sha256 stringlengths 64 64 | language stringclasses 28
values | size int32 1 491k | lines int32 1 23.2k | content stringlengths 1 200k |
|---|---|---|---|---|
2f128dab87a2822f154a58200d937955444fe39c80ba18dfdab43f14540f016a | Python | 5,365 | 133 | import jax
import jax.numpy as jnp
import matplotlib.pyplot as plt
import os
import plot_utils
import json
jax.config.update("jax_default_matmul_precision", "high")
plt.rcParams["font.sans-serif"] = ["DejaVu Sans"]
plt.rcParams["font.family"] = "sans-serif"
plt.rcParams.update({
"font.size": 10,
"axes.t... |
eb1af6363b08bc6ffb6dc277782a3506df8cb36ea06d69a9d2e23026745ae571 | Python | 5,366 | 126 | import pandas as pd
import numpy as np
import os
import glob
root = '{0}Users{0}mococomac{0}Documents{0}data_backups{0}Bouba{0}original_format{0}bouba_scans{0}preproc2{0}'.format(
os.sep)
global_dict = {'round': 1, 'mixed_round': 2, 'mixed_spiky': 3, 'spiky': 4}
subs_list = [os.path.basename(x) for x in glob.glo... |
5d588141fb616bde5f82efe38d7e158a226fdd122466b77c6b367ca2ed2fe830 | Python | 5,367 | 142 | from brainscore_vision.model_helpers.check_submission import check_models
import functools
from transformers import AutoFeatureExtractor, CvtForImageClassification
from brainscore_vision.model_helpers.activations.pytorch import PytorchWrapper
from PIL import Image
import numpy as np
import torch
"""
Template module fo... |
6486707009cf2c8ce6fb462d81f6c4ff2c96bb2c185cfbb43671640ebd2d732b | Python | 5,367 | 142 | from brainscore_vision.model_helpers.check_submission import check_models
import functools
from transformers import AutoFeatureExtractor, CvtForImageClassification
from brainscore_vision.model_helpers.activations.pytorch import PytorchWrapper
from PIL import Image
import numpy as np
import torch
"""
Template module fo... |
951fd2687dac67ea9c8fa4ac606e22060936208170fa76eca45cc518edc3543d | Python | 5,367 | 145 | 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, \
roc_auc_score
from sklearn.metrics import classification_report
from sklearn.metrics import confusion_m... |
35775932e97aa9527dea735aaec6c25bd2e452dc210d06c9a9ec3f58ebe459a0 | Python | 5,368 | 137 | #!/usr/bin/env python3
# -*- coding: utf-8 -*-
"""
Split a tractogram into multiple files, 2 options available :
Split into X files, or split into files of Y streamlines.
By default, streamlines to add to each chunk will be chosen randomly.
Optionally, you can split streamlines...
- sequentially (the first n/nb_ch... |
7d9d9866fdc0ed2fa082d62c81cf64b554949a278cc7502575bbddeee661f070 | Python | 5,368 | 99 | # -*- coding: utf-8 -*-
# Form implementation generated from reading ui file 'destination.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_Dialog(object):
def setupUi(self, Dialog):
Dialog.setObjec... |
cdcf87f87b9c5bd568ba9fd2b7554db56571e596586ea66edeaf0f413d9c3816 | Python | 5,368 | 142 | import math
import torch
import numpy as np
import random
def gaussian_kernel(
sigma: float, k: float=1, size:float=15, norm:bool=False
) -> torch.tensor:
"""Returns a 2D Gaussian kernel.
:param sigma (float): standard deviation of the Gaussian
:param k (float, optional): height of the Gaussian
... |
e80e72e1a6c69c99557425c0b61a2ac03da792668cad7a058abccc9072a843a4 | Python | 5,368 | 179 | import numpy as np
def threshold_classifier(dtheta_seqs, left_threshold, right_threshold):
"""Classify re-orientation angles into 3 states based on 2 thresholds.
Re-orientation angle δθ are classifed as followed :
- δθ < :left_threshold: → 1
- δθ > :right_threshold: → 2
- :left_thres... |
f0680767724649de5658c1c20ff401e44e32769bff1211459022878d2450995b | Python | 5,368 | 134 | # wfield - tools to analyse widefield data - plotting the results / summary plots
# Copyright (C) 2020 Joao Couto - jpcouto@gmail.com
#
# This program 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 ... |
017cf144a4cfc5c8331c04c894cc365cb7cd1a346d5a2df9f5f5828ebb61813b | Python | 5,369 | 133 |
import matplotlib.pyplot as plt
import numpy as np
import figure_properties as fp
from utils import Q_nak, Recorder
from mitochondria import Mito
dt = 0.01
def single_spike(spike_at=150, q=1, t_start=150, t_run=5000, t_ca1=7000, t_ca2=20000):
tt = np.arange(0, t_run, 0.01)
spike_costs = np.zeros_like(tt)
... |
7da2938a57bb290166bcf7e1cbbbd7ca19ec80347cdd4416c181ccd8c388fe5d | Python | 5,369 | 165 | #!/usr/bin/env python3
# inference.py
"""
推理脚本 —— 加载分类与回归模型，生成手术指征与剂量预测
流程：
1. 读取输入特征（6 维），并使用训练时保存的 StandardScaler 做同样的预处理。
2. 对预处理后特征，使用所有折的分类模型做前向，平均概率，阈值化生成初步二值 mask。
3. 对每个样本的冲突预测（同一眼内直肌“缩短”与“后徙”同时为 1），只保留概率更高的一项。
4. 使用所有折的回归模型在 mask 掩码下做前向，平均预测剂量。
5. 将最终的手术指征（0/1）与手术剂量（mm）组合输出。
使用：
$ python inference.py --input... |
f91b8513c7d11425e902a67911a432637a4e3f8530c2ad0bf8041b2a818ce43e | Python | 5,370 | 118 | # Copyright (C) CVAT.ai Corporation
#
# SPDX-License-Identifier: MIT
import unittest
from contextlib import ExitStack, nullcontext
from types import SimpleNamespace
from unittest import mock
from cvat.apps.quality_control import quality_calculators
from cvat.apps.quality_control.data_providers import JobDataProvider
... |
a0d6da5aeb6ae214b67d910368723f39a69c9471c3feddc36dcc0582c84bf2d8 | Python | 5,372 | 174 | #!/usr/bin/env python3
