sha256 stringlengths 64 64 | language stringclasses 28
values | size int32 1 491k | lines int32 1 23.2k | content stringlengths 1 200k |
|---|---|---|---|---|
8929502e9ea8ad80051f60dee8d0580f0bbee00c5c057a369c02531dcc5edfad | Python | 4,590 | 107 | import numpy as np
import matplotlib.pyplot as plt
from matplotlib.colors import Normalize
from matplotlib import cm
# Define x, y, and dz values
x_values = np.arange(1, 17) # x ranges from 1 to 16
y_values = np.arange(1, 17) # y ranges from 1 to 7
# Flattened dz values (provided)
dz = np.array([
0.... |
fd9333ada40fad6dc08915c282e4602af643774dfdae6db8f43ff2f1520698cc | Python | 4,591 | 150 | '''
CH3NH2
'''
import numpy as np
import sys
def intro():
print("""
SHORT List of potential energy surfaces for CH3NH2:
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... |
9cd01aee038281ae5f0f03532b523de2f37aa5922ed91715b29f030f07d1fe3f | Python | 4,593 | 126 | import torch
import numpy as np
import os, sys
sys.path.append(os.path.dirname(os.path.dirname(os.path.abspath(__file__))))
from utils import get_data
from utils import setup_logger
import logging
from TrainingLoop import TrainingLoop
import matplotlib.pyplot as plt
"""
Final value-based model
"""
## ---- Set seed ... |
f644966269fa28cac144f8adf9554f51ad09446e93fe11b4e2fbf5f1d0fe34aa | Python | 4,593 | 128 | import unittest
import logging
import numpy as np
import pandas as pd
import scipy.sparse
import anndata
from batchglm.api.models.numpy.glm_nb import Simulator
import diffxpy.api as de
class TestDataTypesSingle(unittest.TestCase):
def _test_wald(self, data, sample_description, gene_names=None):
test = ... |
02ac63f891fea7d4c76cbf73e5e14589b766a9a275f5637d54ed94689d73ca1e | Python | 4,594 | 132 | import torch
import torch.nn as nn
from torch import Tensor
from monai import transforms as mo_trans
from model.base_model import LocalAttention, MLP
from model.transformer3D import ViT3D
from utils.datasets import get_transform
class BrainAgeEstimator(nn.Module):
def __init__(self, args, device, chan... |
119211c52424b9b76156a549d143f318fe1aef1eed07e65b081092821c6d7744 | Python | 4,594 | 134 |
from typing import Sequence, Union
import torch
import string
import itertools
from Bio import SeqIO
from typing import List, Tuple
from .data import Alphabet, get_rna_fm_token, BatchConverter, RawMSA
rna_msaseq_toks = {'toks': ['A','U','G','C','-']}
class RNAAlphabet(Alphabet):
def get_batch_converter(self):
... |
13ad09c2d620e11e5cc444928a06cd99e062462025254b074fe8e96beb98d9a9 | Python | 4,595 | 116 | # A script to visualize the ERF.
# Scaling Up Your Kernels to 31x31: Revisiting Large Kernel Design in CNNs (https://arxiv.org/abs/2203.06717)
# Github source: https://github.com/DingXiaoH/RepLKNet-pytorch
# Licensed under The MIT License [see LICENSE for details]
# -----------------------------------------------------... |
237688ba25034f26e682fba30032b16d223c98a7933fa43ad15e188282fa2894 | Python | 4,595 | 131 | # transunet.py
import torch
import torch.nn as nn
class ConvBlock(nn.Module):
def __init__(self, in_channels, out_channels, stride=1):
super().__init__()
self.conv = nn.Sequential(
nn.Conv3d(in_channels, out_channels, kernel_size=3, stride=stride, padding=1),
nn.BatchNorm3d... |
a096ca183c5d0e47a8cf1bc5e06bb73c58462dab5f14e656f283bd4a8c0fb5d7 | Python | 4,595 | 161 | #!/usr/bin/env python
"""
HAL module for emulating a 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
class NoneStage(QtCore.QObject):
"""
Emulates a stage hardware object.
... |
9c6314d8c17e0fd892935a8e4a816e7e5f4f3a6d98cf60b511cd12521eb403df | Python | 4,596 | 131 | from nipype.interfaces.base import (
File,
TraitedSpec,
BaseInterfaceInputSpec,
BaseInterface,
isdefined,
)
from traits.api import Str, Either, Int
import os
class minIPInputSpec(BaseInterfaceInputSpec):
in_file = File(exists=True, desc="Input 3D image file", mandatory=True)
axis = Str("z"... |
07a955776bc684dab2ec1ed5e68124a40d8aae0dcb40eb13bc9ca9afe58291cf | Python | 4,597 | 178 | """
This module defines the autoencoder (AE) models.
