sha256 stringlengths 64 64 | language stringclasses 28
values | size int32 1 491k | lines int32 1 23.2k | content stringlengths 1 200k |
|---|---|---|---|---|
ec60b2ed10a1121a7ca121b9512809f0b0372b3a0bc88f3c4a2e31131b08c927 | Python | 3,409 | 83 | from pytorch_lightning import Trainer, LightningModule, Callback
from torch.nn.modules.dropout import _DropoutNd
from typing import Any
__all__ = ['StepDropout']
class StepDropout(Callback):
def __init__(
self,
step_size,
base_drop_rate,
gamma=0.,
updat... |
01491447cc49660b9b594c19690bfe090b014646120c6ff2568adc3b1fd003bf | Python | 3,410 | 112 | #!/usr/bin/env python
import os
import subprocess
import plotting.configure_seaborn as cs
import matplotlib.pyplot as plt
import numpy as np
import pandas as pd
import seaborn as sns
sns.set(context='paper', style='ticks', rc=cs.rc_params)
plots_directory = os.path.join(os.path.sep, "calc", os.getenv("USER"),
... |
071b7406622d157eafd40521bd786f685bf24f466d639d4d3588b19f0b99b658 | Python | 3,410 | 129 | import argparse
import os
from collections.abc import Iterator
from datasets import load_dataset
from eir.setup.input_setup_modules.setup_sequence import (
_get_bpe_tokenizer_object,
)
from eir.utils.logging import get_logger
logger = get_logger(name=__name__)
def create_dataset_text_iterator(
dataset_name... |
597a0bd78deab817c9948f172071e296dce85170f9e42cffb1cdfae270b89d4c | Python | 3,410 | 92 | """Load GROQ models using LangChain."""
import os
from getpass import getpass
from langchain_groq import ChatGroq
from chemgraph.utils.logging_config import setup_logger
logger = setup_logger(__name__)
def load_groq_model(
model_name: str,
temperature: float,
api_key: str = None,
prompt: str = None,... |
a7979930787fc652ce4fe6be8b13173798fc7fc81db18b4bb407ec9dd9939df7 | Python | 3,410 | 105 | #############################################################################
### Recursively moves through directories and extracts parameters and the ###
### mean protein amount across core and non-core neurons ###
#############################################################################
### Cop... |
f9f1c738bba32c51597516e9f492507449ae0ed10a2807825a6e1627dcface30 | Python | 3,410 | 117 | import os
from types import SimpleNamespace
from unittest.mock import Mock
os.environ.setdefault("QT_QPA_PLATFORM", "offscreen")
import matplotlib
import numpy as np
import pytest
from PySide6.QtWidgets import QApplication
from musclex.ui.widgets.image_viewer_widget import ImageViewerWidget
# QuadrantFoldingGUI sel... |
104497f4ece9e5703a4292918a6d2321fc0c03428d6e8fc0ab85155abb9f0a36 | Python | 3,411 | 103 | import sys
import os
import time
import numpy as np
import pandas as pd
import matplotlib.pyplot as plt
import torch
import torch.nn as nn
import torch.optim as optim
from torch.nn import functional as F
import random
from sklearn import metrics
from collections import Counter
from captum.attr import (IntegratedGradien... |
50d8029dfcc2c277262fa7b397ea620d48abe4addc49b0bf158bfeba22e2db45 | Python | 3,411 | 80 | import segmentation_models_pytorch as smp
from torch import nn
from collections import OrderedDict
from typing import List, Callable
from pytorch_lightning.core.mixins import HyperparametersMixin
__all__ = ['SmpEncoder']
class ExternBase(nn.Module):
def __init__(self, model_name: str):
super().__init__()... |
cf202c6e3c1b040a63bc91c694fc58990ee165d681abc2e977f6090a4805a235 | Python | 3,412 | 77 | # Copyright 2021 HIP Applied Computer Vision Lab, Division of Medical Image Computing, German Cancer Research Center
# (DKFZ), Heidelberg, Germany
#
# 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... |
25b2e2bbfa8616db2049d46406d8c0821211500060bc00c8ebdcdb76c603bb9e | Python | 3,413 | 112 | from pathlib import Path
import pandas as pd
from tqdm import tqdm
from transformers import RobertaTokenizer, RobertaModel
import torch
import numpy as np
import os
from torch_geometric.data import Data, HeteroData
import ijson
def get_data_dir(server_id):
if server_id == "206":
return Path("/new_temp/fsb... |
8119dffc9802caa01c7083e41bace05cec8f19bd29866e8e6c17f4236bfa68d0 | Python | 3,413 | 98 | import numpy as np
import torch
from ModelCodes.autoencoderModelv2 import *
from ModelCodes.classificationModelv1 import *
import pickle
import os
import tqdm
from sklearn.metrics import roc_curve, auc
import argparse
def parse_arguments():
parser = argparse.ArgumentParser(description="Autoencoder Training Script"... |
a505f015066fc56466dd70dcbf83fe535d32811e7b799f1f6c9ef6566848b5c6 | Python | 3,413 | 80 | # Need to install sprod first
# Need to do module purge so that the R.cpp will work
# Need R/4.0.2
import pandas as pd
import os
import platform
os_type = platform.system()
sprod_path = os.path.abspath(__file__)
denoise_jb = sprod_path.replace('test_examples.py', 'sprod.py')
input_path = sprod_path.replace('test_exam... |
dc79a58b48df81ebb59b014cd370213eb1b6eb380a562b8ba0fb0cb91898baef | Python | 3,413 | 93 | import argparse
import pandas as pd
