sha256 stringlengths 64 64 | language stringclasses 28
values | size int32 1 491k | lines int32 1 23.2k | content stringlengths 1 200k |
|---|---|---|---|---|
ed455b13b98b1dd3b9ba54cab30863b1e841610ad8346d689e02ba40a495396b | Python | 1,078 | 37 | """
Run a rest API exposing the yolov5s object detection model
"""
import argparse
import io
import torch
from PIL import Image
from flask import Flask, request
app = Flask(__name__)
DETECTION_URL = "/v1/object-detection/yolov5s"
@app.route(DETECTION_URL, methods=["POST"])
def predict():
if not request.method ... |
1c50dd7ad0ed0ffe0bb6329c5de3dfacfc27c4f2d67fb3167a7d4fd0961accb2 | Python | 1,079 | 30 | #!/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... |
952186976f89627adcb457c9496e9f1d08e3b562f9a87832b326e76d2993fc4e | Python | 1,079 | 29 | from enum import Enum, IntEnum
class PreprocessorSteps(IntEnum):
INPUT = 0
COREGISTERED = 1
ATLAS_REGISTERED = 2
ATLAS_CORRECTED = 3
N4_BIAS_CORRECTED = 4
BET = 5
DEFACED = 6
class Atlas(str, Enum):
BRATS_SRI24 = "brats_sri24.nii"
"""Slightly modified SRI24 atlas as found in the ... |
a1edbc643431a04076e9a649e3468f4da03eea67a2341dfb8db3e2d998d8138f | Python | 1,079 | 35 | """Test for QtHelp namespace."""
import pytest
from qtpy import PYQT5, PYQT_VERSION, QtHelp
def test_qthelp():
"""Test the qtpy.QtHelp namespace."""
assert QtHelp.QHelpContentItem is not None
assert QtHelp.QHelpContentModel is not None
assert QtHelp.QHelpContentWidget is not None
assert QtHelp.Q... |
ae44876d4f637094465d466435f7d8d9ccfb4abfe4afed49ff3d3448c3bd8d08 | Python | 1,079 | 33 | import os
from impedancefitter.utils import draw_scheme
# those were used for testing the code
# they do not work with LMFIT!!!
# they were just there to check that everything is alright
working = [
"R + C + L + CPE",
"RC + R + parallel(R, C) + parallel(R, C)",
"parallel(R + R, C + C)",
"parallel(R, ... |
468b980e4f886f64c7383aa73fb3d3d95c95618253c7d414d3cdae0fa95dd0e7 | Python | 1,080 | 27 | from bism.backends.unet import UNet_2D, UNet_3D
from bism.backends.unext import UNeXT_2D, UNeXT_3D
from bism.backends.r_unet import RUNeT_2D, RUNeT_3D
from bism.backends.cellpose_net import CPnet_2D, CPnet_3D
from bism.backends.unetplusplus import UNetPlusPlus_3D, UNetPlusPlus_2D
import torch.nn as nn
import torch
__... |
3d8c756b6d310ae8bd334a0af4b486502763608b2ed3e1bd411ad0250ad7069f | Python | 1,081 | 50 | #!/usr/bin/env python
"""
Read two lists of intervals (with chromosomes) and count the number of entries
in the second set that intersect any entry in the first set.
TODO: This could use bitsets rather than the intervals package, would it be
faster?
usage: %prog bed1 bed2 > out
"""
import sys
from bx import ... |
ad11ed212ecc5b0f85da5da67a326f362d795c3dbaae59d8da1fc46b6f59de2a | Python | 1,081 | 41 | #!/usr/bin/env python3
import sys
from optparse import OptionParser
USAGE = """
convert-dustout-to-bed.py --sddust <sddust file> --bed <output file>s
convert output of SDDust to bed format
"""
###############################################################################
parser = OptionParser(USAGE)
parser.add... |
beef6d1dccdf9d8877a33de1d7b9ab69b922abd1ace48f47979413a3f4587905 | Python | 1,081 | 49 | import os
# Model
MODEL_NAME = 'swin-unetr'
# Classes
ORGANS = ['glomeruli']
NUM_CLASSES = len(ORGANS) + 1 # +1 for background
# CZI Path
PROJECT_PATH = 'kidney_swinunetr'
DATA_PATH = '/hdd/yang/projects/glomeruli_segmentation/data/high-res_training/'
# CS Cluster
# PROJECT_PATH = '/home/zhouyang/kid... |
e05013cb8695f298d4decc14140c81a34001d15f70685749d68684c471afb370 | Python | 1,081 | 36 | """
calculate spearman's cor
"""
import sys
import numpy as np
import pandas as pd
import scipy.stats
from util import get_max_of_dict, get_min_of_dict, read_list, read_expr
import matplotlib.pyplot as plt
from itertools import product
from filter_gene import *
if __name__ == '__main__':
wt_expr = pd.read_csv(sys... |
28998d9433956051b434e65bb370e6abc550cbb0d6bbd4d606d46478aa3b96ba | Python | 1,083 | 45 | # -*- coding: utf-8 -*-
"""
Provides simple formatting tools to print text with parallel process header
"""
#:copyright: Copyright 2015 by Christoph Kirst, The Rockefeller University, New York City
#:license: GNU, see LICENSE.txt for details.
