sha256 stringlengths 64 64 | language stringclasses 28
values | size int32 1 491k | lines int32 1 23.2k | content stringlengths 1 200k |
|---|---|---|---|---|
f4d02bec96f7f7fcdb08716c2458ab2be552c10d74eedf307192029a9801cef2 | Python | 1,119 | 40 | import shutil
from pathlib import Path
import numpy as np
from datasets.download import DownloadManager
from brainways.utils.paths import get_brainways_dir
def _load_sample_project(annotated: bool):
if annotated:
project_name = "sample-project-annotated"
else:
project_name = "sample-project"... |
0af6f97d2763af34d540e079c90a5c69e00a4961adc9668c5ae3d229ffbc78d0 | Python | 1,120 | 45 | #!/usr/bin/env python3
from pathlib import Path
import arbor as A
from arbor import units as U
cat = Path("cat-catalogue.so").resolve()
class recipe(A.recipe):
def __init__(self):
A.recipe.__init__(self)
self.tree = A.segment_tree()
self.tree.append(A.mnpos, (0, 0, 0, 10), (1, 0, 0, 10)... |
802cd1373d70289fa853ce4a5015c2b284898b699bd610eeea80307a9e636d57 | Python | 1,120 | 53 | """Get inferred parameters.
"""
from sys import argv
if len(argv) != 3:
print("Please pass the number of states and run id, e.g. python 3_get_inf_params.py 8 1")
exit()
n_states = int(argv[1])
run = int(argv[2])
#%% Import packages
print("Importing packages")
import os
import pickle
import numpy as np
from... |
b37eca5fad2ef27d30f9796c3405436f55d9d19c64a7f0bbdbc0d9c98d52e266 | Python | 1,120 | 33 | import subprocess
import sys
import yaml
script_gao = 'connectivity_correlations/gao_vs_enrichment.py'
script_harris = 'connectivity_correlations/harris_vs_enrichment.py'
script_harris_zeta = 'connectivity_correlations/harris_vs_zeta_enrichment.py'
script_gao_modules = 'connectivity_correlations/gao_module_hierarchy.... |
d40306271beaddaf2f79518d7c522d8abc3de53ca8f99074bd9ca9e15f021d12 | Python | 1,120 | 28 | #!/usr/bin/env python
import common
import chromatics
import os
import sys
from glob import glob
config_fn = sys.argv[1]
cell_line = config_fn.split('/')[0]
config = common.parse_config(config_fn)
os.chdir(os.path.expanduser(config['working_dir']))
segmentation_df = chromatics.read_bed(glob('../segmentation/*.bed.g... |
f346f18ee28dd3f4b4c82b6348e7d9774ac2781bfd17bce16e2d3c5e1de3d2f3 | Python | 1,120 | 27 | import pytest
from qtpy import PYQT6, PYSIDE2, PYSIDE6
@pytest.mark.skipif((PYSIDE6 or PYQT6), reason="not available with qt 6.0")
def test_qtxmlpatterns():
"""Test the qtpy.QtXmlPatterns namespace"""
from qtpy import QtXmlPatterns
assert QtXmlPatterns.QAbstractMessageHandler is not None
assert QtXm... |
4c9533fc0fa5fd30a2222fe02ed661dca6b9f6d1e29fdcc7340f7c745149b873 | Python | 1,121 | 32 | import torch
from torch.sparse import to_sparse_semi_structured, SparseSemiStructuredTensor
SparseSemiStructuredTensor._FORCE_CUTLASS = True
# Sparsity helper functions
def apply_fake_sparsity(model):
"""
This function simulates 2:4 sparsity on all linear layers in a model.
It uses the torch.ao.pruning flo... |
0b70561b6e9696df160d7642f1aa70e2cf18e4d5798e8f28ab19e68e4d09841b | Python | 1,122 | 32 | # Created by David Coggan on 2024 06 26
import pytest
import numpy as np
import brainscore_vision
@pytest.mark.private_access
def test_Coggan2024_behavior_stimuli():
stimulus_set = brainscore_vision.load_stimulus_set('Coggan2024_behavior')
assert len(stimulus_set) == 22560
assert len(set(stimulus_set['obj... |
6166618d65327371e52e2c1e3e6886af66c7a41542b8067f00d87599034a128a | Python | 1,122 | 26 | # Created by David Coggan on 2024 06 23
from brainscore_core.supported_data_standards.brainio.assemblies import NeuroidAssembly
from brainscore_vision import (
stimulus_set_registry, data_registry, load_stimulus_set)
from brainscore_core.supported_data_standards.brainio.s3 import (
load_assembly_from_s3, load_... |
75e1de558c07efe7464ec186b23f8e1c76e41d0b15ed4b42528d26776a862952 | Python | 1,122 | 39 | """# Main window
Use `MainWindow` to build an application shell with a menu bar, tool bars,
dock widgets, and a status bar around a central widget area.