import numpy as np
from pysnptools.snpreader import Bed, Pheno, SnpData
from fastlmm.association import heritability_spatial_correction
from sklearn.decomposition import PCA
from sklearn.preprocessing import StandardScaler
import os
def run_pca(snp_prefix, out_file, n_components=2):... |
3a8b1688e83a9d12f3f7c2fd27ff545a55f2891b4f582258d128ff10603dd490 | Python | 3,415 | 114 | import torch.nn
from torch.nn.parameter import Parameter
import torch.nn.functional as F
import torch.autograd as autograd
import flair.nn
import torch
import numpy as np
import pdb
import copy
import time
import sys
class EmbedController(flair.nn.Model):
def __init__(
self,
num_actions,
model_structure = N... |
4085dec30269988f01eb76c677e41efe6b2a36b589cb7cb25c94705b394eb295 | Python | 3,415 | 117 | #!/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 os
def parse() -> Namespace:
parser = ArgumentParser(
... |
40cd6cf1e63e8de49d41948cdfe221183fd86b18f2d99d681d5913c8ce045192 | Python | 3,415 | 91 | # Copyright (c) Meta Platforms, Inc. and affiliates. All Rights Reserved
import logging
import numpy as np
import torch
from .masks_ops import mask_iou
try:
from torch_generic_nms import generic_nms as generic_nms_cuda
GENERIC_NMS_AVAILABLE = True
except ImportError:
logging.debug(
"Falling ba... |
a3a591f8f6f5f945e351b240ff03d205e48ac788c73ec547fcc8bf0c537c0249 | Python | 3,416 | 83 | import sys
from torch.utils.data import DataLoader
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.MixerUnetcopy import Rep_UNET_down
#from catalyst.c... |
0d69df8d3ea43b783e780908f91e451fb1f253831981ebf61e0f9b23a092c9f6 | Python | 3,417 | 101 | import torch
from model import GNN_classifier
from preprocess import generate_hetero_graph_loader, generate_homo_graph_loader_only_user
from tqdm import tqdm
import numpy as np
import sys
sys.path.append("..")
from utils.eval import evaluate_on_all_metrics
import argparse
class homo_Trainer:
def __init__(
... |
cdfae7cfdf299cb5e25a4f1a2b9dcb61fb9038559d00e48c6bf621b48780a148 | Python | 3,417 | 86 | import sys
import json
import os
import pandas as pd
import anndata
import time
import numpy as np
from scipy import stats
download_base = os.environ.get("SHMDIR", "/gpfs/bbp.cscs.ch/data/project/proj84/csaba/aibs_10x_mouse_wholebrain/")
write = "/gpfs/bbp.cscs.ch/data/project/proj84/csaba/aibs_10x_mouse_wholebrain/"... |
1e7f54390f15705a4632a3c644e6ecc3bb4c5945730583f6a35102e9c52d31df | Python | 3,418 | 128 |
"""
EEG Preprocessing Pipeline for Cognitive Workload Estimation
This script implements the EEG preprocessing steps used in the study:
"Estimating Cognitive Workload in Robot-Assisted Surgery Using Time and Frequency
Features from EEG Epochs with Random Forest Regression".
Preprocessing steps:
1. Common Average Refe... |
2305105d2e271d45ab7ef87d7712539dce3c57dbcebaba6a0460835a6ed38c00 | Python | 3,418 | 131 | # Copyright (C) CVAT.ai Corporation
#
# SPDX-License-Identifier: MIT
import io
import subprocess
from collections.abc import Generator
from fractions import Fraction
from io import BytesIO
from pathlib import Path
import av
import av.video.reformatter
import librosa
import numpy as np
from PIL import Image
from shar... |
99356a8384b0656ba0bd2b448aed06132bfa1022a9142b900eedd1ec9a5fa677 | Python | 3,418 | 82 | import numpy as np
import pandas as pd
from collections import defaultdict
from tqdm import tqdm
from pingouin import partial_corr
df = pd.read_csv('features_spindles.csv.zip')
df2 = pd.read_excel('ASD-TD(egi-data).xlsx', sheet_name='ASD')
df2 = df2.rename(columns={'病案号':'SID', '性别':'Sex', '年龄':'Age', '精细\n动作':'精细动作... |
a88976d6db4e4bf189c20942aff4ea1acae058788005db72102d33dc0fd7a823 | Python | 3,419 | 116 | _base_ = [
'../_base_/datasets/coco_detection.py',
'../_base_/schedules/schedule_1x.py', '../_base_/default_runtime.py'
]
# model settings
model = dict(
type='FCOS',
backbone=dict(
type='RepLKNet',
large_kernel_sizes=[31,29,27,13],
layers=[2,2,18,2],
channels=[128,256,512... |
facdff7f56d70df9d7666481436deff877f72638df43a3dbb665195fe21c47e6 | Python | 3,419 | 88 | import numpy as np
from dipy.utils.optpkg import optional_package
from scilpy.ml.utils import IMPORT_ERROR_MSG
torch, have_torch, _ = optional_package('torch', trip_msg=IMPORT_ERROR_MSG)
# From https://github.com/tatp22/multidim-positional-encoding
def get_emb(sin_inp):
"""
Gets a base embedding for one di... |
9fab133fdae3531616e4b1cf5780bcc4d295e4026c2962b90f8b5d017a5cb3b6 | Python | 3,421 | 104 | import threading
import time
import os
import warnings
from typing import Any
import pytorch_lightning as pl
__all__ = ['KeepAlive']
def terminate_program(log_fn=None):
from ..mpi.mpi import has_mpi, MPI
import signal
log_fn = log_fn or print
if 'SLURM_JOB_ID' in os.environ:
try:
... |
d2da8c2a8952922b5d731b9e8c587452965fcdda1e945b1fe2aaca2a15b0c6e1 | Python | 3,421 | 83 | import numpy as np
from monai import transforms
class ZScoreNormalisation(object):
'''
Calculate the z-score normalisation of the input image in a batch, i.e. (x-mean)/std.
