sha256 stringlengths 64 64 | language stringclasses 28
values | size int32 1 491k | lines int32 1 23.2k | content stringlengths 1 200k |
|---|---|---|---|---|
76a477c71af007c515b9ab2ecbac8a5c4889cc9276d01779fa7fde08995a341b | Python | 1,697 | 51 |
from torch.utils.data import Dataset
import torch
from functools import lru_cache
DEVICE = "cuda"
IMG_SIZE = 1024
PATCH_SIZE = 64
@lru_cache
def getShiftSteps(stepNum, patchSize):
steps = [round(patchSize*(x/stepNum)) for x in range(stepNum)]
steps = [((x + patchSize//2) % patchSize)-patchSize//2 for x in s... |
91af4ae6b0ba7558fb42b351085d54008a769c4b580d7b94b2fbc1dfcb647a87 | Python | 1,697 | 71 | from __future__ import annotations
from abc import ABC, abstractmethod
from typing import TYPE_CHECKING, Optional
import numpy as np
from qtpy.QtWidgets import QWidget
from brainways.pipeline.brainways_params import BrainwaysParams
from brainways.pipeline.brainways_pipeline import BrainwaysPipeline
if TYPE_CHECKING... |
16126d3ff64662d2c58f3be26a1f29c074b5240fbce5ac22b51d2d9885bb68f3 | Python | 1,698 | 54 | """
test_umitag.py
-------------------------------
Tests for the `umitag.py` module
"""
import unittest
import os
import sys
import shutil
import utils
# Include the parent directory in the PYTHONPATH for relative imports
sys.path.append('..')
import umitag
TEST_OUTPUT_PATH = 'output'
TEST_DATA_FILES = {'read1': '... |
2bfab01dc545873d98398ce2ac7b313529f411d592ed87d43f8c992626a3e5ca | Python | 1,698 | 53 | from __future__ import annotations
from typing import TYPE_CHECKING, Any
from ._widget import Widget
if TYPE_CHECKING:
from magicgui.widgets import protocols
class StatusBarWidget(Widget):
"""Status bar widget, wraps StatusBarProtocol.
Parameters
----------
**base_widget_kwargs : Any
A... |
b85ab5835cd82891215c771d1e602922d5fc0bf862ed85bea039a6b06ccc5f07 | Python | 1,698 | 70 | # -*- coding: utf-8 -*-
# python standard library inputs
import os
# external inputs
import numpy as np
import nibabel as nb
def get_laminar_profile(file_in, path_output, hemi, name_output, mode):
"""Get laminar profile.
This function computes the laminar profile (mean, median, max, min) of data
s... |
bbe990d6741795e5a053ba6c738c3470d005c85e379ef85cf0fe19bef95c63e4 | Python | 1,698 | 57 | import numpy as np
import pandas as pd
from sklearn.ensemble import RandomForestClassifier
from sklearn.metrics import accuracy_score, precision_score, recall_score, f1_score, matthews_corrcoef, auc, roc_curve
from sklearn.metrics import classification_report
from sklearn.metrics import confusion_matrix
from sklearn.mo... |
ca72c2db1b84fc78d0d07976dc5ebd9a75e75c6fbb4b4b1a40f303e9446a9abb | Python | 1,698 | 41 | from pathlib import Path
import numpy as np
import xarray as xr
import pandas as pd
from brainscore_core.supported_data_standards.brainio.fetch import get_stimulus_set
from brainscore_core.supported_data_standards.brainio.assemblies import NeuronRecordingAssembly
from brainscore_core.supported_data_standards.brainio.... |
d89de45cd2d9fef01d2fe62d381f3e0ede51f36ff77146d158b327e49e93b982 | Python | 1,698 | 54 | from typing import Literal, Final
from argclz import as_argument, argument
from neuralib.plot import plot_figure, violin_boxplot
from neuralib.util.verbose import publish_annotation
from rscvp.statistic.core import StatPipeline
from rscvp.util.cli.cli_statistic import StatisticOptions
from rscvp.util.util_plot import ... |
32aaa68ba0f4169e6b9901184f00432fe42a9789ff133dba27e51da5b090d6ce | Python | 1,699 | 57 | import numpy as np
import pandas as pd
from sklearn.ensemble import RandomForestClassifier
from sklearn.metrics import accuracy_score, precision_score, recall_score, f1_score, matthews_corrcoef, auc, roc_curve
from sklearn.metrics import classification_report
from sklearn.metrics import confusion_matrix
from sklearn.mo... |
f58dc02f5c8405c5e9ebc76db092672a0d9e14996a171eee5d66bed6bd1ccd25 | Python | 1,699 | 42 | # This file is part of Mooney computational modeling project.
#
# Mooney computational modeling project 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 option) an... |
33af998585afa8bf57e88ffdca2fe4cac3e8cfd48e1bee5f2cda7fe5c74a5a1c | Python | 1,700 | 43 | import pyvisa as visa
import pyvisascope
import multitimer
import time
import yaml
import logging
from time import sleep
visa.log_to_screen('INFO')
logger = logging.getLogger('pyvisa')
log2file = logging.FileHandler('experiment.log')
logger.addHandler(log2file)
def main():
# enter here the ID of your device.... |
d7cf97f6c0a3b19c68a212efe8e49a7963555b4762b09a8fdac748928a3cc9ab | Python | 1,700 | 50 | from copy import deepcopy
from pathlib import Path
from eir.experiment_io.input_object_io_modules.input_io_utils import (
load_input_config_from_yaml,
)
from eir.experiment_io.io_utils import load_dataclass
from eir.setup.input_setup_modules.setup_omics import (
ComputedOmicsInputInfo,
DataDimensions,
... |
eded5852a742d29174a21ec67dc85e772fc5193984b0605e29f46c18da966fb7 | Python | 1,700 | 60 | '''
'''
