sha256 stringlengths 64 64 | language stringclasses 28
values | size int32 1 491k | lines int32 1 23.2k | content stringlengths 1 200k |
|---|---|---|---|---|
882dd52cf859d070f594f676906b77241e64576357d39e91bd5d87148aac025a | Python | 3,121 | 85 | import glob
import os.path as osp
import re
from ..utils.data import BaseImageDataset
def process_dir(dir_path, relabel=False):
img_paths = glob.glob(osp.join(dir_path, "*.jpg"))
pattern = re.compile(r"([-\d]+)_c(\d)")
# get all identities
pid_container = set()
for img_path in img_paths:
... |
a08cd82723f8d265859c572f1407b75979fba719be4bdbf0ceb7763b8787b823 | Python | 3,121 | 82 | import numpy as np
import torch
import torch.utils.data as data_utils
class DatasetLoader:
def __init__(self, all_dataset, batch_size):
self.all_dataset = all_dataset
self.batch_size = batch_size
@staticmethod
def worker_init_fn(worker_id):
np.random.seed(np.random.get_state()[1][... |
b4b56ff7d367402b88214d67c60546187b82d16a5dbe4288daac6713d3d06c3f | Python | 3,121 | 105 | import os
import os.path as osp
import numpy as np
import torch
from torch.utils.data import Dataset
import cv2
import matplotlib.pyplot as plt
import albumentations as A
from PIL import Image
from albumentations.pytorch import ToTensorV2
def get_training_transform():
return A.Compose(
[
A.Resize(25... |
e386ce522b277938f064f87294a9fdfcdee5d063acd790d465943cd25c0c0845 | Python | 3,121 | 75 | # Copyright (c) Meta Platforms, Inc. and affiliates. All Rights Reserved
from torch import nn
from torchvision.ops import roi_align
# NOTE: torchvision's RoIAlign has a different default aligned=False
class ROIAlign(nn.Module):
def __init__(self, output_size, spatial_scale, sampling_ratio, aligned=True):
... |
1294cd258cbce4255968bb657ae33e1b5482035a30382def7445898c542dd91d | Python | 3,123 | 100 | # Copyright (c) 2019 PaddlePaddle Authors. All Rights Reserved.
#
# 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 app... |
69e55750e4f4f850c80f2282c1c3a6f98369d732889549eacb9896a441cba914 | Python | 3,123 | 91 | # Copyright (C) 2021-2022 Intel Corporation
# Copyright (C) CVAT.ai Corporation
#
# SPDX-License-Identifier: MIT
from drf_spectacular.utils import OpenApiParameter
from rest_framework.filters import BaseFilterBackend
ORG_SLUG_PARAM_DESCRIPTION = """\
Organization unique slug.
If omitted, results from all organization... |
7c5403063456538348556e82fdf106f0d7938e524ff5d750fd73ff5f6a75ffc3 | Python | 3,123 | 64 | # -*- coding: utf-8 -*-
import pandas, numpy, math, multiprocessing, os
from scipy.stats import chisquare
from scipy.spatial import distance
from functools import partial
import matplotlib.pyplot as plt
from matplotlib.ticker import EngFormatter, FormatStrFormatter
def find_average_rho(dots, dot, dc,... |
9d69354b39207693b4e26dcc3a746986025691e488e8275f790843184f5a3526 | Python | 3,123 | 105 | # -*- coding: utf-8 -*-
"""
Gradient nonlinearity correction of time series
This scripts calls the HCP toolbox to correct for gradient nonlinearities in the
input time series. The corrected time series gets the suffix _gnlcorr. The
script needs an installation of fsl.
Dependencies:
- gradunwarp: https://github.com/Wa... |
6ebf3fe8676acef3bca73363afbcd43c940e443fca62bbb31b430fd3677c6d34 | Python | 3,124 | 101 | from psychopy import prefs # noqa
prefs.hardware['audioLib'] = ['PTB', 'sounddevice', 'pyo', 'pygame'] # noqa
from psychopy import visual, core, event, sound, __version__, monitors
import os
from psychopy.hardware import keyboard
import random
# stop the script by pressing escape
def prepare_audio_stim(categories=... |
4af1a2711dfddfaf939cd355a2e3266935fa352a910393c253fe4c65ab83d1a5 | Python | 3,125 | 94 | import sys
import getopt
import json
import scipy.ndimage as nd
from skimage import io as skio
import numpy as np
from PIL import ImageFile
from PIL import Image
ImageFile.LOAD_TRUNCATED_IMAGES = True
Image.MAX_IMAGE_PIXELS = None
# usage
def affine_ssdna_usage():
print("""
Usage : affine_ssdna.py -i <input.tif/... |
6034fd1ab5f21982ec9cb22f000da4def8c250c44653d9ed180dc3185e86b2cc | Python | 3,125 | 98 | import spams
import numpy as np
import cv2
import time
class vahadane(object):
def __init__(self, STAIN_NUM=2, THRESH=0.9, LAMBDA1=0.01, LAMBDA2=0.01, ITER=100, fast_mode=0, getH_mode=0):
self.STAIN_NUM = STAIN_NUM
self.THRESH = THRESH
self.LAMBDA1 = LAMBDA1
self.LAMBDA2 = LAM... |
16096899c8dc821609a5004f6516f99e8c8660e759b3887caca87daaf74b7d80 | Python | 3,126 | 114 | """Utility functions for data loading operations."""