References:
Author:
Julius Glaser <julius.glaser@fau.de>
Soundarya Soundarresan <soundarya.soundarresan@fau.de>
Zhengguo Tan <zhengguo.tan@gmail.com>
"""
import torch
import torch.nn as nn
from torch.nn import functional as F
from typing import Lis... |
9f2035e6bd5b8d5a0c83a2f8c7975a41851f0a74798439fb3f2609845139757c | Python | 4,598 | 143 | import random,sys
import numpy as np
from itertools import combinations, product
def get_Einfo():
Einfo = {}
Chrom = {}
fin = open('human_permissive_enhancers.bed')
for line in fin:
line = line.strip().split('\t')
Einfo[line[3]] = line[1]
if line[0] not in Chrom:
Chr... |
ba77a1e0771d20665364ee4a4faa69ed06719bb3cc533640c4cc5ce7e15935f8 | Python | 4,599 | 79 | #!/usr/bin/env python
# -*- coding: utf-8 -*-
# *************************************************************************** #
# Copyright © 2022, UChicago Argonne, LLC #
# All Rights Reserved #
# Softwar... |
556c93da516905996e0bc72b2ddd9a3714f86955e176990a23d5cb7b3a1cb000 | Python | 4,600 | 120 | import logging
import numpy as np
import os
import requests
import torch
from tqdm import tqdm
from scilpy.ml.bundleparc.bundleparcnet import BundleParcNet
# TODO in future: Get bundle list from model
DEFAULT_BUNDLES = ['AF_left', 'AF_right', 'ATR_left', 'ATR_right', 'CA', 'CC_1', 'CC_2', 'CC_3', 'CC_4', 'CC_5', 'C... |
3711f0ed693b12287ea7761a94d35c0ce8bbfb70f4b6b5240aee6937b58e8b37 | Python | 4,601 | 158 | import nibabel as nib
import numpy as np
import pytest
from numpy.typing import DTypeLike
from pyment.preprocessing import conform, rescale
TARGET_SHAPE = (224, 192, 224)
def make_nifti(
shape: tuple,
zooms: tuple = (1.0, 1.0, 1.0),
dtype: DTypeLike = np.float32,
) -> nib.Nifti1Image:
data = np.ones... |
10ac031faea1a636f7d398c941631d7d17220c229a269270be06e6a81f5d6eae | Python | 4,603 | 80 | # Kai Sandbrink
# 2023-05-26
# This script extracts the survey responses for participants
# %% LIBRARY IMPORT
import numpy as np
import pandas as pd
import os, json
import glob
from utils import get_timestamp
# %% PARAMETERS
participant_ids = ['xyz']
data_folder = os.path.join('data', 'day3B', 'data')
save_file =... |
f8f1abfdd332ba5ba9b2cf3190f1f8fd86a192ef8b1e7cf2c586f14b3950d412 | Python | 4,603 | 152 | # Copyright (C) 2021-2022 Intel Corporation
# Copyright (C) CVAT.ai Corporation
#
# SPDX-License-Identifier: MIT
import argparse
import importlib
import importlib.util
import logging
import sys
from http.client import HTTPConnection
from pathlib import Path
from typing import Any
import attrs
import cvat_sdk.auto_ann... |
538eb0d58b3ff57954431c11f49105d55b34bb372dedb752a6285d2fa8be1431 | Python | 4,604 | 125 | """
For code used in distributed training. Basically just found a stackoverflow implementation
and got it to work.
https://stackoverflow.com/questions/1365265/on-localhost-how-do-i-pick-a-free-port-number
"""
from typing import Tuple
import torch
import torch.distributed as dist
import torch.multiprocessing as mp
fro... |
a3780ea0d442e37100ad49e9b09814dec36603fc8afadc032fe848f5ddbc4992 | Python | 4,604 | 123 | # Copyright (c) 2022, Kwanhyung Lee, Hyewon Jeong, Seyun Kim 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 o... |
c031cf153370a9dfe8864f0f6209f448ab39b6d139bd1595ac006da0d75a9a00 | Python | 4,606 | 132 | '''
CH4OF
'''
import numpy as np
import sys
def intro():
print("""
SHORT List of potential energy surfaces for CH4OF:
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... |
fcdd7735aee32cd7d24bef54508edf4c8ff5c7975c78ac10d8dfb9c246255d19 | Python | 4,606 | 110 | from brainscore_vision.model_helpers.check_submission import check_models
import functools
import numpy as np
from PIL import Image
import torch
import torchvision.transforms as transforms
import torchvision.models
from brainscore_vision.model_helpers.activations.pytorch import PytorchWrapper
from brainscore_vi... |
ff2e47e5b4ba36f8a78482412913d4e7c623300657cb6c300df00d6556958cf7 | Python | 4,606 | 110 | from brainscore_vision.model_helpers.check_submission import check_models
import functools
import numpy as np
from PIL import Image
import torch
import torchvision.transforms as transforms
import torchvision.models
from brainscore_vision.model_helpers.activations.pytorch import PytorchWrapper
from brainscore_vi... |
0d5afded0a419ffa1e635b5a9fb67581a2a4443ecac61a91f57e2cf8633b03d5 | Python | 4,607 | 154 | import numpy as np
import sys
import pickle
import os
import yaml
import argparse
import ast
from scipy.io import savemat
from dannce.engine.io import load_sync, load_com
from dannce.engine.processing import prepare_save_metadata
from dannce import (
_param_defaults_shared,
_param_defaults_dannce,
_param_de... |
00e897f3c8cc27b75e7de5392575f42de7f25a1486a5929283940b35e828c259 | Python | 4,608 | 100 | import numpy as np
from brainscore_core.supported_data_standards.brainio.assemblies import BehavioralAssembly
from brainscore_core.supported_data_standards.brainio.packaging import package_data_assembly
import pandas as pd
'''
** NOTE: This benchmark (silhouette) has a very different stimulus sets then others,
... |
542389913112939b8384b405e26db41b36f8a5e3be33c477b08726222a1ad09f | Python | 4,608 | 111 | from brainscore_vision.model_helpers.check_submission import check_models
import functools
import numpy as np
from PIL import Image
import torch
import torchvision.transforms as transforms
