sha256 stringlengths 64 64 | language stringclasses 27
values | size int32 1 491k | lines int32 1 21.8k | content stringlengths 1 200k |
|---|---|---|---|---|
91e3bd50d831bcec061abe0d863505f347496e7cd122b0ec8b30850cf6bfb25d | Python | 8,504 | 243 | import os
import numpy as np
import librosa
from glob import glob
import torchaudio
import math
import torchaudio.functional as F
#import disvoice
SAMPLE_RATE= 16000
from scipy import stats
from disvoice.prosody import Prosody
import parselmouth
F0_FORMANT_COUNT = 4 # F1~F4
def get_formants(filena... |
9c3c723c4b49b02430fb7d6849eea30fcc1c89264c99a4de12704af1d8f953a2 | Python | 8,507 | 258 | # Generate explainability plots for each models
import os
import multiprocessing
import tqdm
import torch
import torchvision
import pandas as pd
import polars as pl
import numpy as np
import matplotlib.pyplot as plt
import seaborn as sns
from PIL import Image
from scipy.spatial import distance
from sklearn import m... |
4e995dc749f7d7481475d4d4faef8bab0c1e74a67f769a2db92ec5c2f0d00e7d | Python | 8,509 | 168 | #!/usr/bin/env /mnt/nasapps/development/python/3.7.1/bin/python
import argparse, csv, re
def cellLimits(s):
try:
#print(s)
#print(re.split(seps, s))
situp = []
return(tuple(s.split(',')))
# situp.append(si.split(','))
return situp
except:
raise argpar... |
b44003eda0a66a5daea0860155ea04f4303cf2a3ce7650aefd9f353de91f4918 | Python | 8,510 | 213 | import torch
from torch_geometric.nn import GCNConv
from sklearn.neighbors import kneighbors_graph
import numpy as np
# define the celcomen class
class celcomen(torch.nn.Module):
"""
A k-hop Graph Neural Network model for disentangling inter- and intra-cellular gene regulation, and then leveraging to predict s... |
e62a43030038e90bdbdc16c25373a62246458efb6e99e620ee92ace7e21d77de | Python | 8,512 | 158 | from typing import Set
import itertools
from zigzag.classes.hardware.architecture.core import Core
from zigzag.classes.hardware.architecture.dimension import Dimension
from zigzag.classes.hardware.architecture.memory_hierarchy import MemoryHierarchy
from zigzag.classes.hardware.architecture.operational_array import Op... |
f1d9c7e45fb6c054130a959efd97292b299b5bc9ab2edb2509363c83c827b6d4 | Python | 8,514 | 261 | from inspect import isfunction
import math
import torch
import torch.nn.functional as F
from torch import nn, einsum
from einops import rearrange, repeat
from models.unet.util import checkpoint
def exists(val):
return val is not None
def uniq(arr):
return{el: True for el in arr}.keys()
def default(val, d... |
99605bb15ae8cda7118f657813ae0d658c4b5e3c5ba48d563fc60c8752827a48 | Python | 8,523 | 199 | from typing import Union
from pathlib import Path
import tarfile
import pooch
import os
import numpy as np
import torch
from safetensors.torch import load_file
from .model_snapshot_handling import get_latest_snapshot
from .args_from_yaml import load_args_from_yaml
from .model import TransformerModel, get_embedding_lay... |
c5286b90cd48211ec3d4017b334bd563c546e28c62a84c7c913807d121d89bcc | Python | 8,523 | 236 | import os
import numpy as np
import pandas as pd
import torch
os.environ['CUDA_VISIBLE_DEVICE'] = '5'
import math
from tqdm import tqdm
from torch import nn
from sklearn.metrics import accuracy_score, roc_auc_score, f1_score, precision_score, recall_score
from torch.utils.data import Dataset, DataLoader
from pathlib im... |
9d047dda1674ea4b0fd2ae01f30e8f809b93ee639dca1f575eaa14b2070001ba | Python | 8,525 | 185 | # Ultralytics 🚀 AGPL-3.0 License - https://ultralytics.com/license
"""Shared ReID encoder used by BoT-SORT, Deep OC-SORT, and TrackTrack.
* `.pt` YOLO checkpoints — loaded via `YOLO()`; embeddings are pulled from the second-to-last
layer through the predictor's `embed=[...]` argument (works with classification and Re... |
ad1946c2c2ba411ae7f307321e40193c31ff00f17e714011fb4500a1a9af702f | Python | 8,527 | 213 | import torch
import torch.nn as nn
import nibabel as nib
import numpy as np
from torch.optim import Adam
import os
class SIREN(nn.Module):
def __init__(self, input_dim=3, hidden_dim=256, output_dim=3, num_layers=3):
super().__init__()
self.net = []
self.net.append(nn.Linear(inp... |
a605775331e8fd132ea61806fbcc44945dea27601bdd49ea273c7bd5d30c4441 | Python | 8,531 | 265 | # -*- coding: utf-8 -*-
