sha256 stringlengths 64 64 | language stringclasses 27
values | size int32 1 491k | lines int32 1 21.8k | content stringlengths 1 200k |
|---|---|---|---|---|
d375dbceb2bf1ae962a1f8f2bd6cae1b41417b12760d9841c0832a57f80fd448 | Python | 23,335 | 603 | # -*- coding: utf-8 -*-
import unittest
import arbor as A
from arbor import units as U
import numpy as np
from .. import fixtures
"""
Tests for the concentration and amount of diffusive particles across time and morphology.
Four different morphological structures are considered: 1 segment ("soma only"), 2 segments
("... |
18e9a4319fe3ed6dd20b6a12eafd141d8b96bd427357d448937b05411524d45d | Python | 23,344 | 477 | import pytest
import torch
import SimpleITK as sitk
import numpy as np
import os
import subprocess
import logging
from pathlib import Path
import torch.nn.functional as F
from scipy.ndimage import map_coordinates
# this is the lib used to load the images for scipy transforms
# important because the image dimensions ar... |
b03286431415060e99d7ac897dc96c33dc3c19280da2bbbc5de539d56f37513e | Python | 23,373 | 481 | import matplotlib
matplotlib.use("agg")
import matplotlib.pyplot as plt
import numpy as np
import os
def plot_residual(diff_p, diff_s, diff_ps, tol, dt):
box = dict(boxstyle='round', facecolor='white', alpha=1)
text_loc = [0.07, 0.95]
plt.figure(figsize=(8,3))
plt.subplot(1,3,1)
plt.hist(diff_p, r... |
ead5d7e1efe2d6569c70db846e958b0d911eed59cbc860110f74a202b8463287 | Python | 23,386 | 653 | # -*- coding: utf-8 -*-
import numpy as np
import logging
from dipy.reconst.shm import sh_to_sf_matrix
from dipy.data import get_sphere
from dipy.core.sphere import Sphere
from scipy.ndimage import correlate
from itertools import product as iterprod
from scilpy.gpuparallel.opencl_utils import have_opencl, CLKernel, CLM... |
d7b51fb9a5eaaf921adc7b7233b9509df83bfb07f67b8521e4a1e2a8f991f868 | Python | 23,390 | 624 | """
Interface between the data loaders and file loaders.
"""
from abc import ABC
from typing import Dict, List, Optional, Tuple, Union
import numpy as np
import tensorflow as tf
from deepreg import log
from deepreg.dataset.loader.util import normalize_array
from deepreg.dataset.preprocess import resize_inputs
from d... |
9f48d0962ea82b44a625a3d2ab1a16b9062af1cfb6cd1e48e33a5ff130afb12b | Python | 23,398 | 707 | import argparse
from collections import defaultdict
from pathlib import Path
from queue import Queue
import cartopy.crs as ccrs
import matplotlib as mpl
import matplotlib.patches as patches
import matplotlib.pyplot as plt
import numpy as np
import pandas as pd
import seaborn as sns
from cmcrameri import cm
textwidth ... |
533a1930f44ab25d0606b7290f32b02d5cbc2aabb9c454f5849bded1f50dfd9b | Python | 23,413 | 784 | import sys
import os
import re
import logging
import pandas as pd
import numpy as np
from scipy.sparse import csc_matrix
from heig import utils
class Dataset:
def __init__(self, dir, all_num_cols=False):
"""
Read a dataset and do preprocessing
Parameters:
------------
dir:... |
3b6c5ac02ac44659092e6132303b830142777939e09b53bd0436b16e9475a025 | Python | 23,414 | 536 | # Plotting utils
import glob
import math
import os
import random
from copy import copy
from pathlib import Path
import cv2
import matplotlib
import matplotlib.pyplot as plt
import numpy as np
import pandas as pd
import seaborn as sns
import torch
import yaml
from PIL import Image, ImageDraw, ImageFont
from ..utils.g... |
98c15dac8713a3c2d5aef247f98c821494676f97bc1fda88b1e3ca1ae6814c18 | Python | 23,417 | 479 |
import dtiplayground.dmri.common as common
import yaml, inspect
from pathlib import Path
import pkgutil,sys, copy
import os
import markdown
logger=common.logger.write
@common.measure_time
def _load_modules(system_module_paths=[],user_module_paths=[],module_names=None, **options):
options.setdefault('logger', c... |
2b365fa61677e726d53fbc43fde15426f7bd1acd36e890e3e5595b6a0667ce4d | Python | 23,429 | 341 | '''
FH2
'''
import numpy as np
import sys
def intro():
print("""
SHORT List of potential energy surfaces for FH2:
P: potential energy, G: Gradient, D: Nonadiabatic coupling vector
This is listed at the end of description to show the availability.
For example: P/G means both potential energy and g... |
ee6ca16b1d4cee0004bef78181806b4017ebeb6627e3eaf0b0897f7acd96989b | Python | 23,438 | 604 | #Lucas Sancéré
import os
script_dir = os.path.dirname(os.path.abspath(__file__))
import math
from collections import Counter, defaultdict
import lightgbm
import numpy as np
import xgboost
import yaml
from attrdictionary import AttrDict as attributedict
from sklearn.metrics import balanced_accuracy_score
from sklea... |
a118628ba8688cb71a86c4cb4ce3dabba6d9f07413f1f615a2d77c62b00ea87c | Python | 23,453 | 543 | import sys
sys.path.append('..')
import warnings
warnings.filterwarnings("ignore")
import os, random, logging, time, copy
from tqdm import tqdm
from argparse import Namespace
from typing import Callable
import pandas as pd
import numpy as np
import torch
import torch.nn as nn
import torch.nn.functional as F
from torch.... |
5cd98bb8f7d639f4be3f568f9a559905d79655a0a5751cbd069e5ec60c8f1a90 | Python | 23,461 | 601 | import shutil
from collections import defaultdict
import h5py
import numpy as np
import seisbench
import seisbench.util
from .base import WaveformBenchmarkDataset
class SCEDC(WaveformBenchmarkDataset):
"""
SCEDC waveform archive (2000-2020).
