sha256 stringlengths 64 64 | language stringclasses 28
values | size int32 1 491k | lines int32 1 23.2k | content stringlengths 1 200k |
|---|---|---|---|---|
141c589f0c01a69ffe1a1d67c5627c03a10350f804950c7513710b747f2f4e5f | Python | 3,624 | 106 | # Copyright (C) CVAT.ai Corporation
#
# SPDX-License-Identifier: MIT
import textwrap
from drf_spectacular.utils import OpenApiResponse, extend_schema, extend_schema_view
from rest_framework import mixins, viewsets
from rest_framework.decorators import action
from rest_framework.permissions import SAFE_METHODS
from re... |
a645bd9a3a544216486d31b86e7dd712310689442107d950200093bfce295f5f | Python | 3,624 | 105 | # Configuration file for the Sphinx documentation builder.
#
# This file only contains a selection of the most common options. For a full
# list see the documentation:
# https://www.sphinx-doc.org/en/master/usage/configuration.html
# -- Path setup --------------------------------------------------------------
import ... |
e3973c9023ec43622a1e738c0e622bf95dab5f92b83ee2e303dce51bbf4a9498 | Python | 3,624 | 98 | import numpy as np
import pandas as pd
import torch
import unittest
from causallib.contrib.hemm import HEMM
from causallib.contrib.hemm.hemm_utilities import genSplits, returnIndices, getMeanandStd
from causallib.contrib.hemm.hemm_outcome_models import genMLPModule, genLinearModule, BalancedNet
from causallib.contrib.... |
ed7969f300257d813246312fc73d0a6255f3c39915584d12c7d35e9b28b92098 | Python | 3,624 | 107 | import os
from nilearn.maskers import NiftiMasker
from nilearn.interfaces.fmriprep import load_confounds
from nilearn.maskers import NiftiLabelsMasker
import sys
import numpy as np
ex_sid = sys.argv[1]
# 1. Resolve input files for the subject ID
# Use environment variable to avoid personal paths; set BIDS_ROOT acco... |
d7210182f07d7efdb95b2b9eb012940437b41865f83608ac2075b6e4d3019255 | Python | 3,625 | 96 | import torch
from batchgeneratorsv2.helpers.scalar_type import RandomScalar, sample_scalar
from batchgeneratorsv2.transforms.base.basic_transform import ImageOnlyTransform
import numpy as np
class BGContrast():
def __init__(self, contrast_range):
self.contrast_range = contrast_range
def sample_contr... |
df2c620ca10a55072d0b48f8e22ce11cecc80ec12e3367e91443b03694008f31 | Python | 3,625 | 100 | from __future__ import annotations
from collections.abc import Callable
from typing import Final
import PIL.Image
import PIL.ImageEnhance
import PIL.ImageStat
from PySide6 import QtWidgets
from PySide6.QtCore import Qt
from PySide6.QtGui import QImage
_NEUTRAL: Final = 100
class BrightnessContrastDialog(QtWidgets.... |
3ef57c6fb1bffa4145f52cf7d8df833dd834fb645f7046515fe20ac701f129c6 | Python | 3,626 | 75 | import json
import os
import numpy as np
import shutil
import skimage.io as skio
def generate_training_data(im_path, lbl_path, crop_save_path, patch_size, overlap=0.5,):
im_save_path = os.path.join(crop_save_path, 'imagesTr')
lbl_save_path = os.path.join(crop_save_path, 'labelsTr')
im = skio.imread(im_path... |
4b401b2c6ec779c8344581554efdefff585cd1bd092c79cc22a4408341381c94 | Python | 3,626 | 67 | # -*- coding: utf-8 -*-
# Form implementation generated from reading ui file 'area_namer.ui'
#
# Created by: PyQt5 UI code generator 5.5.1
#
# WARNING! All changes made in this file will be lost!
from PyQt5 import QtCore, QtGui, QtWidgets
class Ui_area_namer(object):
def setupUi(self, area_namer):
area_... |
e002d8e8cfa25e210e79595d0953f8ea2ea18a8e2fd1dcecd72084be7a7fdc79 | Python | 3,627 | 133 | import numpy as np
MU_A = 0.1 # in cm-1
MU_SP = 9 # in cm-1
N_IN = 1.4
WAVELENGTH = 1064 # in nm
def dcs_g1(
t: float,
adb: float,
mu_a: float = MU_A, # in cm-1
mu_sp: float = MU_SP, # in cm-1
rho: float = 1, # in cm
n_in: float = N_IN,
wavelength: float = WAVELENGTH, # in nm
):
... |
44a889e621c3c3d15e0c864a8f808eb867857bd6058a695e8397b50794d08eb2 | Python | 3,629 | 86 | import torch
from tqdm import tqdm
from dataset_tool import fast_merge
import numpy as np
from transformers import pipeline, T5Tokenizer, T5EncoderModel
import os
user,tweet=fast_merge(dataset="Twibot-20")
user_text=list(user['description'])
tweet_text = [text for text in tweet.text]
pretrained_weights = 't5-small'
... |
b6a933934546fdbee1df78a2d807e220ca1a6d40b4ea0b0f5a5c03afb63a7438 | Python | 3,629 | 139 | import numpy as np
from scipy.constants import epsilon_0 as e0
import impedancefitter as ifit
from impedancefitter.double_shell import eps_cell_double_shell
from impedancefitter.single_shell import eps_cell_single_shell
from impedancefitter.suspensionmodels import bh_eps_model, bhcubic_eps_model, eps_sus_MW
em = 10.0... |
2485d5d6b10a76017575d97b16fbdb2aaa7a149ba6527da7413d6a3ed23266c4 | Python | 3,630 | 97 | """
Script: Prepare Incomplete-Modality Inference Set for nnUNet Segmentation
Description:
This script prepares a validation subset for segmentation experiments under
missing-modality conditions. It performs the following steps:
1. Reads the validation subject IDs from `splits_final.json`. You can use your own list ... |
71a5a89d36322305b3283e0108b79086e8a0a3c0fd547dde4385bb2d9d60b955 | Python | 3,630 | 150 | # Copyright (c) Meta Platforms, Inc. and affiliates. All Rights Reserved
"""
An awesome colormap for really neat visualizations.