#
# Connectome-Manipulator documentation build configuration file, created by
# sphinx-quickstart on Fri Jul 12 09:43:51 2024.
#
# This file is execfile()d with the current directory set to its containing dir.
#
# Note that not all possible configuration values are present in this
# autogenerate... |
5188887455deea2f5404c93bf0d15547becb5e76a49b235f821675b72f48aa60 | Python | 8,533 | 280 | import json
import os
import os.path as osp
import ijson
import pandas
from tqdm import tqdm
import numpy as np
from sklearn.cluster import KMeans
from queue import Queue
import random
random.seed(20220401)
def get_tag_features():
key_to_index = json.load(open('data/key_to_index.json'))
vec = np.load('data/ve... |
921e97069f80bf9ce9782c006d90c3e8d6c8ddb99ef2de3e49dd1825bbaa1534 | Python | 8,533 | 214 | import numpy as np
import pandas as pd
import os
import matplotlib.pyplot as plt
from IPython.display import Image
import imageio
from .ism import SeqMatrix, MutGenerator
from .motifs import Motif, align_to_pfm, pfm_to_logo
from . import plot_utils
class Evolution():
def __init__(self,
... |
1bc7491e4760b0cb91e97e04bf4b7dd7b232aea6ca61ea1fac1a30c51b22a843 | Python | 8,535 | 219 | import numpy as np
from sklearn.metrics import (
mean_squared_error, mean_absolute_error, r2_score,
average_precision_score, roc_auc_score, f1_score,
precision_score, recall_score, matthews_corrcoef,
accuracy_score, confusion_matrix, roc_curve, precision_recall_curve, auc
)
def calculate_graph_metri... |
beb7d81e34987da7b1d6e2ed5fb964d5f2b7b5ad4a22239d567ad61977d76ebc | Python | 8,535 | 202 | #!/usr/bin/env python3
"""
Script to compute various metrics derivated from asymmetric ODF.
These metrics include the asymmetric peak directions image, a number of fiber
directions (nufid) map [1], the asymmetry index (ASI) map [2] and an odd-power
map [3].
The asymmetric peak directions image contains peaks per hemi... |
0a1dbb2f2869f3428dcdf5b15228f5b4a19cb53d248e7b68c66485cd59fa29f3 | Python | 8,537 | 254 | """Defines the routes of the ADMET-AI Flask app."""
from uuid import uuid4
from tempfile import NamedTemporaryFile
from flask import (
after_this_request,
jsonify,
render_template,
request,
Response,
send_file,
session,
)
from rdkit import Chem
from admet_ai import __version__
from admet_... |
616aee2c98174b6b7d189c71959f39ad34baceed8de484138be7d0823441c612 | Python | 8,538 | 261 | #!/usr/bin/python
#
## @file
#
# Capture pictures from a (generic) USB camera. This is not used as we typically
# use the Thorlabs cameras instead.
#
# This requires the PIL and numpy libraries as well as VideoCapture.
#
# Hazen 03/12
#
import cv2.cv as cv
import numpy
from PIL import Image
#import pyga... |
92807055e90b4dd7356d52d1228b76317d12a527adf7f0a22c18cbfc5b58214e | Python | 8,539 | 204 | #! /usr/bin/env python
"""Maintainer tool: build the small distributable example dataset.
Crops a full tomogram + segmentation pair down to a small sub-volume that still
contains a useful stretch of two membranes (default IMM+OMM), downcasts to keep
the download small (tomogram -> float16, segmentation -> int8), write... |
ea10db0f8ab8a044d23e1bfb43861612853d1a011a7a3e5aa2256c27a20d3110 | Python | 8,541 | 198 | import csv
import json
import nibabel as nib
from nilearn.plotting import show
from nilearn import surface, datasets, plotting
import numpy as np
import os
from os.path import join as ospj
import pandas as pd
import sys
"""
This script applies nilearn.vol_to_surf to GMprobseg and WMprobseg. This is done for 1 subject ... |
93d3ed1d136c5286c2bf80143b0a68bfed39b3c4fa3b1136de6b2c404decc19f | Python | 8,542 | 224 | from argparse import ArgumentParser
import os
import os.path as osp
import pandas
from tqdm import tqdm
import ijson
import json
from datetime import datetime
import numpy as np
from gensim.models import word2vec
from nltk import tokenize
parser = ArgumentParser()
parser.add_argument('--dataset', type=str, default='Tw... |
0b7dcb494c628fa3651d4ff6c89399c2630f1532cb88600f7b374abc7c5d1324 | Python | 8,546 | 229 | # -*- coding: utf-8 -*-
"""
Contrast-enhanced mean epi
This scripts preprocesses the phase data from an epi time series to get the
phase variance over time and an mean epi magnitude image with enhanced GM/WM
contrast. The following steps are executed:
1. motion correction to magnitude time series
2. unwrap pha... |
8b3a797faf5db2199703295daba632db286d8487b103de9f09e194fa15cc89ea | Python | 8,547 | 251 | """Use Virchow to extract latent features from whole slide images."""
from __future__ import annotations
import argparse
from pathlib import Path
from typing import Callable, List, Optional, Sequence, Tuple, Union
import h5py
import numpy as np
import openslide
import torch
from PIL import Image
from torch.utils.data... |
364aeda1d8753e6641d2f970f3430c36fedc3fc4e5d1ef72ed9481164f20c0b6 | Python | 8,548 | 227 | # -*- coding: utf-8 -*-
"""
EPI <-> EPI
The purpose of the following script is to compute the deformation field for the
registration between different epi time series. The script consists of the
following steps:
1. set output folder structure
2. n4 correction epi
3. clean ana (remove ceiling and normalise)... |
8943cbb2314b125e318921574de4a23211aa2bce22f4ff348daebb83554b909e | Python | 8,548 | 272 | # TODO: should this go in nems.layers directory instead?
# or maybe nems.tools?
import logging
import inspect
import re
log = logging.getLogger(__name__)
class KeywordMissingError(Exception):
"""Raised when a keyword lookup fails."""
def __init__(self, value):
default_message = f'"{value}" not... |
e884d3f3ca4a9ab436a1efd44d03434529e5c125292b851048b4a4fc043fc25b | Python | 8,549 | 167 | #!/usr/bin/env python3
# -*- coding: utf-8 -*-
"""
Created on Mon May 20 15:21:26 2024
@author: rl05
Save cross condition decoding scores into a csv.