from typing import Any
import numpy as np
from mcmlnet.utils.tensor import (
TensorType,
array_conversion_decorator,
)
def subsample_data(
data: TensorType, subsample_size: int, random_seed: int = 42
) -> TensorType:
"""Subsample data to a specif... |
26740876ff1b6649c2fe1d12110a45db3b0c2678d8e9de2f9f7d9a770d2f9924 | Python | 3,126 | 81 | 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
stimuli = []
image_paths = {}
stimuli_directory = '../datasets/low-pass/dnn/session-1'
'''
Dataset Meta Info (from http... |
0ceef905f345086a73aad3fb515263a1887dfc5e3cf13667f7b8e70813a85245 | Python | 3,127 | 95 | import os
from importlib import import_module
from pathlib import Path
cell_graph_config = {
"cell_f_list": [
'fourier',
10,
False,
[
'area',
'r_equiv',
'r_maj',
'r_min',
'angel',
'ecc',
'maj_x',
... |
7acabdf6575f0b3bda69fa647150af4dafb1039ea2d5fe44d823ebfaa5becf52 | Python | 3,127 | 82 | 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
stimuli = []
image_paths = {}
stimuli_directory = '../datasets/rotation/dnn/session-1'
'''
Dataset Meta Info (from http... |
8b3246dcddc5cbd05e9edece4d92d623244d24adcafdcaa6c34f50eb215b7bfc | Python | 3,127 | 86 | import json
import pandas as pd
import pytest
from metaprivBIDS.cli import main
@pytest.fixture
def input_file(tmp_path):
path = tmp_path / "input.csv"
pd.DataFrame(
{
"ID": [101, 202, 303, 404, 505],
"age": [25.5, 35.5, 45.5, 25.5, 35.5],
"city": ["A", "B", "A", ... |
b314f0d5d759460243b927b7ed74605cef238ead93bd2cd6e32e69ab52c5525a | Python | 3,127 | 82 | #############################################################################
# Copyright (C) 2020-2026 MEmilio
#
# Authors: Daniel Abele
#
# 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 Licen... |
78000be1bceceae0355e6d7de7b55b9d8f4a4f87bb08e827cc4dc156cc75be90 | Python | 3,128 | 109 | # %% ### 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 / "cs_b_results.xlsx")
# combine Estimate and Std. Error to Estimate (Std. Error)
# round to 5 decimal places
df["Estimate"] = df["... |
e795ca8dceaeaf6d9127d3b2647d9d3582414410fbcaad5c5b23d53e476c284f | Python | 3,128 | 91 | from dataclasses import dataclass
from typing import TYPE_CHECKING
import torch
from torch import nn
from eir.models.layers.mlp_layers import MLPResidualBlock, ResidualMLPConfig
from eir.models.models_utils import create_multi_task_blocks_with_first_adaptor_block
if TYPE_CHECKING:
from eir.setup.output_setup_mod... |
42880cd2af4936ea73f6934597487849aa917d162ee8d0368d42d8b84fbe6a75 | Python | 3,130 | 82 | 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
stimuli = []
image_paths = {}
stimuli_directory = '../datasets/high-pass/dnn/session-1'
'''
Dataset Meta Info (from htt... |
e9de113d9d5f6607fb378bc551d498e02696351a1ec0e90e781cb35499481003 | Python | 3,130 | 108 | import os
import tempfile
from typing import List
import ngs_tools as ngs
from ..config import (
PLATFORM,
TECHNOLOGIES_MAPPING,
UnsupportedOSError,
)
def run_executable(command: List[str], quiet: bool = False, *args, **kwargs):
"""Dry version of `utils.run_executable`.
"""
command = [str(c)... |
0137029c0d8673ee8e6d20c61229d4bbc8a2ac2ebc8e001830d2dd02a250ae17 | Python | 3,131 | 74 | #!/usr/bin/env python
import SimpleITK as sitk
import numpy as np
import os
import argparse
def segment_air(input_file: str, output_mask_file: str, air_max_threshold: float = -990, air_min_threshold: float = -1010):
"""
Segments air from a NIfTI image using a simple thresholding method.
Parameters:
... |
16ad3917c2558e0894739a9c8ce5229bbda6c9a1671877d4e3ef852574c9e72e | Python | 3,131 | 89 | # emacs: -*- mode: python; py-indent-offset: 4; indent-tabs-mode: nil -*-
# vi: set ft=python sts=4 ts=4 sw=4 et:
#
# STATEMENT OF CHANGES: This file is derived from sources licensed under the Apache-2.0 terms,
# and this file has been changed.
# The original file this work derives from is found at:
# https://github.co... |
4189d00213c3acc403ca7e613ad8923e77f1316f0de9dc2ac60d307fca03bd68 | Python | 3,131 | 71 | import os
import nibabel as nib
from dipy.core.gradients import gradient_table
from dipy.data import fetch_hbn
import dipy.reconst.dti as dti
import dipy.reconst.fwdti as fwdti
import numpy as np
from nipype.interfaces.base import BaseInterface, BaseInterfaceInputSpec, TraitedSpec, File, Directory, traits, CommandLineI... |
748166fd025ba770128046b98cd57c1062160d2bc988a3e6ef460147e71f81fd | Python | 3,131 | 95 | # Copyright (C) CVAT.ai Corporation
#
# SPDX-License-Identifier: MIT
"""Prepare the Moto S3 server for cloud storage tests.
Create the fixture buckets, upload sample files and manifests, enable anonymous
access to the public bucket, and create an empty bucket for backing storage.