import torchvision.models
from brainscore_vision.model_helpers.activations.pytorch import PytorchWrapper
from brainscore_vi... |
c56ef122426116accac0e55e08961def207ff8ddeee6f2c74765c63cba6425c0 | Python | 4,608 | 110 | import argparse
import utils
import keras
from keras.models import load_model
from os.path import join
import numpy as np
import gc
'''
calculate standard deviation of ensemble predictions for train/test/val data
for ResidualBind models
'''
def parse_args():
parser = argparse.ArgumentParser()
parser.add_argu... |
cf510140f2a271a3079422c032c151f1285b8192db665db5e1a62135cdd322ac | Python | 4,610 | 136 | import multiprocessing
import nibabel as nib
import numpy as np
from scipy.io import loadmat
from scipy import sparse
from itertools import compress
import os
import sys
import time
import argparse
def argument_parse():
parser=argparse.ArgumentParser()
parser.add_argument('--chunklist',action='store', dest='chunkli... |
dd7ca32018300a5b7aeea8b87e320eee8f2a5febb14fe55be7c7a91d3a56e2ef | Python | 4,610 | 116 | # Copyright (C) CVAT.ai Corporation
#
# SPDX-License-Identifier: MIT
from http import HTTPStatus
from unittest.mock import MagicMock, patch
from django.conf import settings
from django.test import TestCase
from cvat.apps.engine.models import Project
from cvat.apps.iam.models import User
from cvat.apps.webhooks.excep... |
1364d71ab8d9f4936423f3815e406ccff206c1e826a5df7b778866fdd112281f | Python | 4,611 | 164 | # -*- coding: utf-8 -*-
"""Header transformations."""
from pathlib import Path
import nibabel as nb
import numpy as np
from numpy.linalg import inv
__all__ = ["apply_affine_chunked", "read_vox2vox", "read_vox2ras_tkr", "vox2ras_tkr"]
def apply_affine_chunked(aff, pts, chunk_size=10000):
"""Apply an affine matr... |
56ede7830e66ce8a5006f574ced5c97196fae978e64a5269c933bd65dae884c4 | Python | 4,611 | 100 | import numpy as np
from rsatoolbox.util.searchlight import get_volume_searchlight
from rsatoolbox.data.dataset import Dataset
from nilearn.image import load_img
from nilearn.masking import compute_brain_mask
from rsatoolbox.rdm.calc import calc_rdm
from rsatoolbox.rdm import RDMs
import pickle
from rich.progress import... |
639053ddcc55739d8a14f80504c603b6b16cb7d92ddb2b66d7c373239f3901a1 | Python | 4,612 | 118 | # Keywords obtained from https://github.com/tblite/tblite/blob/main/python/tblite/ase.py
# TBLite calculator parameters for CompChemAgent
from pydantic import BaseModel, Field
from typing import List, Optional
import logging
try:
from tblite.ase import TBLite
except ImportError:
logging.warning(
"tblit... |
278e01dc0a079b897bd21beba25ac8a6e3557db32ac9a0ee0ceedd59bbfc2de7 | Python | 4,613 | 96 | import os
import re
import subprocess
from nipype.interfaces.base import (
CommandLine, CommandLineInputSpec, BaseInterface, BaseTraitedSpec, BaseInterfaceInputSpec, TraitedSpec,
File, traits
)
from traits.api import Either, Float, Undefined
class PSMDInputSpec(CommandLineInputSpec):
# -p mode: from pre-p... |
5afae758841fb808e3e9a6e310873ec292c57c22a3bb767f7c1ac8a89f4ac037 | Python | 4,614 | 167 | #!/usr/bin/env python
"""
Tests of the parameters object functionality.
"""
import storm_control.test as test
import storm_control.sc_library.parameters as params
def test_parameters_1():
# Load parameters.
p1 = params.parameters(test.xmlFilePathAndName("test_parameters.xml"), recurse = True)
# Ch... |
ce71f59b383177f1a007bb72aaaa03e272f1afbd2258d119a853777d5a0a8dd8 | Python | 4,614 | 129 | """Server-side policy for the experimental Deep Agent in the web UI.
The CLI's Deep Agent runs in the operator's own terminal. In the web UI the
person typing into the browser need not be the person who started the
server (``--server.address 0.0.0.0``, Docker, Kubernetes), yet the Deep
Agent can run shell commands as... |
b9fda9fa6356ff09ed09edf82bf5ebdc9e3970987c216125fdc33083228647e8 | Python | 4,616 | 129 | import logging
from .constants import *
_logger = logging.getLogger(__name__)
def resolve_data_config(
args=None,
pretrained_cfg=None,
model=None,
use_test_size=False,
verbose=False
):
assert model or args or pretrained_cfg, "At least one of model, args, or pretrained_cfg... |
21a5f14b97e5066e75b9524997db0707211559ce39f4c3551afef7795f27bef6 | Python | 4,617 | 158 | """Model factory to build different types of models."""
import torch
import numpy as np
from .mlp import SpikingMLP, SpikingEiMLP
from .vgg import SpikingVGG, SpikingEiVGG
from .resnet import SpikingResNet, SpikingEiResNet
in_channels_dict = {
'MNIST': 1,
'CIFAR10': 3,
'CIFAR100': 3,
'CIFAR10DVS': 2,... |
6e9baaa16359fae439fabc649e62792260f918febe266adb0474c759db45f014 | Python | 4,617 | 145 | # Copyright (C) CVAT.ai Corporation
#
# SPDX-License-Identifier: MIT
from logging import Logger
from pathlib import Path
from urllib.parse import parse_qs, urlparse
import django_rq
from django.conf import settings
from rq.job import Job, JobStatus
from rq_scheduler import Scheduler
from cvat.apps.engine.log import ... |
4e8b75c3fc7d47a52bb1c02cea768bdece7ee74659901c75dac865ff944fb9b3 | Python | 4,622 | 101 | # -*- coding: utf-8 -*-
"""
Apply deformation to surface mesh
The purpose of the following script is to apply two deformations in succession
(orig -> ana -> mpm) to a surface mesh using generated coordinate mappings. The
script needs an installation of freesurfer.