#
# Adapted from MATLAB code written by S. Nishimoto (see Nishimoto, et al., 2011).
# Anwar O. Nunez-Elizalde (Jan, 2016)
#
# Updates:
# Anwar O. Nunez-Elizalde (Apr, 2020)
##############################
# internal imports
##############################
from . import (pyramids,
utils,
... |
e9dfbfbc956c4cca41c32300aa6ce85202b7308b6fbc6beadf81f5c07e1ae536 | Python | 1,701 | 39 | from PUMI.engine import BidsPipeline, BidsApp
from PUMI.pipelines.anat.segmentation import bet_fsl
@BidsPipeline(output_query={
'T1w': dict(
datatype='anat',
extension=['nii', 'nii.gz']
)
})
def bet_wf(wf, fmri=True, **kwargs):
brain_extraction = bet_fsl('brain_extraction', fmri=fmri)
w... |
36a6525c87b36a16926cfd0a17a60b9add493cbe6b4f36d6dd2a391cae46e6fa | Python | 1,702 | 58 | # -*- coding: utf-8 -*-
# python standard library inputs
import os
# external inputs
import numpy as np
import nibabel as nb
from scipy.signal import fftconvolve
def get_acorr(arr, write_output=False, path_output="", name_output=""):
"""Get acorr.
This function computes a normalized autocorrelation of a 2D... |
6b62d6be9a59286f15a0433eeb72b1a578ae158ca156639f6966f2f6147940eb | Python | 1,702 | 58 | import os
import sys
sys.path.append('.')
import click as ck
import numpy as np
import pandas as pd
import os
from collections import Counter, deque
from deepgo.utils import (
Ontology, FUNC_DICT, NAMESPACES, MOLECULAR_FUNCTION, BIOLOGICAL_PROCESS,
CELLULAR_COMPONENT, HAS_FUNCTION)
logging.basicConfig(level=... |
f1c9e6d5e19fbc6b36ceea224fb08762b4e79903658f6f480311be22e9133fd9 | Python | 1,702 | 50 | #@String(value="This script converts all .traces files in a directory into SWC. Conversion log is shown in Console.", visibility="MESSAGE") msg
#@File(label="Directory of .traces files:", style="directory") input_dir
#@Boolean(label="Open Console", value=false) open_console
#@LogService log
#@StatusService status
#@UIS... |
895013d28e5182644986bf0d0bd0bb56f09e72623a85b3a27008d0cf5361157a | Python | 1,703 | 45 | import pytest
from chemgraph.agent.llm_agent import ChemGraph
@pytest.mark.llm
@pytest.mark.asyncio
async def test_single_agent_graph():
"""
Test that the agent can take a molecule name,
convert it to SMILES, and update the state.
"""
cg = ChemGraph(model_name="gpt-4o-mini", workflow_type="single_... |
0c7aeaa0999a2b4d36f56b550c14d9fd01663f6d0e386fb70215cdf9468e764f | Python | 1,704 | 61 | #!/usr/bin/env python3
# StrabismusClassification/scripts/generate_decision_curve_data.py
import numpy as np
import pandas as pd
from pathlib import Path
from sklearn.metrics import confusion_matrix
def net_benefit(tp, fp, n, p):
"""
计算净获益：
NB = TP/n − (FP/n) × (p/(1−p))
"""
return tp/n - (fp/n)... |
182385b5dbeca521bd71cc13c3e32f46aa28ef629f035e78cb7ee1004e0f4e27 | Python | 1,704 | 47 | # -*- coding: utf-8 -*-
from datetime import datetime
from parser import Model
from parser.cmds.cmd import CMD
from parser.utils.corpus import Corpus
from parser.utils.data import TextDataset, batchify
class Predict(CMD):
def add_subparser(self, name, parser):
subparser = parser.add_parser(
... |
7abc8142b876bdb782b45e6bc5cae59b5fe1b2f25c769678b5a849425f728970 | Python | 1,704 | 57 | from __future__ import annotations
from collections.abc import Callable
from typing import TYPE_CHECKING, Any
from ._widget import Widget
if TYPE_CHECKING:
from magicgui.widgets import protocols
class ToolBarWidget(Widget):
"""Widget with a value, Wraps ValueWidgetProtocol.
Parameters
----------
... |
886dc6bc2acdf619c960cb7f865a4feb50c18f8d007b2718d48d7b3299fe00e1 | Python | 1,704 | 61 | import torch
import torch.nn
from models.convlstm.convlstm import ConvLSTMCell
import torch.nn.functional as F
class LSTMSequentialEncoder(torch.nn.Module):
def __init__(self, height, width, input_dim=13, hidden_dim=64, nclasses=8, kernel_size=(3,3), bias=False):
super(LSTMSequentialEncoder, self).__init__... |
368e6db1990dcd447ea43b5d85a943c8d30de3cfa1d1b8a5887ca6d63fa342f7 | Python | 1,706 | 52 | """Plots a scatter plot of two properties of molecules compared to the DrugBank reference set."""