"""
from magicgui import widgets
main = widgets.MainWindow()
# toolbar
toolbar = widgets.ToolBar()
toolbar.add_button(text="Folder", icon="mdi:folder")
toolbar.add... |
81f4617a7322dc739e85bf782e051fda4d0a5a27b40428f90bf7f8d3734f2bf1 | Python | 1,122 | 27 | import sys
sys.path.append('/extra/mccolgan/work')
from spikepy.developer.file_interpreter import FileInterpreter, Trial
import pyXdPhys as xd
import os
class ExampleText(FileInterpreter):
def __init__(self):
self.name = 'XDPhys' # this name must be unique
self.extentions = ['.bf','.itd'] # Spikep... |
be12eb53a4557fcc99fc13bebe5636e6f696dc16deb9e8eb8bc5128cb9dfe49c | Python | 1,122 | 31 | from argparse import Namespace
from typing import TYPE_CHECKING
from eir.setup.config_validation import validate_input_configs, validate_output_configs
if TYPE_CHECKING:
from eir.setup.config import Configs
def validate_predict_configs_and_args(
predict_configs: "Configs", predict_cl_args: Namespace
) -> No... |
3f271bdfcaef841dbbda452f947da44a25671e49c3b465709ebb4850c52d11f7 | Python | 1,123 | 29 | # wfield - tools to analyse widefield data
# Copyright (C) 2020 Joao Couto - jpcouto@gmail.com
#
# This program is free software: you can redistribute it and/or modify
# it under the terms of the GNU General Public License as published by
# the Free Software Foundation, either version 3 of the License, or
# (at your... |
7a4c2b847552669f350bcee811bedd508a8d43d86419330aeb0380a21c9fe467 | Python | 1,123 | 49 | # coding=utf-8
"""
Tests for deepreg/download.py
pytest style
"""
import os
import shutil
from filecmp import dircmp
from git import Repo
from deepreg.download import main
def has_diff_files(dcmp):
if len(dcmp.diff_files) > 0:
return True
for sub_dcmp in dcmp.subdirs.values():
has_diff_file... |
324d1e028a5830d04f4b11dd32747d581562bc06780b5b24bf42292fb8204703 | Python | 1,124 | 48 | import functools
from typing import Callable
from ..config import is_dry
def dryable(dry_func: Callable) -> Callable:
"""Function decorator to set a function as dryable.
When this decorator is applied, the provided `dry_func` will be called
instead of the actual function when the current run is a dry ru... |
e5036bb1a5f05d95793919a6be7229f6fff0e7ad00bc5d184742be9fc73f51ae | Python | 1,124 | 42 | import yaml
from dataclasses import dataclass, asdict
@dataclass
class Config:
weights_path: str = './checkpoint/'
batch_size: int = 32
NUM_STEPS: int = 2000
patience: int = 10
learning_rate: float = 0.001
save_freq: int = 50
val_freq: int = 100
def update(self, config_dict: dict):
... |
7fbf2678ed0dd3ed1c86f487be61ad048f928f3f8dbb9b514ce3a83b1af2404d | Python | 1,125 | 31 | import torch
from torch.utils.data import Dataset
class DeltaDataset(Dataset):
def __init__(self, data, dim_embedding, inv = False):
self.data = data
self.dim_embedding = dim_embedding
self.inv = inv
def __len__(self):
return len(self.data)
def __getitem__(self... |
055367e967c6d9afa8d37ceca948edd11f23cd42059e949772740920ca9d3a81 | Python | 1,127 | 47 | # -*- coding: utf-8 -*-
# python standard library inputs
import os
# external inputs
import numpy as np
import nibabel as nb
def average_time_series(img_input, path_output, name_output):
"""Average time series.
This function computes the element-wise average of multiple nifti files.
Parameters
... |
289c3fad3352816d8031a5ca4e8d8b725d44a20d95d982a87351d549989834bd | Python | 1,127 | 48 | #!/usr/env python
import numpy as np
import sys
inp = sys.argv[1]
xmin = float(sys.argv[2])
xmax = float(sys.argv[3])
ymin = float(sys.argv[4])
ymax = float(sys.argv[5])
zmin = float(sys.argv[6])
zmax = float(sys.argv[7])
nx = int(sys.argv[8])
ny = int(sys.argv[9])
nz = int(sys.argv[10])
area_tot = (xmax-xmin)... |
8eb1a7a85f43305feadae66a4fc438ebdb092b6edd58eb0db6e911a8f53bc6d3 | Python | 1,127 | 54 | """Get inferred parameters.
"""
from sys import argv
if len(argv) != 3:
print("Please pass the number of states and run id, e.g. python 3_get_inf_params.py 8 1")
exit()
n_states = int(argv[1])
run = int(argv[2])
#%% Import packages
print("Importing packages")
import os
import pickle
import numpy as np
from... |
09de2fe65dfeaad69aca5e370ee4d4277e2d48e268a7907270e7ffb69fc4cf04 | Python | 1,128 | 35 | # Copyright (C) 2019-2022 Intel Corporation
#
# SPDX-License-Identifier: MIT
from django.conf import settings
from rest_framework.exceptions import ValidationError
from rest_framework.pagination import PageNumberPagination
from cvat.apps.engine.types import ExtendedRequest
class CustomPagination(PageNumberPaginatio... |
c65a61ca47548c06f57b8fbf886fd03c609614e45c5942f33cef854dc187cc6a | Python | 1,128 | 36 | # Generated by Django 4.2.16 on 2024-10-22 08:41
from django.conf import settings
from django.db import migrations, models
def set_has_analytics_access(apps, schema_editor):
User = apps.get_model(settings.AUTH_USER_MODEL)
for user in User.objects.all():
is_admin = user.groups.filter(name=settings.IAM... |
e1b0c13f5e13972ab181f98cd4112be9faba8a4207f59e5ffdc554a47a26096e | Python | 1,128 | 26 | from pathlib import Path
