sha256 stringlengths 64 64 | language stringclasses 28
values | size int32 1 491k | lines int32 1 23.2k | content stringlengths 1 200k |
|---|---|---|---|---|
b9154feb7b75464d0667c49b92105a097210f8eb36d9934f56f34b52a5304010 | Python | 4,878 | 219 | # laminar_rs/__init__.py
"""
Laminar resting-state analysis toolkit (functional API).
Public surface:
- LaminarConfig
- IO utilities
- Connectivity & adjacency builders
- Embedding & diagnostics
- Embedding-space plots and brain maps
- Graph metrics & connectograms
- Statistical models
- Reliability analyses
- Gradien... |
2c2bdc7dd7dd0485621fb60730966c689166ccff89971efa541f899d3ba3623a | Python | 4,881 | 123 | import tensornetwork as tn
from my_tensornetwork import FinitePollmann
import numpy as np
import time
class DMRGPollmann:
def __init__(self, n_qubits):
self.n_qubits = n_qubits
# train1
read_data = self._dataset_Pollmann("train1")
self.h1h2_i_train1 = read_data[0]
... |
49f0bdb3aa0293dae541855b7c1633dde4ae3d4277bb21bfe0db9a026a462a01 | Python | 4,882 | 114 | import numpy as np
from nems.models.base import DataSet
def test_array_input(spectrogram, response, state):
# Array, no samples.
d = DataSet(input=spectrogram)
assert d.inputs == {DataSet.default_input: spectrogram}
assert d.outputs == {}
assert d.targets == {}
d2 = DataSet(input=spectrogram... |
e5d9ccf45afadc50474c1c26364ecfb3ffdf60be1a0897ea51b5a114b0189b42 | Python | 4,882 | 173 | """ Activations
A collection of activations fn and modules with a common interface so that they can
easily be swapped. All have an `inplace` arg even if not used.
Hacked together by / Copyright 2020 Ross Wightman
"""
import torch
from torch import nn as nn
from torch.nn import functional as F
def swish(x, inplace:... |
67c8b064c4549cbb39732759e4d60a319ec34c2e5fab9b2a2b026d5b9ded5e5a | Python | 4,883 | 138 | # Copyright (C) CVAT.ai Corporation
#
# SPDX-License-Identifier: MIT
from collections.abc import Callable
from datetime import timedelta
from typing import Any, Protocol
from django.conf import settings
from django.http import HttpRequest, HttpResponse
from django.utils.functional import SimpleLazyObject
from rest_fr... |
dbc80241ae39d8bb1c0322a19ec0a0d5126c8267d11d03c660efb498f590b1cd | Python | 4,883 | 171 | from mpi4py import MPI
import sys
import __main__
import math
import pandas as pd
import numpy as np
from sklearn.neighbors import NearestNeighbors
import pywt
from scipy.signal import hilbert, hilbert2
def get_coords(index):
coords = pd.DataFrame(index=index)
coords['x'] = index.str.split('x').str.get(0).ma... |
ba1dbbc31903e05da252a5c4ac9fb3e497916bd36f83fb7b411580a7fcb8ceb0 | Python | 4,885 | 162 | from types import SimpleNamespace
import numpy as np
import pytest
from matplotlib.backends.backend_agg import FigureCanvasAgg
from matplotlib.figure import Figure
from napari_dmc_brainmap.registration.registration import RegistrationWidget
from napari_dmc_brainmap.registration.sharpy_track.sharpy_track.model.HelperM... |
e360d1660eba95e7c6fb81c33d3913b908e3a16a53c095e10c2141bea6d5d5ce | Python | 4,885 | 136 | # TODO add typing and docs
from typing import Optional
import os
import itk
from brainles_preprocessing.registration.registrator import Registrator
from brainles_preprocessing.utils import check_and_add_suffix
class ElastixRegistrator(Registrator):
def __init__(
self,
):
pass
def regist... |
44f7dbd456f6068fc95c07d3cb7a810c0aff86c32d96e0828882648a997639b8 | Python | 4,886 | 164 | # -*- coding: utf-8 -*-
"""
Created on Mon Jun 19 15:36:01 2017
@author: goel
"""
import operator as op
from functools import reduce
from os import remove
def readfaidxbed(f):
"""
Reads .faidx file from a genome assembly and returns a BED file consisting
for entire chromosomes
"""
from collections... |
10bc9d32dc14a6b697d90801946b5218375a0c8c7d7c57481204f563d1244cd7 | Python | 4,888 | 148 | #!/usr/bin/env python3
import arbor as A
from arbor import units as U
from argparse import ArgumentParser
import numpy as np
import pandas as pd # You may have to pip install these.
import seaborn as sns # You may have to pip install these.
import matplotlib.pyplot as plt
class TwoCellsWithGapJunction(A.recipe):
... |
6feb99a70a246ae05285a165dd98ccecb14a1520766f59c68f5610d3b4cd518b | Python | 4,888 | 114 | #@LogService log
"""
file: Sholl_Extract_Profile_From_Image_Demo.py
author: Tiago Ferreira
info: Demonstrates how to programmatically obtain a Sholl profile from a
segmented image
"""
from ij import IJ
from sc.fiji.snt.analysis.sholl import (Profile, ShollUtils)
from sc.fiji.snt.analysis.s... |
1a9fd719ec244b8237b8b1d0bd3b1c6ec7f080886f6c1c19cd0a7d4690de00f3 | Python | 4,890 | 129 | """
SwinSite — Protein Binding Site Prediction
Predicts binding pockets using a 4-fold ensemble of 3D Swin Transformers.