from pathlib import Path
import pandas as pd
from admet_ai.drugbank import get_drugbank
from admet_ai.plot import plot_drugbank_reference as _plot_drugbank_reference
def plot_drugbank_reference(
data_path: Path,
... |
0a4d4c49d5dd2fc52cfcc37260879612b165fbb44341273485b0bff446596564 | Python | 1,707 | 50 | from argclz import AbstractParser, argument
from neuralib.plot import plot_figure
from neuralib.suite2p import Suite2PResult
from rscvp.selection.utils import moving_average
from rscvp.util.cli import DataOutput, StimpyOptions, Suite2pOptions
__all__ = ['MotionDriftOptions']
class MotionDriftOptions(AbstractParser, ... |
20cde8851aaf6e2afa84385f7a85299efe11a4c2c73af1c627eac60ef85d3d6f | Python | 1,707 | 44 | import pandas as pd
import numpy as np
import joblib
import shap
import matplotlib.pyplot as plt
feature_Filepath = r''
label_Filepath = r''
model_path = r'l'
data_path = r''
feature_data = pd.read_csv(feature_Filepath)
label_data = pd.read_csv(label_Filepath)
feature_names = feature_data.columns.value... |
5a4bb08f8bfce31738d6b6c08a9ebfc47530d42571ec34fa076303753def4bbc | Python | 1,707 | 56 | from setuptools import find_packages, setup
def meta_data():
meta = {
"version": "0.1.0",
"maintainer": "Guillaume Bellec and Christos Sourmpis",
"email": "christos.sourmpis@epfl.ch; guallaume.bellec@epfl.ch",
"url": "https://www.epfl.ch/labs/lcn/",
"license": "Apache 2.0",... |
63b10befebde835c9323425029c17138d008c1b00802ed5393cc48b0c7dcb9c1 | Python | 1,707 | 67 | # -*- coding: utf-8 -*-
class Metric(object):
def __init__(self, eps=1e-5):
super(Metric, self).__init__()
self.eps = eps
self.n = 0.0
self.n_ucm = 0.0
self.n_lcm = 0.0
self.total = 0.0
self.correct_arcs = 0.0
self.correct_rels = 0.0
def __re... |
821189aebed49a07a52787fafaf543a2a46b02c8039a4044efedd9e7bfb7e87a | Python | 1,707 | 52 | from __future__ import annotations
import subprocess
import tempfile
from pathlib import Path
from loguru import logger
from labelme._config import load_config
def main() -> None:
repo = Path(__file__).resolve().parents[1]
tags = subprocess.check_output(
["git", "tag", "--list", "v*", "--sort=versi... |
c8acb14c1373e6b166dd1bc290497844cec12a049379defc4cd6e79eca73708e | Python | 1,707 | 52 | # Copyright (C) CVAT.ai Corporation
#
# SPDX-License-Identifier: MIT
from __future__ import annotations
import unittest
import datumaro as dm
from cvat.apps.dataset_manager.bindings import CommonData
from cvat.apps.engine.models import ShapeType
from cvat.apps.quality_control.datumaro_data_provider import _Memoizin... |
cfb3f9cf34b04200692a531c18b780df96917e8156ab519134158c1b07623c11 | Python | 1,707 | 51 | from seisbench.data.base import WaveformBenchmarkDataset
class AQ2009Counts(WaveformBenchmarkDataset):
"""
AQ2009 aftershocks digital units dataset from Bagagli et al. (2023)
"""
def __init__(self, **kwargs):
citation = (
"Bagagli, M., Valoroso, L., Michelini, A., Cianetti, S., "... |
62790c1ce067057c6975d5b7632aa0a965e5f87e260283285d46541871072d83 | Python | 1,708 | 42 | from sklearn.ensemble import RandomForestClassifier
from sklearn.metrics import accuracy_score, precision_score, f1_score, recall_score, roc_auc_score
import numpy as np
from tqdm import tqdm
train_features = np.loadtxt('train_features.txt')
train_labels = np.loadtxt('train_labels.txt')
valid_features = np.loadtxt('val... |
720f50a06098893ec355a19bc3d2eef14dbe717b22ec39ed35b98290260c0104 | Python | 1,708 | 48 | import os
import sys
import time
from typing import List
# Add project root to path
sys.path.append(os.path.dirname(os.path.dirname(os.path.abspath(__file__))))
from src.llm_orchestrator.self_correcting_agent import SelfCorrectingAgent
def run_prompt_perturbation():
print("="*70)
print("PROMPT PERTURBATION T... |
8c8a80c9497ed915a91006b3e6e876660e0b787d18a8ba28cc1bf83aacb3cd8e | Python | 1,709 | 62 | import numpy as np
from impedancefitter.cole_cole import cole_cole_model, cole_cole_R_model, raicu
from impedancefitter.utils import return_diel_properties
omega = 2.0 * np.pi * np.logspace(1, 8, num=20)
# for cole_cole_model
c0 = 1.0
el = 81.0
eh = 1.8
tau = 9.4e-3
a = 1.0 - 0.009
kdc = 1e-5
# for cole_cole_R_mode... |
a3add1fdef9de786457c44d1ae973676a10ccdba5471591eca2f9b67c6bfda8c | Python | 1,710 | 57 | """Fresh step-1-only Python run to check the ExampleTraces uV-scaling fix.
Runs current spike-detection + step-1 plotting on the bundled Axion example
data with potential_difference_unit='V' (the correct unit for this data, which
is stored in volts). Outputs to parityRun/OutputData_FreshCheck.