Connection settings and credentials c... |
7efe52375b5ad29dc5986caebe5c5f54ebbd5499c3e03d910bf2364b9d40ee10 | Python | 3,132 | 58 | # -*- coding: utf-8 -*-
"""
Created on Fri Oct 21 12:34:47 2022
@author: tianj
"""
import numpy as np
import torch
import os
import generator
import dataset
from dataset import DECAMDataSet
from generator import Generator
patch_size=3
for subj in ['25Q']:
for epoch_label in [40]:
for s ... |
39414ee92ef539ec811e94fc8ef623989c871f3ff0ae54840e26a4de0c7f0651 | Python | 3,133 | 82 | 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
stimuli = []
image_paths = {}
stimuli_directory = '../datasets/eidolonI/dnn/session-1'
'''
Dataset Meta Info (from http... |
bec329f9241528ce028da44006db847f642659e2f5585fa16fd1288c1a8a233f | Python | 3,133 | 95 | # Generated by Django 4.2.14 on 2024-07-22 07:27
import django.db.models.deletion
from django.db import migrations, models
class Migration(migrations.Migration):
dependencies = [
("engine", "0081_job_assignee_updated_date_and_more"),
]
operations = [
migrations.AlterField(
m... |
fbe9e809e118e2927532b76538d54d68ef6403c206b4245e71212e3f3bc5603e | Python | 3,133 | 100 | # -*- coding: utf-8 -*-
from dipy.utils.deprecator import cmp_pkg_version, ExpiredDeprecationError
from functools import wraps
from packaging.version import parse
import warnings
from scilpy import version
class ScilpyExpiredDeprecation(ExpiredDeprecationError):
pass
DEFAULT_SEPARATOR = "="
DEFAULT_DEPRECATIO... |
84ba6bf6ce1c5d73113070b1738489e8a57f113b7405db09ce42cc1328cfe2b9 | Python | 3,134 | 82 | 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
stimuli = []
image_paths = {}
stimuli_directory = '../datasets/contrast/dnn/session-1'
'''
Dataset Meta Info (from http... |
10ffaa44bfc609c3945dc31fcf991892dce7c659ba5a120e2b948e4311fb1f85 | Python | 3,135 | 69 | from qtpy.QtCore import Qt
from qtpy.QtWidgets import QWidget, QHBoxLayout, QSpinBox,QLabel,QPushButton,QDoubleSpinBox
import numpy as np
class AnchorRow(QWidget):
def __init__(self, regHelper):
super().__init__()
self.regHelper = regHelper
# create horizontal layout
self.anc_hbox =... |
316881f277125ff5ac7f93cde0f2fb10e2bb54c3013ffda25dda253c228af44f | Python | 3,135 | 101 | """
Run XANES workflows via the ChemGraph agent using MCP HTTP transport.
Connects to an already-running XANES MCP server via HTTP. The LLM agent
receives the XANES MCP tools and uses them to fulfill the natural language
prompt.
Prerequisites:
- XANES MCP server running (via start_mcp_server.sub or manually)
- S... |
8fd223a983503940c6238e53e5098ed9cd46193e7354b5f2a778410d50e9872a | Python | 3,135 | 82 | 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
stimuli = []
image_paths = {}
stimuli_directory = '../datasets/eidolonII/dnn/session-1'
'''
Dataset Meta Info (from htt... |
96517916d9d6a1a02d7b1ea9a186337a2c84e87a9162b73b7286286bb8ccfb05 | Python | 3,136 | 69 | from PyQt5.QtCore import Qt
from PyQt5.QtWidgets import QWidget, QHBoxLayout, QSpinBox,QLabel,QPushButton,QDoubleSpinBox
import numpy as np
class AnchorRow(QWidget):
def __init__(self, regHelper):
super().__init__()
self.regHelper = regHelper
# create horizontal layout
self.anc_hbox... |
5b8d3c7ab6ce8d6aebbd5c1740b886c77c91f069694e3dd8a4f8ae431a7d3420 | Python | 3,137 | 71 | import numpy as np
import numpy.testing as npt
import pytest
#import torch
from utilities.data_simulation.GenerateData import GenerateData
#run using python -m pytest from the root folder
test_monoexponential_data = [
pytest.param(0, np.linspace(0, 1000, 11), id='0'),
pytest.param(0.1, np.linspace(0, 1000, 1... |
7bef2274f2bc87926c5cd44fad8d4571b9b17f9ac4299c37c3d91fc0093f5455 | Python | 3,137 | 82 | 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
stimuli = []
image_paths = {}
stimuli_directory = '../datasets/eidolonIII/dnn/session-1'
'''
Dataset Meta Info (from ht... |
b1c2e6a4f687ecf17b623ece5df48d237820d172c5574fc64efec6db3d55941d | Python | 3,138 | 91 | import os
import numpy as np
available_gpus = ['0,6', '6,0']
parallel_starts = 8
# args dict
args_dict = {'device': 7, # gpu
'log_steps': 1,
'num_layers': 3,
'hidden_channels': 256,
'dropout': 0.0,
'batch_size': 64 * 1024,
'lr': 1.e-03,
'epo... |
07772027f903b555e160cf76a9c50a7f6494bba5287171c0f82c5c0800cc5820 | Python | 3,139 | 83 | """Tests for the `morphometrics status` command (derived from work_dir artifacts)."""
