sha256 stringlengths 64 64 | language stringclasses 28
values | size int32 1 491k | lines int32 1 23.2k | content stringlengths 1 200k |
|---|---|---|---|---|
2d4079fe4c871e9d3f25bcb1ab7254b2bcad6b7f808858f01f4ea0a389cf78af | Python | 2,761 | 41 | #! /usr/bin/env python
from lab.parser import Parser
def add_absolute_and_relative(parser, attribute, pattern):
parser.add_pattern(attribute, pattern + ' (\d+) .+', required=False, type=int)
parser.add_pattern(attribute + '_rel', pattern + ' \d+ \((.+)\)', required=False, type=float)
parser = Parser()
pars... |
5e12cce0bb3eec58abedbfac50259ff2f5ba71b4d1889a03f3a1712733b819a5 | Python | 2,761 | 68 | import sys, os
import numpy as np
import pandas as pd
import pickle
from scipy.io import loadmat, savemat
import concurrent.futures
sys.path.append('/m/cs/scratch/networks-pm/effects_externalfactors_on_functionalconnectivity/src/analysis')
from utils import get_behav_data_15days
#####################################... |
3605bfc54a14a9c0468c616bd951eb91815e8d5a9e026c2c192bbf7c641bdfce | Python | 2,762 | 83 | """distutils.command.install_data
Implements the Distutils 'install_data' command, for installing
platform-independent data files."""
# contributed by Bastian Kleineidam
import os
from ..core import Command
from ..util import change_root, convert_path
class install_data(Command):
description = "install data fi... |
05348d079232d4c5709175e9365749c91a60c4cda85a10b178e0321d92af15c8 | Python | 2,763 | 65 | import torch
import torch.nn as nn
import torch.nn.functional as F
class GRU(nn.Module):
r'''
A simple but effective gate recurrent unit (GRU) network structure from the book of Zhang et al. For more details, please refer to the following information.
- Book: Zhang X, Yao L. Deep Learning for EEG-Based B... |
24668b003178b9f143e6ac61b96be08da4ad894f1fcb4a6f43d8a852397b6b56 | Python | 2,763 | 73 | import numpy as np
from scipy.stats import norm
from nilearn.masking import apply_mask, unmask
# from nilearn.image import new_img_like, smooth_img
# import scipy
# from scipy.ndimage import label
def hoyer_sparseness(x: np.ndarray, axis: int = 0) -> np.ndarray:
"""
Calculate sparseness of x over given axis.
... |
b6b13e290f58a91ed6aae6e69c71dd3403f41cd1040eb7a39ebac1aed8d85384 | Python | 2,763 | 80 | import torch
import torch.nn as nn
from ..initializer import create_initializer
class Network(nn.Module):
def __init__(self, config):
super().__init__()
model_config = config.model.vgg
self.use_bn = model_config.use_bn
n_channels = model_config.n_channels
n_layers = model... |
e59be5fe362d48f830aa44ea584a7abb998c284b5c3929a79f454e35a43d0957 | Python | 2,763 | 79 | #! /usr/bin/env python3
import os
import subprocess
import logging
import APT_interface
class cd :
"""Context manager for changing the current working directory, and automagically changing back when done"""
def __init__(self, path):
self.path = path
def __enter__(self):
self.old_path = ... |
ee490e9785a2f4ea9bc79c7e80feaa264b7c0a2fd6e169cec9a8a1ec2e7354df | Python | 2,763 | 69 | import torch
import numpy as np
import time
from src.Liver_Glycogen_Phantoms.src_nn.Network import Network
from src.Liver_Glycogen_Phantoms.src_nn.utilities import *
from torch.autograd import Variable
class NOEMRFReconstruction:
def __init__(self):
self.device = check_cuda()
self.dtype = torch... |
1c5218175ca8a5ebb0bf83f8106f9dde6e4596504615a1ca1cd49e3fe3766061 | Python | 2,764 | 92 | """
Author: David Kappel
Copyright (C) 2024, by the author.
See the LICENSE.txt file for more information.
Code snoopies:
run the pairing protocol of Graupner and Brunel 2012
Calcium-based plasticity model explains sensitivity ofsynaptic changes
to spike pattern, rate, anddendritic locati... |
600ee29d7e81dd88bfbc1a90034acb6d07c10aa3b6f7b1fdbf355fd21be55846 | Python | 2,764 | 83 | # coding=utf-8