"""
# python standard library inputs
import os
from ... |
74678a82b9d781374760a1304529600033e0e70355f29d48f080d34d0f678213 | Python | 4,622 | 100 | import numpy as np
from result_caching import store
from brainscore_core.supported_data_standards.brainio.assemblies import DataAssembly
from brainscore_vision import load_metric, load_dataset
from brainscore_vision.benchmark_helpers.properties_common import PropertiesBenchmark, _assert_grating_activations
from brains... |
c3d4697b59f7fb8bd343784747160461cdd3d22358d972ee39dc434a81ebf453 | Python | 4,622 | 137 | # 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.
"""isort:skip_file"""
from .dictionary import Dictionary, TruncatedDictionary
from .fairseq_dataset import FairseqDataset, FairseqIterableDat... |
c27972c6739265f16f2ae262b01461259cbe8e60fc4067a8ecc4b98a31168559 | Python | 4,624 | 119 | import mne
import numpy as np
import rsatoolbox
import pandas as pd
import copy
import scipy.stats
import matplotlib.pyplot as plt
from joblib import Parallel, delayed
import matplotlib
font = {'family' : 'calibri', 'size' : 9}
plt.rcParams['svg.fonttype'] = 'none'
matplotlib.rc('font', **font)
def pretty_plot(ax... |
c99a2be4c0d6deed2b479c439e9d36d66bbdce22c2de4825964514bb1b0af698 | Python | 4,624 | 159 | #Lucas Sancéré -
import json
import os
import joblib
import numpy as np
import yaml
from attrdictionary import AttrDict as attributedict
from histo_miner.feature_selection import SelectedFeaturesMatrix
script_dir = os.path.dirname(os.path.abspath(__file__))
########################################################... |
477c314b75556254f113163afb4fe5d4978b06bf0fb1b23ea512ed4c5c8709f1 | Python | 4,625 | 149 | import os
import random
import numpy as np
import pandas as pd
import tensorflow as tf
import matplotlib.pyplot as plt
from sklearn.model_selection import KFold
from sklearn.metrics import classification_report
from sklearn.metrics import confusion_matrix
from sklearn.metrics import ConfusionMatrixDisplay
from prepro... |
73de22482fc64ebf0183591e9f877dd95cd165c390a8919ab9468d6c59706329 | Python | 4,625 | 87 | if __name__ == '__main__':
from bread.data import Features, Segmentation
import bread.algo.tracking as tracking
from pathlib import Path
from glob import glob
from tqdm import tqdm
import pickle, json
import argparse
import os, sys, datetime
import torch
from importlib import imp... |
a060d7c2f36d31b3deeab1b63306861161efa46138b4510d346f9fba6e162e84 | Python | 4,625 | 125 | # Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under th... |
ee57c4a6d6c0686771b08878a9780298ed1653ff9a2022e6a8512e4262f6d074 | Python | 4,625 | 129 | import torch
import torch.nn as nn
class UNet3D(nn.Module):
def __init__(self, n_in, n_out):
super(UNet3D, self).__init__()
# Encoder
self.ec0 = self.encoder_block( n_in, 32, kernel_size=3, stride=1, padding=1)
self.ec1 = self.encoder_block( 32, 64, kernel_size=3,... |
0ea7422ccba515494537ea5a80981961b80adb7d08591362fc9e48f57fb2b129 | Python | 4,626 | 142 | #!/usr/bin/env python
#
# File dialog that allows for regex filtering.
#
from PyQt5 import QtCore, QtGui, QtWidgets
import re
import sys
import storm_control.steve.qtdesigner.qt_regex_file_dialog_ui as qtRegexFileDialogUi
def regexGetFileNames(caption = "Select File(s)", directory = None, extensions = None, regex =... |
d30615ab8e1a7eeeba2ebef5af742a0a34dce7da9304780d1d71e3727d99ec6d | Python | 4,626 | 113 | import scanpy as sc
import numpy as np
import pandas as pd
import sys
import argparse
import scipy
import anndata as ad
def ParseArgs():
parser = argparse.ArgumentParser(
prog='AP_Profiling',
description='Create AP Profiling for genes.',
epilog='Best wishes'
... |
f317bf62284a96b821ced1aacf58fa69f91c0487e6ad77bacc7dbf0de1f480ee | Python | 4,627 | 92 | 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... |
066f17bdfb881f24565f2a3f5cf9911c6aa7f1e133fb661fed96ef2b8c9eabdf | Python | 4,628 | 92 | from train_gtex import *
"""
Train with a subset of genes while using downsampled train donors
"""
def prepare_genes(config):
"""
Overwrite to get list of genes from SingleGeneDownsampledTrainDonors directory, which will be a smaller list of genes due to the number of extra models being trained
"""
... |
2808e41d0e2c9a35178f0b0ab1f04a0c22d48a82f8b68511048e1c9a5eea3fd2 | Python | 4,629 | 121 | from nipype.interfaces.base import CommandLineInputSpec, File, TraitedSpec, traits_extension, traits, CommandLine
import os.path
class HDBetInputSpec(CommandLineInputSpec):
in_file = File(
desc='file to skull strip',
mandatory=True,
exists=True,
argstr='--input=%s',
hash_fi... |
57d9534873120ce36231791f6c947ab80ecbd12029601f9d82a4fd8d3ef8c3af | Python | 4,629 | 158 | import torch
from torch import nn
from . import utils
from . import model
from . import data
from . import argument
import datetime
import time
import logging
import os
from pathlib import Path
os.environ['CUDA_VISIBLE_DEVICES'] = '7'
script_dir = Path(__file__).parent
project_root = Path(__file__).resolve().parent.pa... |
fac2e7cdc5d18b41e26304d2d86c01e97e6320c5867eca6f1d1980df163cb549 | Python | 4,629 | 134 | """``IsocortexEntireProjector``: one value per streamline, and their ordering."""
