sha256 stringlengths 64 64 | language stringclasses 27
values | size int32 1 491k | lines int32 1 21.8k | content stringlengths 1 200k |
|---|---|---|---|---|
d871806e3bfef067d1d452005a7be9ce37adbc51e44d1bd6e9c331d840a256da | Python | 21,629 | 636 | # Created by: Marc Canela
from pathlib import Path
from typing import Dict, Tuple, Union
import matplotlib.pyplot as plt
import numpy as np
import pandas as pd
from imblearn.over_sampling import SMOTE
from scipy.stats import entropy
from sklearn.cluster import KMeans
from sklearn.decomposition import PCA
from sklearn... |
39fcbfb9be8b82185c739dcb276cc4a258c0a39fa38348ccd346f18e57e1f697 | Python | 21,631 | 499 | import slicer, vtk
import numpy as np
from io import StringIO
import warnings
#
# Feature
#
class Feature():
def __init__(self, name, projectTo, exportXYZ):
self.name = name
self.projectTo = projectTo
self.exportXYZ = exportXYZ
def addSourceNode(self, sourceNodeID, property, visible):
shNode =... |
2a4e33b92cc32fd346c1a4078698793cd3ef5e443bdacfc73a7b89e29a25b826 | Python | 21,633 | 486 | from collections.abc import Sequence
from decorator import decorator
import copy
import math
import types
import inspect
import torch
from torch import nn
from torch import autograd
from torch_scatter import scatter_add
from torchdrug import core, layers, utils, data
from torchdrug.layers import functional
from torc... |
a7c22b5f236b702aa3342a1c5590b3b03c9e8f4cfb8d44f640282c4dd4c33582 | Python | 21,640 | 671 | # -*- coding: utf-8 -*-
"""
Created on Wed Aug 16 11:25:30 2023
@author: DELINTE Nicolas
"""
import numpy as np
from tqdm import tqdm
from sklearn.cluster import KMeans
from dipy.io.streamline import load_tractogram, save_tractogram
from unravel.utils import tract_to_ROI, xyz_to_spherical, get_streamline_density
fro... |
e8fe36959a8b661d67f1bc115fc4d351343ee4a19c829e6ce9e0f8532f4aa11e | Python | 21,641 | 511 | import matplotlib.pyplot as plt
import matplotlib.ticker as ticker
import jax.numpy as jnp
import jax
import os
import json
import sys
import glob
import matplotlib.colors as mcolors
from matplotlib.colors import to_rgba
from collections import Counter
from scipy.stats import gaussian_kde
plt.rcParams["font.sans-s... |
7cd943635bf909ede855ad72d5630ce52e4cb9eb5cf0b359a00397b59a98741d | Python | 21,659 | 517 |
import sys, math
import numpy as np
from Parameters import *
######################
##### GLOBAL #####
######################
s1, s2, W, V, H = '', '', None, None, None
MULTIPLE_HAIRPIN = True
MAX_LOOP = 9999
MAX_SEQ_LENGTH = 100
V = np.zeros((MAX_SEQ_LENGTH, MAX_SEQ_LENGTH))
W = np.zeros((MAX_SEQ_LENGTH, MAX_S... |
45aa20d469c7defaf6e72db230f63d216021358d1d8acd456427f5b551e3585e | Python | 21,679 | 484 | import argparse
import time
import warnings
import torch
import os, time
import sys
import yaml
import wandb
import datetime
import logging
import random
import numpy as np
import pandas as pd
import transformers
import json
import torch.nn as nn
from tqdm import tqdm
from torch.utils.data import DataLoader
from typing... |
d0a109a013b353ec3e98c42ef5061a32152a72b181c4199e465d21bfc34fbc82 | Python | 21,697 | 639 | from collections import defaultdict
from typing import Any, Dict, Iterable, List, Literal, Optional, Tuple, Union
import torch
from torch import Tensor
from torch.utils.dlpack import from_dlpack, to_dlpack
import torch_geometric
from torch_geometric.utils.num_nodes import maybe_num_nodes
def to_scipy_sparse_matrix(... |
75441a5c0fbdba40694a4e0efa4e24cc688686abac5ed8f47883cccd004f79dc | Python | 21,707 | 462 | #! /usr/bin/env python3
# -*- coding: utf-8 -*-
"""
Local streamline HARDI tractography using scilpy-only methods -- no dipy (i.e
no cython). The goal of this is to have a python-only version that can be
modified more easily by our team when testing new algorithms and parameters,
and that can be used as parent classes ... |
04e01417daadbfd679e67ce84fddf8bdfa01235d5f7216caddf4af693a7c20cb | Python | 21,708 | 553 | import importlib.util
import json
import os
import shutil
from pydantic import BaseModel, Field, model_validator, field_validator
from typing import Union, Optional, Any, List, Type
from chemgraph.schemas.atomsdata import AtomsData
from chemgraph.schemas.calculators.emt_calc import EMTCalc
from chemgraph.schemas.calcu... |
17bcfa82cd95fb0bfe9fc74a30bd4ce7d576b0be71fee159f58a46f437abcdcb | Python | 21,711 | 753 | import os
import h5py
import logging
import unittest
import pandas as pd
import numpy as np
from numpy.testing import assert_array_equal
from heig.sumstats import check_input, map_cols, read_sumstats, GWAS, GWASLDR, GWASY2
MAIN_DIR = os.path.join(os.getcwd(), "test", "test_sumstats")
log = logging.getLogger()
log.set... |
c549a73ee20462dd5c71be98b2d54e8c999ea82e1ddf20df24744c08f519468a | Python | 21,712 | 531 | # Ultralytics 🚀 AGPL-3.0 License - https://ultralytics.com/license
from __future__ import annotations
import numpy as np
from ultralytics.cfg import TASK2DATA, TASK2METRIC, get_cfg, get_save_dir
from ultralytics.utils import DEFAULT_CFG, DEFAULT_CFG_DICT, LOGGER, NUM_THREADS, checks, colorstr
RAY_SEARCH_ALG_REQUIR... |
012614ee16277b365a907b1b4e05bba29f628c5de1a078e3e517e04a55f7e734 | Python | 21,721 | 524 | """
(C) Copyright 2019 IBM Corp.