# This script is included in documentation. Adapt line numbers if touched.
import arbor as A
from arbor import units as U
import pandas as pd
import seaborn as sns
import sys
from pathlib import Path
# (1) Read the morphology from an SWC file.
if len(sys.argv) == 1:
print("No SWC file passe... |
14911df9670f6b56ce7199016f1c5d8c2198009fcbcf1c80de87c26d959e6e52 | Python | 5,373 | 176 | # -*- coding: utf-8 -*-
#
# Configuration file for the Sphinx documentation builder.
#
# This file does only contain a selection of the most common options. For a
# full list see the documentation:
# http://www.sphinx-doc.org/en/master/config
# -- Path setup ------------------------------------------------------------... |
2dc8d3e3913faee52b77fb27f70de0a4380440f56cc815b4652da29d2f9f0bf9 | Python | 5,373 | 183 | from __future__ import annotations
import sys
import pytest
from PySide6 import QtGui
from pytestqt.qtbot import QtBot
from labelme._automation import AiOutputFormat
from labelme._widgets._ai_assisted_annotation_widget import AiAssistedAnnotationWidget
@pytest.fixture
def models() -> list[str]:
return []
@py... |
59ea889e1e7d62ce22dcb9d339c9439926a03b05f167b2ecc5d750d5c5c68e6d | Python | 5,373 | 128 | """Density samples outside the tomogram must be NaN, not extrapolated.
`interpn(..., fill_value=None)` extrapolates linearly from the edge, which is
unbounded: a linescan leaving the volume produced invented values that the
thickness fitter could not distinguish from real data. These pin the honest
behavior and the do... |
861e475f2129bac6c72c2ef00fe19d015fa333bf0079edd848716bea0c23531e | Python | 5,373 | 123 | """Console progress for the scaling example, including executor subgraphs."""
from datetime import datetime, timezone
from itertools import islice
import json
from threading import RLock
import time
from langchain_core.callbacks import BaseCallbackHandler
def summarize(value, depth=0):
"""Bound tool payloads wh... |
89359105ad3c829c9dba3ac2d55843df1a4f4e3f6b70422e931a9fa513681362 | Python | 5,373 | 100 | #!/usr/local/bin/python3
from pipeline import experiment, reso, meso, fuse, stack, pupil, treadmill, posture
from stimulus import stimulus
from stimline import tune
import time
import logging
import datajoint as dj
## database logging code
logging.basicConfig(level=logging.ERROR)
logging.getLogger('datajoint.connect... |
beb676b4f560660b72948e2741bdeb9c00b41f677dd6a91f2084a974eb2c21e8 | Python | 5,373 | 82 | #!/usr/bin/python
import os
def create_key(template, outtype=('nii.gz',), annotation_classes=None):
if template is None or not template:
raise ValueError('Template must be a valid format string')
return template, outtype, annotation_classes
def infotodict(seqinfo):
"""Heuristic evaluator for ... |
ddd1ee1a13c877fdcb01d38516707bcd6ab6a8084264b0734ecb5a2a1309335b | Python | 5,373 | 176 | # -*- coding: utf-8 -*-
#
# Configuration file for the Sphinx documentation builder.
#
# This file does only contain a selection of the most common options. For a
# full list see the documentation:
# http://www.sphinx-doc.org/en/master/config
# -- Path setup ------------------------------------------------------------... |
e9ac4caeb38d508872c7dc9fa95de743cff683f60fca41fad2d266bb8ea21767 | Python | 5,374 | 137 | """ Various useful function related to IVIM scanning on Philips MRI systems. """
import os
import numpy as np
import numpy.typing as npt
from ivim.io.base import read_bval, write_cval
from ivim.seq.fwf import c_from_b
def generate_dti_vectors_input(b: npt.NDArray[np.float64], filename: str, dualpol: bool = False, hea... |
20b14e949780ad6cfb2dbc020662be86238547466ddd66ea3ec7aa0003cf9421 | Python | 5,375 | 181 | from collections.abc import Callable, Sequence
from typing import (
TYPE_CHECKING,
Any,
Optional,
Protocol,
Union,
)
from eir.experiment_io.io_utils import get_run_folder_from_model_path
from eir.predict_modules.predict_tabular_input_setup import (
ComputedPredictTabularInputInfo,
)
from eir.se... |
43bc0df983d6eba204a6dfe38442e5733882ed473fb3471ef4311f5e24faec09 | Python | 5,375 | 151 | """Script to extract laminar resting state activity from digit ROIs"""
import nibabel as nb
import numpy as np
import glob
import os
ROOT = '/Users/sebastiandresbach/data/s1Anfunco/Nifti'
# Set subjects to work on
# subs = ['sub-15', 'sub-16', 'sub-17', 'sub-18']
# subs = ['sub-06', 'sub-09', 'sub-10', 'sub-12', 'su... |
2df33dbb0d5449678f516686cc7894999b3b565b8212f9f09feff319f0eb1e28 | Python | 5,376 | 172 | import contextlib
import json
import os
import re
from pathlib import Path
from typing import Optional
import click
import matplotlib as mpl
import matplotlib.colors as mcolors
import numpy as np
import pandas as pd
from simple_mri import SimpleMRI, load_mri, save_mri
def inverse_dict(index):
inverse = {}
fo... |
1a354a32f12ad64dac795b22a1483d70e2136d410edd8c92dcd396ca54f2bd85 | Python | 5,377 | 140 | import matplotlib.pyplot as plt
import numpy as np
import nems
from nems import Model
from nems.layers import WeightChannels, FiniteImpulseResponse, RectifiedLinear, STRF
from nems import visualization
from nems.metrics import correlation
from nems.models.LN import LN_plot_strf
import tensorflow as tf
# Check if eage... |
47e77b22e7fe45b8ab0ffe6b9e52e801eecd27c83b525e2eabdd453f025e6b7c | Python | 5,378 | 118 | import os
import pandas as pd
import numpy as np
import argparse
def perturb_graph(data_path, graph, perturbation_mode, k=0, seed=123):
np.random.seed(seed)
if graph == 'train1':
df = pd.read_csv(os.path.join(data_path, 'train1.txt'), sep='\t', header=None)
elif graph == 'train2':
df = pd.... |
6974add46d50fbcb6569daf2080591384f08dac2a4f56b1bae5c011ec30f6be6 | Python | 5,378 | 238 | # Copyright (C) CVAT.ai Corporation
#
# SPDX-License-Identifier: MIT
"""Read-only annotation model independent of storage and conversion libraries.