For later mixedlm analysis in R for interaction between time window and denotation.
"""
import sys
import os
import os.path as op
import numpy as np
import pandas as ... |
053fa0d27371743ed81cde1a523c99935a233148f98ea73f1c7d052f3aa36848 | Python | 8,553 | 201 | #!/usr/bin/env python
# -*- coding: utf-8 -*-
"""
Cut streamlines using a binary mask or two labels.
--mask: Binary mask. Streamlines outside of the mask will be cut. Three options
are available:
Default: Will cut the streamlines according to the mask. New streamlines
may be generated if the mask is disjoint.... |
44ca03947cb01af812161c4dd9b6b5f518d0cf45caefdce4e430c6ce344c85d0 | Python | 8,555 | 240 | import os
import numpy as np
import torch
from torch_geometric.data import InMemoryDataset, extract_gz, extract_tar
from mlcg.utils import download_url
from mlcg.data import AtomicData
class MaterialsCloudDataset(InMemoryDataset):
"""General base extractor for the MaterialsCloud dataset described in https://doi.... |
be94247b44c13c1b410f7d6528ce84351fcc4b75d1371836ecc07d959fe6a616 | Python | 8,555 | 234 | """
Copyright 1999 Illinois Institute of Technology
Permission is hereby granted, free of charge, to any person obtaining
a copy of this software and associated documentation files (the
"Software"), to deal in the Software without restriction, including
without limitation the rights to use, copy, modify, merge, publis... |
d7f2b3aebaf9406f230cdbec105ba89fefa6a02968b9622f12d5b2394fe1dd39 | Python | 8,557 | 90 | from testsetclass import TestsetClass
class AMINO20x4(TestsetClass):
def __init__(self):
self.weak = 1.0
self.molecules = ['THR_xag', 'GLY_xad', 'TYR_xab', 'GLY_xac', 'MET_xbf', 'GLN_xap', 'THR_xah', 'MET_xbo', 'MET_xag', 'PRO_xaf', 'GLN_xal', 'GLY_xab', 'GLY_xae', 'ILE_xae', 'ILE_xak', 'ASP_xau',... |
9677a6d248280ec4e8a49f75ffee29294c5750a38475b91214f80af6d82440dc | Python | 8,560 | 226 | # @String(visibility="MESSAGE",value="<html><div WIDTH=600>This script tags particles according to skeleton features: It detects maxima on a masked image and clusters detected maxima using features of the mask-derived skeleton. A maxima is considered to be associated to a skeleton feature (junction, tip, etc.) if the d... |
ec83081abb43ae9bb9a461c1d03b82c04d0b838b4fef715d8fb4653fe53897fd | Python | 8,562 | 209 | import math
import torch
import torch.nn as nn
import torch.nn.functional as F
import torchvision.models as models
from torchvision.models import ResNet18_Weights, ResNet34_Weights, ResNet50_Weights, ResNet101_Weights, ResNet152_Weights
class ResNet2D(nn.Module):
def __init__(self, model_type="resnet18", num_class... |
6b1bd1a6304e32e7caa64d55b3b161c85a26307066df1987ac819b44c2cef5d4 | Python | 8,563 | 227 | import os
import yaml
import h5py
import sys
import numpy as np
import matplotlib as mpl
import matplotlib.pyplot as plt
from scipy.stats import kendalltau,pearsonr
pathpath,tempstr = sys.argv[1:]
my_runsets = tempstr.split('___')
print('Comparing %s'%str(my_runsets))
'''
pathpath = 'PATHS/filepaths_carlen.yml'... |
f0b23dac3bfb40a4b8a7dc3f2f8577b176c3f9090affd7a93ac90064ddcb57b9 | Python | 8,564 | 195 | '''
CH5
'''
import numpy as np
import sys
def intro():
print("""
SHORT List of potential energy surfaces for CH5:
P: potential energy, G: Gradient, D: Nonadiabatic coupling vector
This is listed at the end of description to show the availability.
For example: P/G means both potential energy and g... |
914f30853aed1f0b8c979b9ff617738bd958f399bd8133e6baca4617fe4257e6 | Python | 8,565 | 201 | #!/usr/bin/env python3
"""
Binary Model Data Preparation for EEG Artifact Detection
Prepares binary classification datasets for three specialized artifact detection
models using preprocessed EEG data. Each model distinguishes a specific artifact
type from clean EEG signals.
Key Features:
- Three binary models: Eye Mo... |
e4fe6dbe0fd2e7f617b23f520dc7967225a053ec2fbf51710637a4985d10c7e8 | Python | 8,565 | 184 | '''
Preprocessing of brain IVIM data
Requirements:
- ivim
- fsl
- freesurfer
- itk
- itk-elastix
'''
#%%
import numpy as np
import nibabel as nib
import subprocess, os
from nipype.interfaces import fsl
import itk
from ivim.io.base import read_bval, write_bval
from ivim.preproc.base import extract, combine, average
fr... |
ce3bfc0524894a1b4b5df35c92660abe1045b6c19b7102190a602634171e5208 | Python | 8,566 | 219 | """What happens when a suite2p .npy is empty, truncated, or half-written.
An interrupted run, a full disk, or a copy that stopped part-way all leave the
same thing behind: a file at its final name that no longer holds what its name
promises. The failure that motivated this was a batch over a Dropbox share
dying on one... |
24e063fccb8ea0822a2bda909bffc5473c0c8021d0810ea0ddcf2e7c91f1c94f | Python | 8,567 | 216 | # -*- coding: utf-8 -*-
"""
Created on Fri Apr 7 22:58:25 2023
@author: axthi
"""
import re
import os
import logging
import pickle
import shutil
from .preparation import create_cereb_surface, get_central_gm_with_mask, get_center_pos, _relabel_internal_air
from .simulation import run_FEMs, analyse_simus, _create_res... |
2304cbee41bb2f7b8d28dfbfbf177800d0c257a47ee971d89a4c6334baf0b89a | Python | 8,568 | 251 | """
Utilities for working with the local dataset cache.