# Copyright 2026 The Google Research Authors.
#
# 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 applicab... |
aa9d77b3bd9cef10e5f3c5f0fdd897a5e65ff422d03670da1d8e47b33f91b001 | Python | 2,765 | 123 | import os as _os
# project structure
ROOT_DIR = _os.path.dirname(_os.path.abspath(__file__))
RESULTS_DIR = _os.path.join(ROOT_DIR, 'results/')
DATA_DIR = _os.environ.get("REY_FIGURE_DATA")
RESOURCES_DIR = _os.path.join(ROOT_DIR, 'resources/')
# architectures
REYCLASSIFIER_3 = 'rey-classifier-3'
REYCLASSIFIER_4 = 'rey... |
dc1e73e41c95b37982dfaeb08955d6cc5386bc590b1a2d9c132bf439946e0d69 | Python | 2,765 | 112 | ##
import tensorflow as tf
import PoseUNetAttention
reload(PoseUNetAttention)
from poseConfig import aliceConfig as conf
import PoseTools
tf.reset_default_graph()
self = PoseUNetAttention.PoseUNetAttention(conf)
self.train_unet(False,0)
## create the d
import tensorflow as tf
import PoseUNetAttention
reload(PoseUN... |
564806d64c8461e64c6db864f22e1a303a0799865c32bf20764750dcbd3063d8 | Python | 2,766 | 86 | from sockjs.tornado import SockJSConnection, SockJSRouter
from tornado import web, ioloop, httpserver
from collections import OrderedDict
import threading
import sys
import json
import numpy as np
import os
class Controller:
"""Simple class to set & get points from neuroglancer
"""
state = {}
clients ... |
26d76318e91aff26ea5a7bf312cdb2fe2c121b591dd7a3f170eaa1c4deeb6c57 | Python | 2,767 | 85 | import pytest
import torch
from elasticai.creator_plugins.lutron_filter.nn import Binarize
from elasticai.creator_plugins.lutron_filter.precompute.truth_table_generation import (
generate_input_tensor_1d as generate_1d_input_tensor,
)
from elasticai.creator_plugins.lutron_filter.tensor_conversion import (
torch... |
427fad94897425b38fff7bd222a5a69b7577f558f7c375178b53effb9e3b0fe5 | Python | 2,767 | 92 | # EyeNED OCT-ONH segmentation and feature extraction
# Copyright (C) 2024 Erasmus MC
# This program is free software: you can redistribute it and/or modify
# it under the terms of the GNU Affero General Public License as published
# by the Free Software Foundation, either version 3 of the License, or
# (at your optio... |
84676322ac504fb9053ae252de7caf1f93b4d9f1f5261728390c94b45e817a9f | Python | 2,767 | 74 | """
toposampling - Topology-assisted sampling and analysis of activity data
Copyright (C) 2020 Blue Brain Project / EPFL & University of Aberdeen
This program is free software: you can redistribute it and/or modify it under the terms of the GNU Affero General Public License as
published by the Free Software Foundation... |
547d2fb89fedd6e8d2e0362eabaf1dba1deb3b0a56ec34d6bf3c26b9103572c6 | Python | 2,768 | 82 | # flake8: noqa
# There's no way to ignore "F401 '...' imported but unused" warnings in this
# module, but to preserve other warnings. So, don't check this module at all.
# Copyright 2021 The HuggingFace Team. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use thi... |
80dffab41400c6896306b6ef445ba2645f2d39beee01ef4c6b012d5d21a79faf | Python | 2,768 | 96 | import os
import textwrap
import time
from typing import NoReturn
import optuna
from optuna.artifacts import FileSystemArtifactStore
from optuna.artifacts import upload_artifact
from optuna.trial import TrialState
from optuna_dashboard import ChoiceWidget
from optuna_dashboard import register_objective_form_widgets
fr... |
14128c8997eeaf163c1ae845ae90f69b271480b2145ed4dab69c729913bf3d54 | Python | 2,769 | 87 | from typing import Dict
from skimage import transform
import numpy as np
from abc import ABC
from abc import abstractmethod
"""
This module contains tools for measuring and correcting chromatic aberrations.
"""
class ChromaticCorrector(ABC):
"""
An abstract class for color-specific image transformation.
... |
1deec84ae7951cf46d69ea08860843f8eb550312004fa8ef08b8721c2e61da9e | Python | 2,769 | 120 | """
We thank CASIA IVA for sharing his code 'https://github.com/junfu1115/DANet'
that we have build our code on top.
"""
import numpy as np
import torch
import torch.nn as nn
from torch.autograd import Variable
class CAM_Module(nn.Module):
""" Channel attention module """
def __init__(self, in_dim):
... |
271ea71b526cf896aafb24cd614f0c17d17ecdec69f3b8fe282e902fa6967831 | Python | 2,769 | 75 | import matplotlib
matplotlib.use("Agg")
import torch
device = torch.device("cuda" if torch.cuda.is_available() else "cpu")
from utilities.script_func import init, post, ScikitFeat_pre
import pickle
import logging
logging.info("")
def main():
import Models.models as Models
import Models.model_func as Model_F... |
b76a8f1bb3b5b2f871773efa40fa556639a30622f99949db65b08b55b33aad20 | Python | 2,769 | 80 | import torch
from torch import nn
class BaseObserver(nn.Module):
def __init__(self):
super().__init__()
self.forward_num = 0
def update_float_range(
self, running_min_float: torch.FloatTensor, running_max_float: torch.FloatTensor
):
raise NotImplementedError
@torch.no... |
1ac0833880e943b7ea5a8a452660e4e0716a3422188509075235d395b45f0908 | Python | 2,770 | 78 | """Test sequence constructors contained in the package."""
import pytest
from console.interfaces import Dimensions
from console.utilities import sequences
@pytest.mark.parametrize("use_sinc", [True, False])
def test_se_spectrum(use_sinc: bool):
"""Test spin echo spectrum constructor."""