Labels refer to positions in the accompanying catalog, not database label IDs.
Adapters retain source references separately from representation-specific IDs.
"""
from ab... |
ce2bc9f13aa421f6fe67eb0e2a0c91b59bc9c50f1b759265e0082c5963b1f3a1 | Python | 5,380 | 129 | alg_name = 'node2vec'
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.env... |
36c7991e585a1727fc61a6b9d321cb271fb899ba54d3d2ffae8573f6d5bda962 | Python | 5,381 | 141 | # -*- coding: utf-8 -*-
# @Author : LG
import functools
from PyQt5 import QtCore, QtGui, QtWidgets
from ISAT.ui.shortcut_dialog import Ui_Dialog
class ShortcutDialog(QtWidgets.QDialog, Ui_Dialog):
def __init__(self, parent, mainwindow):
super(ShortcutDialog, self).__init__(parent)
self.mainwin... |
6bc5a777dc08e37e42de08ef793e49afe9fd5b27b94f617f69e6d7a66a1f1649 | Python | 5,381 | 152 | # Source: https://github.com/neuraloperator/neuraloperator/blob/main/neuralop/training/training_state.py
"""
Snippet to load all artifacts of training state as Modules
without constraining to use inside a default Trainer
"""
from typing import Union
from pathlib import Path
import torch
from torch import nn
import to... |
cf7d9d7687e58019f972d055ecd48dd0b0a3e26f69235a09eca79d429b85c4d5 | Python | 5,381 | 133 | # Mixed precision
from tensorflow.keras import mixed_precision
mixed_precision.set_global_policy("mixed_float16")
import numpy as np
from tensorflow.keras.optimizers import Adam
from tensorflow.keras.optimizers.schedules import PolynomialDecay
from tensorflow import concat as tf_concat
from json import dump as json_du... |
9fc884c6ea42ab29bbca51f2a103b59383c6ed13fe5848c672a9dff73bd6ea47 | Python | 5,382 | 150 | # -*- coding: utf-8 -*-
# @Author : LG
import os
from PyQt5 import QtCore, QtGui, QtWidgets
from ISAT.ui.file_dock import Ui_Form
class FilesDockWidget(QtWidgets.QWidget, Ui_Form):
def __init__(self, mainwindow):
super(FilesDockWidget, self).__init__()
self.setupUi(self)
self.mainwindo... |
c60a6d2fb67bdee7a9d3262235e4a692de6ded6b7bc814f9a12a91a5201f85f1 | Python | 5,382 | 135 | from zigzag.classes.io.onnx.parser import Parser
from zigzag.classes.io.onnx.utils import (
get_node_input_output_dimension_shapes,
get_attribute_ints_with_name,
)
from zigzag.classes.workload.layer_node import LayerNode
import logging
logger = logging.getLogger(__name__)
class GemmParser(Parser):
"""Pa... |
a0bb1baa1dc76158e0f255b801b290a655b493ec4795b2253a000c17aaf86eb4 | Python | 5,383 | 119 | """ Selective Kernel Convolution/Attention
Paper: Selective Kernel Networks (https://arxiv.org/abs/1903.06586)
Hacked together by / Copyright 2020 Ross Wightman
"""
import torch
from torch import nn as nn
from .conv_bn_act import ConvNormAct
from .helpers import make_divisible
from .trace_utils import _assert
def ... |
68445885ed396ae71b1fdc6554b7f7231bb2dff799b2c74f4cd62bfec55e3f3a | Python | 5,385 | 132 |
import numpy as np
import matplotlib.pyplot as plt
import matplotlib
import scipy.signal
from matplotlib import gridspec
from numpy import loadtxt
import module_utility
import scipy
import random
#
angle_colume = 14 # access angles from this colume
num_samples = 36 # number of samples
output_table = np.zeros((20, num... |
929ac630f160bb19017563f88658f460a0af590fe5eb0bb4242da17ed96a3fd7 | Python | 5,387 | 151 | """Minimal EDF / EDF+ reader.