'''
def __init__(self):
self.eps = 1e-8
def __call__(self, sample):
mean = sample.mean()
st... |
1fb582b640433fdfbbcd1c7dc8ab8de7746e9eefbd526f8321e0c36f8633cf28 | Python | 3,422 | 99 | # /------------------------------------------------------------------------------+
# | 19-JUL-2022 |
# | Copyright (c) Bone Imaging Laboratory |
# | All rights reserved ... |
cb9a0108d51edd48b68a2c8663aae7cc61084f4d774dc678ecc2eabbfd749a03 | Python | 3,422 | 115 | import numpy as np
def rectangle(
timestep: float,
amplitude: float,
start_gap: float,
pulse_width: float,
interpulse_gap: float,
frequency: float,
biphasic: bool = False,
):
"""Rectangular pulse."""
if timestep > 1.0 / (10.0 * frequency):
raise ValueError(
"The... |
7f6eb06152ec8e14ac8af5cce2e3d919fa1d8c971d333e959dc0df1392297298 | Python | 3,423 | 110 | '''
O2H3
'''
import numpy as np
import sys
def intro():
print("""
SHORT List of potential energy surfaces for O2H3:
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... |
85a23fbecbc404c85e7b9d9f541a19f43ec2caf868204be9e51a46f34a1b253d | Python | 3,424 | 88 | #New:
from __future__ import print_function, absolute_import
import os.path as osp
import glob
import re
from ..utils.data import BaseImageDataset
class Brain(BaseImageDataset):
"""
Market1501
Reference:
Zheng et al. Scalable Person Re-identification: A Benchmark. ICCV 2015.
URL: http://www.liang... |
21bb8623ce079d7fa4ffa9522c8e25985be2ffb3a2a40fcf9dc19af24026e4bd | Python | 3,425 | 69 | import numpy as np
from sklearn.metrics.pairwise import euclidean_distances
from .nbfr import generate_grid, radial_basis_function
class Neuron:
''' Neuron class; multiple neuron objects within an FOV comprise an experiment. Each neuron possesses several parameters (n_modes, mode_centers, mode_widths, etc)
that tog... |
2cfe09a8ea7723fca671fba5df464b27a6d6d2cfdf1b2337478e0a84bdca112a | Python | 3,425 | 91 | # Copyright (C) CVAT.ai Corporation
#
# SPDX-License-Identifier: MIT
"""Aggregate what was annotated across a project: object counts per label and
per object type for every task, printed and written to a CSV report.
Steps:
1. Retrieve the project and its label names.
2. Walk the project's tasks and read each task... |
6fa830eaac6ae53ac34af9db553f810f1f148a3e2c25d27b5a21e7a15408cb1d | Python | 3,425 | 98 | #!/usr/bin/env python3
# -*- coding: utf-8 -*-
"""
This script extracts streamlines depending on their U-shapeness.
This script is a replica of Trackvis method.
When ufactor is close to:
* 0 it defines straight streamlines
* 1 it defines U-fibers
* -1 it defines S-fibers
"""
import argparse
import json
import loggi... |
954c4f410a380e7f3a64a734726ddaed8ffb386c5ad65ebe70181df7efa9fe97 | Python | 3,425 | 98 | import os.path as op
import dipy.core.gradients as dpg
import dipy.data as dpd
import nibabel as nib
import nibabel.tmpdirs as nbtmp
import numpy as np
import numpy.testing as npt
from dipy.core.geometry import vector_norm
from dipy.io.gradients import read_bvals_bvecs
import AFQ.utils.models as ut
from AFQ._fixes im... |
af4714043e65c04407251bb1127e64754fab7bdc68819740eae373297e71b833 | Python | 3,425 | 63 | import numpy as np
from pytest import approx
from brainscore_core.supported_data_standards.brainio.assemblies import NeuroidAssembly, DataAssembly
from brainscore_vision import load_metric
from .metric import RDM
class TestCharacterization:
def test_alignment(self):
assembly = NeuroidAssembly([[1, 2], [1... |
c86e2817dcb047a9ffd44aa2a28ca1be7624233e5ef5daf053c992f075296f10 | Python | 3,425 | 100 | import torch
from torch import nn
from torch.nn import functional as F
from torch.nn import init
from .pooling import build_pooling_layer
class ViT(nn.Module):
def __init__(self, depth=0, pretrained=True, cut_at_pooling=False,
num_features=0, new_in_channels=7, norm=False, dropout=0, num_classes... |
f933c5a96dfd037bf7d2b8ab1008c5092cd87b2d84d05bef2546269c180718e7 | Python | 3,425 | 108 | """Utilities for preprocessing images with antspynet skullstripping."""
import ants
import antspynet
import numpy as np
def rescale_intensity(
image: ants.ANTsImage,
dst_min: float = 0.0,
dst_max: float = 255.0,
f_low: float = 0.0,
f_high: float = 0.999,
) -> ants.ANTsImage:
"""Rescales voxel... |
95d0dfe55d2b0e2d4017e20c6af7b07f74398900c4b51dda264a3e57be22e3c3 | Python | 3,428 | 180 | r"""
Set the color palette for plotting.