seq = sequences.se_sp... |
b502f49c65682d4a0b53ba7d3bcb25604715a5926a63e3a845cbbd90833faaed | Python | 2,771 | 96 | import numpy as np
import torch
from torch import nn
def gaussian_filter(sigma, s=11, dims=2):
dim = s//2
ranges = np.arange(-dim, dim+1)
if dims == 2:
xx,yy = np.meshgrid(ranges, ranges)
elif dims == 3:
xx,yy,zz = np.meshgrid(ranges, ranges, ranges)
d = xx**2 + yy**2
d = d +... |
a977f6253277f039b05c5fffcd84849ff1aa9a4631ee9d0bf7a38e7d5f559f03 | Python | 2,774 | 77 | def update_param(name, param):
if name == 'data_leakage_handling':
param['values'] = ["leave_one_out", "k_fold", "none", "LeaveOneOut", "KFold", "None"]
return param
return None # param untouched
extensions = dict(
validate_params="""
if (!missing(columns_to_encode))
columns_to_encode <... |
e36430a6deec8a13096f30ecf4bc9b70189ce72b983b99142cbda677d0a3ddd3 | Python | 2,774 | 67 | from optparse import OptionParser
### help and usage ###
usage = "usage: %prog [options] args"
description = '''Function: calculate the total number of pairwise differences between sequences from two populations '''
version = '%prog 08.08.2021'
parser = OptionParser(usage=usage,version=version, description = descript... |
478ec7a6918fd6c4e148b2a5b799ea14d337dbca73b2f1504f4e5ac4ecfd2776 | Python | 2,775 | 63 | # regtools/registration/gui/orient_overlay.py
"""Orient a 2D image AND its points through the identical transform pipeline.
Used by the Preview2DDialog points overlay. Mirrors the dialog's order
(tissuecyte -> rotate -> flip_h -> flip_v) so points stay on the same pixels as
the image by construction. Points are (... |
935198669b7108befeab33cbacf7c94081e206df42cd3a7de38e881251a6e96f | Python | 2,776 | 69 | """Functions to get and use HED queries."""
import pandas as pd
from hed.models import QueryHandler
def get_query_handlers(queries, query_names=None) -> tuple[list[QueryHandler | None], list[QueryHandler | None], list]:
"""Return a list of query handlers, query names, and issues if any.
Parameters:
... |
5d11ae5fd208526d39e1b38e6ecc060c26cc9f579e0bae9f0b750aecbe1445e2 | Python | 2,777 | 73 | import SimpleITK as sitk
from tiffile import imwrite
from coarse import *
from utils import genFileName, getTformPath
def warpSingle(tform_path: str, f_vol_move:str, n_channel:int, sitkTile=sitkTile()):
'''
warp a single (specified) channel in the specified image
'''
res = [0.1625, 0.1625, 0.2500]
... |
a3954bb307f8823756d3cc79c62392b6aea17700db1aeff8a396ac24b4156569 | Python | 2,778 | 83 | #!/usr/bin/env python3
# -*- coding: utf-8 -*-
"""
Created on Wed Mar 10 15:37:42 2021
@author: eveshalom
"""
from matplotlib import pyplot as plt
import numpy as np
from scipy import ndimage as ndimage
def checkROIs(Ea,Ev):
plt.rcParams.update({'font.size':18})
fig,[ax1,ax2] = plt.subplots(1,2,figsize=(20,10... |
9ac3c75b5e1a178b57acf8903cbe13547f2812ceed139309a3cc41819c8712a1 | Python | 2,779 | 102 |
import modiscolite
import numpy as np
import h5py
import click
######################################################################
# Script modified from one written by Han Yuan, Calico Labs
######################################################################
##########
# inputs #
##########
@click.command()... |
d0bbc98fb9c0d75ce17da491b7961210ed254fd2a890fb0872c7a66a47c909f6 | Python | 2,779 | 80 | from __future__ import print_function
import torch.utils.data as data
import os
import os.path
import torch
import numpy as np
import sys
def gen_modelnet_id(root):
classes = []
with open(os.path.join(root, 'train.txt'), 'r') as f:
for line in f:
classes.append(line.strip().split('/')[0])
... |
130805352a9768582553964f4a444b20261aea7041e3be42242b0fb9ae30db0c | Python | 2,780 | 69 | import numpy as np
import os.path as path
import matplotlib.pyplot as plt
from utils.utils import visualize_traces
from single_nrn_tune.param_generator import nrn_init, syn_exp, simulation
if __name__ == '__main__':
cell_name = 'AWAL'
sti_info = {
"dt": 0.4,
"tstop": 7000,
"v_init": -8... |
9f98cf868535e564b011f9efb7dcef17ad8edaf8ccbfbfad850802632f64ff23 | Python | 2,782 | 80 | import scipy.integrate
import autograd.numpy as np
from autograd import make_vjp
from autograd.builtins import tuple
from autograd.extend import defvjp_argnums, primitive
from autograd.misc import flatten
odeint = primitive(scipy.integrate.odeint)
def grad_odeint(yt, func, y0, t, func_args, **kwargs):
# Extende... |
39da001dbe675e999b204657d616934b4c638a30dc76b0ae9e93091390a7584b | Python | 2,783 | 81 | from importlib.util import find_spec
import anndata as ad
import numpy as np
import pytest
import scipy.sparse as sp
from pertpy.tools._differential_gene_expression._checks import check_is_integer_matrix, check_is_numeric_matrix
if find_spec("formulaic_contrasts") is None or find_spec("formulaic") is None:
pytes... |
2651743265ba4200a1aeb18f3e3e8a0132e21bfa42df124fdf1b3ef1929521ca | Python | 2,784 | 72 | #! /usr/bin/env python
from lab.parser import Parser
parser = Parser()
parser.add_pattern('ms_final_size', 'Final transition system size: (\d+)', required=False, type=int)
parser.add_pattern('ms_construction_time', 'Done initializing merge-and-shrink heuristic \[(.+)s\]', required=False, type=float)
parser.add_patter... |
0a2e1ba8a9c6ffcd1840e4800cf9779fefa990ae4244a38df0f4f8e257a59460 | Python | 2,785 | 91 | # \file TestSegmentationPropagation.py
# \brief Class containing unit tests for module SegmentationPropagation
#
# \author Michael Ebner (michael.ebner.14@ucl.ac.uk)
# \date May 2017
import unittest
# Import libraries
import SimpleITK as sitk
import numpy as np
import os
import pysitk.simple_itk_helper as sitkh... |
3edfdf624e06a5857f1f1f962c3e040d655a34a0075c3092b823881c4558790f | Python | 2,785 | 64 | # -*- coding: utf-8 -*-
import tensorflow as tf
class gEKF():
"""
gradient-based EKF, this should be equivalent with EKF, but faster
Args:
learning_rate: learning rate
epsilon: scale initial guess for P matrix
q_0: initial process noise
q_tau: time constant for noise
... |
e1f42e23abf46ac93e266e19dff452de6c1719ddf10851f7044449b159d9aabb | Python | 2,785 | 100 | from pathlib import Path
from types import SimpleNamespace
import numpy as np
import pytest
from calvados import components as components_module
from calvados.cfg import Components, Config
from calvados.components import Protein, RNA
from calvados.sim import Sim
TEST_DATA = Path(__file__).parent / "data"
def _mak... |
36e0fb72d6c5edf1f392762a15fe3b902fee2b1903bdff19bbad2e43c2f1c8a8 | Python | 2,787 | 60 | # Copyright 2020 Division of Medical Image Computing, German Cancer Research Center (DKFZ), Heidelberg, Germany
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# ht... |
f5405b9a91df9e84b99e242ae65b4f760bd965cc177dbcbc767ff765c2f9c691 | Python | 2,787 | 98 | from enum import Enum, auto
class ActionIfExists(Enum):
"""
Action to take if a statement with a property already exists on the entity.