Copied from Detectron, and removed gray colors.
"""
import random
import numpy as np
__all__ = ["colormap", "random_color", "random_colors"]
# A list of 25 bright and sharp colors for s... |
fd186e6317b919d9251d5295871297282dec4181443f4c1b6201a769dffe7b9f | Python | 3,630 | 46 | from brainscore_vision import model_registry
from .helpers.helpers import CORnetCommitment, _build_time_mappings
from .model import get_model, TIME_MAPPINGS, get_layers
model_registry['ReAlnet01_ALL'] = lambda: CORnetCommitment(identifier='ReAlnet01_ALL', activations_model=get_model('ReAlnet01_ALL'),
... |
12a740fbb27e296aa6a71a5a183f678148c820664c07b869b8c3e0f088a2952e | Python | 3,631 | 116 | # Copyright (C) CVAT.ai Corporation
#
# SPDX-License-Identifier: MIT
from __future__ import annotations
from collections.abc import Callable
from typing import TYPE_CHECKING, Any, ClassVar, Generic, Protocol, TypeVar
import cvat_sdk.auto_annotation as cvataa
import cvat_sdk.datasets as cvatds
from cvat_sdk import Cl... |
df86f8b7ec5a47bce2cf74a1c42b851ea145eacb32565fdc976e2cde612655ae | Python | 3,631 | 106 | """
Example demonstrating the size-preserving warping functionality.
This example shows how to use the new preserve_cell_sizes parameter
to maintain relative size differences between cells during warping.
"""
from stack_corr.warping import warp_dendrites
# Example usage: Preserve cell sizes (recommended)
def exampl... |
4802735df28d5c0658f743184f8f48e50125f2c936ea1a85e6b693478bb64a76 | Python | 3,633 | 102 | #!/usr/bin/env python
# -*- coding: utf-8 -*-
""" Merge multiple json files into a single one.
Typically used during the tractometry pipeline.
Without option it will simply merge all entries at the top level, the top
level must not have any conflicting keys.
--keep_separate option will add a parent for each file, its... |
4e022f12254db4aaa598aa01561542bc29709cb886db7874fdd31939a3c9c21e | Python | 3,636 | 110 | #!/usr/bin/python
#
## @file
#
# A dialog that enables the user to enter the mosaic settings
# when loading older movies without a corresponding .xml file
# off-line.
#
# Hazen 07/15
#
import sys
from PyQt5 import QtCore, QtGui, QtWidgets
import storm_control.steve.qtdesigner.mosaic_dialog_ui as mosaic_... |
a7b9a648992b8e9e761fdef11bcdbd6d5a926b25520ef0c1b170fabc797d6e46 | Python | 3,636 | 84 | #!/usr/bin/env python
# author: Jannes Spangenberg
# github: https://github.com/JannesSP
# website: https://jannessp.github.io
from argparse import ArgumentDefaultsHelpFormatter, ArgumentParser, Namespace
import pysam
import sys
def parse() -> Namespace:
parser = ArgumentParser(
formatter_class=ArgumentDe... |
e3ccc9c00714fc071103d564319252d3ef5973ed1855a2c526d34200cf1ea789 | Python | 3,637 | 123 | import nibabel as nib
import numpy as np
import pandas as pd
import pytest
from pyment.data import NiftiDataset
def make_mgh(path: str, shape: tuple, value: float = 1.0) -> None:
data = np.full(shape, value, dtype=np.float32)
nib.save(nib.MGHImage(data, affine=np.eye(4)), path)
@pytest.fixture
def images_f... |
c40e6e4b6563f44416832029d56d7e85ff0bf6898732d4cac52f733edc66c4c5 | Python | 3,639 | 88 | import nibabel as nib
from scipy import sparse
import sys
import argparse
import numpy as np
import pickle
def argument_parse(argv):
parser=argparse.ArgumentParser(description='Convert a parcellated chacovol output to NIFTI')
parser.add_argument('--in','-i',action='store',dest='infile',help='input chacov... |
17fecf6df6301f95ceddfdc7478819c9757c23e95a3a2e5fed03bea8581abeaf | Python | 3,640 | 93 | import torch
import torch.utils
import torch.utils.data
import torchvision
import torchvision.transforms as transforms
import glob
import os
# CIFAR10 train
mean_cifar10_train = [x / 255 for x in [125.30691805, 122.95039414, 113.86538318]]
std_cifar10_train = [x / 255 for x in [62.99321928, 62.08870764, 66.70489964]]
... |
1e714313cc85729f2d14d79fb093b232d47607c8eba9bdfc84e0d9c2b76302cd | Python | 3,641 | 110 | # This file is part of Mooney computational modeling project.
#
# Mooney computational modeling project is free software: you can redistribute it and/or modify
# it under the terms of the GNU General Public License as published by
# the Free Software Foundation, either version 3 of the License, or
# (at your option) an... |
7d4f63b79454bcac6a81d4dca859491af380af8a42cc26c6a894d23fa37786f6 | Python | 3,641 | 99 | """
All algorithms from the original skyline implementation are included below.