Reference
---------
https://github.com/scverse/scanpy/blob/master/scanpy/plotting/palettes.py
"""
from matplotlib import cm, colors
# Colorblindness adjusted vega_10
# See https://github.com/scverse/scanpy/issues/387
vega_10 = list(map(colors.to_hex, cm.tab10.colors))
vega_10... |
b45161e15bc6ffb6fd1d4ae8c2a8d0c0b36fc89b8930b73abed5d80e60683068 | Python | 3,428 | 111 | import brainpy as bp
import brainpy.math as bm
import numpy as np
import jax
import seaborn as sns
import matplotlib.pyplot as plt
from cann import CANN1D
import scipy
from scipy.stats import ttest_ind
#set default ramndom seed for reproducibility
np.random.seed(0)
#set backend to cpu
bm.set_platform('cpu')
cann = CAN... |
e707982c9fb214ee6eb3e21b34b87cafc59661162635683a350ca16c1c15bf83 | Python | 3,428 | 72 | # -*- coding: utf-8 -*-
"""This sub-package provides routines for volumetric image processing in parallel
This part of the *ClearMap* toolbox is designed in a modular way to allow for
fast and flexible extension and addition of specific image processing
algorithms.
The toolbox part consists of two parts:
* `Vol... |
47db99bcc2e4bde42652729833b5f8b2a7a26afd1b6695ee188ade6261cd8b45 | Python | 3,429 | 99 | # Copyright (c) Facebook, Inc. and its affiliates.
#
# This source code is licensed under the MIT license found in the
# LICENSE file in the root directory of this source tree.
from dataclasses import dataclass
import math
from omegaconf import II
import torch
from fairseq import modules, utils
from fairseq.logging i... |
1ec323f8ec6a785b7c880da92bd97d6b61d04a925d74af0410a9cfb705385cd2 | Python | 3,430 | 83 | 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.Mix... |
3bd6771a9cbee9e20f7fd4b2255dd937fea21b684959da4dd81e00fd0f761de2 | Python | 3,431 | 80 | import unittest
import numpy as np
from numpy.testing import assert_array_almost_equal
import os, sys
sys.path.append(os.path.abspath(os.path.join(os.path.dirname(__file__), "../../")))
from heig.wgs.pvalue import saddle, _handle_invalid_pvalues, liu, liu_mod, saddle2
class Test_saddle(unittest.TestCase):
def te... |
71374483d9b93c6b569addf5ee64f8837debfe54afb7c1832bee939de8e5f977 | Python | 3,431 | 106 | #############################################################################
### Recursively moves through directories and extracts parameters and the ###
### mean protein amount across core and non-core neurons ###
#############################################################################
### Cop... |
129b86189ddacdc611fc65aaa63c138f2cbc616108097908d8a5bb6b3304db7f | Python | 3,432 | 132 | import torch.optim as optim
from attentive import AttentiveMod
from gat import GATMod
from gin import GINMod
from mpnn import MPNNMod
def configure_optimizer(trial, model):
optimizer_name = trial.suggest_categorical(
'optimizer', [
'Adam', 'AdamW', 'RAdam'])
weight_decay... |
4388a2e990311d4204e8c39c314e16ec240bb2ae11fa96128a9b49aa36c6b45a | Python | 3,432 | 101 | # -*- coding: utf-8 -*-
# python standard library inputs
import os
# external inputs
import numpy as np
import nibabel as nb
from nipype.interfaces.ants import N4BiasFieldCorrection
from scipy.signal import argrelextrema
from scipy.ndimage.morphology import binary_fill_holes
def skullstrip_flash(file_in, path_outpu... |
76aca8e4888b5d015d61eb97a75634fa466ea9066db1ea778168f2966273d7a0 | Python | 3,432 | 77 | import unittest
import os
import sys
directory_path = os.path.abspath(os.path.join('../src/'))
if directory_path not in sys.path:
sys.path.append(directory_path)
from utils import get_contig_lengths_dict
from read_process import incorporate_replaced_pos_info,incorporate_insertions_and_deletions,\
get_positions_fr... |
73f75f9e569ffda47bb6edf2b07dff9c11835d818390fbe0f4215577296e9572 | Python | 3,433 | 101 | from functools import cached_property
from typing import ClassVar
from argclz import argument
from neuralib.scanbox.core import SBXInfo
from neuralib.suite2p import Suite2PResult
from neuralib.util.utils import uglob
from neuralib.util.verbose import fprint
from .cli_core import CommonOptions
__all__ = ['SBXOptions']... |
faca137b8b36f585c479d7a399f05e6a4c3bd597ef7bcd847ea07c2a661470b6 | Python | 3,433 | 95 | #############################################################################
# Copyright (C) 2020-2026 MEmilio
#
# Authors:
#
# Contact: Martin J. Kuehn <Martin.Kuehn@DLR.de>
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may... |
53233c748848200ba3226c4eccd11b1a346e3c549d1fb2997c368bb42b906d5c | Python | 3,434 | 102 | # Copyright (C) CVAT.ai Corporation
#
# SPDX-License-Identifier: MIT
import argparse
import math
import time
import traceback
from collections.abc import Callable, Iterable
from django.core.management.base import BaseCommand, CommandError
from ..models import Task
def parse_task_ids(value: str) -> list[int]:
t... |
1bdfb654a93954b1d4dda5bd55bbc710ff10418322d7e430e3c35081a8130570 | Python | 3,435 | 94 | import torch
import torch.nn as nn
import torch.nn.functional as F
import skimage.io as skio
import numpy as np
import config
def get_dice(pred, organ_target):
'''
Tversky loss
:param pred: (B, C, 32, 256, 256)
:param organ_target: (B, C, 32, 256, 256)
'''
# the organ_target should be one-hot c... |
b58934970b9f051e9aa2baceb03b937e0b7a2a9298e2b0439ceab88e036c00e1 | Python | 3,436 | 124 | import torch
import albumentations as A
from albumentations.pytorch import ToTensorV2
from tqdm import tqdm
import torch.nn as nn
import torch.optim as optim
from model import UNET
from utils import (
load_checkpoint,
save_checkpoint,