python parityRun/ru... |
83fa836fa45dd3ea82630908364b48e943a7c98ad066aa53cdd4e8ffceee9674 | Python | 1,712 | 40 | import numpy as np
import pandas as pd
def load_fMRI_data(root_path, sub_name, rois, contrast_name, reduce_labels_to_number=True):
beta_estimates = list()
loaded_rois = list()
for roi in rois:
try:
beta_estimates.append(np.load(f'{root_path}/{sub_name}/fMRI_responses/{sub_name}_{contra... |
d61317807261bbffee4afbd1e32fc352aaab970a5898de87b88f2fff2f948a95 | Python | 1,712 | 55 | import torch
from PIL import Image
from torchvision import transforms
from models.text_encoder import BertTextEncoder
from models.hdc_mlp import HDCMLPEncoder
from inference.lhdm_infer import make_prompt, pearson_corr, LESION_VOCAB, PATHOLOGY_LABELS
DEVICE = torch.device("cuda" if torch.cuda.is_available() else "cpu"... |
7279d93877f9a261aea54cc32ae02d9feef941a893871614c19fcbe069882104 | Python | 1,713 | 71 | import re
import os
import spacy
import zipfile
def count_urls(tweets):
total = len(tweets)
unique =[]
for text in tweets:
text = str(text)
urls = re.findall(r'http[s]?://(?:[a-zA-Z]|[0-9]|[$-_@.&+]|[!*\(\),]|(?:%[0-9a-fA-F][0-9a-fA-F]))+', text)
unique += urls
count = len(uniq... |
d896327ac72758d4bfacfbb70beba15480f523872168a8f8d1142aa2b7868cb5 | Python | 1,713 | 42 | from sklearn.ensemble import RandomForestClassifier
from sklearn.metrics import accuracy_score, precision_score, f1_score, recall_score, roc_auc_score
import numpy as np
from tqdm import tqdm
train_features = np.loadtxt('train_features.txt')
train_labels = np.loadtxt('train_labels.txt')
valid_features = np.loadtxt('val... |
a55049ddc089b5bec2f92270d5ec2084c0d9dcae3ab424c75b484a3175f96a9c | Python | 1,714 | 58 | # Source: https://github.com/neuraloperator/neuraloperator/blob/main/neuralop/data/transforms/data_processors.py
from abc import ABCMeta, abstractmethod
import torch
class DataProcessor(torch.nn.Module, metaclass=ABCMeta):
def __init__(self):
"""DataProcessor exposes functionality for pre-
and po... |
134f4608fff68e884a003ca2bfafefde146d8c2e590c4e661f9f3178b8360f5f | Python | 1,715 | 58 | import functools
from efficientnet_pytorch import EfficientNet
from brainscore_vision.model_helpers.activations.pytorch import PytorchWrapper
from brainscore_vision.model_helpers.activations.pytorch import load_preprocess_images
from brainscore_vision.model_helpers.check_submission import check_models
def get_model(n... |
6992473ada6aaebb0dc0d433ff2b55e394685616879a78a048a9b5febf8a51d0 | Python | 1,715 | 48 | import torch
import torch.nn.functional as F
class AttentionLayers:
"""Attention layer implementations for graph neural networks."""
@staticmethod
def graph_attention_layer(A: torch.Tensor, H: torch.Tensor, v: list) -> torch.Tensor:
"""Cell-to-cell attention layer."""
h1 = torch.mm(H,... |
976e996ac8e2232031dab268735bd4e179f9a34065f2b477beeec3aa410de72e | Python | 1,715 | 54 | import pandas as pd
import joblib
feature_Filepath = r''
model_path = r''
data_path = r''
total_table_path = r''
label = ''
save_dir = r''
total_table = pd.read_csv(total_table_path)
feature_data = pd.read_csv(feature_Filepath)
feature_names = feature_data.columns.values.tolist()
model = joblib.load(... |
e0817120b612b0371528ca66745de74f83adfe0cbd57dfb29ad783f2aa0c366f | Python | 1,716 | 33 | import os
from nipype.interfaces.base import BaseInterface, BaseInterfaceInputSpec, TraitedSpec, File, Directory, traits, CommandLineInputSpec, File, TraitedSpec, CommandLine, Directory
import csv
import numpy as np
from cvdproc.config.paths import get_package_path
class RemoveTractRegionInputSpec(CommandLineInputSpe... |
193d9fae1c912bfbcfe43ce3e344fdab9ffc0a37d0be8d5a5aebd0f23809f59b | Python | 1,717 | 45 | from brainscore_core.supported_data_standards.brainio.assemblies import NeuronRecordingAssembly
from brainscore_vision import data_registry, stimulus_set_registry, load_stimulus_set
from brainscore_core.supported_data_standards.brainio.s3 import load_stimulus_set_from_s3, load_assembly_from_s3
BIBTEX = """@article{ru... |
799b67cf90466f12ba28dc04191516e4e7a3486eb5717ab2f449c946aa4ca987 | Python | 1,717 | 51 | #############################################################################
# Copyright (C) 2020-2026 MEmilio
#
# Authors:
#
# 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 License.
# You may... |
788d04763b84a3ec3f38345098c7edadc346307a7117a5839bc124024ae7e822 | Python | 1,718 | 61 | # Configuration file for the Sphinx documentation builder.
#
# This file only contains a selection of the most common options. For a full
# list see the documentation:
# https://www.sphinx-doc.org/en/master/usage/configuration.html
# -- Path setup --------------------------------------------------------------
# If ex... |
a96a3be330afa71763e3f7c81827ae598ababcff75e0b89c90c83b1b8b56e774 | Python | 1,718 | 49 | import csv
from brainscore_core.supported_data_standards.brainio.stimuli import StimulusSet
from brainscore_core.supported_data_standards.brainio.packaging import package_stimulus_set
CONDITIONS = ['texture_1', 'texture_2', 'dotted_1', 'dotted_2']
def collect_BMD_2024_stimulus_set(condition, stimuli_directory, meta... |
aef8be8c882f7479fcb1bde90ffd312d26aa82c4bcd7f07e803fdbea11bd4efc | Python | 1,718 | 47 | import pytest
from qtpy import PYQT5, PYQT_VERSION, PYSIDE2, PYSIDE6, QtQml
def test_qtqml():
"""Test the qtpy.QtQml namespace"""
assert QtQml.QJSEngine is not None
assert QtQml.QJSValue is not None
assert QtQml.QJSValueIterator is not None
assert QtQml.QQmlAbstractUrlInterceptor is not None
... |
a56f567ed865e18d4405799b2bd645d0a2e630e8ed2f2fe8ea08ba5b7eae5b9b | Python | 1,721 | 37 | """
PyInstaller hook for silx — full collect.