import sys
class ProcessWriter(object):
"""Class to handle writing fr... |
30d020ef94b9081e26a46d06cd6394ff5b899d1f1b2c9a64a9b52fe47ec051ef | Python | 1,083 | 31 | # -*- coding: utf-8 -*-
"""
Created on Wed Nov 6 21:32:30 2019
@author: Yoshi
"""
import numpy as np
from joblib import Parallel, delayed
from scipy.ndimage import gaussian_filter,gaussian_filter1d
def xyz_gaussian_filter(folder_images,x_sigma,y_sigma,z_sigma):
# Goes through each image and applies a 2D ... |
bf840582111de86f63eb3f930ec9f8bed03b465fdee14ea16dedf2ca8f33991b | Python | 1,083 | 40 | import exp_utils
import pandas as pd
import os
import math
import numpy as np
"Script to prepare possible positions for the 20 dot stimulus. To be read in later during the experiment to reduce computation time"
cond = 'constarea'
shape = 'dot'
vf_radius = 0.75
num = 20
# total area that will be maintained over all ... |
d8527f0546b0cead43e5f3ab6a956a2c77eaa8e6d6931e8d4bd00640b9990a8f | Python | 1,084 | 33 | import subprocess
import sys
import yaml
script_unit_couting = 'dataset_general/unit_counts.py'
script_feature_correlations = 'dataset_general/feature_correlations.py'
script_paraminteraction = 'dataset_general/parameter_interactions.py'
scripts = [script_unit_couting,script_feature_correlations]
scripts = [script_pa... |
f82818e8a2b947681e1daba4fe09097499ed1d4dd31a187984390dbb7d0a5683 | Python | 1,084 | 35 | """ Creating 2D mesh using constraints """
import SVMTK as svm
import numpy as np
from pathlib import Path
if __name__ == "__main__":
print("Start ",__file__)
outdir = Path("results")
outdir.mkdir(exist_ok=True)
slc = svm.Slice()
# Hexagon radius
r = 8
# Edges of a hexagon
hexagon =... |
efd7ac72dbc8edd4c2df06dbb84b5d2fc047713f54a9e31c4672760df9f32c81 | Python | 1,085 | 37 | # Copyright (C) CVAT.ai Corporation
#
# SPDX-License-Identifier: MIT
from django.core.management.base import BaseCommand
from cvat.apps.engine.models import Task
from ..utils import move_multiple_tasks, parse_task_ids
class Command(BaseCommand):
help = "Moves data of a given task from backing cloud storage bac... |
386168a5e1985a130711a5a106dcb147021c1dafca43e6ec032fd7aa51a55926 | Python | 1,086 | 37 | import tkinter as tk
from tkinter import filedialog
import pandas as pd
import matplotlib.pyplot as plt
def open_file():
# show dialog to select CSV(acceleration) file
file_path = filedialog.askopenfilename(
title="Select CSV(acceleration) file",
filetypes=[("CSV Files", "*.csv"), ("All Files",... |
4a90035633820a85096904ab4201010f25b960cfe797eb080a32adffa45c4ab0 | Python | 1,086 | 39 | # -*- coding: utf-8 -*-
"""
Created on Wed May 10 19:18:46 2017
"""
import numpy as np
#### Assess purity of a graph
def get_purity(node,neighbors,colors):
l=len([i for i in range(len(neighbors)) if colors[neighbors[i]]==colors[node]])
#return l*1.0/len(neighbors)
return l
def compute_overall_purity(node... |
d25447095c4580c0ef9f167e483264df69daedbba94c653c8a124ddfb94d8db8 | Python | 1,086 | 39 | #!/usr/bin/env python
"""
Hand run tests, not designed for CI as they will take a
while to run.
"""
from storm_control.test.hal.standardHalTest import halTest
def dave_sequence():
halTest(config_xml = "none_tcp_config.xml",
class_name = "StandardDaveSequence1",
test_module = "storm_contr... |
1819b8c193a8d0d058bfcac09c43098c8e58bdb23cce68c2568db14c77e49086 | Python | 1,087 | 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=['filtering.zip'])
tmp_dir = tempfile.Te... |
51c5aca76421453cb2880648b542e913b870ca8434f663c30e042193db9c1f2f | Python | 1,087 | 36 | from __future__ import annotations
import random
from dataclasses import replace
import numpy as np
from brainways.pipeline.brainways_params import BrainwaysParams, TPSTransformParams
def randomly_modified_params(params: BrainwaysParams):
modified_atlas = None
modified_affine = None
modified_tps = None... |
90b134a0b32e7787cc158c6e8f13502887d2d27a92df21f26b1d4fdb8460e893 | Python | 1,087 | 41 | # -*- coding: utf-8 -*-
from ast import literal_eval
from configparser import ConfigParser
from argparse import Namespace
class Config(ConfigParser):
def __init__(self, path):
super(Config, self).__init__()
self.read(path)
self.namespace = Namespace()
self.update(dict((name, lit... |
a1efbc2b3ed418dca55b0e8adb29e9afcc1e0ffbcb9a4f19c17ffe6dced645d5 | Python | 1,087 | 37 | __mindtibval__ = 0.5 # minimum DTI B-value
__maxdtibval__ = 1.5 # maximum DTI B-value
__mindkibval__ = 0.5 # minimum DKI B-value
__maxdkibval__ = 3.0 # maximum DKI B-value
__minfbibval__ = 4.0 # minimum FBI B-value
__maxfbibval__ = 12.0 # maximum FBI B-value
__d0__ = 3.0 # diffusivity of free water at body temp ... |
b795447f22e70485a343d4ae8581f0256189448dbed2a28329bcd3701dfee249 | Python | 1,087 | 29 | '''
PI voltage Z module
Alistair Boettiger, 07/19
adapted from Ludl (voltage controlled) Z stage functionality, George 02/18
not currently implemented -- it looks like I get all I need from mclVoltageZModule
possibly update for aesthetic quality later on.