APPEND_OR_REPLACE: Add the new element to the property if it does not exist, otherwise replace the existing element.
FORCE_APPEND: Forces the addition of the new ele... |
0a41b59516fd4d7a80ccac48b0ea2b96f33d64c0a54e1f0a56151c60da311463 | Python | 2,788 | 90 | import numpy as np
import os
from dimensions.bowls.dimensions import BOWL, BOWL_PROPERTIES
from dimensions.cups.dimensions import CUP, CUP_PROPERTIES
from perception_tools.common import get_models_path
from pybullet_tools.utils import create_obj, apply_alpha
# in_off = 0.0025 m
SCALE = 0.01 # Units are in cm
MODELS... |
0afebd92aac5391bb06f5235a307be231c8ad1900d8aba868222f2c5c6129c12 | Python | 2,788 | 92 | """
distutils.command.install_egg_info
Implements the Distutils 'install_egg_info' command, for installing
a package's PKG-INFO metadata.
"""
import os
import sys
import re
from ..cmd import Command
from .. import dir_util
from .._log import log
class install_egg_info(Command):
"""Install an .egg-info file for... |
8d373b33fd8035c258f7ea5143345dd54f211cf69ef4f1d66746e44e858a6c88 | Python | 2,788 | 70 | from torch.utils.tensorboard import SummaryWriter
from datetime import datetime
class TensorboardWriter(object):
def __init__(self, log_dir, logger, enabled):
self.writer = None
if enabled:
log_dir = str(log_dir)
# Retrieve vizualization writer.
succeeded = Fa... |
44e2995e51cecb5ac6a6d764a567196ef83600257083fd366186dd69b5c305c4 | Python | 2,789 | 86 | import numpy as np
import tqdm
import os
file_path = os.path.realpath(__file__)
script_folder = os.path.dirname(file_path)
package_folder_path = os.path.dirname(script_folder)
"""
Preprocessing for the SO(2)/torus sampling and score computations, truncated infinite series are computed and then
cached to memor... |
62574476036f117db5efd616b09bbe521724225172144837d9cc6a11aa6328d8 | Python | 2,789 | 60 | # Copyright 2020 Division of Medical Image Computing, German Cancer Research Center (DKFZ), Heidelberg, Germany
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# ht... |
3db4fa47624c19de414aa187203101e8099322fe252f7973fdbaa808081124fe | Python | 2,790 | 93 | import os
from pathlib import Path
from setuptools import find_packages, setup
def read(filename: str) -> str:
"""
Read a UTF-8 file relative to this setup script.
Parameters
----------
filename : str
Relative path to the file.
Returns
-------
str
File contents.
... |
81e0a28f9276a42e77ad387b087686f0ed2fbfa7a50066a86acd84280275935e | Python | 2,790 | 98 | # coding=utf-8
# Copyright 2026 The Google Research Authors.
#
# 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 applicab... |
a5d1be589bffdcdd843974d2e466ee8da57dd390cd61864a44d755d1d3292d9f | Python | 2,790 | 89 | """Pre-fitted linear model coefficients.
Port of defineLinearModelCoefficients.m
"""
from dataclasses import dataclass
@dataclass
class LinearCoefficients:
"""Coefficients for the linear photoreceptor model."""