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 applicable law or agreed to in writing, software
... |
4fb6088f7f8ac697109d7858412d7b6d1ca238c23d8f9df1839563013679b804 | Python | 21,727 | 553 | #pylint: skip-file
#type: ignore
"""
Implementation of the context dependent reach task
"""
import time
import math
import typing
import asyncio
import logging
import datetime
import numpy as np
import os
import stl
from . import task_context
from .widgets import Form, ListAsTabsWidget
from .util import wait_for, wai... |
7cef74d041d057669474acd2e7d11e2d8e10b784fc71a160f1d121a5658dce61 | Python | 21,728 | 568 | """The FunctionGui class is a Container subclass designed to represent a function.
The core `magicgui` decorator returns an instance of a FunctionGui widget.
"""
from __future__ import annotations
import inspect
import re
from collections import deque
from collections.abc import Callable
from contextlib import conte... |
5bbaf31adf2ebe446f14030fec481c6724e74e5b7314b758c0fce5d937de8d5c | Python | 21,734 | 568 | # Copyright (C) 2022 Intel Corporation
# Copyright (C) CVAT.ai Corporation
#
# SPDX-License-Identifier: MIT
import json
import operator
from collections.abc import Iterable, Iterator
from functools import reduce
from textwrap import dedent
from typing import Any, TypeAlias
from django.db import models
from django.db.... |
89041bd42272c544afc0f323129ab9c475c11bd1774e7edb9a8b3d48032de9a0 | Python | 21,734 | 470 | """Hermetic usage accounting across providers, storage, and graph execution."""
from concurrent.futures import ThreadPoolExecutor
import uuid
import pytest
from langchain_core.language_models.fake_chat_models import FakeMessagesListChatModel
from langchain_core.messages import AIMessage, AIMessageChunk
from langchain... |
205df60889415cbc60d26177aa363ef28bc2f28fea608bff47673b6950a8a5c1 | Python | 21,739 | 330 | """
If you use this code, please the SynthSR paper in:
https://github.com/BBillot/SynthSR/blob/master/bibtex.bib
Copyright 2020 Benjamin Billot
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:... |
be17430977288bda951d8e5b1689ca4b6d346340c0b998f28a5082a3dc1095b1 | Python | 21,741 | 549 | # Copyright 2024 Google LLC
#
# 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
#
# https://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, ... |
e1f1e30d7f95cb8121be9c0b562106b4092f578389fd133e692b08e5cdfb8b69 | Python | 21,744 | 670 | from tierpsy.gui.HDF5VideoPlayer_ui import Ui_HDF5VideoPlayer
import sys
import tables
import os
import numpy as np
from functools import partial
from tierpsy.analysis.compress.Readers.readLoopBio import readLoopBio
from PyQt5 import QtWidgets, QtCore, QtGui
from PyQt5.QtCore import Qt
from PyQt5.QtWidgets import Q... |
3fbfe11d630a8378637ad8b3d246e9d276c4c4abf33174ec161216e5b10aab02 | Python | 21,765 | 426 | # -*- coding: utf-8 -*-
# @Author: Jie Yang
# @Date: 2017-12-04 23:19:38
# @Last Modified by: Jie Yang, Contact: jieynlp@gmail.com
# @Last Modified time: 2018-12-16 22:15:56
from __future__ import print_function
import torch
import torch.autograd as autograd
import torch.nn as nn
import torch.nn.functional as F... |
c6f709bab66f5b86b4708ee8935198944a8cb20ed9711afeef1e16d20e9a5aa5 | Python | 21,781 | 752 | """Generate a QC summary HTML report from pipeline plots."""
from __future__ import annotations
import html
import json
import shutil
from pathlib import Path
from datetime import datetime
STEPS = {
1: {
"name": "Preprocessing",
"subpanels": [
{
"name": "PSD",
... |
5159bb8020f85eed2e08de3579e99a56d036151f18930eab0a9e8727a396ed5f | Python | 21,783 | 546 | """
ENIGMA-style cortical surface plotter for AAL atlas on fs_LR 32k space.