import numpy as np
import pytest
from ccf_streamlines.projection import IsocortexEntireProjector
@pytest.fixture
def projector(mini_ccf):
return IsocortexEntireProjector(
mini_ccf.surface_paths_file, resolution=mini_ccf.re... |
35d5f6bef95b00068870750f76259e3f892f5f541fef399ee50e5baca83920ad | Python | 4,630 | 137 | import os
import sys
import pprint
import torch
import math
import random
from torchdrug import core
from torchdrug.utils import comm
from torch.utils import data as torch_data
from torchdrug import data, core, utils
sys.path.append(os.path.dirname(os.path.dirname(__file__)))
from biopathnet import dataset, layer, ... |
59cea948656f2bea53db9810393ba2a37ce76cf56831f040b0e432babbbf3a8d | Python | 4,630 | 132 | from collections.abc import Sequence
from pathlib import Path
from typing import TYPE_CHECKING
import matplotlib.pyplot as plt
import numpy as np
import torch
from aislib.misc_utils import ensure_path_exists
from captum.attr._utils.visualization import Union, visualize_image_attr_multiple
from torchvision.transforms i... |
6d74c8102d9640171602d33b957af22abb2f6a5f85f7bcfc100d6a142271b392 | Python | 4,630 | 143 | #!/usr/bin/env python
"""
RS232 interface to a Marzhauser stage.
Hazen 04/17
"""
import traceback
import storm_control.sc_hardware.serial.RS232 as RS232
import storm_control.sc_library.hdebug as hdebug
class MarzhauserRS232(RS232.RS232):
"""
Marzhauser RS232 interface class.
"""
def ... |
9904a95cfbc28cce9b538ac2051519ffcc144df89bd1fdf594f6aabff312ffae | Python | 4,632 | 103 | # -*- coding: utf-8 -*-
"""
Created on Fri Jan 14 14:40:05 2022
@author: Yoshi
"""
import os
import shutil
# import matplotlib.pyplot as plt
# from PIL import Image
from average_radius_calculator import *
# from scale_calculator import *
# from cell_number_mapper import *
# from cell_response_mapper import *
def ... |
f31f1a74714945c01700bc14a3336a7b07c22025d6dfbe7ec4008d0178d65fa3 | Python | 4,632 | 123 | #!/usr/bin/env python
"""
Reads a list of intervals and a maf. Produces a new maf containing the
blocks or parts of blocks in the original that overlapped the intervals.
It is assumed that each file `maf_fname` has a corresponding `maf_fname`.index
file.
NOTE: If two intervals overlap the same block it will be writt... |
f949e4ece3b3a993bddd3c2e65b9f3e499e9cb1cff54c8405ffc50f2af6f0548 | Python | 4,632 | 122 | #! /usr/bin/env python3
import inspect
import torch
from utils import common_functions as c_f
from utils.module_with_records_and_reducer import ModuleWithRecordsReducerAndDistance
from losses.mixins import EmbeddingRegularizerMixin
class BaseMetricLossFunction(
EmbeddingRegularizerMixin, ModuleWithRecordsReduc... |
766e1b47ae477ce7f6e893844f144f517be22497d0db9f208544fa91cf552482 | Python | 4,633 | 171 | # the code is adapted based on a previous version of Dr. Sebastian Schmidt
# adaptation was made to match brunel network simulation in NEST simulator
# load packages needed for this project
import arbor as A
from arbor import units as U
import numpy as np
from numpy.random import RandomState
from parameters import *
... |
7769d22560b6c9b79ce43fe705dd3f2abf62fb68792f2fb230ccce39d3622202 | Python | 4,634 | 111 | from __future__ import print_function
import scipy.sparse as sp
import numpy as np
from scipy.sparse.linalg.eigen.arpack import eigsh, ArpackNoConvergence
def encode_onehot(labels):
classes = set(labels)
classes_dict = {c: np.identity(len(classes))[i, :] for i, c in enumerate(classes)}
labels_onehot = np.a... |
876c7587bc590deea1640c6093fad1b30af8f0e91c9abc23aa6d7fb4ee5a2cdd | Python | 4,634 | 113 | """Level-3 parity check: MATLAB vs Python network metrics on IDENTICAL graphs.