from brainscore_core.supported_data_standards.brainio.stimuli import StimulusSet
from brainscore_core.supported_data_standards.brainio.packaging import package_stimulus_set
import csv
import pandas as pd
stimuli = [] # collect meta
image_paths = {} # collect mapping of image_id to filepath
s... |
7fe428def4e4ff8dde52ffc935e16744483d06314331caf0852c11cbabb66dff | Python | 1,129 | 33 | caner_related_lncrnas = [
"NEAT1", "MALAT1", "SNHG16", "ZFAS1", "MIR22HG", "LINC-PINT", "MIR4435-2HG",
"FGD5-AS1", "CYTOR", "PVT1", "FTX", "FOXCUT", "FENDRR", "LINC00461", "DLEU2",
"MIR34AHG", "LINC00511", "LINC02582", "DLGAP1-AS1", "THORLNC"
]
enhancer_lncrnas = [
"NEAT1", "ABALON", "MALAT1", "ASB16-A... |
a279dd8b48fdc62d02867d89fa3f4a28a8730d1c03dd9f16285e12b801455e95 | Python | 1,129 | 44 | """
This is a minimalist benchmark to compare different versions of the annotate function
"""
import time
import numpy as np
import obspy
import seisbench.models as sbm
def main(n_stations: int = 2, n_samples: int = 8640000):
models = [sbm.PhaseNetLight(), sbm.PhaseNet(), sbm.EQTransformer()]
# models = [s... |
a03b185d321ec4a09ee19b7b5ef3c33dd92445e267b10573eeeec23e40edd112 | Python | 1,130 | 45 | # Copyright (C) CVAT.ai Corporation
#
# SPDX-License-Identifier: MIT
from __future__ import annotations
from abc import ABCMeta, abstractmethod
from dataclasses import dataclass
from io import BytesIO
from typing import Generic, TypeVar
from cvat.apps.engine import models
_T = TypeVar("_T")
@dataclass
class DataW... |
a93b5ec720ad83aa78b763b47e3fe85ffc099284fb47aae234408d51b0bb6a31 | Python | 1,131 | 31 | # %% ### import modules
from pathlib import Path
import pandas as pd
# %% read results table
results_dir = Path(__file__).resolve().parents[1] / "results"
df = pd.read_excel(results_dir / "summary_table.xlsx")
# %% rename and structure columns:
new_columns = [
("", "Group"), # diagnosis -> Group
("Scans", "M... |
42f6f0df393a163c53fc7e9b26f20a1ce9984aaa8f334454fded4625b4d9e1fc | Python | 1,132 | 39 | from torch import nn
from eir.models.input.array.array_models import (
ArrayModelConfig,
ArrayWrapperModel,
al_array_model_configs,
al_array_model_types,
al_array_models,
get_array_model_class,
get_array_model_init_kwargs,
)
from eir.setup.input_setup_modules.common import DataDimensions
... |
c1e113e73a791b5102abc8f942a2c40617fc269c42732a20967c661cf572fd56 | Python | 1,132 | 34 | import pytest
from transcode_dataset import get_component_order_mapping
import seisbench.data as sbd
def test_get_component_order_mapping():
dataset = sbd.DummyDataset(missing_components="pad")
# Wrong missing components
with pytest.raises(AssertionError):
get_component_order_mapping(dataset)
... |
e20fb4abf4700689fee5b388c6f5478d31b5792319cc37e994dba292c3787165 | Python | 1,132 | 33 | # This file is part of connectome-manipulator.
#
# SPDX-License-Identifier: Apache-2.0
# Copyright (c) 2024 Blue Brain Project/EPFL
"""Test that alternate morphologies work."""
import os
import pytest
import bluepysnap
from connectome_manipulator.connectome_manipulation.converters import EdgeWriter
from connectome_ma... |
c3eea7ebe1d9fb152e907d13b65c2eb4a187f55b9b884b32b759e577442b10ea | Python | 1,133 | 51 | import os
# Model
MODEL_NAME = 'vnet'
# wandb logging
WANDB_LOG = False
# Classes
ORGANS = ['glomeruli']
NUM_CLASSES = len(ORGANS) + 1 # +1 for background
# Lab Machine
PROJECT_PATH = os.path.dirname(os.path.dirname(os.path.abspath(__file__)))
print("Project path: ", PROJECT_PATH)
DATA_PATH = '/hdd/yang/projects/g... |
c87b696b17db0b861d79678bca32fab205f67e177b16b2c56d520c386e4bf649 | Python | 1,133 | 24 | from pathlib import Path
from brainways.project._utils import update_project_from_previous_versions
from brainways.project.brainways_project import BrainwaysProject
def test_update_project_from_v0_1_1(brainways_project_path_v0_1_1: Path):
update_project_from_previous_versions(brainways_project_path_v0_1_1)
B... |
09d412c747c5583845d8cceef3490d8adeeb26bc0d7895eba91e47ffb9768b4b | Python | 1,135 | 31 | #!/usr/bin/env python3
# -*- coding: utf-8 -*-
import os
import tempfile
from scilpy import SCILPY_HOME
from scilpy.io.fetcher import fetch_data, get_testing_files_dict
# If they already exist, this only takes 5 seconds (check md5sum)
fetch_data(get_testing_files_dict(), keys=['bst.zip'])
tmp_dir = tempfile.Temporar... |
4440b4ca41323cfe43e1bebc2a89f70e5d62969d93e319a7fc9c675968091b17 | Python | 1,135 | 46 | #! /usr/bin/env python
"""Generate a VTK style vtp file from a ply file
usage: ply2vtp.py mesh.ply mesh.vtp"""
__author__ = "Benjamin Barad"
__email__ = "benjamin.barad@gmail.com"
__license__ = "GPLv3"
import gc
import click
@click.command()
@click.argument('input_ply', type=str)
@click.argument('output_vtp', typ... |
a1fc5100045e71828beb61420dc4968e1f577ec6a89811bc1be5e7a4b87f6b15 | Python | 1,135 | 43 | from pathlib import Path
from typing import Union
import torch
from PIL.Image import Image
from eir.setup.input_setup_modules.setup_image import (
ComputedImageInputInfo,
default_image_loader,
)