Loads fs_LR 32k inflated surfaces and AAL 32k label files, maps per-ROI
statistic values to vertex-level scalars, and renders publication-quality
views with ENIGMA-like matte directional lighting and medial wall masked in
white. It produces o... |
a48580d836983fdaae5b2436b9eb5c5f3dde7eedd12ace3eee48cc06f3fb28f8 | Python | 21,792 | 693 | # Created by: Marc Canela
from pathlib import Path
from typing import Any, Dict, List, Optional, Tuple, Union
import numpy as np
import pandas as pd
from scipy.stats import uniform
from shapely.geometry import Polygon
from skimage.draw import polygon
from skimage.feature import graycomatrix, graycoprops, hog, local_b... |
fd51e8fbb8048f506d03472fe2db9a3494076337053d1071aa138d79bfff4831 | Python | 21,800 | 642 | import asyncio
import random
import time
from collections.abc import Sequence
from concurrent.futures import ThreadPoolExecutor
from contextlib import contextmanager
from math import isclose
from pathlib import Path
from typing import TYPE_CHECKING, Any
import numpy as np
import pandas as pd
import pytest
import torch... |
ae102ae5817e60c05465e28a097447537d2b92155e2680c07a1128d7988d9a7a | Python | 21,805 | 635 | import matplotlib.pyplot as plt
from matplotlib import cm
import numpy as np
import torch
def plot_selected_cell_type_flow(
pcloud_list, model, device, finaltruth,
selected_cell_type, arrow_sample_size_per_type=55,
xlim=(-0.2, 1.5), ylim=(-0.5, 2), height_scale=1.0,size=1,alpha=1,save_path=None
):
fi... |
22fd6c50040d4951a4423d871214ca87a95c2f02215bd5edc2d512ef99831b47 | Python | 21,823 | 515 | #alg_name = 'mlp_cs'
import os
os.environ["OMP_NUM_THREADS"] = "2" # export OMP_NUM_THREADS=1
os.environ["OPENBLAS_NUM_THREADS"] = "2" # export OPENBLAS_NUM_THREADS=1
os.environ["MKL_NUM_THREADS"] = "2" # export MKL_NUM_THREADS=1
os.environ["VECLIB_MAXIMUM_THREADS"] = "2" # export VECLIB_MAXIMUM_THREADS=1
os.envi... |
237fd4e711270b53ceefe992297b4bdbf150dc6e46af3f8cd64ecc91996f3794 | Python | 21,827 | 795 | # !/usr/bin/env python
# -*- coding: utf-8 -*-
'''
@Author: Yong Bai, yong.bai@hotmail.com
@Time: 2022/10/19 15:42
@License: (C) Copyright 2013-2022.
@File: cci_analysis.py
@Desc:
'''
from typing import Union
import numpy as np
import pandas as pd
import squidpy as sq
import scanpy as sc
from scipy.stats import entro... |
5545658daa20c5e8412e83f237b34003b0f3d5de2c83f06a3b0755356ef8f02b | Python | 21,833 | 593 | import pandas as pd
import sys
import os
from glob import glob
import anndata as ad
import scipy.sparse as sp
import anndata
test_name_to_expectations = {
"no_edits_edge_case_test": {
"folder": "strandedness_tests",
"total_edit_sites": 0,
"expectations": []
},
"edge_case_test": {
... |
2c61247b061cfc8532542a627351e8816b75acb3eb16bcdbf45d2cfcd69cd963 | Python | 21,838 | 490 | import pdb
import numpy as np
import glob
import os
from os.path import join
import pandas as pd
import matplotlib.pyplot as plt
from sklearn.linear_model import LinearRegression
from labellines import labelLine, labelLines
import seaborn as sns
import math
from statannot import add_stat_annotation
import pickle
def ... |
5f1d932506949402144dc325c35ef38800715b8f4f3ea195f0434458bc0437b7 | Python | 21,842 | 600 | import torch
from torch import nn
from torch_geometric.nn import RGCNConv,FastRGCNConv,GCNConv,GATConv
import torch.nn.functional as F
class BotRGCN(nn.Module):
def __init__(self,des_size=768,tweet_size=768,num_prop_size=5,cat_prop_size=3,embedding_dimension=128,dropout=0.3):
super(BotRGCN, self).__init__(... |
c360b5be84981ace1b99a08d6e39761b80ce2beef52a710a19f25707dc56d3e9 | Python | 21,848 | 483 | """Assembling the one table every statistical analysis in step 5 is run on.
MATLAB's ``doStats``/``doClassification``/``doLDA`` each take a
``recordingLevelData`` table that ``MEApipeline.m`` builds inline, and each
re-derives the things they need from it — which columns are metrics, which
recordings belong to the sam... |
5049214683feedab5e88c76a98f4de2f82525ce7f8f7e16536728d3166a2fdd8 | Python | 21,860 | 594 | # -*- coding: utf-8 -*-
from importlib.resources import files
import json
import logging
import os
import tqdm
import numpy as np
from scipy import ndimage as ndi
from scipy.spatial import cKDTree
from scilpy.tractanalysis.reproducibility_measures import compute_bundle_adjacency_voxel
SCILPY_LUT_DIR = files("scilpy"... |
97bc42762f90548825ba5c55e2b4962c6f6ba2a51371f6b9f533bb0dc8460523 | Python | 21,864 | 562 | import sys
from pathlib import Path
import os
sys.path.append(str(Path(os.path.abspath(__file__)).parents[3]))
# limit CPU load for the server
os.environ["OMP_NUM_THREADS"] = "2" # export OMP_NUM_THREADS=1
os.environ["OPENBLAS_NUM_THREADS"] = "2" # export OPENBLAS_NUM_THREADS=1
os.environ["MKL_NUM_THREADS"] = "2" # ex... |
162c612980d35c34de2acbcc44983f9a253c8da9496577f21c283e6778d00409 | Python | 21,867 | 485 | # Ultralytics 🚀 AGPL-3.0 License - https://ultralytics.com/license
from __future__ import annotations
import numpy as np
class KalmanFilterXYAH:
"""A KalmanFilterXYAH class for tracking bounding boxes in image space using a Kalman filter.
Implements a simple Kalman filter for tracking bounding boxes in im... |
c6a7716466936d76a2688a00da64ee996a554fca4fe09bbb06eebcf7d59e593a | Python | 21,893 | 696 | # -*- coding: utf-8 -*-
# python standard library inputs
import os
import datetime
import warnings
import subprocess
import functools
import shutil as sh
from shutil import copyfile
from abc import ABC, abstractmethod
# external inputs
import numpy as np
from scipy.stats import norm
from scipy.sparse.linalg import ex... |
aaecd50274d87c0c15c599503155b771389fa14ff9b88be84472750d6b83ad63 | Python | 21,912 | 558 | # Copyright (c) 2026 Rohit Jena. All rights reserved.