Splits are set using standard random sampling of :py:class: ... |
ae9a43c2dcc2070ebaea2fff177013dc4267db8233e5bf0c9f5611636c823346 | Python | 23,476 | 558 | #!/usr/bin/env python3
"""3D ViT-UNet model definition for BraTS tumor segmentation."""
import torch
import torch.nn as nn
from einops import rearrange
from functools import reduce
from operator import mul
import torch.nn.functional as F
import torch.utils.checkpoint as checkpoint
from timm.models.layers import DropPat... |
bea59677b1c9b1b10045c92804fd16f5233e724d3dc4fabf642b41a5362edbc9 | Python | 23,476 | 677 | # -*- coding: utf-8 -*-
"""
MReye-Seg Slicer Utilities
===========================
Project-specific 3D Slicer utility functions for the MReye-Seg pipeline.
Provides wrappers for centerline extraction, cross-section analysis,
visualization, geometry, and fiducial/markup operations.
Used by:
- landmark_transform.py ... |
01fb184e0cbdddf84b775f9621e612f9bbe70b9ad2aee4067d565f0182c2af5f | Python | 23,484 | 394 | #Type something like this from within python: ARGS="20160822orangedm105 M 30 none 10.5 DM"
#template: ARGS="filename sex age drugs theta region"
#then type:
#If not in python, type: python PopSpikeAnal.py 031011_5Or M 30 none 10.5 DM
import os;
import numpy as np
from matplotlib import pyplot
pyplot.ion()
import sys
... |
0d3ddd90a53fae48df1e8326989c2f6b6f024fc7025963da45b9c91e93f25bf0 | Python | 23,488 | 640 | # -*- coding: utf-8 -*-
"""ANTS registration."""
import math
import os
import shutil as sh
from glob import glob
from os.path import exists, join
import nibabel as nb
import numpy as np
from nibabel.freesurfer.io import write_geometry
from scipy.io import loadmat, savemat
from .. import check_installation, execute_c... |
a4d98c3555cc4c0810a7b6282196a74d4c60e9e9acc4be43346158c1f2d7faa5 | Python | 23,492 | 559 | # -*- coding: utf-8 -*-
# @Author : LG
import os
import platform
import time
from collections import OrderedDict
from typing import Union
import numpy as np
import torch
from PIL import Image
osplatform = platform.system()
class SegAny:
"""
Segment Anything model class.
Arguments:
checkpoint:... |
b5003246e195a91c19adac1f3b1f5811360e722ff46b971b4a31a3e199202f1c | Python | 23,498 | 568 | # 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... |
54cf3dd4b418081b1bfbeb7c65132d8a33da3572f85f992235e3474505911cad | Python | 23,500 | 676 | #!/usr/bin/env python3
#
# PRECONFIG, a versatile configuration file generator for varying parameters
#
# Copyright Francois J. Nedelec and Serge Dmitrieff,
# EMBL 2010--2017, Cambridge University 2019--2022
# This is PRECONFIG version 1.59, last modified on 03.02.2023
"""
# SYNOPSIS
Preconfig generates files fr... |
f16a50136b2d82eb800a95946a32cab6ccc89a25f422bae94310ca85048d84b4 | Python | 23,516 | 383 | # -*- coding: utf-8 -*-
# Form implementation generated from reading ui file 'mosaic.ui'
#
# Created by: PyQt5 UI code generator 5.15.4
#
# WARNING: Any manual changes made to this file will be lost when pyuic5 is
# run again. Do not edit this file unless you know what you are doing.
from PyQt5 import QtCore, QtGui... |
fdc06fe3ed79d1bb0ed29131864d8771418dac0f628a3ed569a3400a14894c06 | Python | 23,555 | 529 | #!/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
#... |
a9e8b4df2bda72326ad10cad41bb44f52e2dc4609aba1bfc66f042b3ed59a738 | Python | 23,562 | 501 | # mat_to_tfrecord.py
# Created by Nick Card, July 2023
# Modified May 2024 by Justin Jude
import os
import re
from pathlib import Path
import numpy as np
import scipy.io
import tensorflow as tf
from g2p_en import G2p
import matplotlib.pyplot as plt
import os
import json
PHONE_DEF_SIL = [
'AA', 'AE', 'AH', 'AO',... |
ec889a960f630f3814c287266be3a965b8064de3c76c8ce18a2597f37e9c9b9c | Python | 23,573 | 565 | #############################################################################
# Copyright (C) 2020-2026 MEmilio
#
# Authors: Manuel Heger, Henrik Zunker
#
# 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... |
1f4c45255fd5748912a4b79db3151732a2af3aec381104fca0ffa1a49faa9ec8 | Python | 23,596 | 649 | #!/usr/bin/env python
"""
The handles all the UI elements in the Mosaic tab.