"""
import numpy as np
import scipy
from scipy.stats import t as scipy_stats_t
import statsmodels.api as sm
import traceback
def tail_avg(timeseries, debug, debug_path):
"""
This is a utility function used to calculate the averag... |
41659b48e2d40bd8089014b67085f7ab630cbde418d197946fd8759e80443213 | Python | 3,642 | 134 | """Example entry point for the Waven analysis pipeline.
Run the GUI:
python example.py
Run the batch RF pipeline:
python example.py --run
Create wavelets/Gabor libraries explicitly:
python example.py --run --create-gabor --wavelets --model
"""
from __future__ import annotations
import argparse
import os... |
4f5637797153d14b0dc6b47ff438c0869b982702ff4b0d932d6507bbe4a8f91d | Python | 3,642 | 118 | """
Module to define general nodes in a Bayesian network
All nodes have two main attributes:
- dim: dimensionality of the node
- markov_blanket: the markov blanket of the node
"""
import scipy as s
import numpy as np
class Node(object):
"""General class for a node in a Bayesian network
PARAMETERS
----... |
8e137763d90bea928faeb083f1b65111419b6a5319a681c3343d1ac8ab72066b | Python | 3,642 | 118 | # 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
import torch.nn as nn
import torch.nn.functional as F
from typing import Type
class MLPBlock(nn.Module):
... |
2d9905a926cf09fc8ee40ad24cabc55272f0f15a8ea245f9ba3569a2b3d6a36b | Python | 3,643 | 11 | # setup global variable for HVG251 model
#
#
batch_size = 64
#
CSV_HEADER=['1500002C15Rik', '2610044O15Rik8', 'AA467197', 'AW112010', 'AY036118', 'Acp5', 'Actb', 'Actg1', 'Adgre1', 'Aif1', 'Apoe', 'Apol7c', 'Areg', 'Arfgef1', 'Atf3', 'Atox1', 'Bcl2a1b', 'Bhlhe40', 'Birc5', 'Bmp2', 'Bst2', 'C3', 'C3ar1', 'C5ar1', 'C7300... |
5eaba7e38cbf6d7181791784d3c1b42ca204fa8c1cb2d29faf5f8627bc37673e | Python | 3,643 | 113 | import os, sys
import numpy as np
import scipy.ndimage
def gen_s2s(gen, batch_size=1):
while True:
X = next(gen)
fixed = X[0]
moving = X[1]
# Downsample input for deep supervision
fix_down_2 = scipy.ndimage.interpolation.zoom(fixed, (1,0.... |
ad85e7a112d48ac43bff6a576876b7c1f070e8e1a11d05b2103fcdecb44fdd80 | Python | 3,643 | 95 | import numpy as np
import torch
import torch.nn.functional as F
import torch.nn as nn
from torch import Tensor
from .soft_ce import SoftCrossEntropyLoss
from .joint_loss import JointLoss
from .dice import DiceLoss
class EdgeLoss(nn.Module):
def __init__(self, ignore_index=255, edge_factor=1.0):
super(Edge... |
11ec2cd0459de06e643664874c3a06b375e0ccbd012823694489393cdab2c7a7 | Python | 3,645 | 85 | import csv
# Function to read data from the excel file in a specific format
def get_kymo(input_file_name, head_distances={}):
kymo = {}
with open(input_file_name, 'r') as file:
csvreader = csv.reader(file)
index = -1
for row in csvreader:
if index == -1:
for... |
99feb3bb16246c84aebb63ce8e72ec6fceea49d49e08bcb98a36ac594afe786b | Python | 3,646 | 115 | '''
HOBr
'''
import numpy as np
import sys
def intro():
print("""
SHORT List of potential energy surfaces for HOBr:
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... |
304c90b33d098e95eb03a97b8b64d83a2af56b7ee2568c1759be6ffeb1cb02e1 | Python | 3,648 | 139 | """
Random Forest Regression with 10-Fold Cross-Validation
and Statistical Significance Testing
This script evaluates EEG-based cognitive workload estimation using
Random Forest Regression with 10-fold cross-validation, as described in:
"Estimating Cognitive Workload in Robot-Assisted Surgery Using Time and Frequency... |
5f93803c9f9f19a50c72c026be27d0fc89da7b3fe4072066cb66e1472e81bc58 | Python | 3,648 | 101 | #!/usr/bin/env python3
# -*- coding: utf-8 -*-
"""
Compute a binary mask based on a global SF threshold.
The script masks voxels where the maximum SF amplitude is below
either a relative factor or an absolute threshold (or both).
When fODFs are evaluated on a sphere (SF), the amplitude of the lobes
corresponds to the... |
ae11af87d9a0952556057fbadefca1625951b2f79d21c991e046767ce0efdc36 | Python | 3,648 | 102 | #!/usr/bin/env python3
# -*- coding: utf-8 -*-
"""
Wrapper for SyNb0 available in Dipy, to run it on a single subject.
Requires Skull-Strip b0 and t1w images as input, the script will normalize the
t1w's WM to 110, co-register both images, then register it to the appropriate
template, run SyNb0 and then transform the r... |
92e40381879552575e34ad682e9c93a9c128c9a2737fba99d9f4e613862916b7 | Python | 3,649 | 84 | #!/usr/bin/env python
# author: Jannes Spangenberg
# e-mail: jannes.spangenberg@uni-jena.de
# github: https://github.com/JannesSP
# website: https://jannessp.github.io
from argparse import ArgumentDefaultsHelpFormatter, ArgumentParser, Namespace
import pysam
def parse() -> Namespace:
parser = ArgumentParser(
... |
1344f421ce3ca1076f3b2c920a8f0192800c2ba623d4b4b883f2df6906750b6c | Python | 3,651 | 89 | #This program reads in all IF/IV data and creates SAS output.