Written rather than taking an MNE dependency: the pipeline needs only headers,
signals and EDF+ annotations, MNE does not support this project's Python 3.9
floor cleanly, and a 120-line reader is easier to audit than a large dependency
when the question being asked is "what is actually in... |
1def962d33775b84b2fae9a4c6b936809200327b7ec0821fd2fcfa3270867175 | Python | 5,388 | 117 | # ==============================================================================
# Binaries and/or source for the following packages or projects are presented under one or more of the following open
# source licenses:
# mask.py The OpenLane Dataset Authors Apache License, Version 2.0
#
# See:
# https://g... |
524ac09f3e284486def94f9ebaf916996fc5e9a6b6db8a029d08475af4c727f5 | Python | 5,389 | 145 | """Offline contribution checks; runtime loading remains deliberately permissive."""
from dataclasses import asdict, dataclass
from pathlib import Path
import re
from urllib.parse import unquote, urlsplit
from deepagents.middleware.skills import (
MAX_SKILL_COMPATIBILITY_LENGTH,
MAX_SKILL_DESCRIPTION_LENGTH,
... |
634812541651df8dfedfff5c3ca8af5c7eb9dab14c713d78f1334b03f1a35022 | Python | 5,389 | 176 | # -*- coding: utf-8 -*-
#
# Configuration file for the Sphinx documentation builder.
#
# This file does only contain a selection of the most common options. For a
# full list see the documentation:
# http://www.sphinx-doc.org/en/master/config
# -- Path setup ------------------------------------------------------------... |
6652289f1a3d1d202b66b0ceaa50984c236c14ca3469dcbc7c5b55e58000f702 | Python | 5,389 | 111 | import os
from unittest import mock, TestCase
import kb_python.config as config
class TestConfig(TestCase):
def test_get_provided_kallisto_path(self):
with mock.patch('kb_python.config.PLATFORM', 'linux'),\
mock.patch('kb_python.config.os.path.isfile', return_value=True):
self.as... |
9296cfa5ec4de7b7a14f8a75ac2b91a59c26f7cf6d6eceee920a405a3e093d4d | Python | 5,390 | 124 | from nipype import Node, Workflow
from nipype.interfaces.base import BaseInterface, BaseInterfaceInputSpec, TraitedSpec, File, Directory, traits
from traits.api import Bool, Str
import os, sys
import numpy as np
import nibabel as nib
from dipy.io import read_bvals_bvecs
from dipy.core.gradients import gradient_table
fr... |
7b8c41a557a97ec6fc07c7a029994399743920db04d2bfa125b1f43763ba4e90 | Python | 5,391 | 155 | from collections import namedtuple
import os
import math
import random
from tkinter import W
import pandas as pd
import numpy as np
from tqdm import tqdm
from glob import glob
import torch
import torchaudio
from torchaudio import transforms as T
from .augmentation import augment_raw_audio
__all__ = ['save_image', 'g... |
3e28c7b3d80f5be94bd90fbc0bb52ff6095eb4e37e870c872d4ab6540a403ef6 | Python | 5,392 | 103 | from .util import Partition, weighted_jaccard_distance, describe_sol
from .problem import Problem
from .seeded import solve_seeded, features_and_medians
from numba import njit
import math
import os
import datetime, time
import pickle
import numpy as np
def partition_cost(problem, partition):
return problem.eval_me... |
dc0f8985cfc892bc8c408eed20335cf53b7d5a9dbfbe367be40057c880c593fb | Python | 5,392 | 173 | #!/usr/bin/env python
"""
Basic DAQ module functionality.
Hazen 04/17
"""
import numpy
from PyQt5 import QtCore
import storm_control.hal4000.halLib.halMessage as halMessage
import storm_control.sc_hardware.baseClasses.hardwareModule as hardwareModule
import storm_control.sc_library.halExceptions as halExceptions
... |
bdfb246957fa146502d264e28c1ccb0f1e20b805296e27c0ae1ba0e766caab60 | Python | 5,395 | 144 | """Circular-shift shuffle test for stim-response significance.
Port of ``stimShuffleTest.m`` + ``computeTrialProportion.m`` /
``computeTrialProportionForEachChannel.m`` (origin/main).
The per-electrode metric is the proportion of trials where the post-stim spike
count exceeds the pre-stim (baseline) count. Significan... |
da2ebb6b275a45fea5ea49fa167448a826f05f428c1e9cdaa19bc209b16f92cf | Python | 5,396 | 82 | #!/usr/bin/python
import os
def create_key(template, outtype=('nii.gz',), annotation_classes=None):
if template is None or not template:
raise ValueError('Template must be a valid format string')
return template, outtype, annotation_classes
def infotodict(seqinfo):
"""Heuristic evaluator for ... |
25a91012bc2153d1a1b365d7938481efc7985db6556679ca08d17660df12a061 | Python | 5,397 | 134 | # Importing individual benchmarks directly is discouraged.