Hazen 10/18
"""
import numpy
from PyQt5 import QtCore, QtGui, QtWidgets
import storm_control.sc_library.hdebug as hdebug
import storm_control.steve.coord as coord
import storm_control.steve.imageCapture as imageCapture
import storm_control.... |
cb3dfd39bf86960972781cade293af03da6979c93d897a88f5fb531e1564b32a | Python | 23,607 | 649 | import numpy as np
from scipy.stats import ttest_rel, ttest_1samp, ttest_ind, kstest, wilcoxon
from statsmodels.stats.multitest import fdrcorrection
import pickle
import mne
import pandas as pd
import matplotlib.pyplot as plt
import glob
import os
from update_sub_lists import*
from pp_utils import *
def find_existin... |
b2aadfaf988f32a6e936439ddd3c6a5f3cfe302c3fb37325fa58fa5d42e0656b | Python | 23,642 | 678 | import os
import h5py
import logging
import numpy as np
import pandas as pd
import hail as hl
from tqdm import tqdm
from collections import defaultdict
from numba import njit, prange
from sklearn.model_selection import KFold
import heig.input.dataset as ds
from heig.wgs.utils import init_hail, read_genotype_data, clean... |
67229e75f8d1213fd0db751a7fd151086fe02697d73fa5d342aa78aad02fccbf | Python | 23,675 | 638 | from __future__ import annotations
import numpy as np
import scipy
from functools import cached_property
from scipy.interpolate import interp1d
from typing import NamedTuple
from argclz import argument, AbstractParser, int_tuple_type, union_type, as_argument
from neuralib.decoding.position import place_bayes
from neu... |
dc1563425b193477d71c8c3a1cf43c69b235503fd51721212cbd4a7fd24f5617 | Python | 23,679 | 618 | import os
import argparse
import nibabel as nib
import numpy as np
import csv
from nipype.utils.filemanip import fname_presuffix
############################
# Image Loading and Saving #
############################
def load_image(image_path):
"""Load image data based on file extension."""
ext = os.path.split... |
254bce67b2e6cb8599cf4bc6d896856caa6528693c8ab2375d91be117ad9d4f0 | Python | 23,689 | 463 |
import warnings; warnings.filterwarnings("ignore")
import sys, random, math
import numpy as np
import scipy.stats as stats
import multiprocessing
from operator import itemgetter
from sklearn.preprocessing import StandardScaler
from sklearn.neural_network import MLPClassifier
from Energy import *
####################... |
76b029bc68457f50f4755aac0940f561ffc09b4489131ff232ddd54420028a63 | Python | 23,694 | 752 | import math
from dataclasses import dataclass
from typing import TYPE_CHECKING, Any
import torch
import torch.nn as nn
from eir.models.fusion.seq_out_fusion_attention import CrossAttention
from eir.models.layers.cnn_layers import (
ConvAttentionBlock,
ECABlock,
StochasticDepth,
UpSamplingResidualBlock... |
853d330a034e44a50885cf64cf313bf3ce5d017ed4744a3acff7eaf2684b8e42 | Python | 23,698 | 608 | import torch
from torch import nn
import torch.nn.functional as F
import numpy as np
import copy
from torchsummary import summary
def conv_bn(in_channels, out_channels, kernel_size, stride, padding, groups=1):
result = nn.Sequential()
result.add_module('conv', nn.Conv2d(in_channels=in_channels, out_channels=o... |
a000e329a0f37bb303ed39486925e7f8f7cc9db2fbc7baa78e4759c85a2a0563 | Python | 23,707 | 532 | """Test resuming a CAT-NAP run from a previous run's output ("start at step 4").
Run from the repo root::
uv run python python/test_catnap_resume.py
MATLAB's ``MEApipeline.m`` appends ``adjMs`` to each recording's
``ExperimentMatFiles/<rec>_<folder>.mat`` at the end of step 2, and its
``priorAnalysis == 1 && sta... |
740872f42953cba2173153d31c12b0ad5b8041ec14f78dacd0ed6d97af88dd6e | Python | 23,712 | 613 | """
DMC-BrainMap widget for stitching .tif files.
2024 - FJ, XC
"""
from collections.abc import Iterator, Sequence
from pathlib import Path
from typing import Dict, List, Tuple
import numpy as np
import tifffile as tiff
from magicgui import magicgui
from magicgui.widgets import FunctionGui
from napari import Viewer
... |
a2155da1a4783e6cffb4229e743bcfdb496850045bbeeb7bfb38306584542701 | Python | 23,717 | 592 | # -*- coding: utf-8 -*-
import os
import re
import sys
def find_reference_pcr_file(ref_pcr_name, root_dir):
ref_path = os.path.join(root_dir, 'dat_vestacif_files', 'reference_pcr_format', ref_pcr_name)
if os.path.exists(ref_path):
print("Found reference PCR in reference_pcr_format folder: {}".format(... |
db57f93f87ecafe3d0b27c4ba266162c8de557d4031f3c0c9eb4a556286d67f9 | Python | 23,729 | 535 | # Ultralytics 🚀 AGPL-3.0 License - https://ultralytics.com/license
# Copyright (c) Meta Platforms, Inc. and affiliates. All Rights Reserved
# Based on https://github.com/IDEA-Research/GroundingDINO
from __future__ import annotations
import torch
from torch import nn
from ultralytics.nn.modules.utils import _get_clo... |
c171e6f26206c61ad04eaed701e97044411afe7976fe3f65fe069461beef8e4b | Python | 23,730 | 603 | import argschema as ags
import numpy as np
import pandas as pd
import logging
from multiprocessing.dummy import Pool
from skeleton_keys.database_queries import (
swc_paths_from_database,
)
from skeleton_keys.depth_profile import (
calculate_pca_transforms_and_loadings,
apply_loadings_to_profiles,
earthm... |
ba65712ceba6aa4cae82e86bc3d2c537d830c27ec1b34855ee089cf829e776b3 | Python | 23,742 | 692 | import typing
import asyncio
import numpy
import math
import grpc
import bisect
import pathlib
import datetime
import itertools
import traceback
import matplotlib
import logging
from ..config import *
from ..util import open_preferred_app