Large proteins (>70A span) are automatically handled via multi-grid
surface sampling with C-alpha farthest-point sampling.
Usage:
python predict.py -i <input_dir> -o <output_dir>
python pre... |
8bb814ab53001cc72fd31a24dd0a04de75e1b30b907c922434c66aca167303a1 | Python | 4,890 | 124 | #############################################################################
# Copyright (C) 2020-2026 MEmilio
#
# Authors: Henrik Zunker
#
# Contact: Martin J. Kuehn <Martin.Kuehn@DLR.de>
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the Lice... |
d2755863a342160c882066dc9392b850a8e7c0cbf88ee637bcea0743ab2c93dd | Python | 4,890 | 126 | """Parity test: Python stim detection vs MATLAB detectStimTimes/getStimPatterns.
Ground truth is generated by ``python/test_fixtures/gen_stim_detection_reference.m``
(MATLAB called directly on the two testMEAstim raw recordings). Validates that
the Python port reproduces, per channel:
- the exact stim onset times,
... |
67605f238f77a082b4b1b4a9826cf4784d60fc7e7b1a019f27107cad37b2c2ba | Python | 4,892 | 173 | """
Discover and catalog neural scaling model paths and metadata.
This script scans a base directory for model paths, extracts metadata like
training data ratios, and creates a CSV file with model information for use
by evaluation scripts.
"""
import glob
import os
import re
import pandas as pd
from dotenv import lo... |
7ffd98888eb6bd1113c47a9dd12a361e49faf40d1cc873ca47d0be0b9988ae79 | Python | 4,892 | 115 | ##########################################################################################
### Functions to calculate the quality coefficient Q from the firing rate distribution ###
### during recall of an input-defined cell assembly ###
###############################################... |
c4db72790b12fded97b3d9cf9921fa4e99b6fe11f62b1e77c44e155e76c4133d | Python | 4,893 | 153 | """
DyNeMo: Plotting Networks
=========================
In this tutorial we will plot networks from a DyNeMo model trained on source reconstructed MEG data. This tutorial covers:
1. Load regression spectra
2. PSDs
3. Power maps
4. Coherence networks
5. Coherence maps
"""
#%%
# Download post-hoc spectra
# ^^^^^^^^^^^... |
f5be83de64f0afa714ba334269fed5486a17bdf7c6531a4fc32c13b6c460e9ec | Python | 4,893 | 156 | """MCP client utilities for the ChemGraph CLI.
Handles connecting to MCP servers and loading tools for use with
MCP-enabled workflows (single_agent, multi_agent, etc.).
"""
from __future__ import annotations
import os
import shlex
import time
from typing import List, Optional
from rich.progress import Progress, Spi... |
9ef950bba55fa9b36a25e2e025ffd79223cc68d8c6cc3dab8462d716a79a8cea | Python | 4,894 | 143 | #!/usr/bin/env python3
"""
main.py
-------
Train MoAGNN on custom graphs (.pt) with 5-fold cross-validation.
- Reads folds from data_load.load_5fold_splits (no TU datasets).
- Early stopping on val loss; saves best model per fold.
- NLLLoss (Net outputs log_softmax).
"""
import os
import argparse
import torch
import t... |
fc05cb6401c0706ee9618611bafa54d95f9143a0d473149ab067894b6ee63165 | Python | 4,895 | 157 | import numpy as np
import torch
import matplotlib.pyplot as plt
from scipy import stats
import os
def compute_rmse(predictions, targets):
"""计算RMSE"""
return np.sqrt(np.mean((predictions - targets) ** 2))
def compute_accuracy(predictions, targets):
"""计算准确率"""
return np.mean(predictions ==... |
db17caeb69417911fbb0df30ddb04a4a38e60ebbb5cc6dde5f5f9f98e99af476 | Python | 4,896 | 161 | '''
C6H6O
'''
import numpy as np
import sys
def intro():
print("""
SHORT List of potential energy surfaces for C6H6O:
P: potential energy, G: Gradient, D: Nonadiabatic coupling vector
U: diabatic potential energy matrix
UG: gradient of diabatic potential energy matrix
This is listed at the e... |
2eefe64923a23202a114e7102e9eeab3ab12843589f9134562c4908ca2865963 | Python | 4,898 | 140 | import torch
from torch import Tensor
from typing import Tuple, List, Optional
@torch.jit.script
def _crop3d(img: Tensor, x: int, y: int, z: int, w: int, h: int, d: int) -> Tensor:
"""
torch scriptable function which crops an image
:param img: torch.Tensor image of shape [C, X, Y, Z]
:param x: x coor... |
bd1d6f2443814ee800383539d797bc07557f444d31b96591c87f4cdf5092d5ee | Python | 4,898 | 73 | import argparse
def update_data_args(parser):
parser.add_argument("-g", "--genome", type=str, required=True, help="Genome fasta")
parser.add_argument("-b", "--bigwig", type=str, required=True, help="Bigwig of tn5 insertions. Ensure it is +4/-4 shifted")
parser.add_argument("-p", "--peaks", type=str, requir... |
a6954438813a5fe4eb5363fc5e2a20c2e988a68000c1b06f468ab9319ee4f0b1 | Python | 4,900 | 144 | from pathlib import Path
from typing import Type
import polars as pl
import sqlclz
from argclz import AbstractParser, argument
from argclz.dispatch import Dispatch, dispatch
from rscvp.util.database import RSCDatabase, PhysiologyDB, BaseClassDB, BayesDecodeDB, VisualSFTFDirDB, ResultDB
__all__ = ['DatabaseViewOption... |
bf621f752de0e65c065a6d9bcc3b5f77341c38afbdbe866cd93e241209119ebd | Python | 4,900 | 169 | """
Extracts QA values from perimeter.