'''
from PyQt5 import QtCore
import storm_control.... |
fe584e34d0d1bd3d0f6135ba7bfb0b1fb7ce68d20c143c9e906cdcda6fb86e87 | Python | 1,087 | 35 | # This file is part of connectome-manipulator.
#
# SPDX-License-Identifier: Apache-2.0
# Copyright (c) 2024 Blue Brain Project/EPFL
import os
import pytest
from bluepysnap import Circuit
from utils import TEST_DATA_DIR
from connectome_manipulator.connectome_manipulation.manipulation import Manipulation
from connecto... |
afa154e4cff9b987072a20411ee7842cd455dc1632f2ddd269d121bc207412ba | Python | 1,088 | 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... |
e88c04216934601a9731071539615f35f6a58dc97d01a77f509e6ed1736d0cd6 | Python | 1,088 | 38 | import unittest
import os, sys
sys.path.append(os.path.abspath(os.path.join(os.path.dirname(__file__), "../../")))
from heig.wgs.gwas import parse_ldr_col
class Test_parse_ldr_col(unittest.TestCase):
def test_good_cases(self):
target = (0, 3)
input_string = "1:3"
self.assertEqual(target,... |
4e06bb2c44b41f88e861646651b77f81d2d5abfc261162c9056fe9ec9e911d30 | Python | 1,089 | 36 | # Copyright (C) 2020-2022 Intel Corporation
#
# SPDX-License-Identifier: MIT
import json
import base64
from PIL import Image
import io
from model_handler import FaceDetectorHandler, AttributesExtractorHandler
def init_context(context):
context.logger.info("Init context... 0%")
# Read the DL model
conte... |
c02bb14844329cf8782d0da1acc99e55d42839c8e88e8716d733f02462400f2b | Python | 1,089 | 42 | # -*- coding: UTF-8 -*-
from __future__ import unicode_literals
import sys
import os
sys.path.append("../")
from whoosh.index import create_in
from whoosh.fields import *
from whoosh.qparser import QueryParser
from jieba.analyse import ChineseAnalyzer
analyzer = ChineseAnalyzer()
schema = Schema(title=TEXT(stored=Tr... |
2904063d722a30b6d98b44c3ddc3498152f1334aaa7e5a85ce8b47a07f30d792 | Python | 1,090 | 26 | from dtiplayground.dmri.common.tools.base import ExternalToolWrapper
class BRAINSFit(ExternalToolWrapper):
def __init__(self,binary_path= None, **kwargs):
super().__init__(binary_path, **kwargs)
def affine_registration(self,
fixed_path,
movi... |
8c9e6c13547e6bfbb09c9f8b8d795f813d975cfc944d29bf337118133c269ed1 | Python | 1,090 | 35 | from unittest.mock import MagicMock
from brainways.project.info_classes import (
BrainwaysParams,
MaskFileFormat,
SliceSelection,
)
from brainways.ui.controllers.cell_detector_controller import CellDetectorController
def test_enabled():
params = BrainwaysParams()
enabled = CellDetectorController.... |
f4880db3e2c53f7766a5a3fca65923ff311be768093ad5c23f775df180cf992c | Python | 1,090 | 28 | # -*- coding: utf-8 -*-
from scilpy.tests.dict import (dict_to_average, expected_dict_averaged,
dict_1, dict_2,
expected_merged_dict_12,
expected_merged_dict_12_recursive,
expected_merged_dict_12... |
17b31bae94e60674236e8b5963ac75b426247d95884f461fea6164dcbcda3add | Python | 1,091 | 31 | # Copyright (c) OpenMMLab. All rights reserved.
import logging
from mmcv.utils import get_logger
def get_root_logger(log_file=None, log_level=logging.INFO, name='mmcv'):
"""Get root logger and add a keyword filter to it.
The logger will be initialized if it has not been initialized. By default a
StreamH... |
72cecf06bad73f17183a36867474e6655171d3d4333b24888ace98c8b2198d7a | Python | 1,091 | 40 | ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ##
#
# See COPYING file distributed along with the gradunwarp package for the
# copyright and license terms.
#
### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ##
import logging
VERSION = '2.0.0alpha'
usage = ''... |
0e235665bebdfb592bfe4128c6fd45a0aeaf6181dfe5700632adcfb278f5b4f4 | Python | 1,092 | 43 | # -*- coding: utf-8 -*-
# python standard library inputs
import os
# external inputs
import nibabel as nb
def volume_threshold(file_in, prefix, data_max):
"""Volume threshold.