#No possibility of using the parameter file to select or create subsets
#edit this to calculate IRneg and IRpos same as in MURI
#Also, calculate IFmax and IFhalfmax
import os
print os.getcwd()
#this is subdir for output data, relative to ~sarah
subdir... |
4a702fda22de3390eff86a1afa2303acba60410c25ae3fc595fbffd017c0a828 | Python | 3,651 | 99 | # Configuration file for the Sphinx documentation builder.
#
# This file only contains a selection of the most common options. For a full
# list see the documentation:
# https://www.sphinx-doc.org/en/master/usage/configuration.html
# -- Path setup --------------------------------------------------------------
# If ex... |
6e1a6bcde51964d26aa914f43cc63d704ecc6c183547ea6ae761fea841de63b5 | Python | 3,651 | 113 | """ TanH Scheduler
TanH schedule with warmup, cycle/restarts, noise.
Hacked together by / Copyright 2021 Ross Wightman
"""
import logging
import math
import numpy as np
import torch
from typing import List
from .scheduler import Scheduler
_logger = logging.getLogger(__name__)
class TanhLRScheduler(Scheduler):
... |
e0880954ea83f85df4582ad63fd6819baa02a629ce940792de23ad683608cc14 | Python | 3,651 | 105 | import nibabel as nib
import numpy as np
import numpy.testing as npt
import scipy.ndimage as ndim
from dipy.align.imwarp import DiffeomorphicMap
from dipy.io.stateful_tractogram import Space
from dipy.io.streamline import StatefulTractogram
import AFQ.data.fetch as afd
import AFQ.utils.volume as afv
SHAPE = (40, 40, ... |
00db612d5bfc69697b51b67b39afd8930191408eca34dc9f98f32b92ce379842 | Python | 3,652 | 125 | import glob
import os
import re
from pathlib import Path
import requests
script_dir = os.path.dirname(os.path.abspath(__file__))
def get_parent_path():
"""Get current directory path minus the last folder."""
return os.path.dirname(os.getcwd())
def replace_in_file(path, old, new):
with open(path, 'r', ... |
41e179f3e1d3e881913880edecee9e1822d8316beba9d52a797e3ed4a4e01dcc | Python | 3,653 | 85 | """About ChemGraph page."""
import streamlit as st
from ui.branding import LOGO_IMAGES, first_existing_asset
def render() -> None:
"""Render the About ChemGraph page."""
logo_image = first_existing_asset(LOGO_IMAGES)
if logo_image:
st.image(logo_image, width=320)
st.header("About ChemGra... |
1693d5fd0d7bcfe021f2d9447a0a6e4307e962478882c3e51d4f87064098928f | Python | 3,654 | 84 | # Ultralytics 🚀 AGPL-3.0 License - https://ultralytics.com/license
from __future__ import annotations
from pathlib import Path
from typing import Any
import torch
from ultralytics.utils import LOGGER
def torch2openvino(
model: torch.nn.Module,
im: torch.Tensor | list[torch.Tensor] | tuple[torch.Tensor, .... |
7b785317b8e8986d45139162b15ddb364d791b19c354f16a741b041b3e43bbd2 | Python | 3,654 | 99 | from __future__ import annotations
from collections.abc import Callable
from PySide6 import QtCore
from PySide6 import QtGui
from PySide6 import QtWidgets
from .._utils._qt import new_icon
class EmptyStateWidget(QtWidgets.QWidget):
def __init__(
self,
*,
on_open_image: Callable[[], None... |
ecf1f5f928abdb9f2c71a2dc4e478e56318e9ea8575664f3fd1e21e884cd23af | Python | 3,655 | 77 | import os
import sys
import ultraimport
Cath = ultraimport('../dataset_src/cath_imem_2nd.py','Cath_imem')
# from dataset_src.cath_imem_2nd import Cath_imem as Cath
import os.path as osp
import pathlib
from typing import Any, Sequence
import torch
import torch.nn.functional as F
from tqdm import tqdm
import numpy as ... |
a03cdf1cbbf87cc96e921e5497854a69d2a9cd38402524959892d4475d393ee0 | Python | 3,657 | 90 | import torch
import numpy as np
import config
class Metric():
def __init__(self, reduction = 'mean'):
self.reduciton = reduction
def set_input(self, y_true, y_pred):
'''
:param y_true:
torch.Tensor [b, 32, 256, 256]
:param y_pred:
torch.Te... |
20afcb738903e068c1403e09338c85db8729b7680e9e8e6337153f222cfdaead | Python | 3,659 | 115 | from dataclasses import dataclass
from typing import TYPE_CHECKING, Literal
import torch
from torch import nn
from eir.models.input.array.array_models import al_pre_normalization
from eir.models.input.array.models_locally_connected import LCLModel, LCLModelConfig
from eir.models.layers.projection_layers import get_1d... |
2a0ea650535b006f9c7dff221bb8c14bf79edb7e1f99b511a19d3ba20eef73a3 | Python | 3,659 | 127 | """
Support for parsing phylogenetic tree's in newick format.
TODO: Tree/Edge should be a generic data structure, not newick specific.