"""
import numpy as np
import nibabel as nb
import matplotlib.pyplot as plt
import pandas as pd
import seaborn as sns
import glob
import os
# Set data path
ROOT = '/Users/sebastiandresbach/data/s1Anfunco/Nifti'
# Set subjects to work on
subs = ['sub-05', 'sub-06', 'sub-07', '... |
0a18218e723dda2c59225f0549f3404045c924512514630a20027d374207780d | Python | 4,901 | 133 | import math
from typing import Literal, Final
import polars as pl
from argclz import as_argument, argument
from argclz.dispatch import Dispatch, dispatch
from neuralib.plot import plot_figure
from neuralib.plot.venn import VennDiagram
from neuralib.util.verbose import publish_annotation
from rscvp.statistic.core impo... |
41c9db0881e87bea44b4af85098dce87c894ac727d27f2afa93c2a1e131c968a | Python | 4,902 | 118 | import pandas as pd
from sklearn.preprocessing import OneHotEncoder
from ast import literal_eval
from hashlib import sha256
def load_data_2024_10_10(data_path: str,
ignore_hash: bool = False):
expected_hash = "01d513fe3165bd5eb3ea6a9be52dc54afcf3d7f06cd398c18979653812797d18" # intentiona... |
647b2da6d92529303d32641ca22c6794196a2a6de971919dc10295a69fd005d9 | Python | 4,902 | 128 | #!/usr/bin/env python3
# -*- coding: utf-8 -*-
"""
Created on Sun Jul 16 12:55:01 2023
@author: jstout
"""
import os, os.path as op
import glob
import copy
os.environ["CUDA_DEVICE_ORDER"] = "PCI_BUS_ID" # see issue #152
os.environ["CUDA_VISIBLE_DEVICES"] = ""
from tensorflow import keras
import numpy as np
import p... |
169d6c1d68c6e9659a1842fa850996c93f9ef678c091d30cd227a0dddd87a65c | Python | 4,903 | 149 | # Copyright 2016 Numenta Inc.
#
# Copyright may exist in Contributors' modifications
# and/or contributions to the work.
#
# Use of this source code is governed by the MIT
# license that can be found in the LICENSE file or at
# https://opensource.org/licenses/MIT.
import math
import simplejson as json
from subprocess ... |
5fb001c9968538a2e28a575fdf9fdb9b30ddd884772136b4fc439eb91469d467 | Python | 4,904 | 137 | ## Nhat Duong & J Shapiro
## 2019 - 2020
# Imports in the pep8 order https://www.python.org/dev/peps/pep-0008/#imports
# Standard library
import argparse
import subprocess
import sys
import os
# Related third party
import numpy as np
import pandas as pd
## Define the callers and the extension to give the intermedia... |
cbd76135c8fdc2dfe464a9833784edb5bc5423f61431ae75e83d4cf5ddd79935 | Python | 4,904 | 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 warnings
import torch
import torch.nn as nn
import torch.nn.functional as F
from torchvision.transforms import Nor... |
df7445802fee07a864c1e958fb096e473e209d3b41da7188f6c207b3617023de | Python | 4,904 | 192 | ##################################################################################
### Module : utils.py
### Description : Utility functions
###
###
###
### Written by : scalphunter@gmail.com , 2021/08/31
### Copyrighted reserved by Sentinel Holdings LC
################################################################... |
40b26d0682162c7caf5ea494a033f2f02d9b28151251ebad845e5573cdaa89e6 | Python | 4,905 | 108 | from .survival_utils import canonize_dtypes_and_names
from .standardized_survival import StandardizedSurvival
from causallib.estimation.base_weight import WeightEstimator
import pandas as pd
from typing import Any, Optional
class WeightedStandardizedSurvival(StandardizedSurvival):
def __init__(
self,
... |
319bda3eeed4937b2e6776d5c0bb88e5830cac30ee211c743c36f62e1955a489 | Python | 4,907 | 135 | from typing import Optional, Union, Any
import torch
from torch import Tensor
import torch.nn as nn
if torch.distributed.is_available():
from torch.distributed import ReduceOp
#########################
# From pytorch lightning
def distributed_available() -> bool:
return torch.distributed.is_available() and... |
6f485c8a68569f055b84d582d8654fce1f81a7c1add0bae0fbfe91ba10905807 | Python | 4,907 | 154 | from functools import cached_property
from typing import ClassVar
import numpy as np
from argclz import argument
from stimpyp import (
STIMPY_SOURCE_VERSION,
Session,
PyVlog,
RiglogData,
get_protocol_name, ProtocolAlias, SessionInfo, RigEvent
)
from .cli_core import CommonOptions
__all__ = ['Stim... |
01d3d78edc23608f166786e0936d75f5f445ff227c3d9a050e1c812ce2b9b3a3 | Python | 4,908 | 122 | """Full end-to-end CAT-NAP example run, to inspect what the port produces.