#
# This file is part of FireANTs, distributed under the terms of
# the FireANTs License version 1.0. A copy of the license can be found
# in the LICENSE file at the root of this repository.
#
# IMPORTANT: This code is part of FireANTs and its use, reproduction, or... |
b27fcff53a8e19b80dcbdd271895c8125ec90d41abc6aa36f274bd33ba7cbc9b | Python | 21,912 | 564 | import json
import os
import re
import sys
import numpy as np
import pandas as pd
import tables
from PyQt5.QtCore import QPointF, Qt
from PyQt5.QtGui import (
QPixmap, QImage, QPolygonF, QPen, QPainter, QColor)
from PyQt5.QtWidgets import (
QApplication, QFileDialog, QMessageBox, QWidget, QPushButton)
from ti... |
586641c6b03e9e53cb62de90d5f01957b4b267209ed109f58b9802d7788a74d7 | Python | 21,932 | 549 | #!/usr/bin/env python
"""
This module enables the processing of camera frame(s) with
operations like averaging, slicing, etc..
It is also responsible for keeping tracking of how many
different cameras / feeds are available for each parameter
file, whether the cameras / feeds should be saved when
filming and what exten... |
d40d39cd0fcebd3cfe29e3899f67bc13183fa6e139157d2e8a8b2bcaabff7b02 | Python | 21,937 | 561 | import numpy as np
import scipy as sp
import matplotlib.pyplot as plt
from skimage.feature import peak_local_max
import pandas as pd
from IPython.display import display
from .utils import stat as stat
from .utils import filters as flt
from .utils import util
from .utils import vis
# import NFT.linking as NFTLinking ... |
de3ef3d366f65f96083849f9a13af28668c16f158a9c79e882aa8593d06d8ba0 | Python | 21,945 | 440 | #!/usr/bin/env python
from __future__ import print_function
import os
import json
import argparse
import csv
import re
import sys
import urllib.request
import errno
import gzip
from collections import OrderedDict
def prRed(skk, f): print("\033[91m{}\033[00m" .format(skk), file=f)
def prGreen(skk, f): print("\033[92m{... |
c783c63dcab8af2de916374f487ddb9caa762fd3a2977636eaefee89fb3e5c47 | Python | 21,949 | 601 | # Copyright 2024 Google LLC
#
# 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
#
# https://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, ... |
29c968b293e5ef25bb60c0a5a09fa10ebf130e6c8a5aaed07ee39dcb566a4f6f | Python | 21,958 | 575 | # -*- coding: utf-8 -*-
"""
Analyses of the EMPRISE data set
by Joram Soch <soch@cbs.mpg.de>
"""
# import modules
import os
import time
import shutil
import NumpRF
import EMPRISE
import numpy as np
import scipy as sp
# import pandas as pd
# import nibabel as nib
# import matplotlib.pyplot as plt
### linear-model cv... |
4321884f822f42ad0c4f8baa5091eab215d19468db37dd3875c3b9e1f61cf2f5 | Python | 21,959 | 537 | """
Gated Recurrent Unit
"""
from typing import Callable, Union, Optional
import braintrace
import brainstate
import brainunit as u
import jax
import jax.numpy as jnp
import numpy as np
__all__ = [
'FiringRateState',
'SpikeFunction',
'EGRU',
'MergeEvents',
'Network',
]
class FiringRateState(bra... |
96b9d93f255ccaec77a11eda32dbe4a90a48300902149a254cab6aaf3becd6fb | Python | 21,960 | 573 | import os
import csv
import re
from typing import Tuple
import tkinter as tk
from tkinter import messagebox
from tkinter import font as tkFont
from PIL import Image, ImageTk
from util.config_vars import config
class ManualImageEvaluator:
"""Evaluation GUI for manual labelling of defacing success."""
def __ini... |
11111252b98b26fd6bfd92cacee0a99833e5b85b66a0b5d54c3f0e3dde6c6f4e | Python | 21,963 | 562 | """Tests for mcmlnet.utils.tensor module."""
import numpy as np
import pytest
import torch
from mcmlnet.utils.tensor import (
array_conversion_decorator,
convert_to_numpy,
convert_to_torch,
tensor_conversion_decorator,
)
class TestBasicMethods:
"""Test cases for basic conversion functions."""