from ..util import MeteredUpdater
from .. import thalamus_pb2
from ..qt import ... |
2248b8c4b4e7977ad340d519acfd9f4f860697900eb264b49704afbe84a9c5e7 | Python | 23,761 | 508 | import numpy as np
import pandas as pd
import matplotlib as mpl
import matplotlib.pyplot as plt
from matplotlib.patches import FancyArrowPatch, Patch
from matplotlib.lines import Line2D
from scipy.cluster.hierarchy import dendrogram
import networkx as nx
from . import process as proc
def SemiCirc_coordinates(star... |
1324c0d497fe890c16b313ae63f372df2311344d01123f50253da9c26e9edc46 | Python | 23,772 | 562 | import numpy as np
import multiprocessing as mp
from . import galvo_corrections
import time
def map_frames(f, scan, field_id, channel, y=slice(None), x=slice(None), kwargs={},
chunk_size_in_GB=0.5, num_processes=10, queue_size=10):
""" Apply function f to chunks of the scan (divided in the temporal... |
c29c27e5d0f40907a81e8b5640f499f566b5c9dcb11a0db0c606a9c76391329b | Python | 23,821 | 791 | import base64
import json
import subprocess
import time
from collections.abc import Sequence
from functools import partial
from pathlib import Path
import matplotlib.pyplot as plt
import numpy as np
import pandas as pd
import seaborn as sns
from docs.doc_modules.experiments import (
AutoDocExperimentInfo,
get... |
b4e4c4702c56e09e8e72900a4141ff0176769c0a6f32349e6be20fd15aa522e0 | Python | 23,832 | 583 | from tqdm import tqdm
import numpy as np
import pandas as pd
import os
import gc
from scipy.ndimage import zoom
import matplotlib.pyplot as plt
from traitlets import default
from .gradients import IntegratedGradients, GradientDescent
from .evosearch import Evolution
from .motifs import Motif
from . import ... |
f147edfc944aa81fb5ad4a0b34568c7ed4fa28df29a5b56a405a162cb48eed7b | Python | 23,833 | 489 | from models.keras_vision_transformer import swin_layers
from models.keras_vision_transformer import transformer_layers
from tensorflow.keras.layers import Input, Dropout, Lambda, Conv2D, Conv2DTranspose, MaxPooling2D, Concatenate, Activation, Add, multiply, add, concatenate, LeakyReLU, ZeroPadding2D, UpSampling2D, Batc... |
a1d6b970526c80d967a8ae9d7d4f05c02e30f19661378ef24895f363de9bdb59 | Python | 23,843 | 642 | """
Copyright 1999 Illinois Institute of Technology
Permission is hereby granted, free of charge, to any person obtaining
a copy of this software and associated documentation files (the
"Software"), to deal in the Software without restriction, including
without limitation the rights to use, copy, modify, merge, publis... |
3a6745665d8e8ca22933ffc0fb12d64cca930e0ad8f030dda64689ff1323a8f2 | Python | 23,851 | 677 | # Copyright (C) CVAT.ai Corporation
#
# SPDX-License-Identifier: MIT
import io
import json
import os.path as osp
import zipfile
from logging import Logger
from pathlib import Path
from unittest import mock
import pytest
from cvat_sdk import Client, models
from cvat_sdk.api_client import exceptions
from cvat_sdk.api_c... |
0a3d012335208e3fe14ccb3a0be486941790e9a44b7311beeab1fc8a98034b59 | Python | 23,865 | 563 | import os
import time
import torch
from ignite.engine import Engine, Events
from ignite.handlers import ModelCheckpoint, EarlyStopping, create_lr_scheduler_with_warmup, CosineAnnealingScheduler
from ignite.handlers import Timer
from ignite.metrics import Accuracy
from torch.nn import TripletMarginLoss
from torch.optim... |
f4ffc21821571e8373a0e4021a173b5daf1cb656077a8169706d88abb84bc451 | Python | 23,869 | 764 | """Protocols (interfaces) for backends to implement.
Each class in this module is a [typing.Protocol][typing.Protocol] that specifies
a set of :func:`~abc.abstractmethod` that a backend widget must implement
to be compatible with the magicgui API.
All magicgui-specific abstract methods are prefaced with ``_mgui_*``.
... |
1bd244306e77123062f8bc9edf3a4003f2188ee9940ebe47bf5de9db61242326 | Python | 23,875 | 632 | import matplotlib
matplotlib.use("Agg")
import matplotlib.pyplot as plt
import torch
import torch.nn as nn
import torch.nn.functional as F
import torchvision
import torchvision.transforms as transforms
import numpy as np
import pandas as pd
import os
import cv2
from torch.utils.data import Dataset
import ... |
5545b18a6aecca181fac09db35a4023cac65e11b94ce39100790d9610559e904 | Python | 23,883 | 718 | # coding=utf-8
# Copyright 2018 The Google AI Language Team Authors and The HuggingFace Inc. team.
# Copyright (c) 2018, NVIDIA CORPORATION. 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 cop... |
205dcf68bb05b24b7ea45cc3ebfcaae46cfccd59248dfda2097985b36feec152 | Python | 23,894 | 701 | #!/usr/bin/python
#
## @file
#
# Qt Widget Range slider widget. This is a slider with two bars, one of
# which is used to set the maximum and the other of which is used to
# set the minimum.
#
# Qt Double Spin Box slider widget. This is the range slider grouped
# with two spin boxes to make the range editable.... |
0cba16ef0eb9203c809f8ebffb9ad3699a8e6c5e7be0a6a10905840b34779541 | Python | 23,901 | 507 | from typing import List
import torch
from torch.nn import Module, Parameter
import numpy as np
from ..numpy.generic import MeshPhases
from ..config import BLOCH, SINGLEMODE
from ..meshmodel import MeshModel
from ..helpers import pairwise_off_diag_permutation, plot_complex_matrix
import os
class TransformerLayer(Mod... |
0e85e8344e6e6a0b8df0171a285da1fbb57b1bd6dbef0aa8fe94d04d6300e6e6 | Python | 23,903 | 752 | """Deterministic structured-output judge for ChemGraph evaluation.