sc_fact: float # Scaling factor
tau_r: float # Rising time constant (sec)
tau_d: float... |
4b6aefc00c371b5f09f005bf5ba01599e8215f0b7bddc43427c19e1d1ad4799d | Python | 2,791 | 80 | from molecularnodes.nodes.geometry import StyleCartoon, StyleRibbon, StyleSpheres
def join_nodes(tree):
return [n for n in tree.tree.nodes if n.bl_idname == "GeometryNodeJoinGeometry"]
def branches(tree):
"The nodes feeding the tree's final join"
return [link.from_node for link in join_nodes(tree)[0].in... |
567bf45375f7419fd7c543e705e481551eedbf89d28c418e6c49755c50d79fa8 | Python | 2,791 | 79 | # coding: utf-8
__author__ = 'ZFTurbo: https://kaggle.com/zfturbo'
if __name__ == '__main__':
import sys
import os
# For this test, make sure that only the tested framework is available
sys.modules['tensorflow'] = None
sys.modules['torch'] = None
gpu_use = 0
print(f"GPU use: {gpu_use}")
... |
83246104e6b25c42f2deffdc863ac84b53083b6ae5d82f28d1b2fcbcaa2da348 | Python | 2,791 | 94 | ##
# \file slice_coverage.py
# \brief Class to visualize slice coverage over reconstruction space
#
# \author Michael Ebner (michael.ebner.14@ucl.ac.uk)
# \date Feb 2019
#
import numpy as np
import SimpleITK as sitk
##
# Class to visualize slice coverage over reconstruction space
# \date 2019-02... |
9a350a1de3798edface5c5495074a090ee9c9a734d6d3f5564971332ba672cb7 | Python | 2,791 | 74 | import torch
import torch.nn as nn
import torch.nn.functional as F
def conv3x3x3(in_planes, out_planes, stride=1):
"""3x3x3 convolution with padding"""
return nn.Conv3d(in_planes, out_planes, kernel_size=3, stride=stride, padding=1, bias=False)
class BasicBlock(nn.Module):
expansion = 1
def __init__(... |
9ec290f6ae5b4cfddb133180238da510d7d5bf7e73a507ab050ac0a31d18568e | Python | 2,791 | 79 | # coding: utf-8
__author__ = 'ZFTurbo: https://kaggle.com/zfturbo'
if __name__ == '__main__':
import sys
import os
# For this test, make sure that only the tested framework is available
sys.modules['jax'] = None
sys.modules['tensorflow'] = None
gpu_use = 0
print(f"GPU use: {gpu_use}")
... |
ff02c0b554cae10f6a28913a7d021352b406cade8267b2bf20c16fee487565ea | Python | 2,791 | 72 | """Implementation of nexus acquisition manager for multiprocessing."""
import traceback
from collections.abc import Callable
from multiprocessing.managers import BaseManager
from types import TracebackType
from typing import Any
from console.spcm_control.acquisition_control import AcquisitionControl
# Alias required ... |
06126cf85bff06b615b2bafc37eae84591155ed5e039e3e347740e427ad7d006 | Python | 2,793 | 68 | import pytest
from pathlib import Path
from hmp import io
from hmp import simulations
import numpy as np
import hmp
from test_io import init_data
@pytest.fixture
def fixt_init_data():
return init_data()
@pytest.mark.parametrize("n_comp,whiten,reject_threshold,min_duration,max_duration", [
(5, True, None, Non... |
2a043bf462c2e2826a05c54717f90291ddc8739918b7cf74fedc3eb199433dd1 | Python | 2,793 | 81 | import data_mnist
import matplotlib.image
import matplotlib.pyplot as plt
import autograd.numpy as np
import autograd.numpy.random as npr
def load_mnist():
partial_flatten = lambda x: np.reshape(x, (x.shape[0], np.prod(x.shape[1:])))
one_hot = lambda x, k: np.array(x[:, None] == np.arange(k)[None, :], dtype=... |
80970a8e88e890e0cfccf3039bb2981062c2bc96addefedae6b438e62bb150c3 | Python | 2,793 | 80 | import numpy.testing as npt
import pytest
from pertpy.tools._differential_gene_expression import EdgeR
try:
from rpy2.robjects.packages import importr
r_dependency = importr("edgeR")
except Exception: # noqa: BLE001
r_dependency = None
pytestmark = pytest.mark.skipif(r_dependency is None, reason="Requi... |
d0e6970e3aa486bbf4061eccab29320db2574528fd5bc4ae1fdc2598c02725a9 | Python | 2,793 | 89 | import string
from functools import partial
from os.path import dirname, join
import autograd.numpy as np
import autograd.numpy.random as npr
from autograd import value_and_grad as vgrad
from autograd.scipy.special import logsumexp
def EM(init_params, data, callback=None):
def EM_update(params):
natural_... |
59060d932be0f8ca396d5543607593af310568a15fb8c3f0a9154e0c1d099f5e | Python | 2,795 | 41 | """
FREEZE_DELTA_ALL_TYPES.py written 2026-09-23, BEFORE any transcriptomic data was opened.
The 17 Sept frozen list is the top of a continuous ranking: for every cell type, how much more
ambiguous the classifier is on it than on matched control types (`delta`). The transcriptomic
test (04-NOTES/PREREG-2026-09-... |
c4977b5ea26cfb4f42281525f3638aa6320eb7584e04b14c78dab43ba135f63c | Python | 2,795 | 30 | import os
import shutil
path = os.path.join(os.path.dirname(__file__), "../param/cell")
print(path)
files= os.listdir(path)
AIYL_list = ["I1L","I1R","I2L","I2R","I3","I4","I5","I6","NSML","NSMR","DVA","AINL","AINR","AIML","AIMR","RIH","URBL","URBR","RIR","AIYL","AIYR","AIAL","AIAR","AUAL","AUAR","AIZL","AIZR","RIS",... |
0aaba32bd0d0002872ef70aecf354c9f73ed42c635d35452cc9eb6180b8f408c | Python | 2,796 | 77 | # -*- coding: utf-8 -*-
from __future__ import annotations
from collections import Counter, defaultdict
from typing import Iterable, Tuple, Union
class Vocab(object):
r"""
Defines a vocabulary object that will be used to numericalize a field.