... |
cb7bc6f8de0aa49ffded3b812696625776c4dc71efbfc47de686b0909bdaee7c | Python | 21,963 | 495 | import os
import h5py
import itertools
import numpy as np
import datajoint as dj
from commons import lab
from scipy import ndimage
from pipeline.utils import h5
from datajoint.hash import key_hash
from .exceptions import PipelineException
from pipeline import meso, stack, mice, experiment, shared
#dj.config['extern... |
e8f739356998521cd6e2cf00299915605dade1a17ddbd797175c3ea66b08753e | Python | 21,965 | 149 | import math
import numpy as np
import pandas as pd
import networkx as nx
import matplotlib.pyplot as plt
from numpy import array
import os
def sign(x):
y = 0
if x == '6':
y = -1
elif x == '9':
y = 0
elif x == '1':
y = 1
return y
def xs(x, y, w):
if len(x) == len(y) ==... |
90f8b14c8a1aa086288b248a8cc79f58f099c8b8f7c442ecd813ac686c0ebaa2 | Python | 21,981 | 646 | import asyncio
import random
import time
from collections.abc import Sequence
from concurrent.futures import ThreadPoolExecutor
from contextlib import contextmanager
from math import isclose
from pathlib import Path
from typing import TYPE_CHECKING, Any
import numpy as np
import pandas as pd
import pytest
import torch... |
d3da40f75e11ccb885cb31f7f1abddbae4fd76aa6034fef39065248341fac877 | Python | 21,982 | 548 | ## ------------------------------------------------------------
## IMPORTS
## ------------------------------------------------------------
## ----- MATH / STATS ----- ##
import torch
import numpy as np
## ----- PLOTTING ----- ##
import matplotlib as mpl
from cycler import cycler
from IPython import display
from tqdm.... |
fc35129ead11aad22cdaae2ca22e8c122f2f405ad25275f0bb5ab402a435cea4 | Python | 21,982 | 440 |
import dtiplayground.dmri.preprocessing as prep
from dtiplayground.dmri.common.dwi import DWI
import dtiplayground.dmri.common
import yaml
from pathlib import Path
# import SUSCEPTIBILITY_Correct.utils as utils
from dtiplayground.dmri.common import measure_time
import dtiplayground.dmri.common.tools as tools
import ... |
5b6875ec4b31be21258587efa5f96eb5308de2a2a8b0abf97f9c1f7988db0cc5 | Python | 21,983 | 692 | import warnings
from collections.abc import Callable
from enum import Enum
from functools import partial
from typing import TYPE_CHECKING, Literal, Union
import polars as pl
import torch
from torch import nn
from torchsurv.loss.cox import neg_partial_log_likelihood
from eir.setup import schemas
from eir.setup.output_... |
ae3167253b300a9f1b652994d663fe03037c14fb624b867c1b91573abdb73cd0 | Python | 21,992 | 507 | """Test the remote-data abstraction: store protocol, cache, budgeting, redaction.
Run from the repo root::
uv run python python/test_remote_cache.py
The point of this layer is to let a batch bigger than the local disk run at all,
so the checks that matter are the ones about *bounds*: that a cache honours its
bud... |
99f56a6855525d1c2ccfac58607fcc659f42b8f53a82aa56db047ad9aed5613b | Python | 21,998 | 655 | """
Reuseable widgets
"""
import typing
import logging
import functools
from ..qt import *
from ..config import ObservableCollection, ObservableDict
from .util import remove_by_is, isdeleted
LOGGER = logging.getLogger(__name__)
class ColorWidget(QWidget):
"""
Widget for rendering a selected color
"""
def _... |
802adbeead9970aedd39093b938de1aaf9162d7796b43adc713c648c9720ea9c | Python | 22,000 | 396 | import sys
from pathlib import Path
p_dir = str(Path(__file__).absolute().parents[1])
if p_dir not in sys.path: sys.path.insert(0, p_dir)
import os
import time
from argparse import ArgumentParser, Namespace
import json
import logging
import random
from functools import partial
import warnings
# from rich.traceback im... |
2db6711edc6ab7ea5437457f7bac30febfbbb3f215872c265268040c1361165e | Python | 22,001 | 595 | """
code for interpreting time-series feature hits
and testing specificity of synapse-hctsafeature relationships
"""
import numpy as np
import pandas as pd
import seaborn as sns
import matplotlib.pyplot as plt
from matplotlib.colors import LinearSegmentedColormap
from palettable.colorbrewer.sequential import (PuBuGn_4... |
fc0eaf5a455ba3454fd1fa13b09d84f073a354a33c7dcda00320045d00f3abc8 | Python | 22,011 | 640 | """utils.py."""
import functools
import logging
import operator
from collections.abc import Mapping
from typing import Any
import jax.numpy as jnp
import networkx as nx
import numpy as np
import numpy.typing as npt
import pandas as pd
import scipy.stats as st
from jax import Array
from numpyro.diagnostics import summ... |
f6787828ed2ef765c5c85f8fa1de5f91ca4b5188f2e2371220d19a9d99cdc8ed | Python | 22,021 | 688 | # -*- coding: utf-8 -*-
# Original source: github.com/scilus/scilpy
# Copyright (c) 2012-- Sherbrooke Connectivity Imaging Lab [SCIL],
# Université de Sherbrooke.
# Licensed under the MIT License (https://opensource.org/licenses/MIT).
# Modified by John Kruper for pyAFQ
# OpenCL and cosine filtering removed
# Replaced ... |
ca56385c5e71e59a6d4fdc6c8f2b45c9ac7e47a3d043793f6c4cde90da01f65b | Python | 22,025 | 642 | import json
from collections.abc import Generator, Iterator, Sequence
from copy import deepcopy
from dataclasses import dataclass
from pathlib import Path
from typing import (
TYPE_CHECKING,
Any,
Union,
)
import numpy as np
import torch
from aislib.misc_utils import ensure_path_exists
from diffusers.schedu... |
2bd6614abd3e4f1e83c6f6d57d7ffd7bc6d01f66e7ddd438b15f1fee816a1062 | Python | 22,031 | 451 | import numpy as np
import pandas as pd
import xarray as xr
from xarray import DataArray
import itertools
from brainscore_core.supported_data_standards.brainio.assemblies import DataAssembly, array_is_element, walk_coords
from brainscore_core import Score
from brainscore_vision.benchmarks import BenchmarkBase
from brai... |
a9e23a3b1133b30c2c573d7a5dd7c1a02d4d1d9bd5ed74f605efbb89397517a2 | Python | 22,031 | 504 | import torch
from torch import nn
from torch.nn import functional as F
from torchvision.models import resnet as tvr
from os.path import isfile
from ..util.util import Dict, lookup_nn, get_nd_conv, get_nn, resolve_pretrained
from torch.hub import load_state_dict_from_url
from .ppm import append_pyramid_pooling_
from typ... |
670e2e9249a045d5fd7e92ea03f0d73a961a7b46f25eb60918284921dd5c701e | Python | 22,040 | 597 | import numpy as np
import pandas as pd
from pandas import DataFrame
from scipy.spatial import distance_matrix
import scanpy as sc
from anndata import AnnData
from sklearn.neighbors import kneighbors_graph, NearestNeighbors
import scipy
import ot
import torch
import gudhi
import networkx as nx
from torch_geometric.nn im... |
1810fbe293c0ed5fd66a143f553630dbee87417449243567e79e50083b9117db | Python | 22,054 | 562 | from dataclasses import dataclass, field
from typing import Any, Literal, Protocol, Union, cast
from torch import nn
from eir.models.fusion import fusion
from eir.models.input.array.array_models import CNNModelConfig
from eir.models.input.image.image_models import get_image_model_class
from eir.models.input.sequence.... |
955a7a852884b15ca1028ff5eff5190de8a90b99af51c09e2f12d2b2d929496d | Python | 22,056 | 519 | """
Stratified k-fold linear probe evaluation on the GMA dataset.