from eir.setup.output_setup_modules.image_output_setup import ComputedImageOutputInfo
def prepare_image_data(
... |
a8d8751d9362893c1c38d8fe8f87f5ec26affb0161e5974865ce44bcc1a9b9e7 | Python | 1,135 | 29 | #############################################################################
# Copyright (C) 2020-2026 MEmilio
#
# Authors: Maximilian Betz
#
# Contact: Martin J. Kuehn <Martin.Kuehn@DLR.de>
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the Li... |
3213e5aef73079fc26eb209ef12698591b80b5266b79e85356eb3704d5222e40 | Python | 1,136 | 30 | from curvature_calculation import from_ply_workflow, new_workflow, extract_curvatures_after_new_workflow
import time
from sys import argv
t_begin = time.time()
fold = r"/gpfs/group/grotjahn/bbarad/Surface_analysis/" # output will be also written there
base_filename = "TE1_ER"
#surf_file = "TE2_OMM.ply"
seg_file =
# s... |
5a843f409a41b98e0b868353e78ccde72fd4b63b0f090e9e58362f81eee7fe57 | Python | 1,136 | 28 | import torch
from utils import common_functions as c_f
from reducers.base_reducer import BaseReducer
class ClassWeightedReducer(BaseReducer):
def __init__(self, weights, **kwargs):
super().__init__(**kwargs)
self.weights = weights
def element_reduction(self, losses, loss_indices, embeddings,... |
6d39b529378d555873bcaf62747436adeb859d277188b9c462e9bcedd7b30984 | Python | 1,138 | 46 | import distinctipy
def require_modules(modnames):
"""
Given a list of module names, skip the test if any of them dont exist
"""
import importlib
import pytest
for modname in modnames:
try:
importlib.import_module(modname)
except (ImportError, ModuleNotFoundError):... |
8bc75c0ab4eb5b5a29bd02256fb40ec52ae6e2a8a84ad90bdb33490f4f63712d | Python | 1,138 | 45 | # Copyright (C) CVAT.ai Corporation
#
# SPDX-License-Identifier: MIT
_caches = {}
def _default_cache_value():
from cvat.apps.engine.models import Comment, Issue, Job, Task
return {
Task: {},
Job: {},
Issue: {},
Comment: {},
}
class DeleteCache:
def __init__(self, ca... |
f75b014595be97a424ee14a904da35fd721b657ee23d0d2e2e65cd1c9cd380a4 | Python | 1,138 | 44 | import pandas as pd
import ijson
import csv
import time
def process_posts(posts):
post = posts.replace("'","").strip("[").strip("]")
post = post.split(", ")
post = post[:200]
return post
def get_all_tweet():
df = pd.read_csv('./user_post.csv')
all_tweet_list = []
for index, row in df.i... |
3b0d21b8dce7e608f77070483175b041151dcdc9942024ae030e1d0784cd9a51 | Python | 1,139 | 31 | # ------------------------------------------------------
# This is a simplified version of filter_ko_hierarchy.py
# ------------------------------------------------------
# USAGE modify_ko_hierarchy_keep_all_occurences.py [ORIGINAL_HIERARCHY.tms] [REANNOTATION_FILE.csv]
# 1. read KO hierarchy from tms file
# 2. add ... |
82ef02f948d0120966b611d3847cd2f20acfcba9ebf3e50d688323ae54ff19c4 | Python | 1,141 | 31 | from dtiplayground.dmri.common.tools.base import ExternalToolWrapper
class ImageMath(ExternalToolWrapper):
def __init__(self,binary_path= None, **kwargs):
super().__init__(binary_path, **kwargs)
self.binary_path=None
if binary_path is not None:
self.binary_path=binary_path
... |
bae03c7bfe64e44237b441aa640eba011f084ca2763ccfcdd6f4056d74d0b738 | Python | 1,141 | 44 | import pyvisa as visa
def main():
_rm = visa.ResourceManager()
sds = _rm.open_resource("USB0::62700::60984::SDSMMEBD2R5477::0::INSTR")
sds.write("chdr off")
vdiv = sds.query("c1:vdiv?")
ofst = sds.query("c1:ofst?")
div = sds.query("tdiv?")
sara = sds.query("sara?")
sara = float(sara.rst... |
d4874c098521a73187964d1917ef7f5b7cd6c313f3d8f7cb5ead55cfbdfc9e8d | Python | 1,141 | 39 | # -----------------------------------------------------------------------------
# Copyright © 2009- The Spyder Development Team
#
# Licensed under the terms of the MIT License
# (see LICENSE.txt for details)
# -----------------------------------------------------------------------------
"""Provides QtWebEngineQuick cl... |
78767d95afc80e71d93e9c90e4820484d6b15094b29703b287446486769740f1 | Python | 1,142 | 48 | """Public pipeline API for Waven.
These functions re-export the current implementation in :mod:`Waven.pipeline`.
They are intentionally granular so users can run only the stages they need.
"""
from __future__ import annotations
from Waven.pipeline import (
PipelineOutputs,
RFAnalysisResult,
SimpleModelRes... |
1864f039e22f034b70c239aa5c66a71a612a50d3e7797452be6338fdcc637404 | Python | 1,143 | 46 | import shutil
import tempfile
from pathlib import Path
import pytest
import seisbench
import seisbench.data as sbd
import seisbench.models as sbm
DATA_DIR = Path(__file__).parent / "examples"
@pytest.fixture(scope="session")
def data_dir() -> Path:
return DATA_DIR
@pytest.fixture(scope="session", autouse=Tru... |
62ca2e756c09d9c1045228a670f87f792ab7eb40f024bbd7c398c084f3b6c228 | Python | 1,143 | 41 |
from warnings import warn
import numpy as np
from . import pre
import datajoint as dj
schema = dj.schema('pipeline_aod_preprocessing', locals())
@schema
class Spikes(dj.Computed):
definition = ...