Run from the repo root::
uv run python python/run_catnap_example.py [--out DIR] [--lags 1000 2500]
Uses the gitignored ``local/example2pdataWCellTypes`` dataset and writes a
complete output tree — every per-recording figure, the cell-type... |
3104e6b12a4ad34946964d29fdd0468c09c9b08b62afcd51eefa6001b6de5a3a | Python | 4,908 | 139 | from collections import Counter, OrderedDict
from collections.abc import Iterable
from eir.setup.input_setup_modules.torchtext_port.vocab import Vocab
def vocab(
ordered_dict: dict[str, int],
min_freq: int = 1,
specials: list[str] | None = None,
special_first: bool = True,
) -> Vocab:
"""
Fac... |
800b186d898f9a5b07495c4e5778c6b031c4af1e39b8316f788ae0adc9bfd5b4 | Python | 4,908 | 133 | # -*- coding: utf-8 -*-
import numpy as np
from scilpy.tractanalysis.voxel_boundary_intersection import\
subdivide_streamlines_at_voxel_faces
def mrds_metrics_along_streamlines(sft, mrds_pdds,
metrics, max_theta,
length_weighting):
"""
... |
4b0576ca3fb299db24a5681648413f0cfcc937cfc0cbdd9ceb124cf92775de0c | Python | 4,909 | 94 | import csv
import os
from os.path import join as ospj
from numpy import savetxt
import pandas as pd
import re
import sys
import json
import shutil
"""
This script collates the pyAFQ tract profiles output across subjects in preparation for visualization and fitting GAMs.
Each pyAFQ tract profiles csv should be a 1D arr... |
85cf3a84969d3b305058a171c51977e2595fd4f07453b0c9b91bb3b1b0a7bbed | Python | 4,909 | 123 | # (C) Copyright 2021 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... |
ed7373cecb15f4465b17c98483192bf392ace6a100468938bd5cde9ac1cca771 | Python | 4,909 | 125 | """Repackage per-subject .nc files into Brain-Score S3-ready format.
The only transform is **single-data_var collapse**:
``xr.DataArray.to_netcdf`` (xarray 2022.x) serialises non-dimensional coords
as data_vars, which makes
``brainscore_core.brainio.s3.load_assembly_from_s3`` fail
("Given file dataset contains more th... |
3ff8532b6363e353cb08e31d0bae7fde2bff4b637f09455fec8f291a6a4bdb06 | Python | 4,910 | 109 | import torch
from torch import nn
import torchvision
def get_resnet_backend(
num_classes:int,
p_channels:int,
m_channels:int,
layers:int=18,
with_voneblock:bool=False,
tiny:bool=False
):
"""Returns ResNet18 or ResNet50 backend.
:param num_classes (int): number of clas... |
630a660a542f58d63baab5469016d21581682896e8f067669869e0866271b284 | Python | 4,911 | 107 | import random
import numpy as np
from tqdm import tqdm
from brainscore_core import Score
from brainscore_core.benchmarks import BenchmarkBase
from brainscore_vision import BrainModel, load_stimulus_set, load_metric
from brainscore_vision.metrics.dimensionality import Dimensionality
BIBTEX = """@inproceedings{
... |
0443b71da874dfad231c6a8ab30e9cb795af5165edc96f0e074b65566c4f76e6 | Python | 4,912 | 147 | from __future__ import print_function as _, division as _
import numpy as np
def nonnancount(x):
return (~np.isnan(x)).sum()
#different methods of shuffling
def shuffle_everything(T,shuffles,netsize):
dT = np.diff(T, axis=1)
dT = np.hstack((T.T[:1].T, dT))
dT = np.concatenate([dT[None,...] for _ in ra... |
4b5c6605997ae67e78c6da1b4bff3808d33bfdbcd4e3822141f1a81df1867a0e | Python | 4,912 | 124 | from onnx import ModelProto
from zigzag.classes.io.onnx.default import DefaultNodeParser
from zigzag.classes.io.onnx.gemm import GemmParser
from zigzag.classes.io.onnx.matmul import MatMulParser
from zigzag.classes.io.onnx.conv import ConvParser
from zigzag.classes.io.onnx.utils import (
parse_mapping_from_path,
... |
5330ce29897dd8d379107e2f33e780669544a67755cf8f49f4659da309f4b1d9 | Python | 4,913 | 131 | #!/usr/bin/env python
"""
Voltage controlled Z stage functionality.
Hazen 05/17
George 02/18 - Abstracted from mclVoltageZModule.py
"""
from PyQt5 import QtCore
import numpy as np
import storm_control.hal4000.halLib.halMessage as halMessage
import storm_control.sc_hardware.baseClasses.daqModule as daqModule
import... |
c57eb18d8c8983a8bdb02b7925819524b334c0453b7aa0ffa697b91edbb588a1 | Python | 4,916 | 169 | import logging
import warnings
from typing import List, Sequence
import pytorch_lightning as pl
import rich.syntax
import rich.tree
from omegaconf import DictConfig, OmegaConf
from pytorch_lightning.utilities import rank_zero_only
def get_logger(name=__name__) -> logging.Logger:
"""Initializes multi-GPU-friendly... |
dfc7b7e739de2305d519beaf01b90792f5a01c607b14b9dc81f6d319eacd88aa | Python | 4,917 | 146 | #!/usr/bin/python
# -*- coding: latin-1 -*-
# =============================================================================================
# Librairies importation
import numpy as np
import nrrd
import sys
import re
import os
import nibabel as nib
# ===============================================================... |
f8e137bd9015379337b864e38353200e7b36adbc2f8c3f70bd3c03d4f16ef896 | Python | 4,917 | 158 | #!/usr/bin/env python
# -*- coding: utf-8 -*-
"""
@Author: Yong Bai, yong.bai@hotmail.com
@License: (C) Copyright 2013-2022.