Compares the agent's ``ResponseFormatter`` structured output against a
ground-truth ``structured_output`` dict field-by-field using numeric
tolerances and SMILES canonical comparison -- no LLM required.
Each ``ResponseFormatter`` field is compared ind... |
7651d526911b0b0cebec4922c21a7b8226c5acff92330472bd63bf455c481f23 | Python | 23,943 | 599 | import keras.layers as kl
from keras.models import Model
def DREAM_RNN_Official(input_shape, config, epistemic=False):
'''
Full DREAM-RNN architecture matching the paper specifications.
Architecture:
- BHIFirstLayersBlock: Conv1D with kernel sizes [9, 15], 160 channels each → 320 total
- BHICo... |
fda386ee66c9a1f87a0fe07834906c7a71af926bcb3eac99a330eb6e801fa50b | Python | 23,950 | 484 | from curses import meta
import os
import pickle
import random
import numpy as np
import pandas as pd
from tqdm import tqdm
from glob import glob
import torch
import torchaudio
from torchaudio import transforms as T
from torch.utils.data import Dataset
from copy import deepcopy
from .icbhi_util import g... |
05d573ed838510a3b1b1ca50c085ba4dfe460073cd7aa146146c96d1c2745211 | Python | 23,956 | 537 | # ==============================================================================
# Binaries and/or source for the following packages or projects are presented under one or more of the following open
# source licenses:
# cocoeval.py The OpenLane Dataset Authors Apache License, Version 2.0
#
# See:
# https:... |
58d040aed48c4af39ccd18cb303831d0d3bff98e73875fcdd445745f7b676ed6 | Python | 23,962 | 659 | """
Module containing data augmentation techniques.
- 3D Affine/DDF Transforms for moving and fixed images.
"""
from abc import abstractmethod
from typing import Dict, List, Optional, Tuple, Union
import numpy as np
import tensorflow as tf
from deepreg.model.layer import Resize3d
from deepreg.model.layer_util impo... |
5f821ecc57919bb3994a3945755390e9ff6fcd4f549597da2878e5cdcdaa8c66 | Python | 23,978 | 475 | """Choosing a MEA-NAP version, and keeping the cutting edge current.
Everything runs against throwaway git repositories standing in for GitHub, so
the checks need no network and cannot touch the real clone. Four groups:
A. what is running — main, a release worktree, a branch, no clone at all;
B. is it current — b... |
31aecf86a6efb45ecc8331c48cda9b93686449fdb1aca7e62003b1f230db1701 | Python | 23,980 | 756 | import datajoint as dj
import pandas as pd
from . import mice # needed for referencing
import numpy as np
import os
from commons import lab
schema = dj.schema('pipeline_experiment', locals(), create_tables=False)
@schema
class Fluorophore(dj.Lookup):
definition = """ # calcium-sensitive indicators
fluoro... |
cd7b6800d108b83ee282db0cda73f50313ed4183a91abbba6526922b837f8e73 | Python | 23,988 | 684 | import os
import h5py
import logging
import numpy as np
import pandas as pd
import hail as hl
from tqdm import tqdm
from collections import defaultdict
from numba import njit, prange
from sklearn.model_selection import KFold
import heig.input.dataset as ds
from heig.wgs.utils import init_hail, read_genotype_data, clean... |
71367e883b40b5d2f88c30e8ce37880b3f6b1938866330fc28c0664ea59b530d | Python | 23,997 | 524 | # flake8: noqa
# note: this file has been modified from its original version in TrackEval in
# https://github.com/JonathonLuiten/TrackEval/blob/master/trackeval/datasets/youtube_vis.py
# to support the following:
# 1) bbox evaluation (via `IOU_TYPE`)
# 2) passing GT and prediction data as Python objects (via `GT_JSON_... |
eea91645a74d6089c459c2620b14281973a10751ac6c289be9d8aabd8031ee37 | Python | 23,999 | 571 | """Plot Schirmer vascular-territory statistics as an axial mosaic.
The atlas is displayed over a user-supplied anatomical or perfusion image.
Its outer footprint is clipped to the nonzero background mask, while signed
distance fields provide smooth internal ROI interfaces. Significant and
non-significant territories ... |
14f8742eaf6d4c6b5b2d241c8099e4c122f95790646117af5c0fb6fff4159e3d | Python | 24,009 | 651 | from pathlib import Path
import collections
import functools
import numpy as np
import scipy.optimize
import scipy.stats
import warnings
from matplotlib.axes import Axes
from scipy.interpolate import interp1d
from tqdm import tqdm
from typing import Union, NamedTuple, Optional, Literal, Iterable, overload
from argclz... |
e488a6657d388da1c8dbf5fbbbbade478cd242482cb108a828f1d351e708c836 | Python | 24,012 | 611 | """Codex SDK model adapter.
This module adapts the official ``openai-codex`` Python SDK to LangChain's
chat-model interface. Codex is used only as the model backend; ChemGraph's
existing LangGraph workflow remains responsible for executing all exposed tools.