Args:
counter (~collections.Counter):
:c... |
8a50ea575546eec6888f65be1a48179a5106607e6eb8bf1441e22b99d41e6e87 | Python | 2,796 | 89 | """Elastic constants recipes for EMT."""
from __future__ import annotations
from typing import TYPE_CHECKING
from quacc import flow
from quacc.recipes.common.elastic import elastic_tensor_flow as elastic_tensor_flow_
from quacc.recipes.emt.core import relax_job, static_job
from quacc.wflow_tools.customizers import c... |
35efb56e2e6d9c30ae66f4ddf3933ba69dee89411329866c4d271b5fcdd79792 | Python | 2,798 | 76 | # coding=utf-8
# Copyright 2026 The Google Research Authors.
#
# 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 applicab... |
8dca5cac131678ca6784f1c6619b30b912181b13b5651e180237c1a74dfdba98 | Python | 2,798 | 82 | import h5py
import numpy as np
import torch
from torch.utils.data import DataLoader, TensorDataset
import torch.nn as nn
import torch.optim as optim
class Autoencoder(nn.Module):
def __init__(self, encode_layer=30, info_layer=1, quantum_number_later=1):
super(Autoencoder, self).__init__()
self.in... |
b3abadef4d992bf8bb30084bb9045ade749ac7baf5f520deecc165ded56b1a38 | Python | 2,799 | 65 | from __future__ import annotations
from functools import cached_property
from typing import Literal
import pandas as pd
from ._metadata import MetaData
class Cytokine(MetaData):
"""Cytokine response signatures of human PBMCs from the Human Cytokine Dictionary."""
@cached_property
def dictionary(self) ... |
f09ea006a4ae04cbb5198e61307a56ea7e330804e5ce09fea0828764cd18f326 | Python | 2,799 | 108 | from unittest import TestCase
import numpy as np
import matplotlib.pyplot as plt
from soundsig.sound import plot_spectrogram
from soundsig.incrowd import fast_conv
from soundsig.strfs import fit_strf_lasso, fit_strf_ridge, strf_conv, make_toeplitz
class TestFitStrf(TestCase):
def setUp(self):
pass
... |
cfdf73fd2cb2c1c27e303cd0ba53a0dbdfe6eb8a96e3191b85725d5593f4d852 | Python | 2,800 | 81 | # Copyright (c) 2020, Ko Sugawara
# All rights reserved.
#
# Redistribution and use in source and binary forms, with or without
# modification, are permitted provided that the following conditions are met:
#
# 1. Redistributions of source code must retain the above copyright notice,
# this list of conditions and t... |
10ab6fc7e703c5af5aeae3fdd848175494919662bf75d1eed96d48bc3eb4d8a6 | Python | 2,801 | 81 | # coding=utf-8
# Copyright 2026 The Google Research Authors.
#
# 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 applicab... |
2ea402dc1d8ecca881bd0b34f75f9c53af4ddf7e5740e82d555ddf30c52e377c | Python | 2,801 | 102 | # coding=utf-8
# Copyright 2026 The Google Research Authors.
#
# 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 applicab... |
5f827e5fac05249d14de5ec9a4a01ca002e3c7200f471961b798c4ad421905c9 | Python | 2,801 | 63 | """Helper functions that build the translation model with a corroponding graph and session."""
from collections import namedtuple
import tensorflow as tf
from cddd import models
from cddd import input_pipeline
def build_models(hparams, modes=["TRAIN", "EVAL", "ENCODE"]):
"""Helper function to build a tran... |
3971dae07c3533d5154e5ef39e3c3ba2313f1ba50565d34ab18c3e7455703ffc | Python | 2,802 | 91 | from collections import OrderedDict
import hypothesis.strategies as st
import torch
from hypothesis import given
from torch.nn import Linear, ReLU, Sequential
import elasticai.creator.torch2ir.default_handlers as t2ir_handlers
from elasticai.creator.ir2torch import Ir2Torch
from elasticai.creator.ir2torch.default_han... |
4e685775ef485407daf3b59ab2511998e555b405c63d05c3a780cd6c87eed159 | Python | 2,802 | 50 | """
OXASL - Module to generate additional ROIs for analysis
Copyright (c) 2008 University of Nottingham
"""
import numpy as np
from fsl.data.image import Image
from fsl.data.atlases import AtlasRegistry
from oxasl import reg
def run(wsp):
"""
Generate additional ROIs used for reporting and region analysis
... |
181eae45716578dbaa37c9f71f6f51ce11a43a1ac54ff4bee56415448df0ec40 | Python | 2,803 | 91 | from itertools import product
from .core import make_jvp, make_vjp, vspace
from .wrap_util import get_name, unary_to_nary
TOL = 1e-6
RTOL = 1e-6
def scalar_close(a, b):
return abs(a - b) < TOL or abs(a - b) / abs(a + b) < RTOL
EPS = 1e-6
def make_numerical_jvp(f, x):
y = f(x)
x_vs, y_vs = vspace(x),... |
2062f005e48c475ad27171b037e32fda9634439440c5970f110d4111ea5fa02f | Python | 2,803 | 93 | import json
import numpy as np
import torch
import torch.nn as nn
import torch.nn.functional as F
from pathlib import Path
from ..prixfixe.predictor import Predictor
from .utils import n2id, revcomp
class AutosomePredictor(Predictor):
def __init__(self,
model: nn.Module,
model... |
2b4dfd7d8c09d49bad0e7a99ac8fabc5a8c6257f30bf1544192678e19dda2b61 | Python | 2,803 | 91 | import pandas as pd
import numpy as np
import scipy.io
import h5py
import os
os.environ['TF_CPP_MIN_LOG_LEVEL'] = '3'
import multiprocessing
from math import ceil
import vae_model as VAE
from vae_model import vae_model
from utils import onehot_test_label
def ICVAE_harmonize(HDF5):
file = h5py.File(HDF5, 'r')... |
c9f3e84188626c08e06c58cd3fa79266b46bdfe09f9c38b33b149343f413fa0b | Python | 2,803 | 59 | """Single source of truth for in-plane image rotation.