@File: _utils.py
@Desc:
"""
import numpy as np
from scipy.spatial import Delaunay
import matplotlib.pyplot as plt
from matplotlib.colors import BoundaryNorm
def _panel_grid(fig_w, fig_h, hsp... |
3cab1bcec4335f9558849cea3d62527cd1e92b5c0962d17d883d440b549f7f05 | Python | 4,919 | 161 | '''
C6H5SH
'''
import numpy as np
import sys
def intro():
print("""
SHORT List of potential energy surfaces for C6H5SH:
P: potential energy, G: Gradient, D: Nonadiabatic coupling vector
U: diabatic potential energy matrix
UG: gradient of diabatic potential energy matrix
This is listed at the... |
fac6ba921277c05425a840d5ffcf9d11a109be6ba99b8b7d4c65de67ecc1992d | Python | 4,919 | 131 | # Generated by Django 3.2.15 on 2022-09-19 08:26
import django.db.models.deletion
from django.conf import settings
from django.db import migrations, models
import cvat.apps.webhooks.models
class Migration(migrations.Migration):
initial = True
dependencies = [
("engine", "0060_alter_label_parent"),... |
27bb6e41bbf545482a71131c35d7d00b3f0d6bdb82de100f153867e0d761500d | Python | 4,921 | 140 | import unittest
import logging
import numpy as np
import diffxpy.api as de
class _TestContinuousDe:
noise_model: str
def _test_wald_de(
self,
constrained: bool,
spline_basis: str,
ngenes: int
):
if self.noise_model == "nb":
from batchgl... |
5322655038e53e4427a54114c66cc1239d1f727942b4840de3c6af2b0c86b84c | Python | 4,921 | 121 | import numpy as np
import torch
import random
import pickle as pkl
class NBodyMStickDataset():
"""
NBodyDataset
"""
def __init__(self, partition='train', max_samples=1e8, data_dir='',
n_isolated=5, n_stick=0, n_hinge=0):
self.partition = partition
self.data_dir = data... |
78d23abbcbdb996fe95d9ffa553cc152fec50d5ec92a27fa9c3f6760434801df | Python | 4,921 | 76 | """ This script investigates the features within the components of the trained neural network. """
import os
import argparse
from utils.env_config import setup_environment
from data.dataloader import prepare_dataloaders
from model_analysis.interpret_model import execute_class_activation_mapping
from utils.mlflow_custo... |
bf08149232c19153166510a735c92ec4daa723e69da60e34493e29d9d36dec60 | Python | 4,921 | 93 | # -*- coding: utf-8 -*-
# Form implementation generated from reading ui file '/media/lg/disk2/PycharmProjects/ISAT_with_segment_anything/ISAT/ui/file_dock.ui'
#
# Created by: PyQt5 UI code generator 5.15.10
#
# WARNING: Any manual changes made to this file will be lost when pyuic5 is
# run again. Do not edit this fil... |
ca37dc55dfa11471b32591b3cb320f476c9e0d45b46315bce94a3836386e40e6 | Python | 4,922 | 113 | import pandas as pd
import py_neuromodulation as py_nm
import numpy as np
import os
import sys
import re
import glob
from joblib import Parallel, delayed
sys.path.append('./')
sys.path.append('./')
sys.path.append('./neurokin/')
sys.path.append('./neurokin/experiments/')
#sys.path.append('./neurokin/utils/')
#sys.path.... |
f58947e0c3415833a075c61a7d1b58f9ac8bd2345d3b195d061b4adeefc510bd | Python | 4,922 | 152 | import argparse
import logging
import os.path
import matplotlib.pyplot as plt
import torch
from skoots.validate.lib import (
get_segmentation_errors,
mask_iou,
accuracies_from_iou,
f1_score,
mask_dice,
mask_soft_cldice,
)
from skoots.validate.utils import imread
def main() -> None:
"""
... |
4a8a38360adbb13375168635e1f88b020b912cefbc0339b9c3031374afc2b0c3 | Python | 4,923 | 157 | """Capture reproducible screenshots of the local browser interface."""
from __future__ import annotations
import argparse
import os
from pathlib import Path
import subprocess
import sys
import time
from urllib.error import URLError
from urllib.request import urlopen
ROOT = Path(__file__).resolve().parents[1]
STATIC... |
c6ca027048cda2cb1439a72efa3fa8e4e29f852bba8e642262c2a908a80b406a | Python | 4,923 | 166 | # Copyright (C) CVAT.ai Corporation
#
# SPDX-License-Identifier: MIT
import contextlib
import http.server
import ssl
import textwrap
import threading
from collections.abc import Container, Generator
from dataclasses import dataclass
from pathlib import Path
from typing import Any
from urllib.parse import urlparse
imp... |
b6c258683716f68b40f539b99c1cea6aac5c8e9e6e61ee37ff253ae8aa08337c | Python | 4,925 | 142 | """Perform MDS on the trial-average fMRI responses for the NSD-core training
images and the NSD-synthetic images.
Parameters
----------
subject : str
String indicating the number of the subject used. If 'all', then use all
subjects.
zscore : int
Whether to z-score [1] or not [0] the fMRI responses of each vertex ac... |
c73dbdf98d42c1574e2233120285df5ba92a087c02450d9a29ac959fe26f50d6 | Python | 4,925 | 135 | import math
import torch
import torch.nn as nn
class Identity(nn.Module):
def forward(self, x):
return x
class LinearWithLoRA(nn.Module):
"""
Wraps an existing nn.Linear-like module and adds a LoRA branch.