Loads the adjacency matrices + MATLAB-computed metrics produced by
parityRun/gen_step4_parity_reference.m (MATLAB's own BCT functions run on this
parity run's adjacency), feeds the *same* adjMsub to the Python port's
network_metrics functio... |
14515fda9bd1e610775d9baba1f0d9010ba6f83072439e811cff9cdb066e92ac | Python | 4,636 | 127 | # -*- coding: utf-8 -*-
"""
Created on Thu Jun 6 20:13:38 2024
@author: fmizt
"""
import pandas as pd
from sklearn.decomposition import PCA
from matplotlib import pyplot as plt
import numpy as np
import seaborn as sns
from scipy import signal
from scipy.io import wavfile
import glob
import scipy.stats... |
315c295178960d0ea7d43bfbe3b606720ae0d8ac2a2ceed97c1797dd28adff2a | Python | 4,637 | 141 | import h5py
import os
import matplotlib.pyplot as plt
import numpy as np
from matplotlib.patches import Rectangle
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: ', DAT... |
37c80e423a1914a6a4fe4d7af7fbb2eb4752b67311c0f9b0e02a8a982c49c8a8 | Python | 4,637 | 126 | '''
C2N
'''
import numpy as np
import sys
def intro():
print("""
SHORT List of potential energy surfaces for C2N:
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... |
f1ce41c1bd823aef87c354caec4e3e594da8246f59d6f398079b69da66c383a6 | Python | 4,637 | 103 | import torch
import torch.nn as nn
import torch.nn.functional as F
import timm
# Minimal decoder for Swin-based segmentation
class SimpleSwinDecoder(nn.Module):
def __init__(self, in_channels, out_channels):
super(SimpleSwinDecoder, self).__init__()
self.decode = nn.Sequential(
nn.Conv2... |
f1484344aca0fb54860d1bc959f0608adb75a8941b37e69aeacc5dbda533f29e | Python | 4,639 | 126 | import sys
import argparse
import numpy as np
import pickle
from matplotlib import pyplot as plt
from scipy import sparse
from scipy.io import loadmat
def argument_parse_savematrixfig(argv):
parser=argparse.ArgumentParser(description='Save a matrix image for an input chacoconn or average or multiple input chacoco... |
3086f005f4bf58b94da5581a050046ebcdc93e08fcfe96c14885347a6e6163a2 | Python | 4,640 | 145 | import enum
import importlib
import logging
from dataclasses import dataclass
from enum import auto
from os import path
from typing import List
import onnx
from onnx import AttributeProto
logger = logging.getLogger(__name__)
def parse_mapping_from_path(mapping_path):
"""
Parse the input accelerator residing... |
d20deea523d908934a93803c0269e82a48aa74cb5dd76a1595128d32a3b1bd3b | Python | 4,640 | 121 | # -*- coding: utf-8 -*-
# @Author : LG
from ISAT.segment_any.segment_any import SegAny
from matplotlib import pyplot as plt
import numpy as np
import cv2
import time
import os
def show_mask(mask, ax, random_color=False):
if random_color:
color = np.concatenate([np.random.random(3), np.array([0.6])], axi... |
0b2f1d8f505d12d2e234027202ae71bc23e561cfaccd7fb9d7d53ef1f961a57b | Python | 4,641 | 131 | # Copyright 2025 BrainX Ecosystem Limited. All Rights Reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by appli... |
502ccf0ae160686c94c19476bebce47d1b160f464bb02864429f233fa208d7f0 | Python | 4,641 | 140 | import os
import numpy as np
import torch
from tqdm import tqdm
from torch_geometric.data import InMemoryDataset, extract_zip
from mlcg.utils import download_url
from mlcg.data import AtomicData
class EFADataset(InMemoryDataset):
"""General base extractor for the EFA dataset described in https://doi.org/10.48550... |
511bacd045c861bf18de7276b649b2c3d8d77315db279a5e967796ec0dc6c8a8 | Python | 4,641 | 92 | 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... |
7a159629d2b645f6ec83235e7302c033eb4c330206b9ada00dfee3c71c8c1b1c | Python | 4,641 | 134 | # -*- coding: utf-8 -*-
#
# test_morphology.py
import unittest
import arbor as A
import numpy as N
import math
"""
tests for morphology-related classes
"""
def as_matrix(iso):
trans = N.array(iso((0, 0, 0)))
return N.c_[
N.array([iso(v) for v in [(1, 0, 0), (0, 1, 0), (0, 0, 1)]]).transpose()
... |
a5d7106489136d1a83703c56ac2ba4147276a12974144de7753d82609021c883 | Python | 4,641 | 131 | # LISI - The Local Inverse Simpson Index
# Copyright (C) 2018 Ilya Korsunsky
# 2019 Kamil Slowikowski <kslowikowski@gmail.com>
#
# This program is free software: you can redistribute it and/or modify
# it under the terms of the GNU General Public License as published by
# the Free Software Foundation, e... |
d5000d307bc0a19b99afe4e3286265af995fddb3db4330001f46aba6437e75b3 | Python | 4,641 | 110 | from brainscore_vision.model_helpers.check_submission import check_models
import functools
import numpy as np
from PIL import Image
import torch
import torchvision.transforms as transforms
import torchvision.models
from brainscore_vision.model_helpers.activations.pytorch import PytorchWrapper
from brainscore_vi... |
42b5f5a673af7965701a0e6b3b269e005001186b8aac1e29be022f6e47b9923a | Python | 4,642 | 118 | import copy
import pickle
import numpy as np
import pandas as pd
import fire
from joblib import Parallel, delayed
import sys
sys.path.insert(0,'..')