Takes a nifti volume and sets a maximum threshold value. All values above
the threshold are replaced by the threshold valu... |
92f3ac3b36771a349628f6d81623321d617aec92f6a1c75801454e60f0b2a794 | Python | 1,092 | 38 | from model_architectures import Generator
import nibabel as nib
from tensorflow import convert_to_tensor
from tensorflow.config import list_physical_devices
import numpy as np
##########INPUTS##############
mri_paths = # TO DEFINE
dest_paths = # TO DEFINE
weights_path = './iguane_weights.h5'
#############
if len(lis... |
acc1fb2775dd64706a6a20173d9d7289f7a57b5cf67d6e2dea9970b0df1325d5 | Python | 1,092 | 29 | # Copyright (C) 2018-2022 Intel Corporation
#
# SPDX-License-Identifier: MIT
from django.conf import settings
from django.http import HttpResponsePermanentRedirect
from drf_spectacular.utils import extend_schema
from rest_framework import status, viewsets
from rest_framework.decorators import action
from rest_framewor... |
0b2b1ad174012c6744c31230f9d1e133a3c8ad93dd2723bbaa5f2a32ad7842dd | Python | 1,093 | 30 | #!/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=['connectivity.zip'])
tmp_dir = tempfile... |
2b1491519f76c4d931965ff8ffcf44b33e32b1dc07b2565549e60732586853a7 | Python | 1,093 | 40 | from types import SimpleNamespace
import numpy as np
from napari_dmc_brainmap.results.probe_vis.probe_vis.view.ProbeVisualizer import (
ProbeVisualizer,
)
def test_organize_probe_keeps_coordinates_signed():
visualizer = SimpleNamespace(
probeDict={
"probe": {
"Voxel": [[0... |
7dc5236c60502696e40f64a148c82c69f357d87644e030f5ecf8e455e999f202 | Python | 1,093 | 33 | #!/usr/bin/env python
"""
HAL module for emulating an emission filter wheel.
Hazen 04/17
"""
import storm_control.hal4000.halLib.halMessage as halMessage
import storm_control.sc_hardware.baseClasses.filterWheelModule as filterWheelModule
class NoneEMFilterWheelFunctionality(filterWheelModule.FilterWheelFunctionali... |
91226a0a961d609e4ce693850cea265f297c1e196a3733636e178779d5f4257f | Python | 1,093 | 50 | # -*- coding: utf-8 -*-
# python standard library inputs
import os
def get_filename(file_in):
"""Get filename.
This function gets path, file name and file extension for an input filename.
The loop checks for some given extension names. Otherwise it stops after the
last found dot in the string. ... |
76307219cf51728012695883fd7542327c182be85b53842328b20a82debbc3ac | Python | 1,094 | 36 | import nibabel as nib
import pandas as pd
import numpy as np
from tensorflow import convert_to_tensor
from tensorflow.config import list_physical_devices
from model_architecture import Model
#########INPUTS#########
mri_paths = # to define
ids_dict = # to define
def intensity_norm(mri): # to define
def activation(ou... |
4c64dfff6947d1500303b28e0f4444eed3c3c132fc325943c6aa66dbc2d85db6 | Python | 1,095 | 37 | # Resume all interrupted trainings in yolov5/ dir including DDP trainings
# Usage: $ python utils/aws/resume.py
import os
import sys
from pathlib import Path
import torch
import yaml
sys.path.append('./') # to run '$ python *.py' files in subdirectories
port = 0 # --master_port
path = Path('').resolve()
for last ... |
ac41941feadb28dc806de423ba98f9136727f5af8411244df66d19acd6cef06b | Python | 1,095 | 41 | import nibabel as nib
import sys
import argparse
import numpy as np
def argument_parse(argv):
parser=argparse.ArgumentParser(description='Print dimensions for input volume or multiple input volumes')
parser.add_argument('volumefile',nargs='*',action='store',help='one or more input volumes (eg: .nii files... |
d67685a9f0eca2ffd5e13f2c2d4d51f2865f425df2a4e1196e4e57a945202693 | Python | 1,095 | 41 | #!/usr/bin/env python
"""
Test setting progressions.
"""
from storm_control.test.hal.standardHalTest import halTest
def test_hal_tcp_sp_1():
halTest(config_xml = "none_tcp_config.xml",
class_name = "SetProgression1",
show_gui = True,
test_module = "storm_control.test.hal.tcp_te... |
0e6436747a456a90f58de8170e4b759d37c075c8c4d0a936ad9f06de012f5870 | Python | 1,096 | 36 | class debugtest:
"""
A class to store molecular data and corresponding calculations for debugging and testing purposes.
Attributes
----------
molecules : list[str]
List of molecule identifiers used in test calculations.
exp_values : dict[str, float]
Dictionary mapping test iden... |
30d6f9006589839f30219e966a5c55f82bd777e7cd943dd8e772d83c3d19933e | Python | 1,096 | 38 | # -*- coding: utf-8 -*-
from collections.abc import Iterable
from flair.parser.utils.common import unk
class Vocab(object):
def __init__(self, counter, min_freq=1, specials=[]):
self.itos = specials
self.stoi = {token: i for i, token in enumerate(self.itos)}
self.extend([token for token... |
6a4c4667907f39a2e112263b906b05ea958f1e9f5a409ead5187dccd0f81a599 | Python | 1,096 | 27 | import nibabel as nib
import numpy as np
import os
def remove_region_from_mask(mask_path, dk_path, output_path, region_value=1):
# Load the binary mask and DK atlas
mask_img = nib.load(mask_path)
mask_data = mask_img.get_fdata()
dk_img = nib.load(dk_path)
dk_data = dk_img.get_fdata()
# Set ma... |
7daea2081e495455e0a6ec97af34e0e7146f59ccc2271cf3c893e3234a133125 | Python | 1,096 | 38 | # -----------------------------------------------------------------------------
# Copyright © 2009- The Spyder Development Team
#
# Licensed under the terms of the MIT License
# (see LICENSE.txt for details)
# -----------------------------------------------------------------------------
"""Provides QtNetworkAuth class... |
e0cd8f9fb886dbf286634e015f6a9aa5e220b1dbf90a260397922cfbaa6fb600 | Python | 1,096 | 30 | #!/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... |
2017c8dbcbac70d98eb0d1ad6a76e4172c79f4b9a013c3c9d79e383cb63d9558 | Python | 1,097 | 36 | # Copyright (c) DP Technology.