The wrapped base module is stored as `base`, and its parameters are left as-is
(y... |
a57cac7e595e806885da11ae6952b3649b7bc7c51045f146af2fe6863786563e | Python | 4,926 | 116 | import numpy as np
import matplotlib.pyplot as plt
import matplotlib.patches as mpatches
# from tqdm.notebook import tqdm
def draw_pie(dist, xpos, ypos, size, colors, ax):
cumsum = np.cumsum(dist)
cumsum = cumsum/ cumsum[-1]
pie = [0] + cumsum.tolist()
i = 0
for r1, r2 in zip(pie[:-1], pie[1:]):
... |
c98b4b57069ef9966764991b197bfd5a7f589ba61d3fd813c8bce72ad4f96ddf | Python | 4,927 | 132 | """Tests for the linked optimization-step explorer."""
import json
import re
import pytest
from ui import opt_explorer
@pytest.fixture()
def traj_path(tmp_path):
"""Write a short EMT optimization trajectory of a Cu dimer."""
from ase import Atoms
from ase.calculators.emt import EMT
from ase.optimiz... |
7440fb1ea7d45139670172f52b0d648934bdf9cdbc3238d08144cd76904b09e2 | Python | 4,928 | 120 | """ROI footprints as a registration signal.
The obvious way to align two recordings is to correlate their mean images, and
on this data it does not work: every ``ops_fields.npz`` mean image carries the
same vertical scan-line texture, and it dominates the pixel variance. Unrelated
cultures correlate at 0.87; an image ... |
6f26d321c3b6ca73dc3970a12b6442c77a2618d09939e975d2f14175466d118e | Python | 4,929 | 125 | #!/usr/bin/env python
### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ##
#
# See COPYING file distributed along with the gradunwarp package for the
# copyright and license terms.
#
### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ##
import argparse as arg
impor... |
cd28a58de4081bc6955c32fd268c2fe962729df8922eddb0dbd5f3512bb9f422 | Python | 4,930 | 156 | r"""Utility package."""
import copy
from ._scatter import scatter, group_argsort, group_cat
from ._segment import segment
from ._index_sort import index_sort
from .functions import cumsum
from ._degree import degree
from ._softmax import softmax
from ._lexsort import lexsort
from ._sort_edge_index import sort_edge_in... |
fe98702b12b2299db9db6e1547feeea4b59a6867a05fabb079f29f45b57bbad6 | Python | 4,930 | 88 | import pytest
from tests.utils import pytest_importorskip
def test_qtdatavisualization():
"""Test the qtpy.QtDataVisualization namespace"""
# Using import skip here since with Python 3 you need to install another package
# besides the base `PyQt5` or `PySide2`.
# For example in the case of `PyQt5` yo... |
d4c73668965496cee4ba9a6c651d553bc92612bf7be20120e6dbeb7e6362c99f | Python | 4,931 | 158 | #!/usr/bin/env python
"""
FIXME!
usage: %prog feature.bed ar.bed snp.bed div_directory [options]
-m, --mask=M: Mask AR and features with this file
-s, --suffix=S: append suffix to chromosomes to get filenames from div_directory
-l, --lens=l: Set chromosome ends using LEN file
"""
import sys
from bx.bits... |
36a92a40deef44f8e676056dbaca10585fa302d29e401eeb92834123520cdad1 | Python | 4,933 | 146 | # -*- coding: utf-8 -*-
"""
Created on Thu Apr 2 13:15:59 2015
@author: ajaver
"""
import os
import re
import warnings
import subprocess as sp
import numpy as np
from tierpsy.helper.misc import FFMPEG_CMD, ReadEnqueue
class ReadVideoFFMPEG:
'''
Read video frame using ffmpeg. Assumes 8bits gray video.
... |
c0cf61799992b6b3d25bb7a8f6a5aeb0a748fe55640e42e575af082c1a82d9cf | Python | 4,933 | 124 | from typing import Callable, Dict, List, Optional, Tuple, Union
import torch
from torch_geometric.distributed import (
DistContext,
DistLoader,
DistNeighborSampler,
LocalFeatureStore,
LocalGraphStore,
)
from torch_geometric.loader import LinkLoader
from torch_geometric.sampler.base import Negative... |
560980189c50048b7e3ad9356bed7cb69b64a025d224efeb1ef9601db1e7247b | Python | 4,935 | 135 | """
Originally vgm_MakeTrigInfoFlex.m by Vikram Gadagkar
Ported to python by Ruidong Chen
This function creates time-aligned spike counts for each trial.