"""
import os
import logging
import shutil
import tempfile
import json
from urllib.parse import urlparse
from pathlib import Path
from typing import Optional, Tuple, Union, IO, Callable, Dict
from hashlib import sha256
from functools import wraps
import boto3
fr... |
a839a28c9d73d48218ddea7e65d61054cf257de3b430a023b4c250f31f7b2895 | Python | 8,568 | 216 | """Test pipeline Step 1 — spike detection parity with MATLAB.
Run from the repo root::
uv run python python/test_pipeline_step1.py
Downloads example data if not already present (same files the MATLAB test
pipeline uses), runs Python spike detection with the same parameters as the
``OutputData03Mar2026`` MATLAB r... |
ac93a07203489e29128282ec052fe61c27abe297ce157c764e222c4f80df4713 | Python | 8,568 | 295 | """
Stochastic Gates utils
Copied from: https://github.com/runopti/stg
Original authors: Yutaro Yamada https://github.com/runopti
License: MIT
"""
import torch
import torch.nn as nn
import numpy as np
import six
import torch.optim as optim
import collections
import copy
from torch.utils.data import Dataset
from coll... |
2ff0ec0a22bb2aa9df2228636932e7a94b1976486c2262694b1026fcdf29fccd | Python | 8,569 | 203 | #!/usr/bin/env python3
# -*- coding: utf-8 -*-
"""
Compute BundleSeg & supports multi-atlas & multi-parameters. This is similar to
what our previous RecobundlesX (RBx) script could do, but BundleSeg is better
and more efficient.
For a single bundle segmentation, see the lighter version:
>>> scil_tractogram_segment_wit... |
fe19a5bb340a57f49d01352609202b065b6587b5d1d50703a13a478a685080ba | Python | 8,569 | 209 | #!/usr/bin/env python3
# -*- coding: utf-8 -*-
"""
Visualize bundles.
Example usages:
# Visualize streamlines as tubes, each bundle with a different color
>>> scil_viz_bundle path_to_bundles/ --shape tube --random_coloring 1337
# Visualize a tractogram with each streamlines drawn as lines, colored with
# their local... |
e555bb5064b49d011d3ad4e5375294625042b0196e12b1304a208a5bb869f2d6 | Python | 8,572 | 258 | from copy import copy
from typing import Any, Literal
from eir.models.input.array.models_locally_connected import LCLModelConfig
from eir.models.output.array.array_output_modules import (
ArrayOutputModuleConfig,
LCLOutputModelConfig,
)
from eir.models.output.array.output_array_models_cnn import CNNUpscaleMode... |
dab8c1a9d6d259cfc264ffab9aa6774ece73cbd50d9205d876eeb809a1069ecc | Python | 8,582 | 235 | import os
from sacred.utils import apply_backspaces_and_linefeeds
from sacred.observers import FileStorageObserver
from sacred import Experiment
import sys
sys.path.append("..")
from utils import set_global_seed
from torch_geometric.data.batch import Batch
from itertools import chain
from utils.eval import evaluate_on_... |
0c0c2cbd18907dcbf46fa7de28486e7276bccb4073fa1c73ad473d1c51021580 | Python | 8,583 | 216 | # %% ### import modules
from pathlib import Path
import seaborn as sns
import pandas as pd
import bap1b.figures as figures
# %% set path
data_dir = Path(__file__).resolve().parents[1] / "data"
results_dir = Path(__file__).resolve().parents[1] / "results"
# %% Load data
for adjustment in ["adjusted", "unadjusted"]:
... |
a14ae603a11ad784914ce5bd965603132cf8d743470a9f38c3c7b4d506416942 | Python | 8,583 | 276 | # Copyright (C) CVAT.ai Corporation
#
# SPDX-License-Identifier: MIT
from __future__ import annotations
import base64
import json
import os
import shutil
from functools import cached_property
from pathlib import Path
from types import NoneType
from typing import Any, ClassVar
from uuid import UUID, uuid4
import attr... |
8c1f1483277a9e48bd4341709ad7b3db79b36dea8dafdcf88f888f455f9b7a63 | Python | 8,585 | 178 | # Copyright (c) 2022, Kwanhyung Lee. 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 WARRANTI... |
0d6ece9cc7f1273217c2e5b3f25c82c073ea09d216f78d966b569f6d3270a05e | Python | 8,586 | 231 | from ..qt import *
import asyncio
import typing
import numpy
import grpc
import numpy.linalg
from ..config import ObservableDict
from ..thalamus_pb2 import AnalogRequest, AnalogResponse, NodeRequest, NodeSelector
from ..thalamus_pb2_grpc import ThalamusStub
from ..task_controller.util import create_task_with_exc_handli... |
df9253697ce7d0ce4d30ca00370c35fbef86e7af026e8279d49e2131ceb52555 | Python | 8,587 | 201 | import sys
sys.path.append('../..')
from PAINTeR import connectivity # in-house lib used for the RPN-signature
from PAINTeR import plot # in-house lib used for the RPN-signature
from PAINTeR import model # in-house lib used for the RPN-signature
import numpy as np # hi old friend
import pandas as pd
from sklearn.prepr... |
23eb524717d189f219b5b378b75e8b43b296906a2dd360ec10d4160855ce6fb2 | Python | 8,589 | 265 | #!/usr/bin/env python3
"""
screening_scatter_simple.py
Simplified standalone version for generating iGABASnFR screening scatter plots.