"""
from functools import total_ordering
from pyparsing import (
alphas,
CaselessLiteral,
Combine,
delimitedList,
Forward,
nums,
Optional,
QuotedStrin... |
b7b7d07911c8e2a101fe23cb0ba29a054ece33de922fbb650a3f5d003a9f22c9 | Python | 3,659 | 91 | # FetMRQC: Quality control for fetal brain MRI
#
# Copyright 2023 Medical Image Analysis Laboratory (MIAL)
#
#
# 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/lice... |
fd049d620d00ba5ce62eb9caa5bcacca5734384a22d5cb1b456c922e5110e7bc | Python | 3,659 | 109 | from torch_geometric.nn import GCNConv
import torch
import torch.nn as nn
ALPHA = 2.
def uniform_init(params_list):
for param in params_list:
nn.init.uniform_(param)
class Hist(torch.autograd.Function):
@staticmethod
def forward(ctx, c, bin_centers, hist_l, hist_r, n_bins):
ctx.save_for_... |
f2e7cadcc73cfd0d47a4122f9131bdb1ea0f9fc0ba83f0a562bfec6966cec1e6 | Python | 3,660 | 117 | """Compute physicochemical properties using RDKit."""
import pandas as pd
from rdkit import Chem
from rdkit.Chem.Crippen import MolLogP
from rdkit.Chem.Descriptors import MolWt
from rdkit.Chem.FilterCatalog import FilterCatalog, FilterCatalogParams
from rdkit.Chem.QED import qed
from rdkit.Chem.rdMolDescriptors import... |
adec6aa6799aa6c6a4c32b31cdcef5452910fd0447716cd1300273a55cafab4a | Python | 3,661 | 91 | #%% set environment
import numpy as np
import matplotlib.pyplot as plt
from os import makedirs
from os.path import join
from tqdm import tqdm
from skimage import transform
import torch
from segment_anything import sam_model_registry, SamPredictor
import glob
import os
import argparse
def show_mask(mask, ax, random_co... |
fedb053cee63c2e156d138b2218c300241148f688f1b97ce4128375b201cff02 | Python | 3,662 | 124 | # Copyright (C) CVAT.ai Corporation
#
# SPDX-License-Identifier: MIT
import pickle
from copy import deepcopy
from cvat_sdk import models
from deepdiff import DeepDiff
def test_models_do_not_change_input_values():
# Nested containers may be modified during the model input data parsing.
# This can lead to sub... |
1a9aef0d0ed379cfa93d0c34b846f3ffc31a79c278d370eca6449cd1078d3a48 | Python | 3,663 | 90 | from src.wrappers.OsipiBase import OsipiBase
from super_ivim_dc.source.Classsic_ivim_fit import fit_least_squares_lm
import numpy as np
class TCML_TechnionIIT_lsqlm(OsipiBase):
"""
TCML_TechnionIIT_lsqlm fitting algorithm by Angeleene Ang, Moti Freiman and Noam Korngut, TechnionIIT
"""
# I'm thinking ... |
e7c22b7135afc835607d48c456e7215654e43122d66062c5d043a8dc3106c678 | Python | 3,663 | 122 | import torch
from lightning import Fabric
from eir.setup.config import Configs
from eir.utils.logging import get_logger
logger = get_logger(name=__name__)
def setup_accelerator(configs: Configs) -> Fabric:
gc = configs.global_config
original_hardware = gc.accelerator.hardware
if torch.cuda.is_availabl... |
6c7245cad2e457c97e7a02702ef26a93131f336351a3b27e8370f9b6b2af1dc1 | Python | 3,664 | 106 | import nilearn
import nilearn.plotting
import scipy
import nilearn.image
import numpy as np
import pickle
import fire
import matplotlib.colors as colors
import matplotlib.pyplot as plt
task = "category"
base = "../bids_dataset/derivatives"
fmriprep_path = f"{base}/fmriprep/"
nilearn_path = f"{base}/nilearn/"
cmap=["... |
f2668a32325eca1c7057d91277031bf2e04ed0374fb6c18c11c2b80425dca0c9 | Python | 3,665 | 118 | '''
C2O2
'''
import numpy as np
import sys
def intro():
print("""
SHORT List of potential energy surfaces for C2O2:
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... |
acc405e078f7ecdd985f5905e8285fc4cafa7c7cf9b20da93f1a91ef8911c992 | Python | 3,666 | 75 | #!/usr/bin/env python
"""
threshold_search.py · 逐标签网格阈值搜索 (目标 = MCC)
────────────────────────────────────────────────────────
"""
from __future__ import annotations
import argparse, json, numpy as np, torch
from pathlib import Path
from torch.utils.data import DataLoader
from sklearn.metrics import matthews_corrcoef as... |
c5e163e309b2f82daefe705de68da31fcf097a286ff1c4c02243b2572959339b | Python | 3,666 | 95 | import sys
import pandas as pd
import numpy as np
import matplotlib
import matplotlib.pyplot as plt
plt.switch_backend('agg')
import umap
import umap.plot
import seaborn as sns
import os
matplotlib.rcParams['pdf.fonttype'] = 42
matplotlib.rcParams['ps.fonttype'] = 42
matplotlib.rcParams['svg.fonttype'] = 'none'
plt.rc... |
b4de0d5e3d4065af88265ad4d007886e9bcd3506701dab39500a98e2f7a6ca08 | Python | 3,667 | 47 | import matplotlib.pyplot as plt
from src.ionisation import *
if __name__ == "__main__":
"""
Equation for systematic error removal
E_actual (in eV) = 0.397 + 0.731 * E_vert (in eV) for wB97X-D4
Biliverdin | Calculated energies | Energies after systematic error ... |
baf787f4bc8f31ef23d1f692473f1dc89b7a07e079754062664fded60a47147d | Python | 3,667 | 102 | from __future__ import annotations
from ._core import model as _model
def init(weights_path: str = None, input_size: int = 128, ckpt_name: str = "ckpt-*"):
"""
Initialize a model with optional weights restoration from a checkpoint.