"""
import numpy as np
def _inrange(x, center, width, binsize):
if x < center - width:
return False
if x > center + width + binsize:
return... |
ec1f0d039d4a74310e5de8297c80a81149beacc172b603d9441ada48f3f26035 | Python | 4,936 | 110 | import matplotlib.pyplot as plt
import pygpc
import numpy as np
import os
import h5py
import matplotlib
import pathlib
matplotlib.use("Qt5Agg")
from helper_functions import __file__
MODULE_BASE = pathlib.Path(__file__).parent.parent
if __name__ == '__main__':
SAVE = False
# load time axis
fn_data = str(MO... |
4430b27bf8b74e73f7c8bddb312b599314bc4009d0abf95445257d6c3502eaa0 | Python | 4,937 | 147 | '''
NH3OH
'''
import numpy as np
import sys
def intro():
print("""
SHORT List of potential energy surfaces for NH3OH:
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... |
9d499d0cae79f27133e77ae330a7925a0ce51b633947b59900c7792d2c209443 | Python | 4,937 | 134 | from __future__ import print_function, absolute_import
import time
import collections
from collections import OrderedDict
import numpy as np
import torch
import random
import copy
from .evaluation_metrics import cmc, mean_ap
from .utils.meters import AverageMeter
from .utils.rerank import re_ranking
from .utils import ... |
d1414ac7ab011a49a10685b47c721d3525dad3ccf0c95b4c6dbe50d141fc1e8b | Python | 4,937 | 126 | from collections.abc import Sequence
from dataclasses import dataclass
from typing import Literal
@dataclass
class ImageOutputTypeConfig:
"""
:param adaptive_normalization_max_samples:
If using adaptive normalization (channel / element),
how many samples to use to compute the normalization par... |
ed786516789b9d916d2d5c8782dff2bf27ceb131133b40550d6a9906e65ad94d | Python | 4,937 | 126 | from collections.abc import Sequence
from dataclasses import dataclass
from typing import Literal
@dataclass
class ImageOutputTypeConfig:
"""
:param adaptive_normalization_max_samples:
If using adaptive normalization (channel / element),
how many samples to use to compute the normalization par... |
f75f6023bf6384c76c494952036fbfd5747fa239734205561f0fce3101f8a1f1 | Python | 4,937 | 122 | #############################################################################
### Recursively moves through directories and extracts parameters and the ###
### mean weights across neuronal subpopulations ###
#############################################################################
### Cop... |
6cfba57021a586417c24f3090b0002dad328c30e3001d2c0357a3040daf7eaf0 | Python | 4,940 | 148 | import numpy as np
import pandas as pd
import scanpy as sc
from tqdm import tqdm
import leidenalg as la
import igraph as ig
try:
from scipy.sparse import coo_array
except ImportError:
# google colab compatibility
from scipy.sparse import coo_matrix as coo_array
from scipy.spatial import KDTree
def segmen... |
934dd6c753c9c0c0313f5dd108135d47a11a9c17a8c9ad191a9ac3599d5e2681 | Python | 4,940 | 159 | import torch
import torch.nn as nn
import numpy as np
import ase
from ase.io import read
# utils imports
from utils.plot_corr import plot_corr
from utils.neuralnets.FFNet import FFNet
'''
Calculator for the atomic simulation environment (ASE)
that evaluates energies and forces using a neural network
'''
class KerNNCa... |
06156ccc68094b2ee9d058f0d18d744cd1aad91491ba2bcb3d6dd8b67e8d8e3f | Python | 4,942 | 140 | import torch
import torch.nn as nn
import numpy as np
from brainscore_core.supported_data_standards.brainio.s3 import load_weight_file, sha1_hash
from brainscore_vision.model_helpers.check_submission import check_models
import functools
from brainscore_vision.model_helpers.activations.pytorch import PytorchWrapper
from... |
0ecf8aeef6f033ab3c161b13b7564c5a83d833662b40e728c9a82f85823cb8e4 | Python | 4,942 | 207 | """[ma_task data utilities]
"""
import os
import glob
import re
import json
import numpy as np
from PIL import Image
from .utils import reorder_rdm
__all__ = [
"meadows_subjects",
"load_json_data",
"get_matask_stim",
"get_stim_ids",
"get_matask",
"get_dragrate"]
def meadows_subjects(subj):
... |
1d8af43d7c42a564e85808724d7bfb16078f264086c50425bcd140cbe65238f3 | Python | 4,942 | 101 | from nipype.interfaces import fsl
from PUMI.engine import AnatPipeline, NestedNode as Node, QcPipeline
from PUMI.pipelines.multimodal.image_manipulation import pick_volume, vol2png
@QcPipeline(inputspec_fields=['registered_func', 'func_2'],
outputspec_fields=['out_file'])
def qc(wf, registered_func_volume... |
1dc41ac373c28d9a8f489417ad5e7b6bb666bc57fef0212c9baa1edd64f22acf | Python | 4,942 | 140 | import torch
import torch.nn as nn
import numpy as np
from brainscore_core.supported_data_standards.brainio.s3 import load_weight_file, sha1_hash
from brainscore_vision.model_helpers.check_submission import check_models
import functools
from brainscore_vision.model_helpers.activations.pytorch import PytorchWrapper
from... |
21b064a2325e685434f61d13e29e4f2349feb3d209baa2610528df47383ca0e6 | Python | 4,942 | 140 | import torch
import torch.nn as nn
import numpy as np
from brainscore_core.supported_data_standards.brainio.s3 import load_weight_file, sha1_hash
from brainscore_vision.model_helpers.check_submission import check_models
import functools
from brainscore_vision.model_helpers.activations.pytorch import PytorchWrapper
from... |
3f3f51d7446779cb0bb9c901f58fef7c445c84c3ce08e0700a35258c91f6ad4a | Python | 4,942 | 140 | import torch
import torch.nn as nn
import numpy as np
from brainscore_core.supported_data_standards.brainio.s3 import load_weight_file, sha1_hash
from brainscore_vision.model_helpers.check_submission import check_models
import functools
from brainscore_vision.model_helpers.activations.pytorch import PytorchWrapper
from... |
786369d6ae03dede6063a30c3cf4834df309d37c348bc14e995b5335144806fc | Python | 4,942 | 113 | import numpy as np
from sklearn.linear_model import TheilSenRegressor
from scipy import signal
def compute_quantal_size(scan):
""" Estimate the unit change in calcium response corresponding to a unit change in
pixel intensity (dubbed quantal size, lower is better).