from click.testing import CliRunner
from surface_morphometrics.status import status_cli, _refine_status
def _touch(path):
open(path, "w").close()
def _csv(path, columns):
with open(path, "w") as handle:
handle.wri... |
7e55e981ef7426613ebeb9f34e18c041dcaf04d58e00c4083bd5fdaa8e602ca9 | Python | 3,140 | 109 | import datetime as dt
import json
import os
import sys
from typing import Dict, List, Optional, Union
from . import __version__
from .config import (
get_bustools_binary_path,
get_kallisto_binary_path,
is_dry,
)
from .dry import dummy_function
from .dry import dryable
class Stats:
"""Class used to co... |
1c216f2173afd9ee319e62850fae1876c07975e3b464da247c45138d31e05d0e | Python | 3,141 | 67 | # Ultralytics 🚀 AGPL-3.0 License - https://ultralytics.com/license
from __future__ import annotations
from pathlib import Path
from ultralytics import SAM, YOLO
def auto_annotate(
data: str | Path,
det_model: str = "yolo26x.pt",
sam_model: str = "sam_b.pt",
device: str = "",
conf: float = 0.25... |
3ddff1e0057f73fd2865f82cbf48f83f8711f92d319e516bd013567d9cde01d1 | Python | 3,143 | 82 | 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
stimuli = []
image_paths = {}
stimuli_directory = '../datasets/phase-scrambling/dnn/session-1'
'''
Dataset Meta Info (f... |
d8b1da72fa65aa703978b47fbc1c59f5c1f865210bb1cb2ac43827d6da3f52d6 | Python | 3,143 | 82 | 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
stimuli = []
image_paths = {}
stimuli_directory = '../datasets/uniform-noise/dnn/session-1'
'''
Dataset Meta Info (from... |
cb29106110502610ee895b7ca78d96bd0698f7762ddaabf1b2133232fa0a5887 | Python | 3,144 | 86 | """
EC_GridSearch
@ 2022 Knowblesse
Find the best hyperparameter for EV
"""
import numpy as np
from numpy.random import default_rng
from pathlib import Path
import sklearn
from sklearn.metrics import confusion_matrix
from sklearn.svm import SVC
from sklearn.model_selection import LeaveOneOut
from sklearn.metrics import... |
3ca1139aae5627584c459859b61a0e55767a4079f679eb3d08575e7e5341de59 | Python | 3,146 | 93 | # -*- coding: utf-8 -*-
"""
Created on Wed Jun 4 17:55:18 2025
@author: giga
"""
import pandas as pd
import numpy as np
import os
from pathlib import Path
# Define the base directory and model names
base_dir = r"D:\1Grok\Output"
models = ["ANFIS", "ANN", "Transformer", "SVR", "LightGBM", "XGBoost", "E... |
579d2307c618ea2cb14c755df7b8487c7c69f2b8393558f52904546255d9f34e | Python | 3,146 | 112 | import arbor as A
from arbor import units as U
import numpy as np
import subprocess as sp
from pathlib import Path
# Spherical geometry from the paper
# - V = 4/3 pi r^3 = pi r^3
# - A = 4 pi r^2
# now compute the equivalent square
# cylinder mantle:
# - A = 2 pi l^2
VOLUME = 2160
RADIUS = (0.75 * VOLUME / np.pi) **... |
bb96ea10e8a1b8ec19428cc5e3a2891df7f58e3c4b546cc62365d01fa13e0f94 | Python | 3,146 | 95 | import click
import os
import numpy as np
from torch.utils.data import DataLoader
import torch
from pli_cyto.models.dft_style import DFTStyleLitModule
from pli_cyto.models.dft_wgan import DFTGanLitModule
from pli_cyto.utils.files import get_files, save_section, create_cyto
from pli_cyto.datamodules.components.sectio... |
03e564ff713039030bb66dabec5dc225c09233d571f83e8ebe512795199c91b6 | Python | 3,148 | 101 | import hashlib
from pathlib import Path
import subprocess as sp
import shutil
try:
from rich import print
except ImportError: # pragma: no cover - optional dependency for nicer CLI output
pass
def calcHash(filepath):
return hashlib.md5(
open(filepath, 'rb').read()
).hexdigest()
def shipResu... |
62df1cf773dfaf596f7664a7f676e3ca7abdf50f4370412fbc38bdd6932df5e2 | Python | 3,148 | 76 | from torch.utils.data import DataLoader
from geoseg.losses import *
from geoseg.datasets.cvc_clinic import CVC_Dataset
from geoseg.models.deepunet.DeepUnet import Model
from catalyst.contrib.nn import Lookahead
from catalyst import utils
CLASSES=('background', 'foreground')
# training hparam
max_epoch = 100
ignore_i... |
b462c7fd08ce91a38c3286f5b6b6ddf61c43f295de58132c498201a1be4ad235 | Python | 3,148 | 82 | 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
stimuli = []
image_paths = {}
stimuli_directory = '../datasets/power-equalisation/dnn/session-1'
'''
Dataset Meta Info ... |
d8ace0ba95c8b750ae67f2a12e0074fc99460b16b394062d192a2957218a3cc6 | Python | 3,148 | 101 | # Copyright (C) CVAT.ai Corporation
#
# SPDX-License-Identifier: MIT
import io
import zipfile
from pathlib import Path
from typing import TypeAlias
import pytest
from cvat_sdk.core.proxies.jobs import Job
from cvat_sdk.core.proxies.projects import Project
from cvat_sdk.core.proxies.tasks import Task
from cvat_sdk.core... |
72dbbdb313e9175de765098897be87203accfa9552898a702e002f964ee44c6d | Python | 3,149 | 89 | '''Test the standard calibration class'''
import unittest
from ogo.calibration.standard_calibration import StandardCalibration
import os
class TestStandardCalibration(unittest.TestCase):
'''Test the standard calibration class'''
def test_can_instantiate(self):
'''As an inherited class from an abstra... |
7daec36ae796740cf1f50e7f17b5281a1db961320fd1f2b2aba579a51cf012cf | Python | 3,151 | 77 | from generative.networks.nets import VQVAE
import torch.nn as nn
import torch
from kornia.losses import SSIMLoss
import os
from PIL import Image
import numpy as np
class LdmVQVAE(VQVAE):
def __init__(self, log_image_epoch, log_path, ckpt_path=None, *args, **kwargs):
super().__init__(num_channels=(128, 256)... |
2b1cb96633f5f9762bb3871e081895fb4ac358a8cec8b05fb7b5644b30cbf5a4 | Python | 3,153 | 80 | # -*- coding: utf-8 -*-
"""
Created on Mon Jun 5 14:27:32 2023
@author: DODO
"""
import numpy as np
import sys
import os
import datetime
import matplotlib.pyplot as plt
import scipy.interpolate as itp
import warnings
warnings.filterwarnings('ignore')
def b_constraint_fromabaqus(TASK_NAME = "202310... |
46531db0410ddecbc548867fb96769a266278efaa8423a1af94ee0c25006b130 | Python | 3,153 | 107 | # coding=utf-8
"""
Module to warp a image with given ddf. A CLI tool is provided.