def _make_tuples(self, key):
raise NotImplementedError("""This is an old style part table inherited f... |
78a5900d1cd5933879b273cda567fbfefde2e331a578c64623cd80f7a42be0bc | Python | 1,143 | 45 | #!/usr/bin/env python
# -*- coding: utf-8 -*-
from itertools import product
from PIL import Image
from progress.bar import Bar
from torchvision import transforms
class Loader:
shapes = [
"square",
"rectangle",
"isoTrapezoid",
"parallelogram",
"losange",
"kite",
... |
0e15c51d3ebff5aa953e744ddc6f4da562146ba1b351ee9781f0018e200f7346 | Python | 1,144 | 33 | # Copyright (C) CVAT.ai Corporation
#
# SPDX-License-Identifier: MIT
from __future__ import annotations
from typing import TYPE_CHECKING
from cvat.apps.quality_control.backends.base import QualityBackend
if TYPE_CHECKING:
from cvat.apps.quality_control.data_providers import JobDataProvider
def make_quality_ba... |
9a5f1ffa93f20b33f68e746e37f99e5a55ca2d3e21e517b46576fa83a0ea90e7 | Python | 1,144 | 46 | from typing import List, Optional, Dict
from fastapi import APIRouter
from service.dto.topic import TopicDto
from model.topic import UserEvaluationModel, UserEvaluationDao, TopicModel
router = APIRouter(
prefix="/topics",
tags=["topics"],
responses={404: {"description": "Not found"}},
)
@router.get('/on... |
80d061fb4ff249ad08e24a673b8563d0e5484c712c23ef752ac354fbe4dc5b89 | Python | 1,145 | 43 | from scipy import stats
import numpy as np
from .base import Distribution
class Gamma(Distribution):
"""Gamma prior.
Parameters
----------
alpha : scalar or ndarray
Parameter of distribution
beta : scalar or ndarray
Parameter of distribution
Examples
--------
To crea... |
ad7ba3205e3315dac1d264428782db958f0dc7b9664c99be108f65b1e71d6e07 | Python | 1,145 | 37 | import os
import subprocess
from dataclasses import dataclass
@dataclass(frozen=True)
class ReadsData:
dir_path: str
fwd: bool = True
rev: bool = False
def run_cmd(command: list):
os.system(" ".join(command))
def qiime2_version():
o, e = run_cmd(["conda", "env", "list"])
qiime_version = ""
... |
72ea629af046bc487506ee595ce3fb1bbe21aec8dfba6e886ba6ce43fc8a3bdd | Python | 1,146 | 34 | #Import packages
import cv2
import numpy as np
import nibabel as nib
import matplotlib.pyplot as plt
#Load in the image, identify superior slice with mask, and slice 100mm inferior to that
ants_mask=nib.load('t1name_here_T1wT2w_mask.nii.gz')
a = np.array(ants_mask.dataobj)
tmp=a.mean(axis=0)
tmp=tmp.mean(axis=0)
tmpnz... |
e78d35456b9a124e88ced7a040167e6067541754a6109514c08cba60cc703e1c | Python | 1,146 | 41 | # example_plugin.some_module
from pathlib import Path
from typing import Callable, List, Optional, Sequence, Union
import napari
from napari.types import LayerData
from brainways.ui import BrainwaysUI
PathLike = str
PathOrPaths = Union[PathLike, Sequence[PathLike]]
ReaderFunction = Callable[[PathOrPaths], List[Layer... |
dde25d6492f6fd3ba3a9a5f3ec6bf658962a30b201bbe6a4631290e9ae9c0215 | Python | 1,147 | 41 | # -*- coding: utf-8 -*-
"""Noise utilities."""
import os
import nibabel as nb
import numpy as np
__all__ = ["make_gaussian"]
def make_gaussian(input_file, path_output, mu=0, sigma=1):
"""Creates a NIfTI volume with Gaussian noise as voxel intensities and saves a nifti
volume with matrix size and header inf... |
06eb877de5be46f29a563613e3871645c7dfd72bdbd28c0d5ff1744a9b081f24 | Python | 1,148 | 42 | import torch
from torch import nn
import torch.nn.functional as F
class DeeProBot(nn.Module):
def __init__(self,des_size=50,num_prop_size=9,dropout=0.1):
super(DeeProBot, self).__init__()
self.dropout = dropout
self.des_size = des_size
self.num_prop_size = num_prop_size
... |
7109bc3b7bc63a4abf505421ccafc8b501f3e313c9c8edfdc9956b976b746b09 | Python | 1,150 | 28 | import SimpleITK as sitk
import os
def zip_nifti(path):
"""
Zip all nifti files in a folder
:param path: path to folder containing nifti files
:return: None
"""
files = os.listdir(path)
for file in files:
if file.endswith(".nii"):
img = sitk.ReadImage(os.path.join(path, ... |
7335a0dde2e2271dadf32f436fe0882d7f7cc30434549f1e32a4c2f5eb5e026c | Python | 1,150 | 27 | import numpy as np
import pytest
from impyute.dataset.base import randc
from impyute.ops import error
def test_raise_error_nlevel_exceed_shape():
with pytest.raises(error.BadInputError) as e:
randc(shape=(2, 2))
expected = "nlevel exceeds the size of desired dataset. Please decrease the nlevel or incre... |
de9159c8b4ab9e463f777de9fdebb3c311eb3f1aafa9613e12a6cbc09cfa3e42 | Python | 1,150 | 26 | import torch
from torch import nn
class GlobalSpatialAttention(nn.Module):
def __init__(self, in_channels, num_reduced_channels):
super().__init__()
self.conv1x1_q = nn.Conv2d(in_channels, num_reduced_channels, 1, 1)
self.conv1x1_k = nn.Conv2d(in_channels, num_reduced_channels, 1, ... |
53e163d8c008c5c257fbee66e6c334001497bb8ac2a75d75ac14a724f0c66383 | Python | 1,151 | 48 | """Tests for logger."""
import logging
import os
from pathlib import Path
import pytest
from deepreg import log
@pytest.fixture()
def log_file_path(tmp_path_factory) -> Path:
"""
Fixture for temporary log file.
:param tmp_path_factory: default fixture.
:return: a temporary file path
"""
ret... |
088fae3c36738523026bf044d40aea6e75047698590208c38baa237e1bd505c0 | Python | 1,152 | 42 | # -*- coding: utf-8 -*-
"""
Read bandwidth per pixel in phase encoding direction
This scripts reads the bandwidth per pixel phase encode from siemens dicom data.
This parameter is needed for fieldmap undistortion.