"""
from __future__ import annotations
import json
import... |
63f0fe1faa78b84bcf5d0b049eeb415b2d389dfb6b16be825e6b1a794fb3f666 | Python | 24,030 | 720 | import numpy as np
from scipy.optimize import curve_fit
from scipy import stats
def mse_func(a, b):
return np.sqrt(np.sum((a - b) ** 2))
def interpolate_time_frames(C_A, t_A, C_B, t_B, frame_length):
# Interpolate C_A and C_B to uniform time frames of frame_length [s]
# Make them equally long by shorten... |
a393110510365dce846bb3e2e98ab2063025589c418435eb41632be856471cb9 | Python | 24,033 | 667 | """Control analysis for resting state"""
import nibabel as nb
import seaborn as sns
import numpy as np
import matplotlib.pyplot as plt
import math
import subprocess
import glob
import os
from nilearn.connectome import ConnectivityMeasure
ROOT = '/Users/sebastiandresbach/data/s1Anfunco/Nifti'
subs = ['sub-05', 'sub-0... |
ff6ba6d0834a9c5142ae8bbc9a4c7cf2ad0b9115e854ae22fff51a3af1d188d3 | Python | 24,040 | 765 | """
This module contains functions to plot the results of RNN simulations, including
activity, performance, and angle between evidence and input dimensions.
For comparison with neural data, the module also contains functions to plot
the angle between neural regression dimensions for evidence and outcome.
"""
import nu... |
29a75598f407f1da23031943a8e35e3e23e4b8b357e2708f883c56983b228880 | Python | 24,044 | 562 | import numpy as np
import random
import os
from tensorflow.keras.models import Model
from tensorflow.keras.layers import Input, Activation
from tensorflow.keras.layers import Conv2D, MaxPooling2D, Conv3D, MaxPooling3D, Dropout
from tensorflow.keras.layers import concatenate, UpSampling2D, BatchNormalization, Reshape
f... |
f428735850b08f6b2535c5413a07d5fb0427f8ab1c25eff2ef9d36c3e55fefac | Python | 24,045 | 826 | import functools
from typing import (
Any,
Callable,
Dict,
Iterable,
List,
NamedTuple,
Optional,
Tuple,
Type,
Union,
)
import torch
import torch.utils._pytree as pytree
from torch import Tensor
from torch_geometric.typing import INDEX_DTYPES
aten = torch.ops.aten
HANDLED_FUNC... |
ab4c25948a48bb643cbe69f4e70e07808533287638c827bb66e65090a02f404e | Python | 24,050 | 660 | """
Copyright 1999 Illinois Institute of Technology
Permission is hereby granted, free of charge, to any person obtaining
a copy of this software and associated documentation files (the
"Software"), to deal in the Software without restriction, including
without limitation the rights to use, copy, modify, merge, publis... |
bbcf81d9e7e7dbb5615867d076e2ade52fc41eea7473417b1bd432da284882c4 | Python | 24,055 | 721 | import torch
import numpy as np
from scipy.optimize import linear_sum_assignment
from datasets.dataloader import TrialDataset
import pandas as pd
import json
def prepare_svd_feat(model, filt_data):
T, K, N = filt_data.shape
filt_data = filt_data.permute(2, 1, 0).reshape(N, -1)
mean = filt_data.mean(1, kee... |
da1f5815f494f75d5b17ac97df65776524b0813c8ac9eaff763a2e4f73a7675b | Python | 24,065 | 636 | # python 02_run_lickextraction_fromtrace.py PL077_20230407-probe0 -ipimin 0.015 -npmin 1 -pthr 3.
from scipy.signal import find_peaks
from argparse import ArgumentParser
import sys
import h5py
import numpy as np
import yaml
import os
from scipy.interpolate import interp1d
from copy import deepcopy
from matplotlib.widge... |
1bdf7ba94b5805ef9031c9f7732c5988a26eca6feeaf8fc738f91d088d123a27 | Python | 24,083 | 512 | import numpy as np
import matplotlib.pyplot as plt
from scipy.stats import sem
from matplotlib.colors import ListedColormap, BoundaryNorm
import matplotlib
matplotlib.use('TkAgg')
def plot_3d_line(ax, arr, set_color='lightblue', set_alpha=0.5, set_linewidth=0.5, set_label='None'):
for i in range(arr.shape[0]):
... |
b7ed6386d3db3dd8217e7eb2f6fbccdb8e3f222536426deb7d019a1da894984a | Python | 24,083 | 539 | # Copyright (c) Facebook, Inc. and its affiliates.
from typing import Dict, List, Optional, Tuple, Union
import torch
import torch.nn.functional as F
from torch import nn
from detectron2.config import configurable
from detectron2.layers import Conv2d, ShapeSpec, cat
from detectron2.structures import Boxes, ImageList, ... |
5179561757e8c614a51a2632536f7cf264a88876525a377c8d688460c7c38679 | Python | 24,084 | 653 | import pandas as pd