get_loaders,
check_accuracy,
save_predictions_as_imgs... |
4c122eb6e11c2f0cbdebba8e789b287218795a8ea5e92c6ac036cf334e52d2a5 | Python | 3,437 | 85 | from deepcardio.neuralop_core.transforms import DataProcessor
from torch_geometric.data import Data
class CustomDataProcessorGINO(DataProcessor):
def __init__(
self,
x_normalizer=None,
input_geom_normalizer=None,
query_normalizer=None,
out_normalizer=None
):
supe... |
7d3856adaa13325d019a29e3a2afbd885676fccd06efa8348a5cd36377fb745d | Python | 3,437 | 76 | import torch
import torch.nn as nn
import torch.optim as optim
import Utiliz
def train_model_context(round, epoch, ni, args, trainloader_cifar100, target_extend, optimizer_input, optimizer_net, contexts, my_extended_model, criterion):
my_extended_model.train()
train_loss = 0
correct = 0
total = ... |
6f92f886db2bbb47148ab101a7c6820722c2bd67469687538eec9fe10f6acc27 | Python | 3,440 | 70 | import os,sys
import numpy as np
from chinn.seq_to_hdf5 import load_bed
from chinn.pair_features import load_pairs_as_dict, plot_dist_distr, generate_data, save_data_to_hdf5, load_data_from_hdf5
from chinn.epigenetic_model import train_estimator
from sklearn.externals import joblib
import argparse
if __name__=='__main... |
d9327789c4a5c737c20ab0e87b7229037f69ccc6732fd3825c962c26c8356250 | Python | 3,440 | 103 | from torch.utils.data import DataLoader
from geoseg.losses import *
from geoseg.datasets.potsdam_dataset import *
from geoseg.models.DCSwin import dcswin_small
from catalyst.contrib.nn import Lookahead
from catalyst import utils
from timm.scheduler.poly_lr import PolyLRScheduler
# training hparam
max_epoch = 30
ignore... |
21e1a229d27cb0f08cdb959720ddcd029795c72a92107d1d5bec8633794a4864 | Python | 3,441 | 65 | # NOTE:
# This is a copy of "parula" from MATLAB. We don't claim any rights to this
# file, but The Mathworks does. Consult them and/or a lawyer if you want to
# use it.
from matplotlib.colors import LinearSegmentedColormap
cm_data = [[0.2081, 0.1663, 0.5292], [0.2116238095, 0.1897809524, 0.5776761905],
[0.21225238... |
6bb553b19b4b51dd6b4d6b80695cf0a4154aeceefb5d70bd6f10950bc882ae65 | Python | 3,441 | 102 | """Run with QT_QPA_PLATFORM=offscreen python -m tools.benchmark_undo."""
from __future__ import annotations
import argparse
import collections
import json
import statistics
import tempfile
import time
from pathlib import Path
from unittest.mock import patch
import numpy as np
from PySide6 import QtCore
from PySide6 ... |
cef1214926e826466158f820ef71c8c677ecd5a8cad3af6757db57deceef4dda | Python | 3,441 | 89 | """Tests for process_spectra.py"""
import numpy as np
import pytest
import torch
from mcmlnet.utils.process_spectra import coeff_of_variation, r_specular
class TestRSpecular:
"""Test cases for the r_specular function."""
def setup_method(self) -> None:
"""Setup method to initialize common variables... |
4092ab7986b565b5466af444ed35d8fc3609d8a997fd18658bece6216dbd9214 | Python | 3,442 | 109 | from pathlib import Path
import tempfile
import numpy as np
from registrator_base import RegistratorBase
from brainles_preprocessing.registration.ANTs.ANTs import ANTsRegistrator
from brainles_preprocessing.registration.niftyreg.niftyreg import NiftyRegRegistrator
from brainles_preprocessing.registration.elastix.elas... |
99467b004fc3e3b9569de4c0864a3edbc97aa42aa030b726805ed503ea093d99 | Python | 3,442 | 93 | import numpy as np
#from scipy import sparse
from scipy.io import loadmat
import sys
import time
import nibabel as nib
import argparse
def argument_parse():
parser=argparse.ArgumentParser()
parser.add_argument('--subjects','-s',action='store', dest='subjlist', required=True)
parser.add_argument('--fileroo... |
b9330aee93eda91b77eeccb9e22709ccac631a0575ae06acd94a7741f0814239 | Python | 3,442 | 91 | # -*- coding: utf-8 -*-
"""
Created on Fri Jun 3 15:56:40 2022
@author: Yoshi
"""
import os
import numpy as np
from PIL import Image,ImageDraw,ImageFont
os.chdir("../map_generators")
from cell_drawer import *
def rfs_mapper(map_output_path,canvas,width,height,cell_locations,scale,radius,color_key,cell_flags,extr... |
cb2e46cb86fefe9c28d08dc5d1a0c9375325d5bd5af4ede9d70432d653af479a | Python | 3,442 | 119 | from __future__ import annotations
from pathlib import Path
from typing import Final
import pytest
from PySide6.QtCore import QByteArray
from PySide6.QtCore import QPoint
from PySide6.QtCore import QSize
from PySide6.QtWidgets import QMessageBox
from pytestqt.qtbot import QtBot
from labelme._app import WINDOW_LAYOUT... |
2649adb5a56cee6ae16a755326cc75758b442192ef1fe960036d56aca90a089d | Python | 3,443 | 74 | from dipy.core.gradients import gradient_table
from dipy.io.gradients import read_bvals_bvecs
from dipy.io.image import load_nifti, save_nifti
from dipy.reconst import mapmri
import numpy as np
# --------------------------------------------------
# 1. Paths
# --------------------------------------------------
fraw = "... |
5027efc1d3490893354f657d3726387fc8c43ed31d5e992711cdf42a2e49ebd8 | Python | 3,445 | 106 | import h5py
import os
import pathlib
import matplotlib.pyplot as plt
import numpy as np
DIR = os.path.dirname(os.path.realpath(__file__))
HOME_DIR = DIR.rsplit('/', 1)[0]
HOME_DIR = HOME_DIR.rsplit('/', 1)[0]
print('> HOME: ', HOME_DIR)
DATA_DIR = HOME_DIR + '/data/'
print('> DATA: ', DATA_DIR)
# %% mkdir
GIF_DIR ... |
5b760acf7c9af0b0f59e599411c20679e8e783a4fec6cc03ec84e5c89bb4ce7d | Python | 3,445 | 91 | #!/usr/bin/env python3
# -*- coding: utf-8 -*-
"""
Tests for select_pca_features and pca_extract with new parameters.