"""
# python standard library inputs
import os
# external inputs
import pydicom
# input data
file_in ... |
79f180cf2c30ea4a6b1bb0028f2b9d9a4724bd027f242f4235f865ca4eb3dd71 | Python | 1,152 | 30 | from curvature_calculation import from_ply_workflow, new_workflow, extract_curvatures_after_new_workflow
import time
t_begin = time.time()
fold = r"/gpfs/group/grotjahn/bbarad/poisson_test/" # output will be also written there
base_filename = "fission.ply"
surf_file = "fission.ply"
#seg_file = ""
# surf_file =
lbl=1
... |
10777da3513b7444dc3f9e40b5af5d1ee0c32d02b16d9fca9fa65c96c5c0ace9 | Python | 1,153 | 35 | import pytest
from pytest import approx
from brainscore_vision import benchmark_registry, load_benchmark, load_model
class TestExist:
@pytest.mark.private_access
@pytest.mark.parametrize("identifier", [
'Papale2025.V1-ridge',
'Papale2025.V4-ridge',
'Papale2025.IT-ridge',
'Papa... |
29d2c45cbf5dfe9bb328b0ac8fc8ba8dbb0f9eeec11d24c890f314614e68b7a4 | Python | 1,153 | 35 | import abc
from pathlib import Path
from typing import Generic, TypeVar, get_origin, get_args
import numpy as np
from neuralib.persistence import PickleHandler, PersistenceHandler
from neuralib.persistence.cli_persistence import PersistenceOptions
from .cli_core import cast_opt, CommonOptions
__all__ = ['Persistence... |
ffb551e87067a7d325683399f02899f36f0149cce41e00ac00ea0dbd1eed3c1a | Python | 1,153 | 39 | import sys
import re
class ProgressBar(object):
DEFAULT = 'Progress: %(bar)s %(percent)3d%%'
FULL = '%(bar)s %(current)d/%(total)d (%(percent)3d%%) %(remaining)d to go'
def __init__(self, total, width=40, fmt=DEFAULT, symbol='=',
output=sys.stderr):
assert len(symbol) == 1
... |
6b8cb25e2ec150f5824fece0b2a050cc7e67ad552ad73e07f61b2bd635aafaf7 | Python | 1,154 | 44 | from typing import Literal
from argclz import AbstractParser, argument
from rscvp.util.database import *
__all__ = ['DBtoGspreadOptions']
class DBtoGspreadOptions(AbstractParser):
DESCRIPTION = 'Push a local sql database to a self gspread'
db_type: Literal['base', 'bayes', 'sftf', 'dark', 'blank', 'vr'] = ... |
93481599fab740c0c16f0e0ef19aa76e3acb6e5ac0624e5007f338612e9f8891 | Python | 1,154 | 13 | from brainscore_vision import benchmark_registry
from . import benchmark
benchmark_registry['Malania2007.short2-threshold_elevation'] = lambda: benchmark._Malania2007Base('short2')
benchmark_registry['Malania2007.short4-threshold_elevation'] = lambda: benchmark._Malania2007Base('short4')
benchmark_registry['Malania200... |
a845f0b0a0cac5dca73b9c5805b6490539c53bd65c9bd0e2158e21f6c1bd19a4 | Python | 1,154 | 35 | """
After fine-tuning, all of our model weights, up until the last conv. layer,
are contained within a single layer model object, making it difficult for Keras
to load in these layer weights by name for any subsequent fine-tuning. Here,
the model is loaded, the interior model is extracted,
and its weights are saved.
U... |
414694471fa70ab45f86a31444ae215b6d9ff549c7cc67d09ed7327b7d2a5c14 | Python | 1,156 | 24 | """Bundled data files shipped with osl-dynamics.
This subpackage provides brain atlases, MNI surfaces, masks, and other
reference files needed by the processing and analysis pipelines. Each
submodule exposes a ``directory`` attribute pointing to its data directory
so files can be resolved by name at runtime using
:py:... |
4a83f4e61b42e33a1251325ac4480782b389f388b6b5daf0f679c336cb60b2c4 | Python | 1,156 | 40 | from sklearn import svm
from sklearn.pipeline import Pipeline
from sklearn.preprocessing import StandardScaler
from sklearn.decomposition import PCA
from preprocess import preprocess_dataset
import sys
sys.path.append("..")
from utils.eval import evaluate_on_all_metrics
import argparse
if __name__ == '__main__':
... |
a08c18c32fc63edfa1fa69731b0bbcd2d3d534a794d47524efd2273b406cf922 | Python | 1,156 | 35 | #!/usr/bin/env python
# mr-to-pct_script.py
# Runs mr to pct as a python script
# Inputs:
# input_mr_file Filename of your T1w MRI including full path
# output_pct_file Filename to give the output pCT including full path
#
# SNY: Wed 23 Nov 08:51:11 GMT 2022
import sys, os, torch
sys.path.append('../')
f... |
a13d3d57153350817090b556a6557c29b1e5883ee4377254bc5a2fecb272e258 | Python | 1,156 | 26 | import pytest
from brainscore_vision import load_dataset, load_stimulus_set
from brainscore_vision.benchmark_helpers import check_standard_format
@pytest.mark.memory_intense
@pytest.mark.private_access
def test_assembly():
assembly = load_dataset('Igustibagus2024')
check_standard_format(assembly, nans_expect... |
a8aaa1aa776ef632a8c176134c7c7ae65d7b78b945f1e418a64e7f372bcc4cd1 | Python | 1,156 | 38 | """Deprecated compatibility shim for Gemini model loading.
Construction now lives in ``chemgraph.models.endpoints.google_direct`` behind
the Google-native protocol builder. Prefer
``chemgraph.models.loader.load_chat_model``.