# 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.
"""isort:skip_file"""
import os
import sys
try:
from .version import __version__ # noqa
except ImportErro... |
3fb669f938f6737c88bde75c95962e7e76ec0153fb8b5e931d54534816b5045d | Python | 1,098 | 35 | import os
import unittest
from PUMI.engine import BidsPipeline
from PUMI.engine import NestedWorkflow
from PUMI.engine import NestedNode as Node
from nipype.interfaces.fsl import Reorient2Std
from PUMI.pipelines.func.deconfound import despiking_afni
project_root = os.path.dirname(os.path.abspath(__file__))
class Tes... |
4faa1f207bb3f25898e1619bf334b7aa9e9e759a8bb710dc15ffcda46e9e9e30 | Python | 1,098 | 35 | import pandas as pd
from rdkit import Chem
from rdkit.Chem import AllChem
from rdkit import DataStructs
import numpy as np
# Read CSV file
file_path = './2.construct_network/drug_smiles.csv'
df = pd.read_csv(file_path)
# Extract CID and SMILES
cids = df['drug_cid'].tolist()
smiles_list = df['smiles'].tolist()
# Con... |
b7c6a8fa05675f37faf0444c7bcd235b797c514633a5bcad803646c469fc2831 | Python | 1,098 | 35 | import os
from PUMI.engine import BidsPipeline
from PUMI.pipelines.func.deconfound import despiking_afni
ROOT_DIR = os.path.dirname(os.getcwd())
input_dir = os.path.join(ROOT_DIR, 'data_in/pumi-unittest') # path where the bids data is located
output_dir = os.path.join(ROOT_DIR,
'data_out') ... |
3c38603390add66e383fbb1117164476cd0f673af5fb855655b3e40f67321a5a | Python | 1,099 | 31 | from neuralib.atlas.brainrender.roi import RoiRenderCLI
from neuralib.util.utils import ensure_dir
from rscvp.atlas.dir import AbstractCCFDir
from rscvp.util.cli import RSCRoiClassifierDataFrame
from rscvp.util.io import RSCVP_CACHE_DIRECTORY
from rscvp.util.util_demo import run_demo
class ExampleRun(RoiRenderCLI):
... |
41acfa70a8759ab29590f9f4833f76f1128e375b77c7a72980d93e8746a39dda | Python | 1,099 | 65 |
import os
from pathlib import Path
class ModelConfig:
HIDDEN_CHANNELS = 576
OUT_CHANNELS = 72
NUM_LAYERS = 3
NUM_HEADS = 8
DROPOUT = 0.18
EDGE_ATTR_DIM = 6
USE_GATED_EDGE_ENCODER = True
USE_BOTTLENECK_TRANSFORM = True
USE_LATE_FUSION = True
... |
7411cf7011db153abcf9120e4e5caae8af2c554839dfc79c7b08a6021559979d | Python | 1,099 | 40 | import pandas as pd
import numpy as np
import os
from pcafeat import select_pca_features
np.random.seed(42)
n_samples = 100
n_features = 1000
df_X_train = pd.DataFrame(np.random.randn(n_samples, n_features))
df_X_train.columns = [f'feature_{i}' for i in range(n_features)]
target = pd.Series(np.random.randint(0, 2, n... |
c4fdfadff41b87568d44208a11db8457a9eb16dd37072bb69599439a9ee793b8 | Python | 1,099 | 30 | #!/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=['filtering.zip'])
tmp_dir = tempfile.Te... |
d497eb0b5cd5d53c1c1d225b81dc361a23170036d47e3bdca73f847d5caa0a0b | Python | 1,099 | 27 | import torch
from torch import nn
import torch.nn.functional as F
from .grad_rev_layer import GradReverse
class ImageDomainDiscriminator(nn.Module):
def __init__(self, in_channels: int):
super(ImageDomainDiscriminator, self).__init__()
self.net = nn.Sequential(
nn.Conv2d(in_channels, in... |
4f647d7c91501562628cf0fc9f214b9a4309067fa82676532688a90218a91b2d | Python | 1,100 | 36 | # Copyright (c) DP Technology.
# This source code is licensed under the MIT license found in the
# LICENSE file in the root directory of this source tree.
from functools import lru_cache
import numpy as np
import torch
from tokenizers import BertWordPieceTokenizer
from . import BaseWrapperDataset, LRUCacheDataset
... |
0f0107ee151183d613b87eac848c47c381e6701d504e6d23969f8159eaa1ff49 | Python | 1,101 | 38 | import sys
import pandas as pd
import numpy as np
def get_coords(index):
coords = pd.DataFrame(index=index)
coords['x'] = index.str.split('x').str.get(0).map(float)
coords['y'] = index.str.split('x').str.get(1).map(float)
return coords
def main():
for id in range(9, 12):
filename_data_input =... |
289256a63c656deb132fb3db9dfdaa0165a905ef7c9409b6a9a5cc12143cfefd | Python | 1,103 | 45 | # -*- coding: utf-8 -*-
"""
Created on Wed Dec 4 13:32:31 2019
@author: Yoshi
"""
import csv
def key_reader(path):
# Creates a list for frequencies and intensities
frequencies = []
intensities = []
# Creates an empty dict for the key
key = {}
# Opens key
open_key_file = ... |
7a85ba0ca51093d8fdb3ef838e8d6cc4d6a6812fcc521d6eb355c22c1e58e7ea | Python | 1,103 | 37 | # Generated by Django 3.2.18 on 2023-04-18 09:01
from django.db import migrations
class Migration(migrations.Migration):
dependencies = [
("engine", "0067_alter_cloudstorage_credentials_type"),
]
operations = [
migrations.AlterModelOptions(
name="clientfile",
opt... |
f00b57ed9bb6496902d49668cf43ac39181da8a03370706bad3a14f2d19093f1 | Python | 1,103 | 39 | import os
from datetime import datetime
import logging
from iso_analysis.io import load_eeg_data
from iso_analysis.analysis import run_iso_analysis
from iso_analysis.utils.logging import setup_logging
def main():
base_data_path = './data'
montage_paths = {
'32': 'eeg_ch_coords/coordinates32.xml',
... |
36faaa0d1976628ce5cf5438ab38ec3862894661538daac3cf9e0e4d8bf5588a | Python | 1,104 | 53 | """Get inferred parameters.