Why "collect everything":
silx is a large GUI/scientific library that loads a wide variety of
resources at runtime (icons in .png/.svg/.mng, OpenCL kernels in
.cl, precomputed lookup tables in .npy, etc.) through indirection
layers like ``importlib.resourc... |
d45389b9a51cc267bc3d1904898a0d924285062f3dcb84b89bc7e3681d787871 | Python | 1,721 | 48 | # coding=utf-8
# Copyright 2018 The Google AI Language Team Authors.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by ... |
5f27dbf50a05b914efe42763f246a4a9c8e82a67f529c52928ba9d2b42079281 | Python | 1,722 | 61 | # Copyright (C) CVAT.ai Corporation
#
# SPDX-License-Identifier: MIT
from __future__ import annotations
from datetime import datetime, timezone
from json import JSONDecodeError
from pathlib import Path
import jsonc
from cvat_sdk import Client
def popattr(obj, name):
value = getattr(obj, name)
delattr(obj, ... |
26d9862cb43d94ebcc044f8a5300ccd4a0ff6b7da4548d4f4f6405bfaf18f279 | Python | 1,723 | 24 | from brainscore_vision import benchmark_registry
from brainscore_vision.benchmarks.ferguson2024.benchmark import Ferguson2024ValueDelta
DATASETS = ['circle_line', 'color', 'convergence', 'eighth',
'gray_easy', 'gray_hard', 'half', 'juncture',
'lle', 'llh', 'quarter', 'round_f',
'rou... |
1675418b53340e244fb88a73bb8fbdf62a90203b544824a0500395e3d6ae4e36 | Python | 1,724 | 50 | """ setup.py """
import os
from setuptools import setup, find_packages
def get_description():
""" Makes README file into a string"""
with open("README.rst") as file:
long_description = file.read()
return long_description
def parse_requirements(filename):
""" load requirements from a pip requir... |
121d1a8aa1036f8934242b01e687a0bad302080bdf5aff507bc5cf1c042eade4 | Python | 1,725 | 39 | # -*- coding: utf-8 -*-
# Form implementation generated from reading ui file 'settings.ui'
#
# Created by: PyQt5 UI code generator 5.7
#
# WARNING! All changes made in this file will be lost!
from PyQt5 import QtCore, QtGui, QtWidgets
class Ui_GroupBox(object):
def setupUi(self, GroupBox):
GroupBox.setOb... |
84c2d75cf1901d73f13d663d4c4530f9e3e5fb6132461892ed95c4adb7630693 | Python | 1,725 | 54 | """Helper functions for TensorFlow operations."""
import logging
import os
from typing import List, Union
_logger = logging.getLogger("osl-dynamics")
def gpu_growth() -> None:
"""Only allocate the amount of memory required on the GPU."""
import tensorflow as tf # moved here to avoid slow imports
gpus ... |
26c13519ffbe41c875c3f2f5d3f41c5e3ccb22307bcddfc8dd7cac1ec092745b | Python | 1,726 | 58 | # metrics
import tensorflow as tf
import numpy as np
from skimage.metrics import peak_signal_noise_ratio, structural_similarity
def metrics(IMG1, IMG2):
# input: IMG1, IMG2 - numpy arrays with shape [batch_size, height, width, channels]
# return average psnr, ssim, rmse across all images
batch_siz... |
2c9a065ebd421760d7c10c2797808f064171e0c017917ff39d760f9f2a81bb9a | Python | 1,726 | 44 | #!/usr/bin/env python3
"""Run the EEG preprocessing pipeline."""
import argparse
import logging
import multiprocessing as mp
from artifact_identification.preprocessing import EEGPreprocessingPipeline
logger = logging.getLogger(__name__)
def main():
parser = argparse.ArgumentParser(description='EEG preprocessin... |
8cd1b8119e9518b6e8af185d1f026810835a4f8659e04583d96444a68f8b52ce | Python | 1,726 | 53 | #!/usr/bin/env python3
import arbor as A
from arbor import units as U
import pandas as pd # You may have to pip install these.
import seaborn as sns # You may have to pip install these.
# (1) Create a morphology with a single (cylindrical) segment of length=diameter=6 μm
tree = A.segment_tree()
tree.append(A.mnpos,... |
e754930c1c4ea0800c06da9e276cd74b7b9dd2157f0c3dc0b72c3b8fbca35314 | Python | 1,726 | 38 | #!/usr/bin/env python3
# Author: Francois Aguet
import argparse
import os
import subprocess
from datetime import datetime
parser = argparse.ArgumentParser(description='Run GATK ASEReadCounter')
parser.add_argument('gatk_jar', help='GATK4 .jar file')
parser.add_argument('genome_fasta', help='FASTA reference genome')
p... |
f10e769e8a30da6b244efc743251d29a73e01f9f7c56b3acb8a3e9aa9d02a9bf | Python | 1,726 | 59 | import numpy as np
from neuralib.locomotion import CircularPosition
from neuralib.util.verbose import fprint
__all__ = ['get_binned_velocity']
def get_binned_velocity(lap_time: np.ndarray,
pos: CircularPosition,
track_length: int = 150,
bins: i... |
139e48e8d1f189dbb4e8c5d6c4fe7f4c975339e04e0bed8fece95d132a892ffd | Python | 1,727 | 54 | import torch
import torch.nn as nn
import torch.nn.functional as F
from torchvision import models
from .flash_encoder import FLASHEncoder
class HDCMLPEncoder(nn.Module):
"""
CNN backbone + FLASH HDC encoder + MLP head.
Outputs L2-normalized visual embeddings aligned with text embeddings.
"""
def __... |
fa57cb5a432d178702176969d84692921cbfaf629c893759f1deeb368aaab732 | Python | 1,727 | 59 | # pylint: disable=line-too-long
import argparse
from datetime import datetime
from deepreg.predict import predict
name = "paired_mrus_brain"
# parser is used to simplify testing, by default it is not used
# please run the script with --full flag to ensure non-testing mode
# for instance:
# python script.py --full
pa... |
58d93340b7b1aab8a1ac56b01942661cc9ca9fd19cbba973654342e117372e26 | Python | 1,729 | 53 | # -*- coding: utf-8 -*-
# @Author : LG
import os
import platform
from PyQt5.QtCore import QThread, pyqtSignal
osplatform = platform.system()
class GPUResource_Thread(QThread):
"""
The thread for monitoring GPU0 resources.