import os.path as osp
import os
import numpy as np
from ogb.utils.url import decide_download, download_url, extract_zip
from tqdm import tqdm
### reading raw files from a directory.
### for homogeneous graph
def read_csv_graph_raw(raw_dir, add_inverse_edge = False, additional_node_files = [], addit... |
893e370263947ad439dcc1337a5abeb55ee5cc04f36eb75cd5669871932ab8e4 | Python | 24,102 | 584 | """
EfficientNet3D-B0 Baseline Training Script
Train EfficientNet3D-B0 model with T2W or FLAIR single modality input
"""
import os
import json
import time
import argparse
import numpy as np
import torch
import torch.nn as nn
import torch.optim as optim
from data.dataset import MRIDataset
from models.efficientnet3d_pret... |
74de809a4e66fbf6c38f4424ba455d1da145e71416317186c48effc906ef03da | Python | 24,110 | 472 | import os
import pathlib
import numpy as np
import matplotlib
matplotlib.use('Qt5Agg')
import matplotlib.pyplot as plt
from matplotlib import colors as mcolors
from matplotlib.collections import LineCollection
from numpy.typing import NDArray
from helper_functions.neuron_cell_functions_lib import collect_lines_section,... |
2023ce7c42a9dda75211d2b277037bb929db4a6d48324450c778a3e86de41d47 | Python | 24,123 | 705 | import sys
from dataclasses import dataclass
from enum import Enum
from typing import Any
import numpy as np
import polars as pl
import torch
from numpy.typing import DTypeLike
from eir.utils.logging import get_logger
logger = get_logger(name=__name__)
NULL_STRINGS = frozenset(("", "None", "null", "nan", "__NULL__"... |
a535409c7eb529e08ee92c04ac8fab3d30d58ca42191b963a551372904e7b68d | Python | 24,123 | 670 | #!/usr/bin/env python3
# -*- coding: utf-8 -*-
"""
@author: karajohnson
"""
import os
import numpy as np
from scipy import signal
from fooof import FOOOF, utils
from scipy.stats import sem, pearsonr, ttest_ind, fisher_exact
import math
import pandas as pd
import copy
pd.options.display.max_columns = None
pd.options.d... |
8fe896865277a1a826b3383a79c904541a5a8a70ee4f09be86b3b64d1d7c3741 | Python | 24,136 | 793 | # Copyright (c) Meta Platforms, Inc. and affiliates. All Rights Reserved
import os
from typing import Optional
import torch
import torch.nn as nn
from huggingface_hub import hf_hub_download
from iopath.common.file_io import g_pathmgr
from .model.decoder import (
TransformerDecoder,
TransformerDecoderLayer,
... |
e121fea0e71a9741e32f7dec248b05ad855edb7b23e349539752beeda18ecd48 | Python | 24,168 | 755 | """Entrypoints for dannce training and prediction."""
from dannce.interface import (
com_predict,
com_train,
dannce_predict,
dannce_train,
build_params,
)
from dannce.engine.processing import check_config, infer_params
from dannce import (
_param_defaults_dannce,
_param_defaults_shared,
... |
4c19bff6a4195851266de99d5e1486e5665a6a2112258835298a145b86dfeb14 | Python | 24,176 | 542 | """
Created on Wed Mar 25 19:31:32 2025
@author: Sophie Skriabine
"""
import tkinter as tk
from tkinter import ttk, messagebox
import os
from .config import parse_literal
from .WaveletGenerator import *
from .LoadPinkNoise import *
from .Analysis_Utils import *
from matplotlib.backends.backend_tkagg import FigureCanva... |
a268b8d386800ca887be38ef197feadc5944228aa81743a1239505d504692f57 | Python | 24,177 | 587 | # This file contains modules common to various models
import math
from copy import copy
from pathlib import Path
import numpy as np
import pandas as pd
import requests
import torch
import torch.nn as nn
from PIL import Image
from torch.cuda import amp
try:
from ..utils.datasets import letterbox
from ..utils.g... |
24d2e597f8dea56d7dcbd63cbc725502d1b4bb2dcaea6dae1a24a3d6e204c018 | Python | 24,195 | 680 | # Example of training script
EPOCHS = 200
QAT_EPOCHS = 20
EVALS = 25
# Standard Library imports
import os
import sys
import time
import random
import json
import copy
import fcntl
from pathlib import Path
import warnings
# Third-party Libraries
from tqdm import tqdm
import pandas as pd
import matplotlib.pyplot as ... |
49e52ce5ed5030226337815bc489958b70796e380997d0d1d2f481235d6aa4d3 | Python | 24,215 | 568 | """
This file was written to provide an easy way to load an existing CLAPP trained model.
It is based on codebase of CLAPP as modified by Ariane Delrocq.
Import the function load_model from this file. Check its docstring (with help(load_model)) to know how to use.