"""
import argparse
import os
import nibabel as nib
import numpy as np
import tensorflow as tf
from deepreg import log
from deepreg.dataset.loader.nifti_loader import load_nifti_file
from deepreg.model.layer import Warping
logger = l... |
e26a8baaf6276d6e4f3cf2ee1875c46f1ec08dbee8d68c5cab1dae755e3bc8ff | Python | 3,154 | 78 | from pathlib import Path
from typing import Union, Optional
import nibabel as nib
from auxiliary.io import read_image, write_image
from brainles_preprocessing.defacing.defacer import Defacer
from brainles_preprocessing.defacing.quickshear.nipy_quickshear import run_quickshear
from brainles_preprocessing.constants imp... |
50b61723eff6b39de09cf1ece22bc9a728ba970240f90e5c7d84e1453924c070 | Python | 3,155 | 77 | '''Script to fit RGB heatmap images to a source color palette.'''
import click
import numpy as np
from PIL import Image
from zennit.image import CMAPS, palette
def gale_shapley(dist):
'''Find a stable matching given a distance matrix.'''
preference = np.argsort(dist, axis=1)
proposed = np.zeros(dist.shap... |
530e7249d549c92d25bbe4f305255949c40a6dae42ee2bd253ff7e5295cd7539 | Python | 3,155 | 98 | # 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.
import numpy as np
from functools import lru_cache
from unicore.data import BaseWrapperDataset, data_utils
from copy import deepcopy
from tqdm import tqdm
class C... |
934f4d35d7c09b6fd06e06f9cb88b8e8b5ad00b11a83970ad748bbe2723cae9b | Python | 3,155 | 104 | from torch.utils.data import Dataset
from utilFunc import readCSV
import argParser as ARG
from torchvision.transforms import v2
from PIL import Image
import torchvision.transforms.functional
import torch
TEST = "test"
TRAIN = "train"
VALIDATE = "validate"
POSSIBLE_SPLITS = [
TEST,
TRAIN,
VALIDATE,
]
if A... |
fc8811e53c4d7a0f6201102f36e8d1cc49deb1119f00d45b0cae72f1b92c2b32 | Python | 3,155 | 96 | """Tiny TCP relay used by the dashboard launcher.
Listens on a UAN-visible port and forwards every accepted connection to a
loopback service on the same UAN host. The dashboard launcher pairs this
with a reverse SSH tunnel (Mac argo-shim -> UAN loopback), so compute
nodes can curl http://<uan>:<port>/argoapi/v1 and re... |
0e3e0c541b56f548bc24aa0d7a72f08cbea4118fe87fbab7209ef2ac50a74a54 | Python | 3,156 | 103 | #!/usr/bin/env python
"""
Fit spots for the focus lock using a correlation based approach.
Hazen 04/18
"""
import numpy
import storm_analysis.sa_library.fitting as fitting
import storm_analysis.sa_library.ia_utilities_c as iaUtilsC
import storm_analysis.sa_library.matched_filter_c as matchedFilterC
import storm_analy... |
61fc41e541a366bd0c8c34b91ac552e32f70b6be8ed405c59130fba44003af01 | Python | 3,157 | 68 | # -*- coding: utf-8 -*-
"""
Created on Tue Jun 15 13:53:06 2021
@author: Yoshi
"""
from PIL import Image,ImageDraw,ImageFont
from cell_drawer import *
def cell_number_mapper(tonotopic_map_output_path,canvas,width,height,cell_locations,scale,radius,cell_flags,extra_flag):
# Makes a copy of the canvas
... |
db20de0fef9d7a36d445f0f721a20ff50d5c56f592c0f823bca07a9ed1c43b83 | Python | 3,158 | 93 | import os
import json
import pandas as pd
from tqdm import tqdm
dataset_path = '../../datasets'
dataset_list = os.listdir(dataset_path)
dataset_list = ['Twibot-20', 'cresci-2015', 'cresci-2017']
class User:
"""Class of a User"""
def __init__(self, userid: str):
self.userid = str(userid)
self... |
c1564aabdddab0503efeb5680a47b08bda16e23ecbf9e6d374e10abbc9f3752b | Python | 3,159 | 84 | # -*- coding: utf-8 -*-
"""
Written by Guido Meijer
"""
from powerpixels import Pipeline
import os
import numpy as np
from datetime import datetime
from pathlib import Path
if __name__ == "__main__":
# Initialize power pixels pipeline
pp = Pipeline()
# Search for process_me.flag
print('Lo... |
a8ef1603e436d883f452c5c561862ed990cda041c2c1dde75ed7df2704f28ed9 | Python | 3,160 | 87 | #!/usr/bin/env python3
# -*- coding: utf-8 -*-
"""
Transform Nifti (.nii.gz) using an affine/rigid transformation.