"""
from sys import argv
if len(argv) != 3:
print("Please pass the number of modes and run id, e.g. python 3_get_inf_params.py 6 1")
exit()
n_modes = int(argv[1])
run = int(argv[2])
#%% Import packages
print("Importing packages")
import os
import pickle
import numpy as np
from o... |
6a9ed000f08a40962edfadc36746804e410e831ddcb41fc736511546cbfb1b01 | Python | 1,104 | 33 | #! /usr/bin/env python3
class LossTracker:
def __init__(self, loss_names):
if "total_loss" not in loss_names:
loss_names.append("total_loss")
self.losses = {key: 0 for key in loss_names}
self.loss_weights = {key: 1 for key in loss_names}
def weight_the_losses(self, exclude... |
7adb8f783c7113e27657f1749c9d3fa7ce7dce9754749698f8b934cd700898aa | Python | 1,105 | 34 | """Deprecated compatibility shim for Anthropic model loading.
Construction now lives in ``chemgraph.models.endpoints.anthropic_direct`` behind
the Anthropic-native protocol builder. Prefer
``chemgraph.models.loader.load_chat_model``.
"""
from __future__ import annotations
import warnings
from langchain_anthropic im... |
d11ca8be187500a0b30463dfc237732b3a17fb936c034bc82ae9a15b97de6700 | Python | 1,105 | 39 | # Generated by Django 2.1.3 on 2018-12-05 13:24
import django.db.models.deletion
from django.db import migrations, models
class Migration(migrations.Migration):
initial = True
dependencies = [
("engine", "0014_job_max_shape_id"),
]
replaces = [("git", "0001_initial")]
operations = [
... |
f6518c28adc6e78328c4a2157400f0d0aba71c5c3bb8ad79a5c5d399c3192298 | Python | 1,105 | 40 | # Copyright (C) 2025 Intel Corporation
# Copyright (C) CVAT.ai Corporation
#
# SPDX-License-Identifier: MIT
import io
from collections.abc import Callable
from contextlib import closing
from typing import ClassVar
import attrs
from PIL import Image
from shared.tasks.base import TaskSpecBase
from shared.tasks.enums i... |
651644199aae928ece751bd3e0b62d6d2ad6af084bdb17aa8766101e95e295d1 | Python | 1,106 | 30 | import numpy as np
from brainscore_core import Metric
from brainscore_vision.metrics import Score
'''
This metric takes in two floats and gives a score between 0 and 1 based on
how far apart the numbers are, using a sigmoid function.
'''
class ValueDelta(Metric):
def __init__(self, scale: float = 1.00):
... |
a61332510e2baf352c7171573af1c738784e43b9ee18ce0b652055c97fba608c | Python | 1,106 | 32 | import seisbench
from .base import WaveformBenchmarkDataset
class Iquique(WaveformBenchmarkDataset):
"""
Iquique Benchmark Dataset of local events used for training in Woollam (2019)
study (see citation).
Splits are set using standard random sampling of :py:class:`seisbench.data.base.BenchmarkDatase... |
687f5910858f072c7f274d3b667e5326373690dd0eb056488969de56992e8456 | Python | 1,107 | 43 | #!/usr/bin/env python
"""
Mask out potential CpG sites from a maf. Restricted or inclusive definition
of CpG sites can be used. The total fraction masked is printed to stderr.
usage: %prog < input > output
-m, --mask=N: Character to use as mask ('?' is default)
-r, --restricted: Use restricted definition of C... |
95567043e05ea187b86364286906176f4d879fb5bc059f5aa3b87007f8819460 | Python | 1,107 | 32 | #!/usr/bin/env python3
# -*- coding: utf-8 -*-
import os
import tempfile
import numpy as np
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='surface_vtk_fib.zip... |
27cce82131d7fd4270e525049f93632a3e22407f8258954cbaf4ec81ab95e305 | Python | 1,108 | 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=['commit_amico.zip'])
tmp_dir = tempfile... |
e5344ace459e98d99813874384512501f5941afa94305af3725e21aeadce96a1 | Python | 1,108 | 42 | """Example script for testing if evoked responses are statistically significant.
"""
import numpy as np
from osl_dynamics.analysis import statistics
from osl_dynamics.utils import plotting
# Generate some random data
n_samples = 64
n_modes = 4
n_subjects = 24
epochs = np.random.randn(n_subjects, n_samples, n_modes... |
b91256a361a12e8f66ae0f5f2f64c5d301d352f9a438587723ae942cf30a23b8 | Python | 1,110 | 45 | from tensorflow.keras import mixed_precision
mixed_precision.set_global_policy("mixed_float16")
from tensorflow.keras.optimizers import Adam
from tensorflow.keras.optimizers.schedules import PolynomialDecay
import json
import sys
sys.path.append('..')
from model_architecture import Model
from input_pipeline.tf_datas... |
18f21f80ec650e874e2595b886cf7870d20a6535e13b54fc5b967aadd241c058 | Python | 1,111 | 43 | from scipy import stats
import numpy as np
from .base import Distribution
class Normal(Distribution):
"""Normal prior.