Builds and compiles a model with the specified input size. If a valid
... |
e9a387d80717dfbd3fe26b246e010109fb1361fc2d491e5bd3ffdb077bdb2899 | Python | 3,667 | 118 | '''
CH2O2
'''
import numpy as np
import sys
def intro():
print("""
SHORT List of potential energy surfaces for CH2O2:
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 a... |
a6f0a82c098367df8da31442231409a3a2916240331433f004d1fcff6b6e9839 | Python | 3,668 | 124 | from __future__ import annotations
from typing import Final
import pytest
from PySide6.QtCore import Qt
from pytestqt.qtbot import QtBot
from labelme._app import MainWindow
from ..conftest import close_or_pause
from .conftest import select_shape
# 2011_000003.json lays its shapes out roughly as
#
# amber_kite ... |
8940723229ff36396acd2c127efdf1141951278cf7c8b3a5e47beb261e275523 | Python | 3,669 | 118 | '''
CH2O
'''
import numpy as np
import sys
def intro():
print("""
SHORT List of potential energy surfaces for CH2O:
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... |
94ef31ed8bcdd712d6a3d8c484aed1638255761a96d68a1d516df1b6b167088b | Python | 3,669 | 83 | """
(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
... |
1578fca5a92f07afe765fb68bf45f62a21d988ab8a4cf55e3aa83d7b7fdc7b3f | Python | 3,670 | 125 | """Wakeman-Henson: Source Reconstruction."""
from glob import glob
from pathlib import Path
import numpy as np
import matplotlib
matplotlib.use("Agg")
import mne
from osl_dynamics.meeg import parallel, parcellation, rhino, source_recon
from osl_dynamics.utils.filenames import OSLFilenames
# -----------------------... |
63e12a7555d7e484a2c5cbe76a8a13f9bfcaa5aa8f3a9589467e2b9855e3d4c4 | Python | 3,670 | 110 | import os
import anndata
import numpy as np
import pandas as pd
import scanpy as sc
import scipy
import seaborn as sns
MESA_TARGET_RANGE = 100.0
def _require_columns(df, required, name):
missing = [col for col in required if col not in df.columns]
if missing:
raise ValueError(f"{name} is missing re... |
85165c93c578b5854a72efcdd778cb9abdafe535671b666d4eeb0f54f50f2b3e | Python | 3,670 | 88 | """Tests that every surface_generation setting actually reaches the meshing step.
`ultrafine` was documented in config_template.yml and present in DEFAULTS for
several releases while being silently ignored, because nothing carried it from the
config to the meshing subprocess. These tests close that gap: no pymeshlab n... |
3e9fff4a06eb4ac04703741f9a520c0df5f2a7f3763d22d622abaa430637cff0 | Python | 3,672 | 88 | import sys
from torch.utils.data import DataLoader
from geoseg.datasets.segpc import SegPCDataset
from geoseg.models.MixerUnet import reparameterize_model
from geoseg.losses import *
from geoseg.datasets.isic2018_dataset import ISIC_Dataset
from geoseg.models.MixerUnet import ConvMixer_UNET_down
from geoseg.models.Mixe... |
1db81bcad9876ff4b85551654185651dee3b17157778bf8710d80160c6a95bac | Python | 3,673 | 100 | # -*- coding: utf-8 -*-
import logging
import os
import warnings
# Disable tensorflow warnings
with warnings.catch_warnings():
os.environ['TF_CPP_MIN_LOG_LEVEL'] = '3'
warnings.simplefilter("ignore")
from dipy.nn.tf.synb0 import Synb0
import numpy as np
from dipy.align.imaffine import AffineMap
from dipy.... |
71e0fd66600b3cbcaab245670d2658bf0c3b7e8bb29fff552fec37121e873857 | Python | 3,674 | 125 | """Shared helpers for the scripts/smoke/* test scripts.
A tiny PASS/FAIL reporter so every script has the same output shape and
exit code semantics. No external dependencies beyond the stdlib.
"""
from __future__ import annotations
import sys
import time
import traceback
from contextlib import contextmanager
from pa... |
adf99c25c012195089adb14b2e8050a8f0921cf7293838bbedace86ae987a596 | Python | 3,674 | 95 | from dataclasses import replace
from aicsimageio.types import PhysicalPixelSizes
from pytest import fixture
from pytestqt.qtbot import QtBot
from qtpy.QtWidgets import QCheckBox
from brainways.project.brainways_project import BrainwaysProject
from brainways.project.info_classes import SliceInfo
from brainways.ui.util... |
494a7e2f0871a2d2ee78b2ee6007f65b725c80e9d95b13b59e6dac67c1d2b5eb | Python | 3,675 | 24 | import argparse
"""
python src/generate_experiment_files_and_scripts_cmds.py --experiment_names dataset_unified_balanced_speakers_conv_bn_linear_z128 dataset_unified_balanced_speakers_conv_bn_linear_z256 dataset_unified_balanced_speakers_conv_bn_linear_z512 dataset_unified_balanced_speakers_conv_bn_linear_z1024 d... |
d49d3c7abae2881b37ccb71408802ba7a19ed214b72187c7bb9c5fd0809c3b79 | Python | 3,675 | 101 | '''
in this script, I will read into the sam file and the barcode file, and then count the reads number per
barcode
'''
import sys
import matplotlib as mpl
mpl.use('Agg')
import matplotlib.pyplot as plt
from matplotlib.backends.backend_pdf import PdfPages
def samfile_barcode_count(sam_file, barcode_file):
#ge... |
bdf586b026e2e9011315ba1e69d28e3b3d15b661fb051940d9e39ecaa83faf58 | Python | 3,677 | 85 | #!/usr/bin/env python
# author: Jannes Spangenberg
# e-mail: jannes.spangenberg@uni-jena.de
# github: https://github.com/JannesSP
# website: https://jannessp.github.io
from argparse import ArgumentDefaultsHelpFormatter, ArgumentParser, Namespace
import pysam
import sys
def parse() -> Namespace:
parser = ArgumentP... |
d5271929e4444b0fc53198ee0e7051d23ffff6b51a85248aa378e26218ef3e67 | Python | 3,677 | 81 | # HD-BET brain extraction (https://github.com/MIC-DKFZ/HD-BET, Apache-2.0), run through its hd-bet command so that its