Counting (cellpose) and registration both rotate sections to orient them. They
historically used *different* primitives - ``np.rot90`` (90° steps only) in the
counting path and ``scipy.ndimage.rotate`` (arbitrary angle) in registration -
which let the two sta... |
6df35f33a657091adce6778a701ce08ad5b1a72f8006be24de1eca0c532651f4 | Python | 2,804 | 68 | """Tests for the report's light / dark / system theme toggle."""
import json
from regtools.registration.report import build_html_report
from regtools.registration.report.assets import _CSS, _JS
from regtools.registration.report.render import _THEME_HEAD_JS, _THEME_TOGGLE_HTML
def _build(tmp_path):
met... |
96de17f6139377f5525f4a6d13299cce3caa10d69de1c86a60127e264c5d7f94 | Python | 2,804 | 88 | from torch import Generator
from torch.utils.data import DataLoader
from pathlib import Path
from ..prixfixe import DataProcessor
from .utils import (preprocess_df,
DataloaderWrapper)
from .dataset import SeqDatasetProb
class AutosomeDataProcessor(DataProcessor):
def __init__(
... |
aa3510adef61d546d7e1468ecdc2ef435dd4b592bee8ed96aea3395c07fea30a | Python | 2,806 | 77 | """
Specifies parameters common to different individual tomogram (synapse)
processing scripts in order to make setting up multiple scripts easier.
This file is normally placed in another directory at the seme level as this
on (e.g. ../common). Scripts that need to use parameters defined here need
to import this scri... |
b9fd17423e057a15d4432e85ea8fbe7549bf8b6aa3e459a4b6d6f85798a2ef9b | Python | 2,806 | 76 | import numpy as np
import scipy.sparse as sp
import torch
import torch.nn as nn
import torch.nn.functional as F
import math
def sparse_or_dense_dropout(x, p=0.5, training=True):
if isinstance(x, (torch.sparse.FloatTensor, torch.cuda.sparse.FloatTensor)):
new_values = F.dropout(x.values(), p=p, training=tr... |
e62f9e0797e73867b5b49ec42f18de8f87173a24b452366f5fcc51dbe6cae371 | Python | 2,806 | 80 | #! /usr/bin/env python
# ==============================================================================
# Copyright (c) 2020, Ko Sugawara
# All rights reserved.
#
# Redistribution and use in source and binary forms, with or without
# modification, are permitted provided that the following conditions are met:
#
# 1. Re... |
0cfe4a746956e80f8aaf30088c1d096ca2910832d2ac8dc08bd864f65e77460a | Python | 2,807 | 96 | #!/usr/bin/env python
import defopt
import sys
import logging
from pathlib import Path
from typing import Optional
from cyvcf2 import VCF, Writer
from tqdm import tqdm
def add_phasing_format_to_header(vcf):
vcf.add_format_to_header(
dict(ID="PS", Number=1, Type="Integer", Description="Phase set identifier... |
a26b2f9230ade95b3d3b2023e045fd421c487af37815f41b1a90977d0bb0f8a8 | Python | 2,807 | 100 | # -*- coding: utf-8 -*-
import logging
import os
from logging import FileHandler, Formatter, Handler, Logger, StreamHandler
from typing import Iterable, Optional
from supar.utils.parallel import is_master
from tqdm import tqdm
def get_logger(name: Optional[str] = None) -> Logger:
logger = logging.getLogger(name... |
08d97303d555462f0f8498530b35d6ad51ce99d123421a8cb63b6125dabce9c0 | Python | 2,808 | 113 | #!/usr/bin/env python3
# -*- coding: utf-8 -*-
"""
Created on Tue Nov 2 09:59:40 2021
@author: leupinv
"""
import os
import platform
platform.system()
# define starting datafolder
if platform.system()=='Darwin':
#os.chdir('/Users/leupinv/switchdrive/BBC/WP1/data/EEG/tsk/')
os.chdir('/Volumes/BBC/BBC/WP1/... |
90e786d24d226e6f4528ca298024efb095c5ea604a6bc348f7fcc6701c545fda | Python | 2,808 | 38 | """This is an example to show how to interact with GhostInMesh offline"""
from os import path
from eworm.ghost_in_mesh_sim.pre_interaction import *
if __name__ == "__main__":
# data_path = path.join(path.dirname(__file__), "output", "find_circuit",
# "11-01-1928_active_0.1_1.0_0.000010_0.... |
ccfb293729c694edfde597865fc3c84121efb5707cdaa47e043fca498b8a7ca3 | Python | 2,808 | 113 | import matplotlib
import numpy as np
matplotlib.use("agg")
import matplotlib.pyplot as plt
from meep.materials import SiO2
import meep as mp
resolution = 100 # pixels/um
dpml = 1.0
pml_layers = [mp.PML(thickness=dpml)]
r = 1.0 # radius of cylinder
dair = 2.0 # air padding thickness
s = 2 * (dpml + dair + r)
ce... |
7637b9157ac16aa36a2423342fccd86ecd387c5a21cc595fcfa420ded6c94690 | Python | 2,809 | 72 | import torch
import torch.nn.functional as F
from torch.nn import Parameter
from net.brainmsgpassing import MyMessagePassing
from torch_geometric.utils import add_remaining_self_loops,softmax
from torch_geometric.typing import (OptTensor)
from net.inits import uniform
class MyNNConv(MyMessagePassing):
def __ini... |