# Use `brainscore_vision.load_benchmark` instead which provides dependency support.
"""
A :class:`~brainscore.benchmarks.Benchmark` runs an experiment on a :class:`~brainscore.model_interface.BrainModel`
and tests the resulting measurements against primate `da... |
445e707618b3edb6a5088e01d73f47711f515d628ae6b3388dd647b7f22091d5 | Python | 5,397 | 148 | #!/usr/bin/env python
import os
import storm_control.sc_library.halExceptions as halExceptions
import storm_control.hal4000.testing.testActions as testActions
import storm_control.hal4000.testing.testing as testing
import storm_control.test as test
#
# Test taking a 10 frame movie, 512 x 512.
#
class FilmTest1(tes... |
a73e252eb3e412bffbd322341dec5512146e785f14aa09b38ce6783b422eebf9 | Python | 5,397 | 124 | import nighres
import os
import nibabel
import numpy
import glob
import scipy.ndimage
indir = '/home/pilou/Projects/Cerebellum/Cerebellar-segmentation-ABC/sereno/tissues/'
outdir = '/home/pilou/Projects/Cerebellum/Cerebellar-segmentation-ABC/sereno/topology/'
wmprior = indir+'serenocb20_T1_cr_def-img_n4_wmprior.nii.g... |
351754c4079ae8e9e44ba970a6f8d5bc12690f3f361b3b37042edff2ceb2ab7e | Python | 5,400 | 120 | #!/usr/bin/env python
# -*- coding: utf-8 -*-
# *************************************************************************** #
# Copyright © 2022, UChicago Argonne, LLC #
# All Rights Reserved #
# Softwar... |
f89d8c03b9c0561b75f92d819e6629d899a67819a0fc5b8b6205871d1e8ebcad | Python | 5,400 | 136 | #!/usr/bin/env python
"""
Emulated QPD functionality
Hazen 04/17
"""
import math
import random
import time
from PyQt5 import QtCore
import storm_control.hal4000.halLib.halMessage as halMessage
import storm_control.sc_hardware.baseClasses.hardwareModule as hardwareModule
import storm_control.sc_hardware.baseClasses.... |
484c1f5d856b23c1cddcacb9ef4923d120f6e022c1d6c3753a8e32484bb25156 | Python | 5,401 | 137 | #!/usr/bin/python3
from __future__ import absolute_import
from __future__ import division
from __future__ import print_function
import numpy as np
import torch
from torch.utils.data import Dataset
class TrainDataset(Dataset):
def __init__(self, triples, nentity, nrelation, negative_sample_size, mode, count, tru... |
7cd4a43182725037b892b3cbc1d347f4d2e1eefcd66db484884c7eb75672900b | Python | 5,401 | 165 | """Tools for visualizing the inputs, outputs, and parameters of Layers."""
import numpy as np
import matplotlib.pyplot as plt
from matplotlib.ticker import MaxNLocator
from nems.layers.stp import ShortTermPlasticity
from nems.preprocessing.normalization import minmax, joint_minmax
from nems.distributions import Norma... |
4030295cfc95edf817b37c7d9f5cf1691e8f8e8ed7aa1008749f058c00cb5ab2 | Python | 5,402 | 132 | import time
import torch
import torchvision
import torchvision.transforms as transforms
from torch.utils.data import DataLoader
import os
from conf import global_settings as conf_set
from spikingjelly.datasets import cifar10_dvs
from spikingjelly.datasets import dvs128_gesture
def get_cifar100_training_dataloader(ba... |
c3b9994f8250dd16aa3e9ce32d3444fe872c2296d5d838d6e571a0448e990dc6 | Python | 5,402 | 150 | """
Functions for visualizing analyses
"""
import numpy as np
import matplotlib.pyplot as plt
from scipy.stats import sem
from stats_utils import *
"""
Plots the sections in time corresponding to each playing mode: inv, shinv and norm. Each is shaded a different colour.
section_list: the list of start and end times o... |
595c7481ec23be86f2e3b93c7cfe7ec14c22cd495c54eb6215ba9284e35669d3 | Python | 5,405 | 178 | # -*- coding: utf-8 -*-
#
# Configuration file for the Sphinx documentation builder.
#
# This file does only contain a selection of the most common options. For a
# full list see the documentation:
# http://www.sphinx-doc.org/en/stable/config
# -- Path setup ------------------------------------------------------------... |
7e8f769d6ce514e0e0dc91d8601700ece1579c69e027b21a79787d84fff540c3 | Python | 5,407 | 149 | import torch
from torch.nn import Parameter
from torch_geometric.nn.conv import MessagePassing
from torch_geometric.nn.inits import reset, uniform
import torch.nn.functional as F
import torch.nn as nn
class NNConv_old(MessagePassing):
r"""The continuous kernel-based convolutional operator from the
`"Neural Mes... |
63041150ab1056095239c8b7648c6c3d31f4ddb468b497d6c4aa7ba44f02b562 | Python | 5,409 | 133 | """An example script, which uses memoization to store (intermediate) results."""
# pylint: disable=duplicate-code
import time
import typing
from collections.abc import Sequence
from typing import Annotated, SupportsIndex
import h5py
import numpy
from corelay.base import Param
from corelay.io.storage import HashedHD... |
8a384ffd68e75add6c2e379e6afb5b25b650ca7b7e555a7bb4706c8d122e16b3 | Python | 5,409 | 146 | """Perform MDS on the trial-average fMRI responses, or on the DDN features, for
the NSD-core images.
Parameters
----------
subject : int
Number of the used subject.
data_ood_selection : str
If 'fmri', perform MDS on the fMRI responses for the NSD-core images.