# dependencies (nnunetv2, SimpleITK) can live in a separate Python environment.
#
# Isensee F, Schell M, Pflueger I, et al. Automated brain extraction of multisequence MRI using artificial neural... |
352a9a6b7bf4e6b327893e14e6e0182f6a79198a322570c338d55d02f2310afc | Python | 3,678 | 124 | import torch
import torch.nn as nn
import torch.nn.functional as F
class LowRankCrossAttention(nn.Module):
"""
低秩投影的交叉注意力机制
通过分解投影矩阵降低参数复杂度
"""
def __init__(self, dim=1024, heads=8, attn_bottleneck=256):
super().__init__()
self.dim = dim
self.heads = heads
self.att... |
3054aa728ef378b6fddba49e8465bf5c24fe585d73182b3b7acadc71e82cc4c8 | Python | 3,679 | 107 | #!/usr/bin/env python3
# -*- coding: utf-8 -*-
"""
Script to reshape a volume to match the resolution of another
reference volume or to the resolution specified as in argument. The resulting
volume will be centered in world space with respect to the reference volume or
the specified resolution.
This script will pad or... |
435ef6a38fd9e1f4e1d018eb67eb7e0ed40d9b483105d2c3cedc298a6031ea7c | Python | 3,679 | 102 | import onnx
from zigzag.classes.io.onnx.parser import Parser
from zigzag.classes.io.onnx.utils import get_node_input_output_dimension_shapes
from zigzag.classes.workload.layer_node import LayerNode
import logging
logger = logging.getLogger(__name__)
class MatMulParser(Parser):
"""Parses an ONNX MatMul operator... |
ccd9d48136272270a4f23419588da9f75777f2e03c0ab2abbfed07fbe168f609 | Python | 3,679 | 121 | import tkinter as tk
from tkinter import messagebox
import os, argparse
def Input_2D(Spec_dirc,P3_dirc):
text = f"""Format = Pipe
# define the Spectrum path
Spec_dirc = {Spec_dirc}
# path to save the P3 processed spectrum
P3_dirc = {P3_dirc}
# define the network path
Dirc_2D = Path_to_Trained/Probability_2D/US
... |
ab76929c55eb79e98c65ec8107c468c8d0bd6e2961ca3d05b823370d28f6875a | Python | 3,680 | 122 | """
Read COCO-17 pose CSVs into the canonical kinescope DataFrame format.
Compatible with sam3d-video-pose output and any other tool that produces
COCO-17 keypoints in CSV form.
"""
from pathlib import Path
from typing import Union
import numpy as np
import pandas as pd
from kinescope.skeleton import COCO_PART_NAME... |
ad8d0b6154c85732d6fea0b50d554a5d0f00567e81ed240a5e85288c77704a26 | Python | 3,680 | 131 | import random
from tqdm import tqdm
import torch
from torch.utils.data import DataLoader
from models.text_encoder import BertTextEncoder
from models.hdc_mlp import HDCMLPEncoder
from data.oct_dataset import OCTDataset
from loss.la_loss import la_loss
DEVICE = torch.device("cuda" if torch.cuda.is_available() else "cp... |
2be32c697fc2c5c5199ec985b9fbfde9b0a30f771417ae07ae827e64f17d32d2 | Python | 3,681 | 90 | import os
import numpy as np
alg_name = 'node2vec'
parallel_starts = 16
available_gpus = ['0,8', '8,0']
# args dict
args_dict = {'dataset': 'node_vessap_roi3_pb_minRadiusAvg',
'log_dir': '../tensorboard_logs',
'device': 1,
'embedding_dim': 128,
'walk_length': 40,
... |
a0e3906575c5077578c1e1c0f712ed6f31dc440542cba10182695a6208b7d31e | Python | 3,681 | 68 | from nipype import Node, Workflow
from nipype.interfaces import fsl
from nipype.interfaces.base import CommandLineInputSpec, File, TraitedSpec, CommandLine, InputMultiPath
from nipype.interfaces.utility import IdentityInterface
from traits.api import Bool, Str, List
import os
# Usage:
# $0 \
# --t1w <T1w image> ... |
1ef246a4f925ee2e6941c1ddc7ee69c1e3d9e31cdec47c0cb4275b64547cfe93 | Python | 3,683 | 96 | # Copyright (C) 2020-2022 Intel Corporation
#
# SPDX-License-Identifier: MIT
import os
import numpy as np
from model_loader import ModelLoader
class FaceDetectorHandler:
def __init__(self):
base_dir = os.path.abspath(
os.environ.get(
"DETECTOR_MODEL_PATH", "/opt/nuclio/open_mo... |
df6fb9ab7b5c87c19a9cfaef9b40d4046d774ef962e33599f595cd7f805feef0 | Python | 3,683 | 107 | #!/usr/bin/env python
"""
Custom parameter types for illumination.
Hazen 04/17
"""
import ast
import storm_control.sc_library.halExceptions as halExceptions
import storm_control.sc_library.parameters as params
#import storm_control.hal4000.illumination.buttonEditor as buttonEditor
class IlluminationParameterExcep... |
45519e704c452a2483d704c20abec78c5d5c39725cd1d441d74dc918e658126b | Python | 3,684 | 117 | import tensorflow as tf
import keras.backend as K
import numpy as np
class NCC():
"""
local (over window) normalized cross correlation
"""
def __init__(self, win=9, eps=1e-5):
self.win = win
self.eps = eps
def ncc(self, I, J):
# get dimension of volume
# assumes I... |
3fcdcf9ff3608cf5fd179fbea3b33cb61699298184a1806e8e2918fb787fc232 | Python | 3,686 | 95 | from __future__ import annotations
import os
import tempfile
from pathlib import Path
import onnxruntime # noqa: F401 # load DLLs before PySide6 on Windows
from PySide6 import QtCore
from PySide6 import QtGui
from PySide6 import QtWidgets
import labelme
from labelme import __appname__
from labelme import _locale
f... |
9770644998b048b5d4be71218bdae6afbcdb71773d532420f6f8da385d577efe | Python | 3,688 | 96 | #!/usr/bin/env python3
# -*- coding: utf-8 -*-
"""
Script to compute the SH coefficient directly on the raw DWI signal.