Arguments:
gpu_id (int): The id of the GPU device to monitor. default 0... |
5c655246875627147b30750b0726c0d4ed1ff47fc69be68d769eacd5ca77f439 | Python | 1,729 | 38 | """
Embellishes the lasagna status bar in a pointless way
"""
from lasagna.plugins.lasagna_plugin import LasagnaPlugin
# Must be a class called "plugin" and must inherit LasagnaPlugin first
class plugin(LasagnaPlugin):
def __init__(self, lasagna_serving):
# The following calls the LasagnaPlugin constructo... |
66a2b7a3b988b2ea7792207e53a045b39b6c72599bdcce3ec09435c55a17119b | Python | 1,729 | 49 | from pathlib import Path
import click
import numpy as np
import simple_mri as sm
@click.command()
@click.option("--input", type=Path, required=True)
@click.option("--reference", type=Path, required=True)
@click.option("--mask", type=Path, required=True)
@click.option("--output", type=Path, required=True)
def T1w_sig... |
b195b9ababdc01c5b668c317786dce39f9fe58af82beb0c8a873aeef8b0b0c6b | Python | 1,729 | 64 | """
Load Au + Au TPC data
"""
from pathlib import Path
import numpy as np
import torch
from torch.utils.data import Dataset
AXIS_MAP = {'azimuth': 0, 'beam': 1, 'layer': 2}
DEFAULT_ORDER = ('azimuth', 'beam', 'layer')
class DatasetTPC(Dataset):
"""
Load TPC data as multi-channel 2d dataset
"""
def _... |
bcc95349a0e17a7a3f706f34d863b8cd5434d4cc76f8611caae3443868f356ec | Python | 1,729 | 74 | import re
import datetime
import calendar
def get_user_id(user):
return user['id']
def get_longevity(user):
create = user['created_at'].split(' ')
if len(create)<6:
return 1
month = list(calendar.month_abbr).index(create[1])
day = int(create[2])
year = int(create[5])
create_time =... |
e0a22c9db2b2dd393c7e1d5de166b753407fc0623ee8755f349a7596596a75ee | Python | 1,729 | 61 | #!/usr/bin/env python3
# -*- coding: utf-8 -*-
"""
Return the number of streamlines in a tractogram. Only support trk and tck in
order to support the lazy loading from nibabel.
"""
import argparse
import json
import logging
import os
from scilpy.io.utils import (add_json_args,
add_verbose... |
129ab56901817cd74d64883551b442c3ed0ef0e355c44179f1b51db03bfcd2a6 | Python | 1,730 | 39 | import logging
import os
from pathlib import Path
import click
from parallel import submit_jobs
from project.utils.dips_plus_utils import impute_postprocessed_missing_feature_values
# -------------------------------------------------------------------------------------------------------------------------------------... |
26a4191c85cab4025b1b83cb6e7394de36e284070a305952b4747e88d180052e | Python | 1,730 | 62 | # -*- coding: utf-8 -*-
"""
Some statistics tests not in standard python packages
"""
#:copyright: Copyright 2015 by Christoph Kirst, The Rockefeller University, New York City
#:license: GNU, see LICENSE.txt for details.
import sys
import numpy as np
from scipy.stats import rankdata
from scipy.stats import distribut... |
8f80c7ac77b95969a47527bfe0dffa954d78addd60ca23a902e0014a1ad23ce7 | Python | 1,730 | 60 | # Copyright (C) 2022 Intel Corporation
# Copyright (C) CVAT.ai Corporation
#
# SPDX-License-Identifier: MIT
from enum import StrEnum
from django.conf import settings
from cvat.apps.iam.permissions import OpenPolicyAgentPermission, get_iam_context
class LogViewerPermission(OpenPolicyAgentPermission):
has_analyt... |
9ea186ea83958b489e9745613af28797ffa05433944f58ed3268f7faba03c937 | Python | 1,730 | 57 | # -*- coding: utf-8 -*-
import functools
import ssl
from timm.models import create_model
from brainscore_vision.model_helpers.activations.pytorch import (
PytorchWrapper,
load_images,
preprocess_images,
)
from brainscore_vision.model_helpers.check_submission import check_models
ssl._create_default_https_c... |
08544498d8c4a80b6b1a35bc93052fbc96ff94cdce1ee6cee93632e786d584f7 | Python | 1,731 | 17 | """Supplement hierarchy snapshot with two descriptive reaction annotations."""