Uses a multiple-instance learning (MIL) setup:
- All sessions per infant are used (not just the last).
- Each seq_len window of a recording is a separate training example.
- Splits are subject-level: no infant spans train and test folds.
- Test ... |
d5062a54653ae00bca339d082572934ee66ee7f37759df6b7ebdba579c982b3d | Python | 22,066 | 622 | # Copyright 2019 Image Analysis Lab, German Center for Neurodegenerative Diseases (DZNE), Bonn
#
# 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... |
15e275ae1ae1e2fba9cbfbbae344711d08f343cde2275a39b54877fbc8b5c383 | Python | 22,081 | 449 | """(C) Copyright 2019 IBM Corp.
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 applicable law or agreed to in writing, software
d... |
588535ded815b581ea4850d915616f80955cea7d0403a6da77bb733899dc70c0 | Python | 22,084 | 543 | """
Membrane thickness measurement for surface morphometrics pipeline.
Analyze density sampling CSV files to measure membrane thickness by fitting
dual gaussians to density profiles. Writes per-triangle thickness back into the
surface graph/.vtp/.csv in place, and generates summary statistics and plots.
Pipeline Cita... |
16ce65fcf3bbd68cd5d97038ba8b406c57bb6e49e51405fcc75fd9084e540e47 | Python | 22,085 | 405 | #!/usr/bin/env python
# Copyright (c) 2015 Tobias Neumann, Philipp Rescheneder.
#
# This file is part of Slamdunk.
#
# Slamdunk is free software: you can redistribute it and/or modify
# it under the terms of the GNU Affero General Public License as
# published by the Free Software Foundation, either version 3 of the
#... |
561e7bb736d3e0371a5f70d8b123d5fa6b7e63112f6e9109a2e8b27296896cb1 | Python | 22,085 | 608 | """Atomistic LIne Graph Neural Network.
A prototype crystal line graph network dgl implementation.
"""
from typing import Tuple, Union, List
import dgl
import dgl.function as fn
import numpy as np
import torch
from dgl.nn import AvgPooling
# from dgl.nn.functional import edge_softmax
try:
from pydantic.typing im... |
d4ef4b0a58a9d6e17af73ef95cfbc5c4f92223683df277da8209683a2ecd1e67 | Python | 22,105 | 632 | """Data preprocessing functionality."""
import numpy as np
import torch
import torch.jit
from sklearn.model_selection import KFold
from mcmlnet.transforms.physiological import PhysiologicalToPhysicalTransformer
from mcmlnet.utils.loading import SimulationDataLoader
from mcmlnet.utils.logging import setup_logging
from... |
8eee096c748c41c168200f1d30ec26d10baf037c36a48522636ae258385e56cc | Python | 22,121 | 662 | # Copyright (C) 2021-2022 Intel Corporation
# Copyright (C) CVAT.ai Corporation
#
# SPDX-License-Identifier: MIT
from collections.abc import Callable
from http import HTTPStatus
from pathlib import Path
from typing import Any
from uuid import uuid4
import pytest
from cvat_sdk import exceptions
from cvat_sdk.core impo... |
63d51fa299b2ba2feed969718ef2f718bf650fd284d4cdc92d4e58d33aefc8ae | Python | 22,127 | 553 | #!/usr/bin/env python
"""
This module enables the processing of camera frame(s) with
operations like averaging, slicing, etc..
It is also responsible for keeping tracking of how many
different cameras / feeds are available for each parameter
file, whether the cameras / feeds should be saved when
filming and what exten... |
ee1b4288327b580d5a5faa7a3857ab6f0dd512743fd403f1d1bc948196473b43 | Python | 22,133 | 702 | from pathlib import Path
from typing import TYPE_CHECKING
import numpy as np
import pandas as pd
import torch
from lifelines import KaplanMeierFitter
from matplotlib import pyplot as plt
from sklearn.preprocessing import KBinsDiscretizer
from torchsurv.metrics.auc import Auc
from eir.experiment_io.output_object_io im... |
7b03b786be6c45ebc4775fe1b12f24c2c2a4f5f009a0613884786590dab6d3af | Python | 22,165 | 560 | #!/usr/bin/env python3
"""
Non-Physiological Artifact Detector using Deep Lightweight CNN (DLCNN)
Binary classifier for detecting non-physiological artifacts (electrode artifacts,
cable noise) in EEG data.