If 'dnn', perform MDS on the DNN features for the NSD-co... |
ce5b7f3f3dfcd320c07470eda963c3684028a7cddc8079e1feceabee0c47c9ce | Python | 5,411 | 88 | import numpy as np
from brainscore_core import Score
from brainscore_vision import load_dataset, load_metric
from brainscore_vision.benchmark_helpers.screen import place_on_screen
from brainscore_vision.benchmarks import BenchmarkBase, ceil_score
from brainscore_vision.model_interface import BrainModel
BIBTEX = """@A... |
e39c860a414e1d646d19374fb0120b82a26057f6925e09444b33a79e5c46b00c | Python | 5,412 | 151 | import sys
import numpy as np
from matplotlib import pyplot as plt
import h5py
def prColor(word, color_type):
''' function to print color text in terminal
input:
word: word to print
color_type: which color
'red', 'green', 'yellow'
... |
9309ca56c26d4a4e395e595e004d027378dd63a977d85105e8d478e007afab8c | Python | 5,414 | 137 | #!/usr/bin/env python
"""
Long runnings tests that are run manually, not designed for CI
"""
import os
import storm_analysis.sa_library.datareader as datareader
import storm_control.sc_library.halExceptions as halExceptions
import storm_control.hal4000.testing.testActions as testActions
import storm_control.hal4000.... |
4940b95d37cdd47b55ee255f026d0103dfad41cf9c2d957a3b9766ad630816d0 | Python | 5,416 | 124 | """
Compare final Dice scores for deformable registration with Adam vs Levenberg
optimizers, for both Greedy and SyN methods.
"""
import logging
import pytest
from pathlib import Path
from fireants.registration.greedy import GreedyRegistration
from fireants.registration.syn import SyNRegistration
from fireants.io.imag... |
b247913baf0498a48c1d3ad1b8b0dce6d4e3a814d51d63fca18d7ae3a2647c36 | Python | 5,416 | 137 | # Copyright (c) Meta Platforms, Inc. and affiliates. All Rights Reserved
from collections import defaultdict
import torch
import torch.nn.functional as F
from .masks_ops import mask_iou
from scipy.optimize import linear_sum_assignment
def associate_det_trk(
det_masks,
track_masks,
iou_threshold=0.5,
... |
e311641c8fbdbdd5329a8d64067ce0b62f28e8c59181b557a2f960252facdffd | Python | 5,417 | 174 | # -*- coding: utf-8 -*-
__author__ = "Felix Niemöller"
__email__ = "usnrb@student.kit.edu"
import torch
# torchaskivit.utils
from . import utils
def train_one_epoch(epoch, P, d, print_interval=50):
len_train = d["loader_train_len"]
# Initialize loss tracking
running_loss = 0.0
last_l... |
829b939bc371115e9559eea5cc6e484554d4d7e7fcf87fc4b150a704f1ebb03a | Python | 5,418 | 171 | #!/usr/bin/env python
import argparse
import sys
from pathlib import Path
import imgviz
import numpy as np
from numpy.typing import NDArray
sys.path.insert(0, str(Path(__file__).resolve().parent.parent))
import utils # noqa: E402 # examples/utils.py, vendored alongside this script
def _create_output_directories... |
06d03463ea00e458906b37219a71ff8132ed6067282e05bc5f4ecd7e3c2ff397 | Python | 5,419 | 123 | import os
import numpy as np
import cv2
import argparse
import onnxruntime
from tqdm import tqdm
parser = argparse.ArgumentParser()
parser.add_argument("--model-path", type=str, default="./yolov5s6_pose_640_ti_lite_54p9_82p2.onnx")
parser.add_argument("--img-path", type=str, default="./sample_ips.txt")
parser.add_argu... |
1bdabde7eb1bcec15e302c652b86c5d74d2bbc83e4e420d43770e2b42b6b0e61 | Python | 5,419 | 149 | import torch
import torch.nn as nn
import torch.nn.functional as F
from torch import einsum
# --- 辅助模块 ---
class Swish(nn.Module):
def forward(self, x):
return x * torch.sigmoid(x)
class ConvBlock(nn.Module):
"""
轻量级卷积块，用于捕捉局部特征.
使用深度可分离卷积 (Depthwise Separable Convolution) 提升效率.
结构: Point... |
5590d6a3102631d9c28dc194a4fe475df7e51d1cd8dd9ede7b81035cabfe0be9 | Python | 5,420 | 93 | """
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:... |
fb28cf5b53bcc65cab46748ab2c80cbc60718821eb902ae2ed77ca896e35c89c | Python | 5,421 | 140 | import sys, os, copy
import torch
from monai.config import print_config
from monai.transforms import (
AddChannel, Compose, LoadImage, EnsureChannelFirst,
ScaleIntensity, ToTensor, HistogramNormalize, ResizeWithPadOrCrop
)
from monai.data import NibabelWriter
from utils.netdef import ShuffleUNet
import numpy as... |
11286b296898f701d4848e58e19f4a9c02fc7de81433dbb85190fd86e2b1c48b | Python | 5,422 | 152 | """mapsurfacetovolume
"""
import numpy as np
from scipy import sparse
from nsdcode.utils import zerodiv
__all__ = ["mapsurfacetovolume"]
def mapsurfacetovolume(data, vertices, res, specialmode, emptyval):
"""mapsurfacetovolume(data, vertices, res, specialmode, emptyval)
Args:
data (nd-array): is th... |
8463ac67eb7eff381e615ef4dcba94db5fc2688cd2d50203602f8fd6a9d5a218 | Python | 5,422 | 150 | import SimpleITK as sitk
import numpy as np
import torch
import cv2
import tkinter as tk
from tkinter import messagebox
from PIL import Image, ImageTk
from torchvision.utils import make_grid
import torchvision
import matplotlib.pyplot as plt
from mpl_toolkits.axes_grid1 import ImageGrid
from display_gui import load_... |
84a5e0029e3e8518d852e5fde535435ecab073641849eda98b9595b8db1ea31a | Python | 5,422 | 138 | from typing import TYPE_CHECKING, Tuple