import datetime,hashlib,json,subprocess
from pathlib import Path
ROOT=Path(__file__).resolve().parents[2];out=ROOT/'data/raw/context/reactome_dna'
p=ROOT/'metadata/reactome_dna_reactions.json'
if p.exists():
d=json.loads(p.read_text())
for... |
3efab4de3e7210aa695dca08f925a68dcefdce25a8597726c6d24b55ad1c94c2 | Python | 1,731 | 54 | #!/usr/bin/env python2.4
"""
Returns all positions of a maf with any pwm score > threshold
The positions are projected onto human coordinates
"""
import sys
from bx.align import maf as align_maf
from bx.pwm.pwm_score_maf import MafMotifScorer
def main():
if len(sys.argv) < 4:
print(f"{sys.argv[0]} motif... |
cc7fcc1de209d64af592479cbe28e18881dce7b32d4eb0edc2a5efd365148da6 | Python | 1,731 | 42 | import torch
import torch.nn as nn
import s3prl.hub as hub
from transformers import Wav2Vec2Model, HubertModel
class PretrainedSpeechModels_hf(nn.Module): # using pretrained speech models from huggingface
def __init__(self, pretrained_model, pretrained_name, final_feat_dim):
super().__init__()
... |
ce70bf52c824678bdf38282aa7047c08f8be30c1a3825d976ae09a21336308fe | Python | 1,731 | 36 | from collections import defaultdict
option_list = defaultdict(list)
def get_option_list(dataset):
if dataset == 'MBC':
# Input parameters
option_list['data_dir'] = '/home/featurize/work/DANST_model/DANST/data/Mouse_Brain_Coronal/'
option_list['ref_dataset_name'] = 'scRNA.h5ad' #scRNA_data... |
718aa097eec8c7ec6c94bf3737c01eea4cc020a96975ddaa90c61c89104ee0f0 | Python | 1,732 | 45 | import os
from typing import Optional
from .reader_image_folder import ReaderImageFolder
from .reader_image_in_tar import ReaderImageInTar
def create_reader(
name: str,
root: Optional[str] = None,
split: str = 'train',
**kwargs,
):
kwargs = {k: v for k, v in kwargs.items() if v is... |
ffe9748e1d8fed3b3284236a5fae9024604c157f160f87984e96403bc5123fd0 | Python | 1,732 | 65 | import os
import numpy as np
import tensorflow as tf
from tensorflow.keras.callbacks import EarlyStopping, ModelCheckpoint
def set_seed(seed=42):
"""
재현성을 위한 시드 고정
"""
import random
os.environ["PYTHONHASHSEED"] = str(seed)
random.seed(seed)
np.random.seed(seed)
tf.random.set_seed(seed)... |
2c77f24a07df0947dde3774ec71ac9b55b1aacaa2300eac5ee68717ed210bca0 | Python | 1,733 | 47 | from tomocupy_stream import GPURecRAM
import numpy as np
import tifffile
import dxchange
theta = np.linspace(0,180,256).astype('float32')
obj = np.random.random([256,256,256]).astype('float32')*1e-5#[:,64:-64,64:-64]
dark = np.zeros([1,obj.shape[0],obj.shape[-1]],dtype='float32')
flat = np.ones([1,obj.shape[0],obj.sh... |
355746225d256c42e388fd1e6c27d5f376508e8f56998c97db6d0abc09fdecad | Python | 1,733 | 53 | # -*- coding: utf-8 -*-
"""
Created on Mon Aug 21 11:01:06 2023
@author: Guido Meijer
"""
import json
from datetime import date
from pathlib import Path
# Get data folder path
project_root = Path(__file__).parent.parent
settings_file = project_root / 'config' / 'settings.json'
with open(settings_file, 'r') as openfi... |
71de5ec9150e1bdd0899278b66c222ce3a1a4e49c802a4c2acc12d0655e4f9f4 | Python | 1,733 | 56 | import pytest
from typing import Tuple
from flair.data import Dictionary, Corpus
from flair.data_fetcher import NLPTaskDataFetcher, NLPTask
from flair.embeddings import WordEmbeddings, DocumentRNNEmbeddings
from flair.models.text_regression_model import TextRegressor
# from flair.trainers.trainer_regression import Re... |
034b34da290a9a3488eb3bf4c37f0105aede49c8e8f3982671470afc2a989c4c | Python | 1,734 | 69 | AZURE_CONFIG = {
"api_version": "2024-12-01-preview",
"azure_endpoint": "YOUR_AZURE_ENDPOINT_HERE",
"api_key": "YOUR_API_KEY_HERE",
"deployment_name": "YOUR_DEPLOYMENT_NAME",
"model": "gpt-4",
"temperature": 0.3,
"max_tokens": 2000,
}
EMBEDDING_CONFIG = {
"azure_endpoint": "YOUR_EM... |
a115c52068190fad430bd7ead746c9bfb9b0cf21d236fa3f91b4ce970f2f542b | Python | 1,735 | 52 | # Copyright (C) CVAT.ai Corporation
#
# SPDX-License-Identifier: MIT
from django.conf import settings
from django.db.models import QuerySet
from django.db.models.functions import Coalesce
from django.utils import timezone
from cvat.apps.access_tokens import models
from cvat.apps.dataset_manager.util import current_fu... |
5bdeb2e4256d167350656f1b595044fa47688ae175d61af6ba868879c2f94139 | Python | 1,736 | 71 | #!/usr/bin/env python
"""
Read a maf and print the text as a fasta file, concatenating blocks. A
specific subset of species can be chosen.
usage %prog [options] species1,species2,... < maf_file > fasta_file
--fill="expression": Insert this between blocks
--wrap=columns: Wrap FASTA to this many columns
"""
im... |
61a361bca0ff0d93a465a1991e8c467ddc3710cfaeaedb33b1bb566a1f695229 | Python | 1,736 | 46 | # This file is part of Mooney computational modeling project.
#
# Mooney computational modeling project 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 option) an... |
6e485582ec06f982e297a86eaf1531b84e42005887d665bf64ef34a2141dbaf5 | Python | 1,736 | 47 | import pytest
from brainscore_vision import load_dataset
@pytest.mark.private_access
@pytest.mark.parametrize('assembly_identifier', [
'Rust2012.single',
'Rust2012.array'])
def test_existence(assembly_identifier):
assert load_dataset(assembly_identifier) is not None
class TestRustSingle:
@pytest.mar... |
b0f260cb48298741be19a4e0eaa887b9e41135b90e7bf58b8b546f8f65a87c6e | Python | 1,737 | 48 | from syri.scripts.func import revcomp, readfasta
def test_ins_coord():
'''
Test that the matching bases for INS (before the inserted sequence) are same
:return:
'''
refseq = readfasta("col.TAIR.fasta.filtered")
qryseq = readfasta("Ler.chr.all.v1.0.fasta.filtered")
with open("sv.txt", 'r') a... |
1538ba84f8d8ca31f2cf2249bf2c00245e84ef20a2a2fac8ea7f68349ffcfd0f | Python | 1,738 | 54 | # Generated by Django 4.2.13 on 2024-07-09 11:08
import django.db.models.deletion
from django.db import migrations, models
class Migration(migrations.Migration):
dependencies = [
("engine", "0078_alter_cloudstorage_credentials"),
]
operations = [
migrations.AlterField(
model... |
a58af889b16e434ef85041121e827b864d36427a3d776b92dad6a19d8417bec0 | Python | 1,738 | 52 | import torch
from torch import Tensor
import torch.nn as nn
from typing import List, Union, Tuple
class Generic(nn.Module):
def __init__(self, backbone: nn.Module, activations: List[nn.Module], channel_indicies: List[List[int]] = []):
"""
A generic wrapper to a segmentation model. Often, it is des... |
37bd234835c23c22ca6b63a94462a4e020fd3a270706ca49b560d464dca8563d | Python | 1,739 | 52 | # Copyright (c) Meta Platforms, Inc. and affiliates. All Rights Reserved
from typing import Callable, Iterable, Optional
from torch.utils.data import DataLoader, Dataset, DistributedSampler, IterableDataset
class TorchDataset:
def __init__(
self,
dataset: Dataset,
batch_size: int,
... |
9d2b518865a79473abf8af73715042ad35825b8faa0d21c3afef028989329436 | Python | 1,739 | 63 | # tifffile/tests/conftest.py
"""Pytest configuration."""