Assumes images are stationary from one ... |
7f818a7f21a0bcffc2f3425e22f26088bf802abaac21f2106a64e2ff3712afe5 | Python | 4,942 | 140 | import torch
import torch.nn as nn
import numpy as np
from brainscore_core.supported_data_standards.brainio.s3 import load_weight_file, sha1_hash
from brainscore_vision.model_helpers.check_submission import check_models
import functools
from brainscore_vision.model_helpers.activations.pytorch import PytorchWrapper
from... |
8267fbe09dc526424d58e4537de21893538e40c6eb24076f66acdaa60e2d2e86 | Python | 4,942 | 140 | import torch
import torch.nn as nn
import numpy as np
from brainscore_core.supported_data_standards.brainio.s3 import load_weight_file, sha1_hash
from brainscore_vision.model_helpers.check_submission import check_models
import functools
from brainscore_vision.model_helpers.activations.pytorch import PytorchWrapper
from... |
a4558361f0f20fc9979c584d2814dff0cfae466ac91964dbf3d4746ee721a7ea | Python | 4,942 | 140 | import torch
import torch.nn as nn
import numpy as np
from brainscore_core.supported_data_standards.brainio.s3 import load_weight_file, sha1_hash
from brainscore_vision.model_helpers.check_submission import check_models
import functools
from brainscore_vision.model_helpers.activations.pytorch import PytorchWrapper
from... |
b2443a14e6664495d8da2423fae88e3140cb838d1df63674f22db32f655fb873 | Python | 4,942 | 140 | import torch
import torch.nn as nn
import numpy as np
from brainscore_core.supported_data_standards.brainio.s3 import load_weight_file, sha1_hash
from brainscore_vision.model_helpers.check_submission import check_models
import functools
from brainscore_vision.model_helpers.activations.pytorch import PytorchWrapper
from... |
b5d92647cfb4ce0d540ccccfd3317cddc9eeac5ded5f58a883cdca7610b5740b | Python | 4,942 | 140 | import torch
import torch.nn as nn
import numpy as np
from brainscore_core.supported_data_standards.brainio.s3 import load_weight_file, sha1_hash
from brainscore_vision.model_helpers.check_submission import check_models
import functools
from brainscore_vision.model_helpers.activations.pytorch import PytorchWrapper
from... |
f966b22a040f2e990f28369799acf75ecd8079f0b1a7c2a905dc7600ab5cef5e | Python | 4,942 | 140 | import torch
import torch.nn as nn
import numpy as np
from brainscore_core.supported_data_standards.brainio.s3 import load_weight_file, sha1_hash
from brainscore_vision.model_helpers.check_submission import check_models
import functools
from brainscore_vision.model_helpers.activations.pytorch import PytorchWrapper
from... |
a21613eced0a68ed3cbb1401362dcf9d92cfbd530177995a358576a5a2d579d9 | Python | 4,945 | 166 | # -----------------------------------------------------------------------------
# Copyright © 2009- The QtPy Contributors
#
# Released under the terms of the MIT License
# (see LICENSE.txt for details)
# -----------------------------------------------------------------------------
"""Provide a CLI to allow configuring... |
39b427e9dba6d32c0d8320f2842878d82a4e40d9a20c030e68e36c82c94cad9f | Python | 4,946 | 156 | #!/usr/bin/python
# -*- coding: latin-1 -*-
# =============================================================================================
# Librairies importation
import numpy as np
import nrrd
import sys
import os
from voxcell import RegionMap
# ==================================================================... |
06a08b4f504819f5d159c8d9269cba1dbcd13cfd5b82d0995a85027b307790e7 | Python | 4,947 | 147 | import numpy as np
def compute_log_idx(bins_per_step: int, idx_max: int) -> np.ndarray:
"""
Compute the indices at which to resample data to get "log" spacing
of values from a linear sampling with increment = 1.
Returns an array of indices where the spacing between values doubles
every bins_per_s... |
25d7c280a679e05ffa6bf1321cbcbd23e44d6a0515044a84bbcd8bf7003f8ba0 | Python | 4,947 | 154 | import numpy as np
import scipy.ndimage
from . import _perlin
XYSCALEBASE = 100
def filter_frames(im, filt, *args, frame_start=0):
"""Apply a filter/transformation to an image batch
Parameters
----------
im : 3D float ndarray, values ∈ [0,1]
Frames to filter
filt : str
The name of... |
676bf6f3999bcbd3b8529c39bfdd6d356c4ccdc9735dbb6c0013798834c13c42 | Python | 4,947 | 162 | # -*- coding: utf-8 -*-
#
# Configuration file for the Sphinx documentation builder.
#
# This file does only contain a selection of the most common options. For a
# full list see the documentation:
# http://www.sphinx-doc.org/en/master/config
# -- Path setup ------------------------------------------------------------... |
620e027fb86cf9b560ab91e0977747d1708a1294507000cbdcdd6e1399f2da06 | Python | 4,948 | 153 | import logging
from pathlib import Path
import click
import pandas as pd
from pandas import ExcelWriter
from tqdm import tqdm
from brainways.project.brainways_subject import BrainwaysSubject
from brainways.utils._imports import NAPARI_AVAILABLE
from brainways.utils.cells import get_cell_struct_ids, get_struct_colors
... |
3af957e8fecef35dceab2ed1f5b7adc432cb0d730c2c467c7e40968f9968cc70 | Python | 4,950 | 172 | """
Test the sensitivity of nest results on input parameters
"""
import numpy as np
import scanpy as sc
import pandas as pd
import os
import matplotlib.pyplot as plt
import random
import seaborn as sns
import nest
from anndata import AnnData
from typing import Optional, Tuple
from numpy.typing import ArrayLike
from... |
01a705093fe349ab5c0225dbd13bf83b84c232667e01d359816402ce120205e3 | Python | 4,951 | 142 | import numpy as np
import scipy
import scipy.signal
import scipy.ndimage as ndimage
def plot_C(ConSink):
plt.close('all')
fig = plt.figure(figsize=(7, 7))
ax = fig.add_subplot()
ax.imshow(ConSink, cmap='jet')
ax.get_xaxis().set_ticks([])
ax.get_yaxis().set_ticks([])
ax.get_xaxis().set_ticks... |
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