"""
import numpy as np
import pandas as pd
import pytest
from pcafeat.select_pca import select_pca_features
@pytest.fixture
def sample_data():
"""Generate synthetic data where a few PCs are stron... |
fd01ec4c0e932257302a435fc59aa901a776e226769e650e290b96bc50546e13 | Python | 3,445 | 90 | #!/usr/bin/env python3
# -*- coding: utf-8 -*-
"""
Created on Thu Jun 11 15:26:23 2026
@author: stoutjd
"""
# ============================================================================
# augmentation_generator.py
# Drop into MEGnet/prep_inputs/training/ alongside new_train_model_pkl.py
# Env: tensorflow 2.6.2, keras... |
ed1d7776f40cb7e9347013c38af81236159e8b4562fdda09519db1a0fa609d4a | Python | 3,446 | 149 | r"""
This module provides voxel transformations.
.. note::
* All randomness under the hood is controlled with PyTorch.
* All geometric transformations assume input of shape ``(C, D, H, W)``.
"""
from itertools import combinations
import torch
class RandomRotate90:
r"""
Rotate voxels around a random... |
f4252321e09735643f8cc2fae710aae63b50f4836148baff5b99799795cbac45 | Python | 3,446 | 104 | # -*- coding: utf-8 -*-
"""
Created on Fri Apr 7 21:58:30 2023
@author: axthi
"""
import numpy as np
import os
from simnibs import mesh_io, sim_struct, __version__
from simnibs.utils.file_finder import SubjectFiles
from simnibs import localite, brainsight
version = [int(x) for x in __version__.split('.')[:3]]
isSi... |
00733320e4466ac211ffc60c1dc79f0d5e616ca0868e74c4093f6858a87388cf | Python | 3,450 | 122 | #!/usr/bin/env python
"""
RS-232 interface to an ASI tiger controller.
Hazen 05/18
"""
import traceback
import storm_control.sc_hardware.serial.RS232 as RS232
import storm_control.sc_library.hdebug as hdebug
class Tiger(RS232.RS232):
"""
Tiger controller interface class.
"""
def __init__(self, **kwd... |
29b02ce57a34121b435822ebf6634655fca8ff247d4abf68820edb7eec030f31 | Python | 3,450 | 92 | from pathlib import Path
import pandas as pd
from brainscore_core.supported_data_standards.brainio.assemblies import BehavioralAssembly
from brainscore_core.supported_data_standards.brainio.packaging import package_data_assembly
'''
Experiment information
- 4 experimental conditions
- Texturized stimuli 1 --> '... |
3a9657973e83c594e97d8695a93273cb893ffae5f41e6b5175ce6c9c5c34a88a | Python | 3,450 | 96 |
import numpy as np
import matplotlib.pyplot as plt
def load_file(fname):
data = np.load(fname)
dt = 0.1
times = data['times']
idx = np.where(np.diff(times) > 1)[0]
idx_end = np.append(idx, len(times))
idx_strt = np.append(0, idx+1)
atps = []
pyrs = []
print('At time 0, ATP:', dat... |
268df5341a0e3ef4cedaca67890276eb89d79841b439cde09a57e8ff2d5d71c1 | Python | 3,452 | 66 | '''
This file contains functions to produce hdf5 files for training/validation/test.
The validation chroms are 5, 14
The test chromosomes are 4, 7, 8, 11
'''
import os,sys
import argparse
from chinn import variables
from chinn.data_preparation_helper import get_and_save_data, load_pairs
if __name__ == '__main__':
... |
f0d7bf2a1bb43cdf16302e22d77af133563a39d1e8725b7d2c8942c605855215 | Python | 3,452 | 78 | #!/usr/bin/env python3
# -*- coding: utf-8 -*-
import os
import tempfile
from scilpy import SCILPY_HOME
from scilpy.io.fetcher import fetch_data, get_testing_files_dict
# If they already exist, this only takes 5 seconds (check md5sum)
fetch_data(get_testing_files_dict(), keys=['tractometry.zip'])
tmp_dir = tempfile.... |
0a4306b9a5b28013ac7d6094af0cb0ea7f551bd3c0f01f184f14f708675d41bd | Python | 3,453 | 44 | from testsetclass import TestsetClass
class ISO34(TestsetClass):
def __init__(self):
self.weak = 1.0
self.molecules = ['P4', 'P3', 'P2', 'P26', 'P21', 'P28', 'P17', 'E32', 'P10', 'P11', 'E34', 'P29', 'E33', 'P16', 'P20', 'P18', 'P27', 'E5', 'E20', 'E27', 'E18', 'E11', 'P34', 'P33', 'E16', 'E29', '... |
09ce5e4e74d27b723983db469f65478cd5e0ece78de8c5ff8e466adde93d5ed5 | Python | 3,454 | 127 | ######################################################
### Averages early- and late-phase weight matrices ###
######################################################
### Copyright 2019-2022 Jannik Luboeinski
### licensed under Apache-2.0 (http://www.apache.org/licenses/LICENSE-2.0)
### Contact: mail[at]jlubo.net
impor... |
68ed1c810869e6a1aeea6d993aad68c01e978e917ffeb297dc63993c0c5e7bbd | Python | 3,454 | 89 |
import os
import sys
import torch
import random
import logging
import traceback
import numpy as np
class InfiniteDataLoader(torch.utils.data.DataLoader):
def __init__(self, *args, **kwargs):
super().__init__(*args, **kwargs)
self.dataset_iterator = super().__iter__()
def __iter__(self):
... |
89d62476e119a9a73f70b0f5a6908f4e76c54d808a14d427f0d85742caa4b161 | Python | 3,454 | 111 | # Copyright (c) DP Technology.