"""
from __future__ import annotations
import warnings
from langchain_google_genai import C... |
f8d53bc9235af9ba3305f7edc98c948535856630df4a11fa4d73661dd535b5f1 | Python | 1,156 | 32 | #!/usr/bin/env python3
# -*- coding: utf-8 -*-
import os
import tempfile
from scilpy import SCILPY_HOME
from scilpy.io.fetcher import fetch_data, get_testing_files_dict
# If they already exist, this only takes 5 seconds (check md5sum)
fetch_data(get_testing_files_dict(), keys=['processing.zip'])
tmp_dir = tempfile.T... |
8cd913e245d97669a4f6ef286a2660b9e004b706063e5e5eca892a96fe618c52 | Python | 1,157 | 39 | import pickle
import os
from musclex.modules.QuadrantFolder import CACHE_FORMAT_VERSION, QuadrantFolder
def test_nested_result_parent_can_be_created(tmp_path):
result_file = (
tmp_path
/ "qf_results"
/ "F10_cre-flnc-224"
/ "F10_cre-flnc-224_21_00001_folded_compressed.tif"
)
... |
f3d03e3b8910f73ae2c1f501b5f4a9e8b6529b504c0488cae9c59bafe9674d6f | Python | 1,157 | 35 | import subprocess
import sys
import yaml
script_compare = 'flatmaps/compare_flatmap_enrichments.py'
pathpath = 'PATHS/filepaths_carlen.yml'
with open(pathpath, 'r') as myfile: pathdict = yaml.safe_load(myfile)
sys.path.append(pathdict['code']['workspace'])
from pfcmap.python import settings as S
setkeys = [key for k... |
2ae17b6a0ba1679ce80e99f411b92088cd7c41bc9c13bc7c21c8b37f5ecc5675 | Python | 1,159 | 48 | # noinspection PyUnresolvedReferences
import math
# noinspection PyUnresolvedReferences
import pathlib
# noinspection PyUnresolvedReferences
from neuron import h
# noinspection PyUnresolvedReferences
import neuron_interface.neurosim
from .cell_modification_parameters.cell_modification_parameters import (
CellMod... |
8115ae4ec7246147d305e0e7571e124e7aaf03b5e1ee7c87b45a79eb3f11c392 | Python | 1,159 | 36 | """ Full assembly of the parts to form the complete network """
from .unet_parts import *
class UNet(nn.Module):
def __init__(self, n_channels, n_classes, bilinear=False):
super(UNet, self).__init__()
self.n_channels = n_channels
self.n_classes = n_classes
self.bilinear = bilinear... |
d132aa7286a671c893a3aaefb29e0a22ade7b8f1695935468f5abc1be273571b | Python | 1,159 | 39 | import socket
from time import time, ctime
list_clients = []
list_connections = []
sock_server = socket.socket(socket.AF_INET, socket.SOCK_STREAM)
local_hostname = socket.gethostname()
local_fqdn = socket.getfqdn()
ip_address = 'IP'
port = PORT
print("working on %s (%s) with %s" % (local_hostname, local_fqdn... |
595d913a11a6598973545aaf3bee12c93da2d2a61f4ff04ecf7be988de3c8aff | Python | 1,160 | 32 | #!/usr/bin/env python3
# -*- coding: utf-8 -*-
import os
import tempfile
from scilpy import SCILPY_HOME
from scilpy.io.fetcher import fetch_data, get_testing_files_dict
# If they already exist, this only takes 5 seconds (check md5sum)
fetch_data(get_testing_files_dict(), keys=['tracking.zip'])
tmp_dir = tempfile.Tem... |
94987fd4b717d0409d717c63ce915afd9289ab40e23248fe6b87d943131d3c58 | Python | 1,161 | 30 | import sys
sys.path.append("..")
from utils.dataset import merge_and_split, simple_vectorize
import torch
from torch.utils.data import Dataset, DataLoader
class simple_dataset(Dataset):
def __init__(self, data, labels):
super().__init__()
self.data = torch.FloatTensor(data)
self.labels = t... |
b0d712c81465adc89eca46bbab55d85a808db85317e6cff87c38fcdb9b30bc18 | Python | 1,161 | 51 | #import serial
from psychopy import visual, core, parallel
class Simulated:
'''
'''
def __init__(self):
'''
'''
pass
def setData(self, code: str):
'''
'''
print(f'trigger::Simulated::setData(): Received `code`={code}.')
c... |
ff616f9964f02a3a16bf31895f7672d4b4a71bcc88021b88fefb59b7ef688356 | Python | 1,161 | 40 | import os
import sys
import scipy
import numpy as np
import pandas as pd
import scanpy as sc
import celltypist
from celltypist import models
import seaborn as sns
import scipy.io as sio
import scanpy.external as sce
import matplotlib.pyplot as plt
os.chdir("/data/wuqinhua/phase/covid19")
adata = sc.read('./Alldata.h... |
54ea78bfa0a7aca47f5d409071779140cb3ec9fe16695b6ed80c5927b84cb62e | Python | 1,163 | 34 | from abc import ABCMeta, abstractmethod
class Parser(metaclass=ABCMeta):
"""Abstract base class that represents a parser of an onnx operator.
Example: Conv, MatMul, etc.
"""
def __init__(
self, node_id, node, nodes_outputs, mapping, onnx_model, accelerator=None
) -> None:
self.nod... |
57a015a17e21550185962762fdb64671fc6015e0cb646e06ae977754cb72918d | Python | 1,163 | 33 | # Copyright (C) CVAT.ai Corporation
#
# SPDX-License-Identifier: MIT
from .command_base import CommandGroup, DeprecatedAlias
from .commands_config import COMMANDS as COMMANDS_CONFIG
from .commands_functions import COMMANDS as COMMANDS_FUNCTIONS
from .commands_profile import COMMANDS as COMMANDS_PROFILE
from .commands_... |
909ba6c649914e5528ba48eabde116ff6f09ca6abc42d34bbd246cb74365953b | Python | 1,163 | 45 | """Examples copying utility function."""
from pathlib import Path
import mkdocs_gen_files
EXAMPLES_DIRECTORY_PATH = Path("tutorials")
def write_file(file_path: Path) -> None:
"""
Copies file from examples directory into mkdocs scope.
Args:
file_path (Path): Current file path.