For more information on how to use the registration script, follow this link:
https://scilpy.readthedocs.io/en/latest/documentation/tractogram_registration.html
"""
import argparse
import logging
import... |
c35dfac7c8141e6efaa28f2b4187b20d5575d789eb12116df7f015f9285a729e | Python | 3,160 | 102 | import hashlib
from pathlib import Path
import subprocess as sp
import shutil
try:
from rich import print
except ImportError: # pragma: no cover - optional dependency for nicer CLI output
pass
def calcHash(filepath):
return hashlib.md5(
open(filepath, 'rb').read()
).hexdigest()
def shipResu... |
c87e220b58e05583023425a75de17948e3dcd13803787292323e7950726a62c4 | Python | 3,160 | 94 | import os
import numpy as np
parallel_starts = 8
available_gpus = available_gpus = ['4,6', '4,6']
# args dict
args_dict = {'device': 1, # gpu
'log_steps': 1,
'num_layers': 3,
'hidden_channels': 256,
'dropout': 0.0,
'batch_size': 64 * 1024,
'lr': 1.e-... |
45298bbfc1f4017cbb3ee26d198014210c7533fc8da34746c4a7f19e904a2265 | Python | 3,161 | 106 | from typing import Callable, Dict, Tuple
from magicgui import magicgui
from qtpy import QtCore
from qtpy.QtWidgets import QMessageBox, QPushButton, QVBoxLayout, QWidget
class Affine2DWidget(QWidget):
def __init__(self, controller):
super().__init__()
self.controller = controller
self.pa... |
5eede358e2e9e05d681f063cc91e2b53ebc1e7e5899b8af36642b5b2bfcce165 | Python | 3,161 | 97 | import pytest
import numpy as np
from nems.layers.weight_channels import (
WeightChannels, WeightChannelsGaussian, WeightChannelsMulti,
WeightGaussianExpand
)
def test_constructor():
with pytest.raises(TypeError):
# No shape
wc = WeightChannels()
with pytest.raises(TypeError):
... |
b1acd7bf3c5bd376a9da5fab7b908a75faf35b1ed6422bc56401d52625217084 | Python | 3,161 | 75 | from src.wrappers.OsipiBase import OsipiBase
from src.original.fitting.OGC_AmsterdamUMC.LSQ_fitting import fit_least_squares, fit_least_squares_array
import numpy as np
class OGC_AmsterdamUMC_biexp(OsipiBase):
"""
Bi-exponential fitting algorithm by Oliver Gurney-Champion, Amsterdam UMC
"""
# I'm thin... |
fc88b9129b2a40ca090ab235d58913b744140a606b4edee98755f160349f71b4 | Python | 3,161 | 87 | import numpy as np
import seaborn as sns
from tqdm import tqdm
from argclz import AbstractParser
from neuralib.io import csv_header
from neuralib.plot import plot_figure
from neuralib.util.verbose import publish_annotation
from rscvp.spatial.main_cache_occ import ApplyPosBinCache
from rscvp.util.cli import DataOutput,... |
b7572418cf6d694787fe96bf138e4f168276af1c6a00d5df3a4051cd17bc6bed | Python | 3,162 | 77 | from matplotlib import pyplot as plt
import numpy as np
from numpy import ndarray
from typing import Union
import cv2
__all__ = ['label_cmap', 'random_colors_hsv']
def random_colors_hsv(num, hue_range=(0, 180), saturation_range=(60, 133), value_range=(180, 256), ubyte=False):
colors, = cv2.cvtColor(np.stack((
... |
3db572a644a010cb659ab3dc2db6050c497db894a33ac7f50aa699de745cd095 | Python | 3,163 | 90 | #!/usr/bin/env python
"""
Python interface to the LMMoment object finder. This object finder
works by indentifying local maxima, then computing their first moment.
Note that the maximum number of objects found per image is limited to 1000.
Hazen 09/13
"""
import ctypes
import numpy
from numpy.ctypeslib i... |
fd9028022775c64e7946650483b622149fa7761ee2a505622066a8ea3672ca6b | Python | 3,163 | 98 | from copy import deepcopy
from typing import TYPE_CHECKING
import pytest
from eir.data_load import label_setup
from eir.setup.output_setup import get_output_name_config_iterator
from eir.setup.output_setup_modules.tabular_output_setup import (
set_up_num_outputs_per_target,
)
if TYPE_CHECKING:
from eir.setup... |
2db9e1f6aca9e4a188174f404e13874abdf29566927c9f98771a832ee4fb72c5 | Python | 3,164 | 100 | '''
Registering high resolution anatomical images to boost SNR
'''
import glob
import ants
import numpy as np
import os
import nibabel as nb
# Set data path
DATADIR = '/Users/sebastiandresbach/data/s1Anfunco/Nifti'
# Set subjects to work on
subs = ['sub-07','sub-09','sub-10']
# Set sessions to work on
sessions = ... |
67f785790ca853c3494c6dfa187d50a90bde0c8dd16ce8b595e6512690b682c9 | Python | 3,164 | 81 | import sys
from torch.utils.data import DataLoader
from geoseg.models.MixerUnet import reparameterize_model
from geoseg.losses import *
from geoseg.datasets.segpc import SegPCDataset
from geoseg.models.Unet import UNet
from catalyst.contrib.nn import Lookahead
from catalyst import utils
from torchinfo import summary
... |
eea78bb19940536c7931fba8786c264ed172f992885c5d2138f6d478bf01c705 | Python | 3,166 | 76 | import warnings
warnings.filterwarnings("ignore", message="It is not recommended to directly access")
import os
import pickle
import json
import datetime
def save_dataset_split(train_dataset, valid_dataset, test_dataset, dataset_name, seed, split_dir='./dataset_splits'):
os.makedirs(split_dir, exist_ok=True)
... |
5e0065053e0c77c2d843beec0cdb23d954d5f3d7da986210c45674f7902ecc99 | Python | 3,168 | 116 | import io