Parameters
----------
mean : scalar or ndarray
Mean of distribution
sd : scalar or ndarray
Standard deviation of distribution
Examples
--------
Defi... |
e04be4c9dc42f5fd9ac17b0c685e72687a08758b70d7ebdffa2217b577529f86 | Python | 1,111 | 43 | """test_locf.py"""
import numpy as np
import impyute as impy
from impyute.ops.testing import return_na_check
from impyute.ops import error
SHAPE = (5, 5)
def test_locf_(test_data):
data = test_data(SHAPE)
imputed = impy.locf(data)
return_na_check(imputed)
def test_na_at_i_start(test_data):
data = t... |
b0f03b1b2e665407fe9536c5d842c54f38826f24d4d7aa6295115d6f3dbd837a | Python | 1,112 | 27 | from pathlib import Path
from typing import Optional, Tuple
from aicsimageio.readers.czi_reader import CziReader
from PIL import Image
from tqdm import tqdm
from brainways.utils.image import resize_image, slice_to_uint8
def convert_czi_to_jpg(
input_path: Path, output_path: Path, size: Optional[Tuple[int, int]]... |
b912d75163a4dfd14257bb53cd4a5c336a1750061780e3ec6439d7d5cf6ac0a1 | Python | 1,112 | 35 | #!/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=['stats.zip'])
tmp_dir = tempfile.Tempor... |
dbafdaaf67a4f33f8a6d991cc071ddefd3975e77ef37346067dc152e9b8ab90d | Python | 1,112 | 55 | #!/usr/bin/env python3
import arbor as A
from mpi4py import MPI
import sys
T = 1000
dt = 0.025
class recipe(A.recipe):
def __init__(self, num=1):
A.recipe.__init__(self)
self.num = num
self.weight = 20.0
self.delay = 0.1
def num_cells(self):
return self.num
def ... |
0b4fdf413646f3514bc139fc6417c889e9ecdd1e1e960f86aa7304c4d0c52eea | Python | 1,113 | 42 | #!/usr/bin/env python
# -*- coding: utf-8 -*-
import jieba
import threading
def inittokenizer(tokenizer, group):
print('===> Thread %s:%s started' % (group, threading.current_thread().ident))
tokenizer.initialize()
print('<=== Thread %s:%s finished' % (group, threading.current_thread().ident))
tokrs1 = [jieba.Tok... |
0c3303b44f572589931309d06a879e44c0e3bf9e75a0c581c63504b4ded34d2f | Python | 1,113 | 37 | """Every module in the package must be importable.
Catches typo'd import paths and missing dependencies before they reach a user.
"""
import importlib
import pkgutil
import sys
import pytest
import histo_miner
MODULES = [m.name for m in pkgutil.walk_packages(histo_miner.__path__, "histo_miner.")]
# Packages declar... |
5a4837dfd01c6eeeacd31a3f7951037d132a58d301b4a4d51d05a1cca5b66052 | Python | 1,113 | 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=['bundles.zip'])
tmp_dir = tempfile.Temp... |
82b8d544c3cae4b4c178e3b446915f33ae2911025006705c58ef55dc070980ea | Python | 1,113 | 45 | from __future__ import division
from __future__ import print_function
import numpy as np
import scipy.sparse as sp
import torch
def normalize(mx): #
"""Row-normalize sparse matrix"""
rowsum = np.array(mx.sum(1))
r_inv = np.power(rowsum, -1).flatten()
r_inv[np.isinf(r_inv)] = 0.
r_mat_inv = sp.di... |
0a6878d50bb7ceffc73b4bce49702e220a7b136622090f29cba8fd2b3d4897a6 | Python | 1,114 | 29 | import click
from brainways.scripts.batch_create_thumbnails import batch_create_thumbnails
from brainways.scripts.create_excel import create_excel
from brainways.scripts.create_reg_model_data import create_reg_model_data
from brainways.scripts.import_cell_detections_keren import import_cell_detections_keren
from brain... |
5376ee8a9f91e4ebe29b2308d59adad5a9c5f026e41eb4b86a97b93e461895be | Python | 1,114 | 23 | import os
from nipype.interfaces.base import (CommandLineInputSpec, CommandLine, traits, TraitedSpec, BaseInterface, BaseInterfaceInputSpec, File)
from traits.api import Directory, Str, List, Bool, Enum, Int, Float, TraitError, Either
####################
# Make BIANCA mask #
####################
class MakeBIANCAMaskI... |
593f126a819237dbcec4c7ab2b1ec66d26d98c93f159e8924cd389a2f8954c09 | Python | 1,114 | 33 | # src/models/regression_model.py
"""
Multi-output regression MLP for 8 surgical doses (0–10 mm).