"""
root_... |
c0dbef56062920abf89bfdd9a1d12db17789e0d1552d3dd0ca0f3a8dc4922563 | Python | 1,163 | 61 | import re
# maybe item = item.replace('\n',' ')
def count_characters(text):
text = text.replace('\n',' ')
return len(text)
def count_hashtags(text):
hashtags = re.findall(r'#\w', text)
return len(hashtags)
def count_words(text):
text = text.replace('\n',' ')
return text.count(' ')
def hasta... |
e5f6b218f29def3350fe734d64b536306413592051fb5f4b8fc3d43879d0d283 | Python | 1,163 | 40 | import os
import sys
# Add the project's root directory to sys.path
sys.path.insert(0, os.path.abspath('../..'))
# -- Project information -----------------------------------------------------
project = 'Comet Toolbox'
copyright = '2026, Micha Burkhardt'
author = 'Micha Burkhardt'
release = '2026'
# -- General config... |
1e2bfde597f7a216520a4cb005a523852f331ea74166d1be36bee966a59022b2 | Python | 1,164 | 30 | import torch
from utils import common_functions as c_f
from losses.mixins import WeightRegularizerMixin
from losses.nca_loss import NCALoss
class ProxyNCALoss(WeightRegularizerMixin, NCALoss):
def __init__(self, num_classes, embedding_size, **kwargs):
super().__init__(**kwargs)
self.proxies = tor... |
242cb9c1f1bca1d8c047a6e9f6324007bf3b663bde90a8b6d35c77cd15babb2f | Python | 1,164 | 39 | """Build the Academy exchange factory matching a daemon config."""
from __future__ import annotations
from typing import Any
from chemgraph.academy.core.campaign import ChemGraphDaemonConfig
def build_exchange_factory(config: ChemGraphDaemonConfig) -> Any:
"""Return the Academy exchange factory matching ``conf... |
85d0adcc6613cf1917e4fe8d31e98910331eb06ad46125576a28469793030aee | Python | 1,164 | 36 | from nipype.interfaces.fsl import Reorient2Std
from PUMI.engine import BidsPipeline, NestedNode as Node, BidsApp
from PUMI.pipelines.anat.segmentation import bet_deepbet
@BidsPipeline(output_query={
'T1w': dict(
datatype='anat',
extension=['nii', 'nii.gz']
),
'bold': dict(
datatype=... |
97290807e108c1a35799644c0b780083d3bbfe1665fe58b6fa82a80a901c1a29 | Python | 1,164 | 45 | """ Helper utility functions. """
import os
import numpy as np
def create_dir(directory):
if not os.path.exists(directory):
os.mkdir(directory)
return directory
def log_string(log_file, log_str):
log_file.write(log_str + '\n')
log_file.flush()
print(log_str)
def iterate_in_chunks(l, n)... |
99b9c814ab233ae04bbeb8c1238013c443080dcb9dcdbaa0f125b2f5d2f519d0 | Python | 1,164 | 41 | # Copyright (c) Meta Platforms, Inc. and affiliates. All Rights Reserved
import math
class InverseSquareRootParamScheduler:
def __init__(
self,
base_lr: float,
warmup_steps: int,
cooldown_steps: int,
timescale: int,
):
self.base_lr = base_lr
self.warmup... |
cacdf93d1a0b2a540f570a1a136d45220f752766429a6bf5a6d393fe8018728f | Python | 1,164 | 43 | import pandas as pd
import sys
def find_unique_combinations(path):
# Combine path with params.txt
file_path = f'{path}/params.txt'
# Read the data from params.txt
df = pd.read_csv(file_path, sep="\s+", header=0)
# Group the data by the specified columns
grouped = df.groupby(['lambda', 'mu', ... |
9e235f889448ed34d7632f6e57fcd03fca720d1628eb4236766f9b55fe27e062 | Python | 1,165 | 53 | from .annotations import (
ClassifyOutput,
DASPick,
Detection,
DetectionList,
Pick,
PickList,
)
from .arraytools import pad_packed_sequence, torch_detrend
from .auxiliary import in_notebook, MissingOptionalDependency
from .decorators import log_lifecycle
from .file import (
callback_if_uncac... |
0322c10d83cac2443b46b7f59b4f7df8de2ac117b06207be041d5a22127d1410 | Python | 1,166 | 49 | import os.path
import sys
template='''
# Execute job in the queue "std.q" unless you have special requirements.
##$ -q std.q
##$ -q all_24.q
# The SGE batch system uses the current directory as working directory.
# Both files (output.dat and error.dat) will be placed in the current
# directory. The batch system assum... |
1d749f9120318c5bc04ad8a2c64793cde4e0d08e2f75049133e18a0d46631ca1 | Python | 1,166 | 46 | """
Build the Cython extension for the model_cython variant.
Run from this directory::
python setup.py build_ext --inplace
Or use the helper script::
python -m musclex.tests.fitting_ab.model_variants.model_cython.build
After building you will see a file named ``_eval_cy.cpython-3XX-*.so``
(Linux/macOS) or ... |
a2f58032c3051443251156395caeedabadd3a22adf2c04953389f187e692b780 | Python | 1,166 | 40 | from glob import glob
import os
import numpy as np
import h5py
import git
dsdir = 'IBLPATH/IBL_Passive'
dstdir = 'ZENODOPATH/preprocessing/metrics_extraction/timeselections/IBL_Passive'#
tintdur = 3.
ttag = 'passive'
savepattern = '%s__TSEL{}{}.h5'.format(ttag,int(tintdur)) #
myfiles = glob(os.path.join(dsdir,'*.nw... |
a6544505e9588ce2e7d3a728f256408dea47e54aae2270c67f3a7f4ce7234ae1 | Python | 1,166 | 27 | # /------------------------------------------------------------------------------+
# | 22-AUG-2022 |
# | Copyright (c) Bone Imaging Laboratory |
# | All rights reserved ... |
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