No external dependencies beyond standard scientific Python packages.
Usage:
python screening_scatter_simple.py
python screening_scatter_simple.py --data "good-40AP-all-omit_mi... |
067d0543c123b9d0a4ca9fe4ddb5b943e3ea1ef080a73b7d33ac6e60780e8b19 | Python | 8,590 | 258 | #!/usr/bin/env python
"""
Image file writers for various formats.
Hazen 03/17
"""
import copy
import datetime
import struct
import tifffile
import time
from PyQt5 import QtCore
import storm_control.sc_library.halExceptions as halExceptions
import storm_control.sc_library.parameters as params
cl... |
77b1e48d13a1a43f0a1cf9ad1cd178c6f179b24d50834740701147d0af6d486d | Python | 8,590 | 265 | # Copyright (C) CVAT.ai Corporation
#
# SPDX-License-Identifier: MIT
import csv
import json
import os
import random
import sys
from itertools import product
NAME = "webhooks"
def read_rules(name):
rules = []
with open(os.path.join(sys.argv[1], f"{name}.csv")) as f:
reader = csv.DictReader(f)
... |
f82ab86c23eeff16948f05cc0738ab2e0763fd9ebca65828bfa17465f15fbd69 | Python | 8,592 | 173 | import numpy as np
from brainscore_core import Score
from brainscore_vision import load_metric, load_dataset
from brainscore_vision.benchmark_helpers.neural_common import NeuralBenchmark, RSABenchmark
from brainscore_vision.metrics.regression_correlation.metric import (
CrossRegressedCorrelation, dual_ridge_cv_reg... |
2fc0414b3033bc3b20d7b676d8e44527bc3765f5a3d4a9c4bdbfe01a0228323f | Python | 8,593 | 214 | # 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 numpy as np
import torch
from torch import nn
from typing import Any, Optional, Tuple, Type
from .common import L... |
2131176889482f4c769085d8f81ef5bcd97ded45fb97393f35eccd90761b7c31 | Python | 8,594 | 277 | import os
import shutil
import tempfile
from typing import Dict, Optional
from urllib.parse import urljoin, urlparse
import requests
from typing_extensions import Literal
from .config import (
BUSTOOLS_RELEASES_URL,
BUSTOOLS_TARBALL_URL,
COMPILED_DIR,
KALLISTO_RELEASES_URL,
KALLISTO_TARBALL_URL,
... |
6146336cf3abac1c1c29a420eb05dd6854bc50a96300fb220218ed37266da25e | Python | 8,594 | 258 | from copy import copy
from typing import Any, Literal
from eir.models.input.array.models_locally_connected import LCLModelConfig
from eir.models.output.array.array_output_modules import (
ArrayOutputModuleConfig,
LCLOutputModelConfig,
)
from eir.models.output.array.output_array_models_cnn import CNNUpscaleMode... |
f20c92759a8da1cd791564909dd2d827a079d400eb56c70d9fe7bdea878058f0 | Python | 8,594 | 244 | # 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 torch import Tensor, nn
import math
from typing import Tuple, Type
from .common import MLPBlock
clas... |
29fde86ac1e5979db0ba7ee69edf858f9bd612aa306a168aa8157ce0736fd205 | Python | 8,595 | 215 | #!/usr/bin/env python
"""
HAL module for controlling a Tiger controller.
Hazen 05/18
"""
import math
from PyQt5 import QtCore
import storm_control.sc_library.halExceptions as halExceptions
import storm_control.hal4000.halLib.halMessage as halMessage
import storm_control.sc_hardware.baseClasses.amplitudeModule as am... |
38e96a16a5a0dda3cdaf7c3919932b44dc1d1cd00e855ffb741048b8daafa947 | Python | 8,596 | 255 | import numpy as np
import numpy.random as npr
import matplotlib.pyplot as plt
import pickle as pkl
import os
from scipy.io import loadmat, savemat
from math import ceil
def create_hyperparameters(data_path, save_path, *args):
"""
Create/Modify hyperparameters settings for RNN.