import contrasts
import nilearn
import nilearn.image
import nilearn.plotting
import glob
from nilearn.interfaces.bids import get_bids_files
ref_img = nilearn.image.loa... |
7b6a80d6bfce51648c15b22242e909c79bd84ffda40d7e44ef5577cd3ffa4bd3 | Python | 4,645 | 133 | '''
AlmHn
'''
import numpy as np
import sys
def intro():
print("""
SHORT List of potential energy surfaces for AlmHn:
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... |
8639eca6894e4bb5be76fc555da795bc705806b1881c00a3971a12d73cf7b113 | Python | 4,645 | 172 | # -*- coding: utf-8 -*-
"""
Routines to generate various structure elements
Structured elements defined by the ``setype`` key include:
.. _StructureElementTypes:
Structure Element Types
-----------------------
=============== =====================================
Type Descrition
=============== =======... |
a65ca2066e2e5bdc14f9d522a33a37d858b4a2f4885a3526f2b47617a4bc72fe | Python | 4,646 | 135 | import matplotlib.pyplot as plt
import numpy as np
import nems
from nems import Model
from nems.layers import WeightChannels, FiniteImpulseResponse, RectifiedLinear, STRF
from nems import visualization
from nems.metrics import correlation
from nems.models.LN import LN_plot_strf
## Synthesize some data
#
# Model has... |
bd054a0231cb4f7315199029ed4ffd824ad32397a24cfc0d27f4af5115d7b363 | Python | 4,646 | 121 | import mne
import numpy as np
import rsatoolbox
import pandas as pd
import copy
import scipy.stats
import matplotlib.pyplot as plt
from joblib import Parallel, delayed
import matplotlib
font = {'family' : 'calibri', 'size' : 9}
plt.rcParams['svg.fonttype'] = 'none'
matplotlib.rc('font', **font)
def pretty_plot(ax... |
adb8be891922e8d520a9932df623ad9ef984d6abd5372d716a8b8d3a4c53a0a4 | Python | 4,647 | 110 | import pingouin as pg
import polars as pl
import seaborn as sns
from argclz import AbstractParser, argument
from neuralib.plot import plot_figure
from neuralib.util.verbose import print_load, printdf, publish_annotation
from rscvp.statistic.core import print_var
from rscvp.util.cli import CommonOptions
__all__ = ['Se... |
263a9f208453e889a19a2f43b5100f42312496022dffe9e91e33ff582fd47c47 | Python | 4,648 | 175 | import torch
import torch.nn as nn
import torch.nn.functional as F
from torch_geometric.utils import softmax
from torch_geometric.nn import (
MessagePassing,
GATv2Conv,
GraphNorm
)
class AttentiveLayer(MessagePassing):
def __init__(
self,
input_dim,
output_d... |
ed6c72855eb466ddb7aa4bfa6de19bb5ce3a57b593e24784c7ca996ac18fc17c | Python | 4,648 | 162 | """Plotting helpers for Waven RF correlation analysis."""
from __future__ import annotations
from pathlib import Path
from typing import Iterable, Optional, Sequence, Tuple
import numpy as np
def finite_abs_max(values: np.ndarray, fallback: float = 1.0) -> float:
"""Return a finite absolute max, with a nonzero ... |
1031d46739f6a3386745ae0695907475ac2f86c4450da09b588698bd722c4a25 | Python | 4,649 | 158 | #!/usr/bin/env python
"""
Provides the functionality of camera. Basically this is everything
another module would need to know to display and/or save the
output of the camera.
Hazen 4/17
"""
import copy
from PyQt5 import QtCore
import storm_control.hal4000.halLib.halFunctionality as halFunctionality
class CameraF... |
564674968e4458db73cb02e3749e0183e53e80e258ce3c9fe185238e8533bdee | Python | 4,649 | 118 | import numpy as np
import pandas as pd
import os
import time
import matplotlib.pyplot as plt
import copy
from .entropy import get_entropy, get_io_entropy
from .vectorisation import get_all_vectorisation
def get_oneway_ent(all_vector, id_lst, df, keyed, in_columns, out_columns):
'''
Get the entropy of in/ou... |
36be8a918235e54f7dd2fbbcb7d6c3fa0f508772d088c7670c5b0aabf57ac56a | Python | 4,650 | 113 | from brainscore_core.supported_data_standards.brainio.assemblies import NeuronRecordingAssembly
import brainscore_vision
from brainscore_vision import data_registry, stimulus_set_registry
from brainscore_core.supported_data_standards.brainio.s3 import load_stimulus_set_from_s3, load_assembly_from_s3
BIBTEX = """@arti... |
59e9cbdec8ab3353d4f272330357eae35b797af99601da1f438738aa966a0703 | Python | 4,650 | 111 | # # TODO currently broken, make this work again
# from brainles_preprocessing.core import (
# Modality,
# preprocess_modality_centric_to_atlas_space,
# )
# def preprocess_brats_style_t1_centric(
# input_t1: str,
# output_t1: str,
# input_t1c: str,
# output_t1c: str,
# input_t2: str,
# ... |
bb145b47c6836f948e69a173c3fff431f50d1fd774b1022748ad1c88f364e5bb | Python | 4,650 | 127 | from typing import Any, Callable, Dict, List, Optional, Union
import numpy as np
import pyro # type: ignore
import torch
from numpy.typing import NDArray
from pyro.infer import Predictive, Trace_ELBO # type: ignore
from torch.cuda import empty_cache