d3bb501f558672131b92f6fd0b39968f47f3eb4e5b6195c4f3d2f8ba802b1790 | Python | 2,809 | 30 | """POST HOC confirmation of AL_FIX on Shiu's exact v630 matrix: S vs F4-like (every AL LN inhibitory except bench
acetylcholine) vs K_LN+ (excitatory AL LNs silenced). Only AL LNs whose root id is unchanged v630->v783 can be typed
(306 of 429); the other 123 keep Shiu's sign, so this is a partial fix. Output 06-OUTPUT/... |
d8dd118e87d685e9421a8f94a65d0aeab0e89aad7a0f13d63f8696b32bfad1ef | Python | 2,809 | 79 | ##
# \file residual_evaluator_test.py
# \brief Test ResidualEvaluator class
#
# \author Michael Ebner (michael.ebner.14@ucl.ac.uk)
# \date November 2017
import os
import unittest
import numpy as np
import re
import SimpleITK as sitk
import pysitk.python_helper as ph
import niftymic.base.stack as st
import nifty... |
48b3e762b39ec083e603e3a059d79d4b200424f1895f72d74bed3fbb7dc49314 | Python | 2,811 | 78 | from unittest import TestCase
from codex.utils.parsing import tokenize, extract_links
class Test(TestCase):
def test_tokenize(self):
self.assertEqual(["1", "2", "3"], tokenize("'1', '2', '3'"))
self.assertEqual(["hello", "world"], tokenize("hello world'"))
self.assertEqual(["who's", "home... |
c8f28d2d9ed3533d500dc70bbcb44411513c67663e2826087e006943701dae1c | Python | 2,811 | 72 | """A single event process with starting and ending times."""
from hed.errors.exceptions import HedFileError
from hed.models.hed_group import HedGroup
from hed.models.model_constants import DefTagNames
class TemporalEvent:
"""A single event process with starting and ending times.
Note: the contents have the... |
2673d6acceaa4a64bff6363704ec2ba447a844cd5e4fbab09a17cd552d132cdf | Python | 2,812 | 82 | # coding=utf-8
# Copyright 2026 The Google Research Authors.
#
# 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 applicab... |
f26d3c51be78f741f88d0e8b617bc5cac1ad80aa0ab0751ddb31ff8bcfd39d5c | Python | 2,812 | 82 | ######################## BEGIN LICENSE BLOCK ########################
# The Original Code is mozilla.org code.
#
# The Initial Developer of the Original Code is
# Netscape Communications Corporation.
# Portions created by the Initial Developer are Copyright (C) 1998
# the Initial Developer. All Rights Reserved.
#
# Con... |
2c756e2471a5f6f131c87d2575640a6514dacaa5a398be12196dad4eaee0111d | Python | 2,813 | 106 | from __future__ import annotations
from pathlib import Path
import numpy as np
import pytest
from ase.atoms import Atoms
from ase.build import bulk, molecule
from ase.calculators.emt import EMT
from ase.io import read
from numpy.testing import assert_allclose
from quacc.atoms.core import (
check_is_metal,
ge... |
8640dd03dc4e094d86a249135c253ea2a4a2fb7dd1a120c92c0bbf56e971ad24 | Python | 2,813 | 85 | import torch
import torch.nn as nn
import torch.nn.functional as F
import numpy as np
class ConvBlock(nn.Module):
def __init__(self, in_channels, out_channels, kernel_size, pool_size, dropout):
super().__init__()
self.conv = nn.Conv1d(in_channels=in_channels, out_channels=out_channels, kernel_size... |
13a9536e18d3081fedd559075c1f982ed5afbe57ff187841a51278879c02b0be | Python | 2,814 | 67 | """Main module for training the translation model to learn extracting CDDDs"""
import os
import sys
import argparse
import json
import tensorflow as tf
from cddd.model_helper import build_models
from cddd.evaluation import eval_reconstruct, parallel_eval_qsar
from cddd.hyperparameters import add_arguments, crea... |
315cfec0ad068d5ace37255c737ace2151aadafb0cd67618b53b4fad5ac39fba | Python | 2,815 | 89 | import click
import pandas as pd
import json
import numpy as np
from collections import OrderedDict
from prediction import max_value, weighted_mean
transformation = {
"maxvalue" : max_value,
"weightedmean" : weighted_mean
}
# options
@click.command()
@click.option('--predicted',
'pre... |
c4b65c4d9f47ff2d0e850fddd5f7aff0c36632fcc9b61be6a4fd3299e123c9a9 | Python | 2,815 | 83 | # flake8: noqa
# There's no way to ignore "F401 '...' imported but unused" warnings in this
# module, but to preserve other warnings. So, don't check this module at all.
# Copyright 2020 The HuggingFace Team. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use thi... |
533c6dfd80f5848bc1d405b99b1b7a215721b791bbd7602d32a768e7550c8664 | Python | 2,816 | 79 | """Primary application entrypoint.
"""
import locale
import logging
import os
import sys
import warnings
from typing import List, Optional
from pip._internal.cli.autocompletion import autocomplete
from pip._internal.cli.main_parser import parse_command
from pip._internal.commands import create_command
from pip._intern... |
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