# Copyright (c) Facebook, Inc. and its affiliates.
#
# This source code is licensed under the MIT license found in the
# LICENSE file in the root directory of this source tree.
from collections import OrderedDict
import torch
from torch.utils.data.dataloader import default_collate
from... |
6eacd0f022d6aae65ebdb05bae719f01f57e9f97ce4dd41ea77b0a2c9f3a47f5 | Python | 3,455 | 85 | from deepcardio.neuralop_core.transforms import DataProcessor
from torch_geometric.data import Data
class CustomDataProcessorGINO(DataProcessor):
def __init__(
self,
a_normalizer=None,
input_geom_normalizer=None,
query_normalizer=None,
out_normalizer=None
):
supe... |
ac4e110d709ca41325f79785f823afa893bde1e3a47068c0fdedb79908965a6a | Python | 3,455 | 90 | # This file was automatically generated by SWIG (http://www.swig.org).
# Version 4.0.2
#
# Do not make changes to this file unless you know what you are doing--modify
# the SWIG interface file instead.
from sys import version_info as _swig_python_version_info
if _swig_python_version_info < (2, 7, 0):
raise Runtime... |
27db0f6a86ea2c10875fa4ed73ea16117238c04210a83c464a0c886de6443d50 | Python | 3,457 | 88 | import argparse
import torch
from torch_sparse import transpose
from torch_geometric.nn import MetaPath2Vec
from ogb.nodeproppred import PygNodePropPredDataset
@torch.no_grad()
def save_embedding(model):
embedding = model('paper').cpu()
torch.save(embedding, 'embedding.pt')
def main():
parser = argpar... |
70a9fb99702f4a9f0c92bd5faa345253e3fc1f8323823b7701fb3d97395d7e49 | Python | 3,457 | 107 | import numpy as np
from scipy import ndimage
def h(pvals):
return 2*(pvals > 0.5).astype(float)
def s(pvals):
return 1-pvals
def g(pvals):
return np.minimum(pvals, s(pvals))
def sinv(tdpvals):
return 1-tdpvals
def sdot(pvals):
return -1
def fdp_hat(pvals, mask):
if np.sum(mask) == 0:
... |
d6e93791d6c5bdc0b3754634b70f464c26e41ce86069ed4e600976110f1ceded | Python | 3,458 | 127 | ######################################################
### Averages early- and late-phase weight matrices ###
######################################################
### Copyright 2019-2022 Jannik Luboeinski
### licensed under Apache-2.0 (http://www.apache.org/licenses/LICENSE-2.0)
### Contact: jannik.lubo[at]gmx.de
i... |
7779f99b371ca24cdbf23f92756f1ec840773da783ae8f0cff2c1a5ec5bb0434 | Python | 3,460 | 119 |
######################################################
## Template script to train a MOFA+ model in Python ##
######################################################
from mofapy2.run.entry_point import entry_point
import pandas as pd
import io
import requests # to download the online data
###############
## Load data... |
85a3654d5bb6915332f172bbb4396f19fd7655d7a84c3e2e742e8c208e3ecdfa | Python | 3,460 | 122 | import torch.nn as nn
import torch_geometric.nn as gnn
from torch_geometric.data import Data
__all__ = ['GNNTracker']
class GNNTracker(nn.Module):
"""Graph neural network node classifier.
based on : https://github.com/pyg-team/pytorch_geometric/blob/master/examples/ogbn_proteins_deepgcn.py
Attributes
----------... |
5c0d24935e9d3b7db29f0978cf07fb0b7bab5474ce1d52de290d1900c2886b1a | Python | 3,461 | 63 | single_agent_prompt = """You are an expert in computational chemistry, using advanced tools to solve complex problems.
Instructions:
1. Extract all relevant inputs from the user's query, such as SMILES strings, molecule names, methods, software, properties, and conditions.