Args:
data_path: Directo... |
467e1ae263f7d76fb70b91085b7776b7125a0628678955bf4100bf204504a62c | Python | 8,596 | 177 | # 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 ... |
c3cb5fe38d7bc27dc9d73df004cda019558e9320d0bd789b5092942a48cc7537 | Python | 8,596 | 250 | # Adapted from https://github.com/amarquand/nispat/blob/master/nispat/bayesreg.py
from __future__ import print_function
from __future__ import division
import numpy as np
from scipy import optimize, linalg
from scipy.linalg import LinAlgError
class BLR:
"""Bayesian linear regression
Estimation and pred... |
88473911a6ee98fda0093b1d2f036073de1d5a883c0e247ed16be5728c97f254 | Python | 8,599 | 276 | import json
import shutil
from copy import deepcopy
from dataclasses import asdict, replace
from pathlib import Path
from typing import List, Tuple
from unittest.mock import Mock
import numpy as np
import pytest
import torch
from aicsimageio.types import PhysicalPixelSizes
from brainglobe_atlasapi import BrainGlobeAtl... |
930982543cd87c1c576b34dd998551ded2bb1e70992920c7b2c328d977bbc249 | Python | 8,599 | 218 | from sklearn.cluster import KMeans
from sklearn.mixture import GaussianMixture
from scipy.linalg import eigh, cholesky
from scipy.stats import norm
import numpy as np
import scipy.cluster.hierarchy as hac
from sklearn.metrics import davies_bouldin_score,silhouette_score
from pfcmap.python.utils import cluster_validatio... |
5b48bde2cfd6252d7396184a51b339545da88874a7ecef8910d86fd88df1c1c9 | Python | 8,600 | 209 | # define multi-offset transformer reconstruction network
import torch
import numpy as np
import torch.nn as nn
from torch import Tensor
from utils.utils import *
import torchkbnufft as tkbn
from einops import rearrange
import torch.nn.functional as F
class Attention(nn.Module):
def __init__(self, dim, d... |
399d3b131449cbb9725083199595e4c6beb13f36d0a95b3bce20a030aef34e1f | Python | 8,603 | 69 | from testsetclass import TestsetClass
class HAL59(TestsetClass):
def __init__(self):
self.weak = 1.0
self.molecules = ['30_CF3I-benB', '26_benI-mSHAB', 'MeI_NCH', '20_benBr-acetoneB', 'NH3_F3CI', 'PCH', '21_benI-acetoneB', 'FI_PCH', 'BrBr_OCH2', 'NCH_NIS', 'MeI_FCCH', 'NCH_FCl', 'F3CI', 'PCH_FBr',... |
473e7bed90666ae51b1accbf15b7562d2119eb2cde7c88f16fd7521a1cc01dc2 | Python | 8,605 | 224 | # Ultralytics 🚀 AGPL-3.0 License - https://ultralytics.com/license
from __future__ import annotations
import contextlib
import glob
import os
import shutil
import tempfile
from contextlib import contextmanager
from datetime import datetime
from pathlib import Path
class WorkingDirectory(contextlib.ContextDecorator... |
c23f3e676439a7ad3bae972a6bacbd1c5e1d05bb241df7dd4dff80d3cbd16ff2 | Python | 8,608 | 240 | """Predictor classes.
Predictors generate sets of predictions for a single fold with no cross-validation
or train-test logic.
"""
import abc
from copy import deepcopy
from typing import Union
import pandas as pd
from ..estimation.base_estimator import IndividualOutcomeEstimator
from ..estimation.base_weight import ... |
1424dc30da60cb1d08a0b5a5ff76a3d6c7a7f82cfd66e4bf6424687d028ab789 | Python | 8,613 | 259 | # %%
import os
import glob
import random
from os import listdir, makedirs
from os.path import join, isdir, basename, dirname, isfile
from tqdm import tqdm
import numpy as np
import torch
from torch._dynamo import OptimizedModule
from torch import multiprocessing as mp
import cv2
import torch.nn.functional as F
from mat... |
b5142e0532536417af8c81824d5710fe17aacf4a06280d1d460586414e390b7a | Python | 8,616 | 218 | #!/usr/bin/env python3
"""
Supplementary Information Figures 4 and 5: Single compartment orientation dependence from SpinWalk simulations at 3 T and 9.4 T.
Combined figure (2x3 layout): All simulations across compartments
- Top row: ΔR1 relative changes (%) for extra-axonal, intra-axonal, and myelin compartments
- Bot... |
6e6945ddd26ce55988e046624173355d5bbd3acf91ec02f3960a5e04cb5951c2 | Python | 8,617 | 268 | from __future__ import annotations
import base64
import re
from pathlib import Path
from urllib.parse import urljoin
import requests
import streamlit as st
from bs4 import BeautifulSoup
from htbuilder import HtmlElement, div, ul, li, br, hr, a, p, img, styles
from htbuilder.funcs import rgba, rgb
from htbuilder.units... |
23e8a26137b44f37e9a319313822c5b38d9c55796e756202eb46d64f1979d2b0 | Python | 8,618 | 227 | # %BANNER_BEGIN%
# ---------------------------------------------------------------------
# %COPYRIGHT_BEGIN%
#
# Magic Leap, Inc. ("COMPANY") CONFIDENTIAL
#
# Unpublished Copyright (c) 2020
# Magic Leap, Inc., All Rights Reserved.
#
# NOTICE: All information contained herein is, and remains the property
# of COMPAN... |
3f09a07814fd266925b5146e922eb50e8e01d0f7a23ba847f6183a69e582ed6b | Python | 8,618 | 213 | #! /usr/bin/env python
"""Shared helpers for loading the pipeline config.yml."""
__author__ = "Benjamin Barad"
__email__ = "benjamin.barad@gmail.com"
__license__ = "GPLv3"
import copy
import click
import yaml
# Directory settings that the pipeline joins with filenames by plain string
# concatenation (e.g. work_dir ... |
97d8f852b09a8c21ac8d32ea68e90dd52c40d9449d0188f21e381313bd6cac6d | Python | 8,618 | 264 | from __future__ import annotations
from dataclasses import replace
from typing import TYPE_CHECKING, Callable, Optional
import numpy as np
from PyQt5.QtWidgets import QApplication
from brainways.pipeline.brainways_params import BrainwaysParams
from brainways.pipeline.brainways_pipeline import PipelineStep
from brain... |
83f4e95d17a17bbbfae1facecbbcf6c00d0917208f7b87b530f8b0e199b3a2e8 | Python | 8,621 | 188 | import os
import subprocess
import shutil
import nibabel as nib
import time
import numpy as np
import pandas as pd
from nipype import Node, Workflow
from nipype.interfaces.base import BaseInterface, BaseInterfaceInputSpec, TraitedSpec, File, Directory, traits, CommandLineInputSpec, File, TraitedSpec, CommandLine, Direc... |
df2701b99bbb5626cf2e74349ce15a19a7fc8b6cef59ae15f461686a581f55d1 | Python | 8,621 | 206 | #!/usr/bin/env python
"""
build_pca_basis.py
==================
Build a PCAwarp head-shape basis from your own set of segmented head meshes.