Authors: Evans Nyanney, Parthasarathy D Thirumala, Shyam Visweswaran, Zhaohui Geng
Year: 2025
License: MIT
"""
... |
8b331c7499fc1fcfc24fade3309958a970df0387bd2870c7d9225b8b96ca03a4 | Python | 22,168 | 499 | """Gabor-filter entropy features for arbitrary image sets.
This is a standalone Python port of the descriptor behind the
GaborFilterEntropy4x4Cosine model from the EntropyReanalysis MATLAB scripts.
The default settings match that model: 256x256 grayscale images, six octave
frequency bands [1, 2, 4, 8, 16, 32], si... |
83bbd94d078312b8417c8479a32b277d94ab16dc522d201c1d21f7a0c81088fc | Python | 22,170 | 517 | import numpy as np
import pandas as pd
from pathlib import Path
import json
import cv2
import tifffile
from typing import List, Tuple, Union
from concurrent.futures import ProcessPoolExecutor, as_completed
from brainglobe_atlasapi import BrainGlobeAtlas
from napari_dmc_brainmap.registration.sharpy_track.sharpy_track.mo... |
f91299e973eb76ccf06e137c57b959a558797ff0088350d0772fa27f91647e15 | Python | 22,175 | 465 | """Test CAT-NAP (suite2p calcium imaging) parity with MATLAB.
Run from the repo root::
uv run python python/test_pipeline_catnap.py
Ground truth comes from a complete MATLAB CAT-NAP run kept in the gitignored
``local/`` folder (see ``python/CATNAP_PORT_PLAN.md``). Because that data is not
committed, this test **... |
eb9c48f03c7de5e2e86036a60cce1d0f8f8ce6370538ee21704fdd28937112b6 | Python | 22,202 | 660 | import os, json, sys, shutil
sys.path.insert( 0, os.path.join( os.sep, 'usr', 'share', 'gkg', 'python' ) )
import os, json, sys, shutil
import nilearn
from nilearn import image
import numpy as np
import nibabel as nib
import pandas as pd
from CopyFileDirectoryRm import *
def runFuncPreproccessing( Dir,
... |
12cfc70dbc319b277810af1c50a3667dc4053113ea3bf32005d55985fec28c88 | Python | 22,203 | 589 | #############################################################################
# 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... |
72e28f9827252a6722aa0f6a0ae6b6a822ae5a9f2b9d452799db93fbab71e02c | Python | 22,208 | 598 | """ BANet
Paper: ``
- https://arxiv.org/abs/2104.01136
ResT code and weights: https://github.com/wofmanaf/ResT
"""
import torch
import torch.nn as nn
from torch.nn import Module, Conv2d, Parameter, Softmax
from torchvision import models
from timm.models.layers import DropPath, to_2tuple, trunc_normal_
class Mlp(... |
d0091191fe05e9a1acf476cf11fa92dd14c3bf2e233a31a17054e36c09915c3c | Python | 22,212 | 521 | # Copyright (c) Meta Platforms, Inc. and affiliates. All Rights Reserved
import datetime
import gc
import multiprocessing as mp
import os
import queue
import socket
import sys
import time
import uuid
from contextlib import closing
from typing import List, Optional
import psutil
import torch
from ..logger import get_... |
1f0e89a6ec964abbde280918e54d70fd6d1faf3508c46f42c47713358bf04d38 | Python | 22,219 | 535 | # Required libraries
import os
os.environ['PYTORCH_CUDA_ALLOC_CONF'] = "max_split_size_mb:100"
os.environ['KMP_DUPLICATE_LIB_OK']="True"
os.environ['CUDA_LAUNCH_BLOCKING']="1"
import random
import glob
import matplotlib.pyplot as plt
from dataset_patches import MyDataset
from dataset_patches import Custom3DAugmentation... |
2697603b28dd595df3fdedd51755ba6b3745b1b31cf8345c6e31332defc93885 | Python | 22,222 | 585 | """
Ablation studies and additional experiments from the TChemGNN paper.
This script implements:
1. Ablation study with different GNN layer types (Table 2)
2. Random Forest baseline for FreeSolv
3. Analysis of predictions at different node positions (Table 5)
"""
import os
import argparse
import pandas as pd
import nu... |
e27d0534849f1234d4cec5041d3410ad8724b483b6f63082d28e2362a35d4dda | Python | 22,227 | 590 | #############################################################################
# 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... |
de64a7fa3949f93f5abf3f9b1186c35c99be811e48303a5adce1de0d47b8e12b | Python | 22,240 | 626 | # Copyright (C) CVAT.ai Corporation
#
# SPDX-License-Identifier: MIT
from __future__ import annotations
import logging
from collections.abc import Callable, Mapping, Sequence
from typing import TypeAlias, cast
import attrs
import cvat_sdk.models as models
from cvat_sdk.core import Client
from cvat_sdk.core.progress... |
2b55fa8ad90470ba523934bbd3aa82445d431f770969aa70aaf21674d538ab4a | Python | 22,280 | 526 | # This file is part of Zennit
# Copyright (C) 2019-2021 Christopher J. Anders
#
# zennit/rules.py
#
# Zennit is free software: you can redistribute it and/or modify it under
# the terms of the GNU Lesser General Public License as published by the Free
# Software Foundation; either version 3 of the License, or (at your ... |
539bdc6609e91369022342437b77a35e94115ff1a8b8b38c283eb5e7bc16d7ed | Python | 22,283 | 536 | import sys
import os
import numpy as np
import glob
import fabio
from functools import partial
from PySide6.QtWidgets import (
QGroupBox,
QDialog,
QWidget,
QScrollArea,
QGridLayout,
QLabel,
QCheckBox,
QVBoxLayout,
QDoubleSpinBox,
QPushButton,
QHBoxLayout,
QSizePolicy,
... |
5a630c199a0a7c95ec4a4c0f3b198e8b9741a31f682f9d82bd9a0245ec5f256b | Python | 22,303 | 536 | # Required libraries
import os
os.environ['PYTORCH_CUDA_ALLOC_CONF'] = "max_split_size_mb:100"
os.environ['KMP_DUPLICATE_LIB_OK']="True"
os.environ['CUDA_LAUNCH_BLOCKING']="1"
import random
import glob
import matplotlib.pyplot as plt
from dataset_patches import MyDataset
from dataset_patches import Custom3DAugmentation... |
a8fcac620f6f5bc5507ac87faf5c1ba6b3e4bc365aa2d831510f79de84f37a1c | Python | 22,308 | 663 | # Copyright 2024 Google LLC
#
# 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
#
# https://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, ... |
e0aa574c7629f92fc2d9ee75fae6e5f028482713ce2d59add26db579d3d80a9d | Python | 22,314 | 662 | # Copyright 2024 Google LLC
#
# 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
#
# https://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, ... |
3accbfc4f847ac2ef826ad687adfc366f8d2bc3ab63ef5e4a13adfed1d291b57 | Python | 22,325 | 576 | """``IsocortexCoordinateProjector``: depths, 2-D placement, and hemispheres.