import os
import re
import sys
from shutil import rmtree
from typing import Tuple, List
from setuptools import Command, find_packages, setup
# Package meta-data.
name = "PhaseNet"
description = "PhaseNet"
url = ""
email = "wayne.weiqiang@gmail.com"
author = "Weiqiang Zhu"
requires_python = ">=3.6.0"
current... |
fce48067fae606c8d7d6e84f32c00dfb8f683825251eb626013c6e2256cafd2b | Python | 3,168 | 87 | # -*- coding: utf-8 -*-
"""
This file contains the script for defining characteristic functions
and using them as a way to embed distributional information
in Euclidean space
"""
import cmath
import math
import matplotlib.pyplot as plt
import numpy as np
import seaborn as sb
def plot_characteristic_function(phi_s, bu... |
559448786156fd332a7c9ea1f8a386e69f58de295ca071dc6384b6151eb893ce | Python | 3,169 | 67 | import argparse
import utils
from os.path import basename
import numpy as np
from os.path import join
'''
for an ensemble or set of models, analyze attribution scores (saliency or shap)
if rmse flag set: calculates Euclidean distance as RMSE (must provide reference file)
if var flag set: calculates variance in attribu... |
f4bd02041bf5afa640bb12253018815182b2c99a33daf6e1bbcaa1aa4d909e00 | Python | 3,169 | 85 | # This file was automatically generated by SWIG (https://www.swig.org).
# Version 4.3.1
#
# Do not make changes to this file unless you know what you are doing - modify
# the SWIG interface file instead.
from sys import version_info as _swig_python_version_info
# Import the low-level C/C++ module
if __package__ or "."... |
07aab11bf3e428057f177c261371d43ccd90083c6d033b2e0824cdfe2dcd9798 | Python | 3,170 | 101 | #!/usr/bin/python3
#
import os
import sys
import argparse
import numpy as np
from sklearn.neighbors import NearestNeighbors
from uac import utils
# Create the parser
my_parser = argparse.ArgumentParser(description="UAC scalar mapping")
# Add the arguments
my_parser.add_argument("target_path", metavar="path", type=st... |
28d4183d8944783b2c2208e8588a65a7b73adc58c88a23d1ef3ecba629b05e7c | Python | 3,171 | 63 | import torch
import torchvision
import torchvision.transforms as transforms
datapath = './datafile'
def get_indices(dataset,class_name):
indices = []
for i in range(len(dataset.targets)):
if dataset.targets[i] in class_name:
indices.append(i)
return indices
def DLTrain(idx... |
b753f18f1b97a804b0611a3d376d1887dbfcf7fb8a7569bb17abf20b988a4fda | Python | 3,171 | 101 | import platform
import shutil
from pathlib import Path
from typing import Optional
from brainglobe_atlasapi.utils import check_internet_connection
from paquo import settings as paquo_settings
from paquo.jpype_backend import find_qupath
from brainways.utils.paths import get_brainways_dir
def get_brainways_qupath_dir... |
d8e89bcb93aa6656771e23fd227d2f20d6d8b642735140dca32a22a4510b6925 | Python | 3,171 | 76 | from torch.utils.data import DataLoader
from geoseg.losses import *
from geoseg.datasets.ham10000 import HAM10000_Dataset
from geoseg.models.deepunet.DeepUnet import Model
from catalyst.contrib.nn import Lookahead
from catalyst import utils
CLASSES=('background', 'foreground')
# training hparam
max_epoch = 100
ignor... |
271f2044c486a7e2357186a29ef5a2eba53171370d9c3c33b793bf513de99d23 | Python | 3,172 | 94 | import os
import numpy as np
parallel_starts = 8
available_gpus = available_gpus = ['0,7', '7,0']
# args dict
args_dict = {'device': 7, # gpu
'log_steps': 1,
'num_layers': 3,
'hidden_channels': 256,
'dropout': 0.0,
'batch_size': 64 * 1024,
'lr': 1.e-... |
9f936268211c98dae1b2dc506a202644cd4c2377888d1c1869d15df4abda3b1d | Python | 3,172 | 93 | # Source: https://github.com/neuraloperator/neuraloperator/blob/main/neuralop/layers/segment_csr.py
from typing import Literal
import importlib
import torch
from torch import einsum
def segment_csr(
src: torch.Tensor,
indptr: torch.Tensor,
reduce: Literal["mean", "sum"],
use_scatter=True,
):
"""... |
d34d88ed7d14ff300a10b5de5d1ff3978640cbbfd4335401b66c1be61f2fdd84 | Python | 3,173 | 59 | import sys
sys.path.append('..')
from torch import nn
from torch_geometric.nn.models.attentive_fp import GATEConv
from torch_geometric.nn.conv import GATConv
from layers.fastegnn import FastEGNN
from layers.conv import ConvBlock
from layers.egnn_pyg import EGNNConv
class ConvBlockPyG(ConvBlock):
def forward(self, ... |
fb1cc937f147ca7ca8089ebcfaeb31e83348f61040c248602da75502a26e891c | Python | 3,173 | 98 | # %% ### import modules
from pathlib import Path
import pandas as pd
# %% read results table
results_dir = Path(__file__).resolve().parents[1] / "results"
# %% data
df = pd.read_excel(results_dir / "long_c_results.xlsx")
# %% round intercept and coef to 3 decimal places. same for intercept_ste and coef_ste
df["odds"... |
fd3016db4d80c765f122378f97e250300a22f413bac00c5b0f03cad4a6b2d4db | Python | 3,173 | 89 | #!/usr/bin/env python3
# -*- coding: utf-8 -*-
"""
Conversion of '.tck', '.trk', '.fib', '.vtk' and 'dpy' files using updated file
format standard. TRK file always needs a reference file, a NIFTI, for
conversion. The FIB file format is in fact a VTK, MITK Diffusion supports it.