from tqdm import tqdm # type: ignore
from scpca.train.handler imp... |
6ec5b385287f4a95962198a8fb7b34b617e8063936f92aea13bd29d2d5fa1427 | Python | 4,653 | 111 | # # TODO currently broken, make this work again
# from brainles_preprocessing.core import (
# Modality,
# preprocess_modality_centric_to_atlas_space,
# )
# def preprocess_brats_style_t1c_centric(
# input_t1c: str,
# output_t1c: str,
# input_t1: str,
# output_t1: str,
# input_t2: str,
# ... |
a5d6352ba62b2d9066c44c4d2b0b4a16446ae7663cf04a12f88dbe17d7236a59 | Python | 4,653 | 158 | from __future__ import annotations
import json
from collections.abc import Callable
from pathlib import Path
from typing import Final
import pytest
from PySide6 import QtWidgets
from pytestqt.qtbot import QtBot
from labelme._app import MainWindow
from ..conftest import close_or_pause
from .conftest import MainWinFa... |
5f5d973045e90df9d0d58bc8bfa7989dad5f2ad076ddb52a6da136d80797661d | Python | 4,654 | 108 | from brainscore_vision.model_helpers.check_submission import check_models
import functools
import numpy as np
from PIL import Image
import torch
import torchvision.transforms as transforms
import torchvision.models
from brainscore_vision.model_helpers.activations.pytorch import PytorchWrapper
from brainscore_vi... |
62f655b26239be6fca555024fcd9d873ce919b28d00795d2885988f6c6d40a56 | Python | 4,654 | 123 | # Created by David Coggan on 2024 06 23
from brainscore_core.supported_data_standards.brainio.stimuli import StimulusSet
from brainscore_core.supported_data_standards.brainio.packaging import package_stimulus_set
import glob
import os.path as op
from brainscore_core.supported_data_standards.brainio.assemblies import D... |
a5a8cd827d17e43980e5578a653859aa4db8a106281566625532e1e80eeb5f89 | Python | 4,654 | 136 | #!/usr/bin/env python
# coding: utf-8
'''
Dependencies:
pip install SimpleITK nrrd requests matplotlib pandas cv2
chmod +x script.py
In this code we leverage the rotated resampled and aligned annotation volumes.
We have to guess the anontations in each voxel though as they were changed to an INT between 0 and 3000 f... |
63d1a6307df645935539ee118a78d0d4f2ab43746e75ee6a17064c85134a3c93 | Python | 4,655 | 139 | '''
C2H6OH
'''
import numpy as np
import sys
def intro():
print("""
SHORT List of potential energy surfaces for C2H6OH:
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... |
738e61a1614cead33bac9aefa173a2aca6dcdc36ffaf573b7317ea2378a8a669 | Python | 4,655 | 105 | from copy import deepcopy
import numpy as np
def merge(dict1, dict2):
keys = np.unique(list(dict1.keys()) + list(dict2.keys()))
keys = np.unique(keys)
res = {}
for k in keys:
all_configs = []
if dict1.get(k) is not None:
all_configs += list(dict1[k])
if dict2.get(k)... |
99c443b2db833bfcc48f3e9b90056b686605284789ddf2e82a389670177aef2c | Python | 4,655 | 113 | import torch
import torchvision
import torchvision.transforms as T
from torch.utils.data import DataLoader
import click
import h5py
import EIANN.utils as utils
@click.command()
@click.option("--data-file-path", required=True,
type=click.Path(exists=True, file_okay=True, dir_okay=False),
... |
c99e33ae41ccdf9e29698a3bdbd8c0621efaa84f74ee720148cda122b46fe105 | Python | 4,658 | 124 | """Read structure diagrams and print their SMILES.
Two ways to use the OCSR tools, both runnable from this directory:
python run_ocsr.py # call the tool directly, no agent, no LLM
python run_ocsr.py --agent # drive it through a ChemGraph agent
The direct path needs no API key. It ca... |
dd001a93c2e102c9d63cb2bae8e2ef01abfe72356ed8b8afcf6b52e76a334822 | Python | 4,658 | 124 | import os
from abc import ABC
import vtk, qt, ctk, slicer
from slicer.ScriptedLoadableModule import *
from slicer.util import VTKObservationMixin
#
# NetstimPreferences
#
class NetstimPreferences(ScriptedLoadableModule):
"""Uses ScriptedLoadableModule base class, available at:
https://github.com/Slicer/Slicer/blo... |
4c6a7ff3b51f20ab5db2214f00dc0f73ba013454072c9c50002d528106504336 | Python | 4,660 | 146 | import os
import os.path as osp
import time
import numpy as np
import torch
import torch.nn.functional as F
import pandas as pd
import json
import ijson
import torch_geometric.transforms as T
from torch_geometric.nn import ChebConv, GCNConv, Linear # noqa
from tqdm import tqdm
from sklearn.metrics import roc_auc_score... |
3f19b42dbdb1db18a7ed83a08ab8380806bf37b4c6f7abe4fb2ca54549a49993 | Python | 4,661 | 136 | #cd Desktop/GCN/pygcn/env2/
import os,csv,re
import pandas as pd
import numpy as np
import scanpy as sc
from scipy.sparse import issparse
from anndata import AnnData
import torch
from sklearn.decomposition import PCA
import math
import matplotlib.colors as clr
import matplotlib.pyplot as plt
from . models import *
cl... |
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