"""
import argparse
import logging
from dipy.core.gradients import gradient_table
from dipy.io.gradients import read_bvals_bvecs
import nibabel as nib
import numpy as np
from scilpy.gradients.bvec... |
1246c045452ed435fff3971920dc97db531be7810a32c6079492c6c5ec663359 | Python | 3,689 | 123 | from __future__ import annotations
import functools
from pathlib import Path
import torch
import torch.nn as nn
import torch.nn.functional as F
from torchvision import models
from brainscore_core.supported_data_standards.brainio.s3 import load_weight_file
from brainscore_vision.model_helpers.activations.pytorch impo... |
3f652c0da749b062c64338fafe279350894a38b7d56bc79f61c76f4c3ab438c7 | Python | 3,689 | 94 | from pkg_resources import resource_filename
from tensorflow.keras.models import load_model
from mmsplice.layers import SplineWeight1D
from mmsplice.utils import encodeDNA
from mmsplice.exon_dataloader import SeqSpliter
import numpy as np
_MODELS = ['models/mtsplice'+str(i)+'.h5' for i in range(8)]
_MODELS_DEEP = ['mod... |
60d2a56f16f1f687728d820fd7077dd2c48aafbf00e6f70759f9eb1bf756ec4e | Python | 3,689 | 90 | # Copyright (c) 2022, Kwanhyung Lee, AITRICS. All rights reserved.
#
# Licensed under the MIT License;
# you may not use this file except in compliance with the License.
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT ... |
b64f10afe470b04cce5988be935de95bfa13a62c0accbd933bd51b6c43af3a8e | Python | 3,689 | 94 | from typing import List
import numpy as np
from brainscore_core.supported_data_standards.brainio.assemblies import BehavioralAssembly
from brainscore_core import Metric, Score
# controls how many half-splits are averaged together to get human delta.
HUMAN_SPLITS = 100
class BakerAccuracyDelta(Metric):
def __in... |
2e2cf0113732b8cf4415f499770f0a2ab89963d0d0bfa1deaf6dd24c715b3c70 | Python | 3,690 | 86 | import torch
import torch.nn as nn
import spikingjelly.activation_based.layer as layer
from copy import deepcopy
from spikingjelly.activation_based import neuron, surrogate
import torch.cuda.nvtx as nvtx
from conf import global_settings as conf_set
class Spikingjelly_VGG(nn.Module):
def __init__(self, features, nu... |
6bcbae28aa8ecc23da48a7a4116d78375119192c28cac6c5551313a47cfca0b4 | Python | 3,690 | 111 | # -*- coding: utf-8 -*-
# python standard library inputs
import os
# external inputs
import numpy as np
import nibabel as nb
from nibabel.freesurfer.io import write_geometry
from nighres.surface import levelset_to_mesh
from cortex.polyutils import Surface
# local inputs
from ..io.affine import read_vox2ras_tkr
from ... |
9227f0a741b283606d38cb9c1e51a83e49e543a9bd4933874866328f7c5cd220 | Python | 3,690 | 118 | import math
from typing import TYPE_CHECKING, Literal
import torch
from torch import nn
from eir.models.layers.attention_layers import TransformerBlock
from eir.models.meta.meta_utils import (
al_fusion_modules,
al_input_modules,
al_output_modules,
run_meta_forward,
)
from eir.utils.logging import get... |
bb6db970c19b77f6c6695fbba361fbc7868a3c8f1f1da6332253efe2042bd089 | Python | 3,691 | 110 | import pickle
from typing import Literal
import numpy as np
from matplotlib.axes import Axes
from rich.pretty import pprint
from argclz import as_argument, argument
from neuralib.plot import plot_figure
from neuralib.util.verbose import publish_annotation
from rscvp.statistic._var import VIS_DIR_HEADERS
from rscvp.st... |
16dba63ef2be9ae9295ac5636a48659fa775da6639e36badf4195f22314b51e8 | Python | 3,693 | 116 | #!/usr/bin/env python
class DNA3Bit(object):
"""
Compact 3-bit encoding scheme for sequence data.
"""
@staticmethod
def bits_per_base():
return 3
# TODO: The sam reader needs to be fixed so text files are read as text not binary
str2bindict = {65: 0b100, 67: 0b110, 71: 0b101, 84: 0b01... |
608f65a29d3f3be667e077c0ee3c213d6cd9c4959a49e822ce1cd4089e5fcac8 | Python | 3,693 | 95 | """OCSR graph: read a molecule's structure diagram and return its SMILES.
Reuses the single-agent graph setup, changing only the default tool list and the
default system prompt so the agent is focused on reading structure images. Keeping
the OCSR tools in their own graph, instead of adding them to the single-agent
def... |
2ee166be8e61086c70a619f67dde186135b51e70f867ca56c28bda366fdde127 | Python | 3,694 | 127 | """LangChain ``@tool`` wrappers for XANES/FDMNES functions.
Each tool delegates to the pure-Python implementation in
:mod:`chemgraph.tools.xanes_core`.
"""
from __future__ import annotations
from pathlib import Path
from langchain_core.tools import tool
from chemgraph.schemas.xanes_schema import xanes_input_schema... |
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