"""
import argparse
import logging
impor... |
1686c60af6e8bc1f0d3cdbbd1b88045f5015a580183bbf3a8726db39396432ab | Python | 3,174 | 72 | ################## PURPOSE #################
# This script is to restructure the 4th(start pos), 5th(end pos), 6th(copy number), and 7th(seg.mean) columns of the input file
# Because these columns hold the "raw" coordinates of the CNV after filtering out for IGLL, telomerics, centromeric
# and segup regions, we want to... |
240fa286865290180014fcd69756638b8d31dc8293fbe1684129eef619245a09 | Python | 3,174 | 87 | """
Cropping functional images to decrease number of voxels (and therefore
processing demands)
"""
from nipype.interfaces.fsl import ExtractROI
import glob
import os
# Set data path
ROOT = '/Users/sebastiandresbach/data/s1Anfunco/Nifti'
# Set subjects to work on
subs = ['sub-12', 'sub-15', 'sub-16', 'sub-17', 'sub... |
86c8ac9bde4c205d875561da767596e1ddeaacf09d6edd6ea488a07e71b6caf7 | Python | 3,174 | 58 | from dtiplayground.dmri.common.tools.base import ExternalToolWrapper
class ResampleDTIlogEuclidean(ExternalToolWrapper):
def __init__(self,binary_path= None, **kwargs):
super().__init__(binary_path, **kwargs)
def filter_dti(self, inputfile, outputfile,correction='zero'):
arguments=[inputfile,... |
d6f20aa88593cd9dbf996d04d281dbdc4fd213af34a4eae1ed65284b1ac4c160 | Python | 3,174 | 122 | import os.path as op
import random
import tempfile
import numpy as np
import numpy.testing as npt
from AFQ.models.csd import fit_csd
from AFQ.models.dti import fit_dti
from AFQ.tractography.tractography import track
from AFQ.tractography.utils import _is_int
from AFQ.utils.testing import make_tracking_data
seeds = n... |
7b0a9b92a6b402a8400869a2cf723c6b4608b145c9af087197220c980bcebdf2 | Python | 3,175 | 96 | #!/usr/bin/python3.8+
# -*- coding: utf-8 -*-
# @Time : 2022/3/4 10:16
# @Author : Z.-H. G.
# @Email_0 : guozhenhao17@mails.ucas.ac.cn
# @Email_1 : guozhenhao@tongji.edu.cn
# @File : loss.py
# @IDE: PyCharm
import torch
import torch.nn as nn
import torch.nn.functional as F
from torch.autograd import Variable
... |
aa526761b9a9fc8d286045db15ab9ad037b291baf507c43b1e230d19bd40309d | Python | 3,175 | 70 | import os
import subprocess
import nibabel as nib
import numpy as np
from nipype import Node, Workflow
from nipype.interfaces.utility import IdentityInterface, Merge
from ...bids_data.rename_bids_file import rename_bids_file
class SCNPipeline:
def __init__(self,
subject,
session,... |
ded0c3b1958335cc9bde5e70fc8919c8f2c088a883c63787b61320604b6ceb13 | Python | 3,176 | 67 | #!/usr/bin/env python3
# Author: Francois Aguet
import argparse
import os
import struct
import subprocess
from datetime import datetime
import contextlib
@contextlib.contextmanager
def cd(cd_path):
saved_path = os.getcwd()
os.chdir(cd_path)
yield
os.chdir(saved_path)
parser = argparse.ArgumentParser... |
0f9c5da72e121f4152a64fd75c59e472807fba0a9bcb9051c236248564e0aeb0 | Python | 3,177 | 117 | import lmfit
import numpy as np
import pandas as pd
import impedancefitter as ifit
from impedancefitter.time_domain import (
calculate_impedance_spectrum_using_cwt,
calculate_impedance_spectrum_using_fft,
fit_impedance_from_time_domain,
)
data = pd.read_csv("MEA_signal.zip")
time = data["time"].to_numpy()... |
9c41ea88f76b4776f5a7f50d9c401ad8276e6ee99f7fb33b14303244f90cbd34 | Python | 3,177 | 97 | import os
from pathlib import Path
from typing import Optional
import dotenv
import pytorch_lightning as pl
from omegaconf import DictConfig, OmegaConf
def get_env(env_name: str, default: Optional[str] = None) -> str:
"""
Safely read an environment variable.
Raises errors if it is not defined or it is em... |
693b637f1f7d4871d569dd34509d9dc4c4fca04a98402bd2c12ad7f139542f52 | Python | 3,178 | 101 | import torch
from reducers import DivisorReducer
from utils import common_functions as c_f
from utils import loss_and_miner_utils as lmu
from losses.base_metric_loss_function import BaseMetricLossFunction
class MarginLoss(BaseMetricLossFunction):
def __init__(
self,
margin=0.2,
nu=0,
... |
979d2028c1a4d7fdd519181a0bf390e37ff53f0abe62dd304f6f2e42d6466ad1 | Python | 3,178 | 94 | #!/usr/bin/python
# This script is a slightly modified version of the original found at
#
# http://wiki.wxwidgets.org/Embedding_PNG_Images-Bin2c_In_Python
#
# without any copyright attribution so it is assumed it can be used under
# wxWindows licence as the rest of the wiki material.
import sys
import os
import... |
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