This is the step that comes AFTER the MRIsegmentation pipeline
(https://github.com/harmening/MRIsegmentation). That pipeline segments each
subject into corrected four-tissue bou... |
c5eaa573d63ff7a33da5b53bcf9523e1988e8b99f5eb712f7082f6e3a37b1b90 | Python | 8,622 | 199 | 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 ... |
a6e83e4bc8c6427bb94d1ed30a799def49741e698b792690395b46b74ebbac6c | Python | 8,628 | 248 | """PR 2 regression tests for the single-loader migration (issue #201).
These lock in the behaviors PR 2 promised beyond the endpoint-level route
matrix (which already covers per-endpoint ``prepare`` parity):
- The ordered endpoint registry resolves each family to the right endpoint,
with prefix routes winning over ... |
daf7a3b5ded9f09f16391572edcb1ad9f4325ef4e3dab48934e6228fa168a4ea | Python | 8,629 | 240 | import json
import mmcv
import numpy as np
import os.path as osp
from PIL import Image
from ..builder import PIPELINES
@PIPELINES.register_module()
class LoadKITTICamIntrinsic(object):
"""Load KITTI intrinsic
"""
def __call__(self, results):
"""Call function to load multiple types annotations.
... |
973ba0d0b9ac68f0b47b10c83fb68f9f6b032aad942d73d1648e71123e730de0 | Python | 8,631 | 199 | #!/usr/bin/env python3
# -*- coding: utf-8 -*-
"""
Created on Fri Jun 21 23:15:17 2024
@author: costantino_ai
"""
from brainscore_core import Score
from brainscore_vision.benchmarks import BenchmarkBase
from brainscore_vision.benchmark_helpers.screen import place_on_screen
from brainscore_vision.model_interface import... |
d917d21af67e2b1f1f27094d0ad95fdcdce42e21199a6113ba3de8073b7f2bc5 | Python | 8,631 | 289 | import sys
import typing
import asyncio
import traceback
import threading
import subprocess
import multiprocessing
import multiprocessing.connection
from thalamus.qt import *
from .thread import ThalamusThread
from .config import ObservableDict
from . import thalamus_pb2
from . import thalamus_pb2_grpc
import datacl... |
3da00748685bd1f7a45ba9490349ea6ac73e1e37df6ed745e186f3305a5d3a60 | Python | 8,632 | 246 | """
This script makes behavior plots for the paper, for the single player human task.
"""
import sys
import os
sys.path.insert(0, os.path.dirname(os.path.dirname(os.path.abspath(__file__))))
import matplotlib as mpl
import matplotlib.pyplot as plt
import seaborn as sns
import pandas as pd
from pathlib import Path
fr... |
62e07a46e5908e4d454c16bc962775f1c84d0c2613f01d3b52c1206e15a85d18 | Python | 8,633 | 259 | #!/usr/bin/env python
"""
Image file writers for various formats.
Hazen 03/17
"""
import copy
import datetime
import struct
import tifffile
import time
from PyQt5 import QtCore
import storm_control.sc_library.halExceptions as halExceptions
import storm_control.sc_library.parameters as params
cl... |
31b656082ecea47d3cd30347d70559ee853ce21fe54300eb052d4d5a40da4556 | Python | 8,636 | 238 | """``BoundaryFinder`` against the mini-CCF's 2-D atlas.
The atlas holds two rectangles, each inset from every edge, so every contour
is a closed loop whose corners are computable by hand: a region occupying rows
r0..r1 and columns c0..c1 has its boundary at r0-0.5 .. r1+0.5 by
c0-0.5 .. c1+0.5.
``tests/test_projectio... |
e6e7ef4654f7112cf2b1d0ea52a72b01bac1754f45461e038c008670220d6ce3 | Python | 8,637 | 303 | # The ImpedanceFitter is a package to fit impedance spectra to
#
# equivalent-circuit models using open-source software.
#
# Copyright (C) 2021, 2023 Henning Bathel, henning.bathel2[AT]uni-rostock.de
# Copyright (C) 2021, 2023 Julius Zimmermann,
# julius.zimmermann[AT]uni-r... |
2b21366bf526059098bd5eaef991f8c99a3806d3f2b9974fe562445b538b7ef8 | Python | 8,638 | 237 | """
Implementation of the simple task
"""
import typing
import logging
import datetime
from ..qt import *
from . import task_context
from .widgets import Form, ListAsTabsWidget
from .util import wait_for, wait_for_hold, TaskResult, TaskContextProtocol, CanvasPainterProtocol
from .. import task_controller_pb2
from ..c... |
fa3a504a59212d979ede62a54bdc1e9d1bde44c682e8fc2f697912f03604e18e | Python | 8,638 | 252 | """Use Virchow2 to extract latent features from whole slide images."""