import magicgui
from magicgui.widgets import request_values
from qtpy.QtWidgets import QLabel, QPushButton, QVBoxLayout, QWidget
from brainways.project.info_classes import MaskFileFormat, SliceSelection
from brainways.ui.widgets.warning_dialog import show_warning_dialog
if TYP... |
a9fe2cb8f12f64a189693dcffac12a798986f61bf87f52641661edea6b672673 | Python | 5,422 | 175 | import reprlib
from collections import defaultdict
from collections.abc import Callable, MutableMapping
from functools import partial
from inspect import signature
from typing import (
TYPE_CHECKING,
Any,
)
import torch
from adabelief_pytorch import AdaBelief
from aislib.pytorch_modules import AdaHessian
from ... |
e638914cd31b8637fab53915337fb19009544a944d07fa249d30f90421a154dc | Python | 5,423 | 106 | #!/usr/bin/env python3
import pandas as pd
import numpy as np
import argparse
import os
import subprocess
import gzip
def has_dependency(name):
return subprocess.call('which '+name, shell=True, stdout=subprocess.DEVNULL, stderr=subprocess.DEVNULL) == 0
def patch_bim_ids(bim_in, bim_out):
"""Modifies long i... |
3e0c3e4be84a8512e82d13311c247ee5ff460d0606820ee1d1aa627a980c8ad4 | Python | 5,424 | 114 | import pandas as pd
import numpy as np
from typing import Optional
from sklearn.base import BaseEstimator as SKLearnBaseEstimator
from .survival_utils import safe_join
from .regression_curve_fitter import RegressionCurveFitter
class UnivariateCurveFitter:
def __init__(self, learner: Optional[SKLearnBaseEstimator]... |
0aa1831318d7fa539e1c8c698ade78db6ff70895f8d40a7f6d324169681a4ace | Python | 5,425 | 171 | #!/usr/bin/python
#
## @file
#
# ctypes interace to a phidgets control library.
#
# Hazen 12/10
#
import time
from ctypes import *
#class ProductInformation(Structure):
# _fields_ = [("axis_bitmap", c_ubyte),
# ("ADC_resolution", c_short),
# ("DAC_resolution", c_short),... |
4b336547f9e419d9f4b5bda671c24bd721658ebff17adbefd9d7e3d7733a71de | Python | 5,425 | 180 | import logging
import os.path as op
from AFQ.utils.path import drop_extension
logger = logging.getLogger("AFQ")
__all__ = ["Definition", "find_file", "name_from_path"]
class Definition(object):
"""
All Definitions should inherit this.
For a given subject and session within the API, the definition is u... |
0f2dceb3fcf6a88f400342273cdd28ae839d1135bbc1e61bd5493b0b4657bab9 | Python | 5,426 | 127 | import abc
from abc import ABC
from typing import Any, Dict, List, Optional
import torch
class Scheduler(ABC):
""" Parameter Scheduler Base Class
A scheduler base class that can be used to schedule any optimizer parameter groups.
Unlike the builtin PyTorch schedulers, this is intended to be consistently... |
86652ae45505af58e7145ded96a57c2a3f6bcc6bf60daf35a5d1c6c46d1260f1 | Python | 5,427 | 157 | # Copyright 2025 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, ... |
fc055e8a31aeef834357e33c13c1c41adfe52917aca4b3fe70b5abf1cfcd1d5e | Python | 5,429 | 153 | import numpy as np
import pandas as pd
from tqdm import tqdm
from typing import Iterable
from argclz import int_tuple_type, AbstractParser, argument
from neuralib.plot import plot_figure
from neuralib.suite2p import get_neuron_signal, sync_s2p_rigevent, Suite2PResult
from neuralib.typing import AxesArray
from rscvp.ut... |
0bf5b0ee1d232a55557cdd8b9d344e86b6fe3ec142eff2508e9481135f13645e | Python | 5,430 | 166 | from typing import Any
import torch
import torch.nn as nn
import seisbench.util as sbu
from .base import WaveformModel
class GPD(WaveformModel):
"""
.. document_args:: seisbench.models GPD
"""
_annotate_args = WaveformModel._annotate_args.copy()
_annotate_args["*_threshold"] = ("Detection thre... |
722057e1958a665ec20803de06db735807690d22381a4c17163cf1e3998d6f59 | Python | 5,432 | 167 | # Copyright (c) Meta Platforms, Inc. and affiliates.
# All rights reserved.
# This source code is licensed under the license found in the
# LICENSE file in the root directory of this source tree.
import torch
from functools import partial
from .modeling import ImageEncoderViT, MaskDecoderHQ, PromptEncoder, Sam, Two... |
780a650554953d1b84365463394374d9687adc5725a9b20958614e2e65478d1b | Python | 5,432 | 211 | #!/usr/bin/python
#
## @file
#
# LDC210 diode laser driver on/off control
#
# Hazen 04/12
#
import sys
import time
import storm_control.sc_hardware.nationalInstruments.nicontrol as nicontrol
## LDC210
#
# Turn on/off with a digital line connected to the
# TTL input of the laser diode controller.
... |
d4441b61e2353f40b2cfd6520f23e9a083f411cd3437c4f07ce76f3d2be02427 | Python | 5,432 | 111 | import numpy as np
import pandas as pd
from typing import Tuple, Union
from . import ELA_Network_functions
#-----------------------------------------------------------------------------------
# ④calc TP for all combinations of SS
#-----------------------------------------------------------------------------------
#-... |
ebe8892fb5778a9457a48116acb498f4582831922e382e0695b7cf9aa81b1b48 | Python | 5,432 | 160 | """
Classes for working with position specific matrices.