2. If a tool is needed, call it using the cor... |
de92ab1d22512c30d5b18a9c349243c276fbf366f1bce89834b45f11d041839b | Python | 3,461 | 83 | from pathlib import Path
import pytest
from pytest import approx
from brainscore_vision import benchmark_registry
from brainscore_vision.benchmark_helpers.test_helper import StandardizedTests, PrecomputedTests, NumberOfTrialsTests
from brainscore_core.supported_data_standards.brainio import s3
standardized_tests = S... |
0479aeb89911b219b2e2ee458d6b7ee6be23daf0d3d45c4ab54ca4ddff045856 | Python | 3,463 | 85 | from deepcardio.neuralop_core.transforms import DataProcessor
from torch_geometric.data import Data
class CustomDataProcessorGINO(DataProcessor):
def __init__(
self,
a_normalizer=None,
input_geom_normalizer=None,
query_normalizer=None,
out_normalizer=None
):
supe... |
56bb3820ee43fb13332c9fa3f72b6e94c23d3c158afde72e01c40c0618b41f9a | Python | 3,463 | 112 | import brainpy as bp
import brainpy.math as bm
import numpy as np
import jax
import seaborn as sns
import matplotlib.pyplot as plt
from cann import CANN1D
import scipy
from scipy.stats import ttest_ind
#set default ramndom seed for reproducibility
np.random.seed(0)
#set backend to cpu
bm.set_platform('cpu')
cann = CAN... |
f97ab3a5b9972572dc1635f0b1077ec79ae762874b40a928d436d342eb047827 | Python | 3,463 | 85 | import pandas as pd
import numpy as np
import matplotlib.pyplot as plt
import seaborn as sns
from scipy.cluster.hierarchy import dendrogram, linkage
import sys
def get_newick(node, parent_dist, leaf_names, newick='') -> str:
"""
Convert sciply.cluster.hierarchy.to_tree()-output to Newick format.
:param n... |
cbb503b38c900673790e40d3fb7caf661c495929c024bc96d1911e85f7bb1406 | Python | 3,464 | 95 | """Academy Agents integration for ChemGraph.
Public re-exports come in two tiers so the package honours the
``[academy]`` optional-dep contract:
* **Eager** (pure stdlib + pydantic, always importable):
``ChemGraphAgentSpec``, ``ChemGraphCampaign``,
``ChemGraphDaemonConfig``, ``MCPServerSpec``, ``ResourceSpec``,
... |
11c6b9f46ae1d8931d944aa31a9c982e1f440bcd77e3b59f1bff68d892fc4edf | Python | 3,465 | 109 | import torch
from torch.utils.data import DataLoader
from torchvision import transforms
import pytorch_lightning as pl
from pytorch_lightning.loggers.neptune import NeptuneLogger
from pytorch_lightning.callbacks import ModelCheckpoint
from torchmetrics import MetricCollection, AUROC, AveragePrecision
import yaml
imp... |
553eca74d2b390d507ce712dc355d4486173ea25e1fae512b0e21c6902781dbf | Python | 3,465 | 102 | from __future__ import division
import numpy.ma as ma
import numpy as np
import scipy as s
import math
from mofapy2.core.utils import dotd
from mofapy2.core import gpu_utils
# Import manually defined functions
from .variational_nodes import Constant_Variational_Node
class Y_Node(Constant_Variational_Node):
def _... |
754214051fa811f3845c123d3e2aba1c1c56fc3698f4d7edacee7e4435ffed6b | Python | 3,465 | 96 | #!/usr/bin/env python3
# -*- coding: utf-8 -*-
"""
Clean a bundle (inliers/outliers) using hiearchical clustering.
http://archive.ismrm.org/2015/2844.html
If spurious streamlines are dense, it is possible they will not be recognized
as outliers. Manual cleaning may be required to overcome this limitation.
"""
import ... |
156c7fa3dd6f617c9d304e83a665d7efef592490219a816bd9250c4546715b95 | Python | 3,466 | 110 | import pytest
from scilpy.utils.scilpy_bot import (
_make_title, _get_docstring_from_script_path,
_split_first_sentence, _stem_word, _stem_keywords, _stem_text,
_stem_phrase, _highlight_keywords, _get_synonyms,
_extract_keywords_and_phrases, _calculate_score
)
have_nltk = True
@pytest.mark.skipif(no... |
171561ae411514cd9e8c20a1dd25a66ccd739de47d792ede169228af7239c795 | Python | 3,466 | 103 | # -*- coding: utf-8 -*-
"""
Transform time series to target space
In the following script, epi time series in native space are transformed to a
target space using a deformation field. The transformed time series get the
prefix r. Because of heap size limits, the time series is split and the
deformation is applied sepa... |
33657a3dc75afc6aae851479b80628532443269d74c9892298372680934f1332 | Python | 3,466 | 89 | #!/usr/bin/env python3
# StrabismusClassification/scripts/plot_per_label_roc.py
import importlib.util
from pathlib import Path
import numpy as np
import pandas as pd
import matplotlib.pyplot as plt
from sklearn.metrics import roc_curve, roc_auc_score
from sklearn.utils import resample
def load_config(project_root: ... |
b8eedd664669e4800318f9509e08fdbb364c60d99ad7eec40afe3de6b3061c91 | Python | 3,467 | 95 | import numpy as np
import matplotlib.pyplot as plt
def load_file(fname):
data = np.load(fname)
dt = 0.1
times = data['times']
idx = np.where(np.diff(times) > 1)[0]
idx_end = np.append(idx, len(times))
idx_strt = np.append(0, idx+1)
atps = []
pyrs = []
print('At time 0, ATP:', data... |
c24708cbfe1236bfa7649e16df86c65523f59929db8e272f269493e5e7cdcd9c | Python | 3,467 | 58 | #!/usr/bin/env python
# -*- coding: utf-8 -*-
# *************************************************************************** #
# Copyright © 2022, UChicago Argonne, LLC #
# All Rights Reserved #
# Softwar... |
2d822f108863c6e8e8a3cb25b82ddc6e9aa4f950bea665df5a18b440499db880 | Python | 3,468 | 100 | #!/usr/bin/env python3
# -*- coding: utf-8 -*-
"""
Split a label image into multiple images where the name of the output images
is taken from a lookup table (ex: left-lateral-occipital.nii.gz,
right-thalamus.nii.gz, ...). Only the labels included in the lookup table
are extracted.
IMPORTANT: your label image must be o... |
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