from __future__ import annotations
import argparse
from pathlib import Path
from typing import Callable, List, Optional, Sequence, Tuple, Union
import h5py
import numpy as np
import openslide
import torch
from PIL import Image
from torch.utils.dat... |
1f63a16bd917a5643afe5814ef2ab0c8c39fa0de5a39e7f839e3a20f3f15d2ef | Python | 8,639 | 216 | import copy
import torch
import torch.nn as nn
import torch.optim as optim
import torchvision
from torchvision import datasets, transforms, models
from torch.utils.data import DataLoader, random_split
import timm
from transformers import ViTForImageClassification, ViTFeatureExtractor
import matplotlib.pyplot as plt
imp... |
903ebdcf916e28a0d2b505baa397397c922cda5007452676e40d9c312d511256 | Python | 8,639 | 227 | import pandas as pd
import torch
import numpy as np
import pandas as pd
from glob import glob
from tqdm import tqdm
import os
import random
from torch_geometric.utils import to_undirected, remove_isolated_nodes, remove_self_loops, train_test_split_edges, negative_sampling
import math
# our modified example
def custom_... |
a84b4b78890550b3b298843805c23093b17c7e3abd87b9cb27b46d605fd2f338 | Python | 8,640 | 229 | import os
import glob
import sys
import random
import time
import torch
import numpy as np
import scipy.ndimage
from argparse import ArgumentParser
# project imports
import datagenerators
import networks
import losses
def Dice(vol1, vol2, labels=None, nargout=1):
if labels is None:
labels = np.uniqu... |
e826810ab9a8ac52b76f45d591831ed6742f49a5d9695c6a1cfdd5ee4d11c7f1 | Python | 8,641 | 252 | from datetime import datetime
from typing import Callable, Literal, TypeVar, Generic, ParamSpec, Any
import numpy as np
from scipy.stats import sem
from argclz import AbstractParser, as_argument, try_float_type, argument
from argclz.dispatch import Dispatch, dispatch
from neuralib.plot import plot_figure, plot_peri_o... |
1e95cd8fa5d4d5c794ea1ddcbeff3988ba84cc53eca02ae65b4900f12c767c2d | Python | 8,643 | 243 | # -*- coding: utf-8 -*-
"""
Created on Thu Apr 20 19:12:38 2023
@author: rl05
"""
import numpy as np
import csv
import random
from psychopy import visual, core, data, event
from scansync.meg import MEGTriggerBox
MEG = MEGTriggerBox()
MEG.set_trigger_state(0) # reset trigger state
number_of_blocks = 5
show_photodio... |
aea7718e28f86291a14b7908a601fb00ed26bf91ce27719030d46b16a95e065a | Python | 8,647 | 143 | """ This scripts generates 3 examples of trainig data for joint SR/synthesis between low resolution (LR) and high
resolution (HR) T1 scans. We use here real HR T1 scans.
The synthetic scans are generated by sampling a Gaussian Mixture Model conditioned on label maps, which must
correspond to the real HR scans used as t... |
e72d3343198602a5d65c30254f089816ecdac592e68b4825c1fa06fab3b2296c | Python | 8,648 | 228 | #!/usr/bin/env python
"""
HAL module for controlling a Marzhauser stage.
Hazen 04/17
"""
from PyQt5 import QtCore
import storm_control.hal4000.halLib.halMessage as halMessage
import storm_control.sc_hardware.baseClasses.stageModule as stageModule
import storm_control.sc_hardware.marzhauser.marzhauser as marzhauser
... |
2e7d7eab2d5d759ad3aed4fb05a747f0dbff42d4d7a88ce114887a00c3f662db | Python | 8,652 | 282 | from collections.abc import Sequence
from enum import Enum
from pathlib import Path
from typing import Annotated, Optional, Union, get_args
from unittest.mock import Mock
import pytest
from magicgui import magicgui, register_type, type_map, type_registered, types, widgets
from magicgui.type_map import TypeMap
def t... |
a31830805b1872c669feeac4db2cda6dc38a291a95f26efb80ffafe30a2228b0 | Python | 8,655 | 251 | import json
import random
from collections.abc import Callable, Sequence
from dataclasses import dataclass, field
from pathlib import Path
from typing import Any, Literal
import numpy as np
import pandas as pd
import pytest
from _pytest.fixtures import SubRequest
from tests.setup_tests.setup_modelling_test_data.setup... |
760abb07951365088dfd8676848cc20dd1229c8fedcedf03e9251d28acc7fd82 | Python | 8,658 | 238 | import os
from dataclasses import dataclass
from typing import Optional
import numpy as np
import scipy
from matplotlib import pyplot as plt
from numpy.typing import NDArray
from mc_analysis.simulator.g1_simulator_utils import get_cw_jac_list, get_td_jac
from mc_analysis.utils.absolute_paths import DATA_PATH
from mc_... |
4160d2eb9be64414ea449ea6495f20d5764fa1d10220e6828542fc9f870ebe09 | Python | 8,659 | 266 | """
Batch fitting script for simulated or experimental g1 time series.
This script fits all `.pkl` recordings in a folder (or a single file) using a specified fitting method:
- Time domain (td)
- Continuous wave (cw)
- Speckle contrast optical spectroscopy (scos)
Usage:
python mc_analysis.examples/run_fitting.py... |
a471ebbe5ce8159e8d248e62fa94ec249f352612460fba5a17522d8e65452307 | Python | 8,660 | 265 | # ==============================================================================================================================
# Script used to plot the state-vector traces from a simulation that uses the 'save_as_text_or_binary' [save_result].
# 1) Run the simulation and store the 'V_it_<id>.txt' files in the outpu... |
96c73c51040348067b78f345099e57e7f995194175b89fb3036f784a9a2b2d93 | Python | 8,661 | 317 | """
Main script for generating laminar inferred cortical surfaces using
equidistance, equivolume, and curvature-based linear models
Reference:
Lee H, ..., Huang S, Communications Biology, 2026
Requirements:
- Python 3.11
- FreeSurfer installed and configured
- cortech Python package available (https://github.com/simn... |
aaf6d91384e79365fda3f9ad801c5fcbe60be70f939f41466b9e7ab7b0fd9165 | Python | 8,662 | 217 | import pfp_api_client
from pfp_api_client.pfp.calculators.ase_calculator import ASECalculator
from pfp_api_client.pfp.estimator import Estimator, EstimatorCalcMode, EstimatorMethodType
from ase import Atoms
from ase.io import Trajectory, write
from ase.build import bulk, surface, molecule, add_adsorbate, fcc111
from a... |
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