The mini-CCF's streamlines run straight down +y, so a query at a voxel corner
has an offset residual of exactly zero and the projected view coordinate is an
exact integer -- assertions here are equalities, not tolerances.
"""
import numpy as... |
dd68b5a7a9756674084a0671afa35dc6cc60e0931c1e98c26e45507497df44b1 | Python | 22,327 | 552 | """Automatic sleep staging of polysomnography data."""
import glob
import logging
import os
import warnings
import antropy as ant
import joblib
import matplotlib.pyplot as plt
import mne
import numpy as np
import pandas as pd
import scipy.signal as sp_sig
import scipy.stats as sp_stats
from mne.filter import filter_d... |
2a31a868ffcbf70b11fb6df6784639b017c879a3454483683a7d48b60ff85108 | Python | 22,330 | 457 | import pathlib
import shutil
import matplotlib
import argparse
import matplotlib.patches as mpatches
import numpy as np
import h5py
matplotlib.use('Qt5Agg')
import matplotlib.pyplot as plt
from postprocessing_modules.axonal_delay_kernel import get_axonal_delay_kernel
from helper_functions import __file__
MODULE_BASE = ... |
d09eb8739d7496568b8022a64d2af5f11167e0094fc4f4d2bb83509645988f35 | Python | 22,332 | 467 | import warnings
import logging
from pathlib import Path
import torch.nn
from torch.nn.parameter import Parameter
import torch.nn.functional as F
import torch.autograd as autograd
import flair.nn
import torch
from flair.data import Dictionary, Sentence, Token, Label
from flair.datasets import DataLoader
from flair.emb... |
3836473d39fa355499b4dca0c5d257169168870e1063f4082c194deb8811219b | Python | 22,336 | 595 | '''
Created on Nov 7, 2022
@author: Yanay Rosen
'''
import torch
import torch.nn as nn
import torch.nn.functional as F
from scvi.distributions import ZeroInflatedNegativeBinomial
from sklearn.cluster import KMeans
from scipy.stats import rankdata
import scanpy as sc
import numpy as np
def full_block(in_features, ou... |
af43610a5be80fa8c1752da0cefe74ae5e626aeae4385156214b244b6127fa22 | Python | 22,341 | 566 | #pylint: skip-file
#type: ignore
"""
Implementation of the distractor suppression task
"""
import time
import math
import typing
import asyncio
import logging
import datetime
import numpy as np
import os
import stl
from ..qt import *
from . import task_context
from .widgets import Form, ListAsTabsWidget
from .util i... |
c862bc007e47a31d2270aa750596b83f85e95411040a1bd2e88df085356ae97a | Python | 22,349 | 588 | """
Module for reading a config file and wrapping it in a ObservableCollection
"""
import os.path
import abc
import json
import enum
import typing
import pathlib
import itertools
RemoteStorage = typing.Callable[['ObservableCollection.Action', str, typing.Any, typing.Callable[[], None]], bool]
def get_storage_type(va... |
b6b137496498529a59feac09b93e7c609263952ed140bbc8b3b4c08fcd122ce3 | Python | 22,363 | 526 | import multiprocessing
import os
import random
import time
from collections import deque
import matplotlib.gridspec as gridspec
import matplotlib.pyplot as plt
import numpy as np
import torch
from torch import nn, optim
from torch.distributions import Normal
from env import Env # 导入自定义环境
from utils imp... |
22bc75fa1b6c7073df9ad85a7384fc48ed79abb217564fdf945649ca5c00054b | Python | 22,364 | 706 | #############################################################################
# Copyright (C) 2020-2026 MEmilio
#
# Authors: Kathrin Rack, Wadim Koslow, Martin J. Kuehn
#
# Contact: Martin J. Kuehn <Martin.Kuehn@DLR.de>
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file exce... |
0f7aa64433a7f713804ca6c47e023288e71f6464e04422ef9ba43db692e136a3 | Python | 22,373 | 555 | # Ultralytics 🚀 AGPL-3.0 License - https://ultralytics.com/license
# Copyright (c) Meta Platforms, Inc. and affiliates. All Rights Reserved
"""ViTDet backbone adapted from Detectron2.
This module implements a Vision Transformer (ViT) backbone for object detection.
Rope embedding code adopted from:
1. https://githu... |
Subsets and Splits
No community queries yet
The top public SQL queries from the community will appear here once available.