Note that due to CLAPP training requirements, CLAPP mod... |
f15cf14107c2f25b43c58d0d4f954a176e03aacd9f8e23098e92d761f7262e08 | Python | 24,215 | 582 | #Lucas Sancéré -
import json
import os
import matplotlib.pyplot as plt
import numpy as np
import pandas as pd
import plotnine
import seaborn as sns
import yaml
from attrdictionary import AttrDict as attributedict
from plotnine import (
aes,
geom_density,
ggplot,
labs,
scale_color_manual,
scale... |
1e5b99a17fa9ddee7ec5ecf204099eb91a8b8dd98da74afa54eae6e32e76eead | Python | 24,222 | 499 | # Ultralytics 🚀 AGPL-3.0 License - https://ultralytics.com/license
from __future__ import annotations
import glob
import math
import os
import random
import shutil
from copy import copy, deepcopy
from multiprocessing.pool import ThreadPool
from pathlib import Path
from typing import Any
import cv2
import numpy as n... |
9b9d09aeb1bde966175ebd6d56cdca5cfd820594f2c6176dde1bd3331f6c1d5c | Python | 24,225 | 517 | from torch.utils.data import Dataset, DataLoader
import torch
import torch.nn.functional as F
import numpy as np
import openbabel
from openbabel import pybel
import os
import pickle
from math import ceil, sin, cos, sqrt, pi
from itertools import combinations
from random import choice
from skimage.draw import ellipsoid
... |
125167f2f2d74403b15ae5b845260db316c62a0b8982ee2a20795c1e05e7830a | Python | 24,230 | 833 | # Copyright (C) CVAT.ai Corporation
#
# SPDX-License-Identifier: MIT
import traceback
from typing import Any
import rq
from crum import get_current_request, get_current_user
from django.db import DatabaseError
from django.db.models import Model
from rest_framework import status
from rest_framework.exceptions import N... |
263732a659281557ac8e8565845b4009d8f82257bca80dab63094c8afe1ba983 | Python | 24,236 | 626 | #############################################################################
# Copyright (C) 2020-2025 MEmilio
#
# Authors: Agatha Schmidt, Henrik Zunker
#
# 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 complian... |
8e1b8e5acf51cb854cedc705f9644e56f5cbefe80b7606eefa500307e9c66249 | Python | 24,251 | 614 | #####
# ogo_sideways_fall_fe.py
#
# This script sets up the sideways fall FE model on the hip from the density (K2HPO4)
# calibrated image. This script sets up the model for either a left or right femur, as
# specified by the user. The analysis resamples the image to isotropic voxels, transforms
# the image, applies th... |
dbc3535bd6e273971d874401fad1f4c2227bca2705ff01ace4ce4eaf4badac27 | Python | 24,258 | 583 | import matplotlib.pyplot as plt
import numpy as np
from matplotlib.animation import FuncAnimation
import json
import numpy as np
import os, cv2, glob, json, gc
import pandas as pd
import itertools
from itertools import chain
from moviepy.editor import VideoFileClip
import skvideo.io
from tqdm import tqdm
import circsta... |
23ea367357550300f2ed9c3c31336c977e570da9275f66468706edaeefddcc08 | Python | 24,283 | 752 | # Kai Sandbrink
# 2023-04-27
# This script analyzes Prolific Participants with different efficacy using neural networks
# %% LIBRARY IMPORTS
import numpy as np
import pandas as pd
import os, ast, glob
import matplotlib.pyplot as plt
import matplotlib as mpl
import seaborn as sns
import torch
from ObserveBetEfficacyT... |
d2e9f221a9dbbd708249c1a072392c711468cd03ef0e06e019b04a7ae13e881d | Python | 24,286 | 706 | import os
import glob
import cmat
import pickle
import math
import collections
from collections import Counter
import numpy as np
import pandas as pd
import sklearn.model_selection
import src.featurizer
import wandb
import tempfile
import zipfile
def replace_classes(y, replace_dict):
if replace_dict:
ret... |
07e7bd9ebd614934dfa7c47f59df099ae76b2564a6dc37c5bfd91bedde3bf335 | Python | 24,291 | 383 | import cv2, os, glob
import numpy as np
from PyQt5.QtGui import QImage, QPixmap
from napari_dmc_brainmap.registration.sharpy_track.sharpy_track.view.DotObject import DotObject
from napari_dmc_brainmap.registration.sharpy_track.sharpy_track.model.calculation import fitGeoTrans
# from napari_dmc_brainmap.preprocessing.pr... |
bfad2c05c88983487b16c8f9fa42172d025c90717e38512729f867990f679e43 | Python | 24,298 | 759 | # emacs: -*- mode: python; py-indent-offset: 4; indent-tabs-mode: nil -*-
# vi: set ft=python sts=4 ts=4 sw=4 et:
#
# Copyright 2022 The NiPreps Developers <nipreps@gmail.com>
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may... |
ac03572448372617f4e6c6ece7c8e186f5b88d49b0263d00eeb006d1cc291f50 | Python | 24,301 | 575 | # -*- coding: utf-8 -*-
# @Author : LG
import os
import platform
import time
from collections import OrderedDict
from typing import Union
import numpy as np
import torch
from PIL import Image
from ISAT.segment_any.sam2.utils.misc import AsyncVideoFrameLoader
from ISAT.utils.dicom import load_dcm_as_image
osplatform... |
3bd5c3bb1f852a74aea7f9f5b98543e26779dde298f8d9e52062000d4f1db242 | Python | 24,302 | 653 | """Reusable, non-interactive privacy and anonymisation functions.
The functions in this module contain no GUI dialogs, terminal prompts, file
pickers, or plotting side effects. They are shared by the command-line and
browser interfaces.
"""
from __future__ import annotations
from dataclasses import dataclass
from i... |
5a7336dcd7ab7b013ddd37267c19cc2ed94cfc24b044bb5f5e7c00f11a880166 | Python | 24,304 | 596 | """ Utilities for motion and raster correction of resonant scans. """
import numpy as np
import datajoint as dj
from scipy import interpolate as interp
from scipy import signal
from scipy import ndimage
from tqdm import tqdm
from ..exceptions import PipelineException
from ..utils.signal import mirrconv
def compute_r... |
45ae184cfa326c703367dd23f5a9cd497bf809163cfa63004982f9b1694b9eb6 | Python | 24,325 | 371 | from train_AE import init_from_config
from brainvoice.visualization import gen_spectrogram_cmap, plot_spectrogram_on_axis, save_borderless
from brainvoice.spectrogram_utils import linearspectrogram, inv_linear_spectrogram, get_better_synth_hparams
from brainvoice.waveform_utils import write_waveform
from brainvoice.dat... |
5351830f46a839596fc8822dad329e872a8b2281782b2cdab0d10969e59ee922 | Python | 24,368 | 935 | # -*- coding: utf-8 -*-
"""Channel Estimation in OTFS and NOMA .ipynb
Automatically generated by Colab.
Original file is located at
https://colab.research.google.com/drive/15yyB9BhgmOkvNJMxbi7VOCyKRn2tEhNc
"""
pip install numpy scipy torch scikit-learn matplotlib
import numpy as np
import torch
import torch.nn ... |
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