"""
from copy import copy
import numpy
from numpy import (
float32,
int16,
log2,
maximum,
nan,
newaxis,
ones,
zeros,
)
from . import _pwm # type: ignore[attr-defined]
class BaseMatrix:
"""
Base class for position spec... |
32f4c8d2e9316af7c0a2c9894550989ec46ae76112a9e8e2b060b3f2a3365f0b | Python | 5,433 | 159 | """
HierarchicalEventClassifier_noace
@ 2024 Knowblesse
Similar to `HierarchicalEventClassifier`.
But in this script, I manually remove some neurons from the dataset to test the predictiveness of the model.
"""
import numpy as np
from numpy.random import default_rng
from pathlib import Path
import sklearn
from sklearn.... |
02b89b1c39d1c4e64d884af25b3d04e015f5406f86da435e1f6a424b30b75f8b | Python | 5,434 | 164 | # coding=utf-8
"""
Tests for deepreg/dataset/util.py in
pytest style
"""
import h5py
import numpy as np
import pytest
from testfixtures import TempDirectory
import deepreg.dataset.util as util
def test_sorted_h5_keys():
"""
Test to check a key is returned with one entry
"""
with TempDirectory() as ... |
802e8f64495caaa332e273b0f8b2232d6af326c56ad73bec7a7a866b05fae36e | Python | 5,434 | 161 | import jax
import jax.numpy as jnp
import matplotlib.pyplot as plt
import glob
import sys
import os
import re
import json
plt.rcParams["font.sans-serif"] = ["DejaVu Sans"] # Best available
plt.rcParams["font.family"] = "sans-serif"
plt.rcParams.update({
"font.size": 10,
"axes.titlesize": 10,
"axes.l... |
cc16692906bc34248548698a02642a8da9d38a1b0ab254d30b935af6fb74689d | Python | 5,434 | 151 | #!/usr/bin/env python3
# -*- coding: utf-8 -*-
"""
Performs an operation on a list of images. The supported operations are
listed below.
This script is loading all images in memory, will often crash after a few
hundred images.
Some operations such as multiplication or addition accept float value as
parameters instead... |
8cb38587a7a5991b8f70e46e1e261dbb7c9259ff5cd2880fdbe5dad9d49d3294 | Python | 5,438 | 143 | # -*- coding: utf-8 -*-
# python standard library inputs
import os
import random
# external inputs
import numpy as np
import nibabel as nb
# local inputs
from ..io.get_filename import get_filename
from ..cmap.generate_coordinate_mapping import generate_coordinate_mapping
from ..utils.apply_affine_chunked import appl... |
c67a9247f3bc11293e1fedbc487c2e1b283c50d9aaa0172c989ebbdc73185033 | Python | 5,438 | 143 | import os
from copy import deepcopy
import numpy as np
import argparse
import innvestigate.utils as iutils
from keras.models import Model
from keras.preprocessing import image
from keras.utils import to_categorical
import keras
import tensorflow as tf
from numpy import average, dot, linalg
from utils import *
from lrp ... |
4543da232f33887bfe1c7b7e4f070eb0d6b97c31f87f88237d4c9440baa6dd83 | Python | 5,439 | 155 | """Local endpoint probes validate URLs without blocking remote providers."""
from contextlib import nullcontext
from email.message import Message
from io import BytesIO
from types import SimpleNamespace
from unittest.mock import Mock
from urllib.error import HTTPError, URLError
from urllib.request import HTTPHandler, ... |
c3b618fee5827368547f8df9a3f63a64a02cc6c385f9b036875a18918c120a63 | Python | 5,439 | 150 | # 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, ... |
db5da062c93b3ef17ea9c9af33661768e06116b4bbf5ebc01a0fec3c75e2878c | Python | 5,439 | 145 | import json
import os
from typing import Callable, List, Optional
from torch_geometric.data import (
Data,
InMemoryDataset,
download_url,
extract_zip,
)
from torch_geometric.io import fs
class AirfRANS(InMemoryDataset):
r"""The AirfRANS dataset from the `"AirfRANS: High Fidelity Computational
... |
c42527365ca729ac44e93edc12f139742e281a02cc1ced669ef8426c3f9cf493 | Python | 5,442 | 135 | #!/usr/bin/env python3
# -*- coding: utf-8 -*-
"""
Script to compute fODF lobe-specific metrics derived from a Bingham
distribution fit, as described in [1]. Resulting metrics are fiber density
(FD), fiber spread (FS) and fiber fraction (FF) [2].
The Bingham coefficients volume comes from scil_fodf_to_bingham.
A lobe... |
88726123a9261bf151178090a58881334d1de889f224262634bb9fe7605c47f8 | Python | 5,443 | 170 | # Copyright 2024 BDP Ecosystem Limited. All Rights Reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicab... |
e4ab0ccb11d1285994d44f29a86621f4e02e9402e92e026aa13e0419272a8ddb | Python | 5,443 | 156 | # py imports
import os
import sys
import glob
import time
import numpy as np
import torch
import scipy.ndimage
from argparse import ArgumentParser
# project imports
import networks
import datagenerators
def Dice(vol1, vol2, labels=None, nargout=1):
if labels is None:
labels = np.unique(np.concatenat... |
1c572cc8e62e79102492887a21fbe08fadd77172a4344de58f85a62af0bd0b9e | Python | 5,446 | 146 | from typing import Callable, Optional, Union
import torch
from torch import Tensor
import torch_geometric.typing
from torch_geometric.nn.conv import MessagePassing
from torch_geometric.nn.inits import reset
from torch_geometric.typing import Adj, OptTensor, PairOptTensor, PairTensor
if torch_geometric.typing.WITH_TO... |
Subsets and Splits
No community queries yet
The top public SQL queries from the community will appear here once available.