"""
from __future__ import annotations
import torch, torch.nn as nn
from src.config import C
class RegressionModel(nn.Module):
def __init__(self):
super().__init__()
in_dim = getattr(C, "INPUT_DIM"... |
5b96206b419b9ba799920efcf3f34a7a216ad60c961bfd533425ee1e17836d16 | Python | 1,114 | 39 | import string
import sys
import os
import glob
import re
import csv, logging
PROTEOMIC_DATA_FILE = '../data/hsa_nagaraj/hsa_actin_tubulin_abundance.csv'
KO_TO_UNIPROT_FILE = '../data/KO_gene_hierarchy/KO_gene_hierarchy_organism_mapping/hsa_mapping.csv'
OUTPUT_PATH = '../res/hsa_nagaraj/'
if not os.path.exists(OUTPUT_P... |
6cd306967aeeb1eb1219692f42246b4b5939b7784d41732ccfc2a6f318fddb25 | Python | 1,115 | 54 | import os
# Model
MODEL_NAME = 'unetr'
# wandb logging
WANDB_LOG = False
# Classes
ORGANS = ['glomeruli']
NUM_CLASSES = len(ORGANS) + 1 # +1 for background
# CZI Path
# PROJECT_PATH = '/hdd/yang/kidney_seg/kidney_unetr'
# DATA_PATH = '/hdd/yang/data/kidney_seg'
# CS Cluster
# PROJECT_PATH = '/home/zhouyang/kidne... |
91d158ff485807ebebcbd9c5139b5b2f158bf12291f2d2f79b2b2b881133f8ea | Python | 1,115 | 31 | import numpy as np
import torch
from sklearn.metrics import mean_absolute_error, mean_squared_error, r2_score
@torch.no_grad()
def evaluate(model, X, y_scaled, device, radius_max):
model.eval()
preds = model(torch.from_numpy(X).to(device)).cpu().numpy()
y_pred = np.zeros_like(preds)
y_pred[:... |
9602f62346397fced7e5831d6f6d805db51a512d6eecd4ed38a519911aab3e55 | Python | 1,116 | 69 | from .application import ApplicationBackend
from .widgets import (
CheckBox,
ComboBox,
Container,
DateEdit,
DateTimeEdit,
FloatRangeSlider,
FloatSlider,
FloatSpinBox,
Image,
Label,
LineEdit,
LiteralEvalLineEdit,
MainWindow,
Menu,
MenuBar,
Password,
Pro... |
9b1e1d4685439a45ab0252670fad04422f2377f0dd2b603b8fb3ae9ad56d633a | Python | 1,116 | 52 | import os
import os.path
import shutil
def double_quote(v):
return '"{}"'.format(v)
def recreate_dirs(dir_paths):
for dir_path in dir_paths:
if os.path.isdir(dir_path):
shutil.rmtree(dir_path)
os.makedirs(dir_path)
def gene_id_str(n):
# pad n with '0' on the left to make i... |
4d6a978532cfbdfea003ab028a4284365b668ab4e6ac1a00c128ce40db8d3181 | Python | 1,118 | 39 | """ Create a 3D mesh with conforming bifurcation """
import SVMTK as svm
from pathlib import Path
if __name__ == "__main__":
print("Start ",__file__)
surf = svm.Surface()
outdir = Path("results")
outdir.mkdir(exist_ok=True)
# Cube corner coordinates and edge length.
x0,y0,z0,x1,y1,z1, edge_le... |
703d2aa81daccaf246973c147df8d499598eb7fe4ed33ef46b28aadfa3f92df8 | Python | 1,118 | 30 | import os
def split_file():
"""
To split up a donor file into chunks to test effect of sample size on training
"""
current_dir = os.path.dirname(__file__)
for fold in range(10):
original_file_path = os.path.join(current_dir,f'gtex/cv_folds/person_ids-train-fold{fold}.txt')
# Read a... |
9519d857e6971835d1b101a90bf3ea70a0d9355052e65105c5d512ea1ba3052f | Python | 1,118 | 42 | """ Export slice meshes as surface in 3D """
import SVMTK as svm
from pathlib import Path
if __name__ == "__main__":
print("Start ",__file__)
outdir = Path("results")
outdir.mkdir(exist_ok=True)
# Load Surface
surf = svm.Surface("../Data/lh-pial.stl")
### Create and export slice mesh 1 #... |
b336e948a99da3a2c111327aa9e1d31f6e1744305890bd854efa8812ed46bcce | Python | 1,118 | 28 | import os
from typing import Tuple
from dotenv import load_dotenv
from util.io import MissingEnvironmentVariables
def get_environment_variables() -> Tuple[str, str, str, str]:
"""
Gets the environment variables needed for logging into the XNAT-Server.
Please set environment variables in a .env file in the... |
f9d5a7520bc2b30bd78fbd00cba0543c1e24018e359a6272aad028e970d3b0dd | Python | 1,118 | 39 | """ Create 3D mesh with two conforming edge helixes inside """
import SVMTK as svm
import numpy as np
from pathlib import Path
if __name__ == "__main__":
print("Start ",__file__)
surf = svm.Surface();
outdir = Path("results")
outdir.mkdir(exist_ok=True)
# Lower center coordinates
x0,y0,z0 =... |
259d53f8eb1d04ff125a14d9d0dc05cebc53df4f8671a33c5e47e4c743893b9d | Python | 1,119 | 32 | import pytest
from chemgraph.agent.llm_agent import ChemGraph
from unittest.mock import Mock, patch
from langchain_core.messages import HumanMessage, AIMessage
@pytest.fixture
def mock_llm():
return Mock()
def test_chemgraph_initialization():
with patch("chemgraph.agent.llm_agent.load_openai_model") as mock... |
6a76c100bc949fe8a4a004c54e7b8e25d58ba005745773dde2e54f39a4534f55 | Python | 1,119 | 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='surface_vtk_fib.zip')
tmp_dir = tempfil... |
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