torch
import torch.nn as nn
class MTCNN(nn.Module):
r'''
Multi-Task Convolutional Neural Network (MT-CNN). For more details, please refer to the following information.
- Paper: Rudakov E, Laurent L, Cousin V, et al. Multi-Task CNN model for emotion recognition from EEG Br... |
f31c789d299b4486e9ab414774265dbb95ef99085dc56f304c46f1de60f12eab | Python | 5,837 | 139 | import os.path
import gzip
from collections import defaultdict
from ckg.graphdb_builder import mapping as mp, builder_utils
def parser(databases_directory):
directory = os.path.join(databases_directory, "PhosphoSitePlus")
builder_utils.checkDirectory(directory)
config = builder_utils.get_config(config_nam... |
9ee3d948514644f9f94f3638feea1534a253e6b8fe65b0fc961aa21e88b3d1b3 | Python | 5,839 | 140 | import os
import pandas as pd
from scipy.io import loadmat
from sklearn.model_selection import train_test_split
from datasets.SequenceDatasets import dataset
from datasets.sequence_aug import *
from tqdm import tqdm
signal_size = 1024
#1 Undamaged (healthy) bearings(6X)
HBdata = ['K001',"K002",'K003','K0... |
a8769ce22d674ec8d188023f5952b35712e220f41fbfc5c3621ed44d1cec3f72 | Python | 5,839 | 144 | # 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... |
b5e4d9006368dc6c57602754755870200cf4f76617d6c81de6a5cd6097bbfe66 | Python | 5,841 | 184 | #!/usr/bin/env python
#================================================================
# Copyright (C) 2023 Yufeng Liu (Braintell, Southeast University). All rights reserved.
#
# Filename : bouton_analyzer.py
# Author : Yufeng Liu
# Date : 2023-01-03
# Description :
#
#===============... |
0b81b76fdfe0b62aba94d5c81c483f737a83b76603ef11463783e04c46541140 | Python | 5,842 | 169 | #!/usr/bin/env python
# encoding: utf-8
"""
tl train
========
(Alpha release - usage might change later)
The tensorlayer.cli.train module provides the ``tl train`` subcommand.
It helps the user bootstrap a TensorFlow/TensorLayer program for distributed training
using multiple GPU cards or CPUs on a computer.
You nee... |
4a16c59e09dd8ff7b415acd869adb2da3d5605c9ce12ffafba93c0efb83472db | Python | 5,842 | 125 | """Shared two-stage ANTs helper: explicit affine pass -> nonlinear-only pass,
composed into a single [warp, affine] transform list.
Extracted from mind_driver (the descriptor path proves this pattern); the intensity
path seeds the nonlinear stage via initial_transform (no moving pre-resample).
"""
import glob
... |
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