from __future__ import annotations
import os
import sys
from typing import Any
if os.environ.get('VSCODE_CWD'):
# work around pytest not using PYTHONPATH in VSCode
sys.path.insert(
0, os.path.abspath(os.path.join(os.path.dirname(__file__), '..... |
eeed3157fb1944487ab7623b4fb0b69d80082c9b9ae68d698fc5479e36fd02b9 | Python | 1,739 | 42 | from argclz import AbstractParser
from neuralib.plot import plot_figure
from rscvp.spatial.main_cache_align_peak import ApplyAlignPeakCache
from rscvp.spatial.main_cache_occ import ApplyPosBinCache
from rscvp.spatial.util_plot import plot_alignment_map
from rscvp.util.cli.cli_output import DataOutput
__all__ = ['Align... |
9fba3fc4f6483403ca257a2129b3cbcd41b91bde5259119a630863d526f13a51 | Python | 1,740 | 44 | import torch
from itertools import combinations_with_replacement
__all__ = ['texture_filter']
def symmetric_image(images: list):
nd = images[0].ndim - 2
# Array[..., nd, nd] required e.g. for eigvalsh
sym = torch.zeros(images[0].shape + (nd,) * 2, dtype=images[0].dtype, device=images[0].device)
for i... |
f3b3db65cd26eab1d1df0141b7a7c47427c9f621ea5365220a1d8711ea62a003 | Python | 1,740 | 46 | # The ImpedanceFitter is a package to fit impedance spectra to
# equivalent-circuit models using open-source software.
#
# Copyright (C) 2018, 2019 Leonard Thiele, leonard.thiele[AT]uni-rostock.de
# Copyright (C) 2018, 2019, 2020 Julius Zimmermann,
# julius.zimmermann[AT]un... |
548f668d20d508783efc364703d502e0cb963f8ac03b84e3a135a653d6e31f33 | Python | 1,743 | 66 | # emacs: -*- mode: python; py-indent-offset: 4; indent-tabs-mode: nil -*-
# vi: set ft=python sts=4 ts=4 sw=4 et:
### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ##
#
# See COPYING file distributed along with the PyMVPA package for the
# copyright and license terms.
#
### ### ### ### ###... |
a3eab09f52799c3b2df6f381697eed403a55277b8a228668eefeb0ad260f7dd7 | Python | 1,743 | 64 | # -*- coding: UTF-8 -*-
from __future__ import unicode_literals
import sys,os
sys.path.append("../")
from whoosh.index import create_in,open_dir
from whoosh.fields import *
from whoosh.qparser import QueryParser
from jieba.analyse.analyzer import ChineseAnalyzer
analyzer = ChineseAnalyzer()
schema = Schema(title=TEX... |
174bee7d799f72a8fe47781a0d6c0a26ca8a01fd885a1390498dbea450d3a74c | Python | 1,744 | 57 | # SPDX-FileCopyrightText: Copyright © Timo Koch
# SPDX-License-Identifier: GPL-3.0-or-later
from zenodo_download import download_single_file, get_file_list, Settings
from pathlib import Path
import argparse
import shutil
def main():
parser = argparse.ArgumentParser(description="Download files.")
parser.add_a... |
438bcc541c2dcaf03dcf68ae379fb2762adc7fe1f743c25b2bd53d494f71da7f | Python | 1,744 | 54 | import dipy.core.gradients as dpg
import nibabel as nib
import numpy as np
def prepare_data(data_files, bval_files, bvec_files, mask=None, b0_threshold=50):
"""
Parameters
----------
data_files : str or list
Files containing DWI data. If this is a str, that's the full path to a
single ... |
67e44786e1514730e7515dade748a1f8c8ef4af3dfc3cdaf5d4a7a76c1062588 | Python | 1,745 | 57 | from django.db import migrations, models
import cvat.apps.engine.models
def check_list_chunks(apps, schema_editor):
Data = apps.get_model("engine", "Data")
CHUNK_TYPE = "list"
related_rows = (
Data.objects.filter(
models.Q(compressed_chunk_type=CHUNK_TYPE) | models.Q(original_chunk_... |
fc78e78c14c75eca763762b6fa01cd09acd60e855675ba70a15dfce70918531c | Python | 1,745 | 42 |
import dtiplayground.dmri.preprocessing as prep
from dtiplayground.dmri.common.dwi import DWI
import yaml
from pathlib import Path
import os
import markdown
class UTIL_Merge(prep.modules.DTIPrepModule):
def __init__(self,config_dir,*args,**kwargs):
super().__init__(config_dir,*args,**kwargs)
glo... |
Subsets and Splits
No community queries yet
The top public SQL queries from the community will appear here once available.