sha256 stringlengths 64 64 | language stringclasses 28
values | size int32 1 491k | lines int32 1 23.2k | content stringlengths 1 200k |
|---|---|---|---|---|
8afe1d6fdad42e523e5dd679b0ea19c4995a8e48520c03b44a907cdcc626669e | Python | 1,938 | 57 | # -*- coding: utf-8 -*-
# (C) Copyright 2020, 2021, 2022, 2023 IBM. All Rights Reserved.
#
# This code is licensed under the Apache License, Version 2.0. You may
# obtain a copy of this license in the LICENSE.txt file in the root directory
# of this source tree or at http://www.apache.org/licenses/LICENSE-2.0.
#
# Any... |
d34f06a981d408d29148783e0bbf206c86fe2c981bca2a661dfc5b88247c2171 | Python | 1,941 | 61 | # -*- coding: utf-8 -*-
import numpy as np
import pytest
from numpy.testing import assert_array_almost_equal
from pysteps.noise.motion import generate_bps
from pysteps.noise.motion import get_default_params_bps_par
from pysteps.noise.motion import get_default_params_bps_perp
from pysteps.noise.motion import initializ... |
cd23d7adb1ccffab7473179bde9c6d31ef9ad3631fbf7c48b4742f2c979aad9e | Python | 1,946 | 57 |
import torch
import torch.nn as nn
import torch.nn.functional as F
from torch.autograd import Variable
######################################################################
#
# Model automatically generated by modelGenerator
#
######################################################################
# ----------------... |
5b8d5197c31ce891b8d9ca8c2dc15e62b0f625c1a729e43cd51a232af6dbb1e3 | Python | 1,947 | 56 | import numpy as np
from .dataset import Datasets, Dataset
from .download import maybe_download_and_extract
import os
URL = 'https://transfer.sh/GeGJ8/m2nist.zip'
class M2NIST(Datasets):
def __init__(self, data_dir='data/M2NIST', batch_size=32, test_rate = 0.2, validation=False):
maybe_download_and_extract(U... |
2161f54231addbcfc7c68a94c4238d5d8828899708001e0fc889da30e09e1406 | Python | 1,950 | 54 | # Configuration file for the Sphinx documentation builder.
#
# This file only contains a selection of the most common options. For a full
# list see the documentation:
# https://www.sphinx-doc.org/en/master/usage/configuration.html
import os
# -- Path setup -------------------------------------------------------------... |
467560d7aeb4205b880f82a3b47fcaf9101bc2e9d96fa2c5c5c170d97e47daa1 | Python | 1,950 | 62 |
"""
MIT License
Copyright (c) 2022 Pawan Goyal
Permission is hereby granted, free of charge, to any person obtaining a copy
of this software and associated documentation files (the "Software"), to deal
in the Software without restriction, including without limitation the rights
to use, copy, modify, merge, publish, ... |
a8a60cfe56567a3fc0ca40a4710e0e4398bb633d0f85fd954ccfcd988d53b4dd | Python | 1,951 | 65 | #!/usr/bin/env python3
# Copyright 2021 Alexander Meulemans, Matilde Tristany, Maria Cervera
#
# 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
... |
7993c2071901362d7630bb1b56777050c255b2a2f232be3294a89855a5b2fb13 | Python | 1,952 | 62 | import torch
import torch.nn as nn
from ..models.base import Model
from .activation import ExU
from .activation import LinReLU
class FeatureNN(Model):
"""Neural Network model for each individual feature."""
def __init__(
self,
config,
name,
*,
input_shape: int,
... |
3718a0fa333e6be68a94ad3d3cd8b5ce136e944a4b4f28e7b18fe819029d8e14 | Python | 1,953 | 53 | import yaml
from typing import Union
from dicomanonymizer import anonymize
from .convert_to_nifti import convert_to_nifti
# from .slide_anonymizer import anonymize_slide
def run_anonymizer(
input_path: str, output_path: str, parameters: Union[str, list, int], modality: str
) -> None:
"""
This function pe... |
f491605800c8a44548de68ebb800efcbf350e5de964f7a07ffd492967c12d556 | Python | 1,955 | 49 | import torch
import torch.nn as nn
from torch_geometric.nn import TransformerConv
from network import Multi_layer_locally_feature_extraction, Nonlinear_feature_interaction
class GECNVNet(nn.Module):
def __init__(self,
GE_dim,
LF_stride,
LF_input_shape,
... |
2f0560e92deae214c68fd60563e7431894aa066087c44e19d35968cb6b2a48c4 | Python | 1,958 | 65 | #!/usr/bin/env python3
# Copyright 2021 Alexander Meulemans, Matilde Tristany, Maria Cervera
#
# 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
... |
0e5f1e9f7cbdef4db3c6fd41fed5d6418a572ce8b5d98857d855a1ef1a0568eb | Python | 1,961 | 55 | from breaststudies.models import BasicModel
import monai.networks.nets as nets
class nnUNet(BasicModel):
def __init__(
self,
in_ch,
out_ch,
roi_size,
spatial_dims=3,
kernel_size=[[1,3,3], [1,3,3], 3, 3,3],
strides= [ 1, [1,2,2], [1,2,2],2,2]... |
8cc042e8d15dada14b0d25bf85d34b8e0dd030634fbc3967ce0d944398220dd9 | Python | 1,963 | 91 | from numpy import (allclose,
append,
apply_along_axis,
isclose,
mean,
moveaxis,
sqrt,
std,
vstack,
zeros, ones, absolute)
def _fa(evals, axis=0):
... |
9282dda13d4e2891a04f89a109252b42282389ac87689449f745bd9c5c90e813 | Python | 1,963 | 59 | import os
from ._does_not_predicate import DoesNotPredicate
from ._does_predicate import DoesPredicate
from ._file_predicate import FilePredicate
from ._filter import CONTAINS_PREDICATE
from ._filter import CONTAINS_REGEXP_PREDICATE
from ._filter import ENDSWITH_PREDICATE
from ._filter import EQ_PREDICATE
from ._filte... |
e0bc63f093130d3f1d52af2a104809377c33baca136d5a1cfaab4a491a0ab66a | Python | 1,970 | 72 | ##########################################################################
### Load Fly & Worm Data and Prepare X, Y, Corr for Manifold Alignment ###
##########################################################################
import pandas as pd
from os import sys
datOrtho = pd.read_csv(sys.argv[3]) # Modencode.merged.... |
0881950c80fcc5b5ed265ce75a92d8dfdd4b2f970740b76ab241c949c3509811 | Python | 1,971 | 54 | #!/usr/bin/env python3
import unittest
import logging
import importlib
import random
import pytest
from unittest.mock import patch, MagicMock, mock_open
recon = importlib.import_module('ciftify.bin.cifti_vis_recon_all')
logging.disable(logging.CRITICAL)
class TestUserSettings(unittest.TestCase):
def test_exits... |
378a175af19e5264eb15a78e25d5f9b666a58a6b0f2426c6dc4b67a7a9c68f23 | Python | 1,971 | 60 | # -*- coding: utf-8 -*-
# (C) Copyright 2020, 2021, 2022, 2023 IBM. All Rights Reserved.
#
# This code is licensed under the Apache License, Version 2.0. You may
# obtain a copy of this license in the LICENSE.txt file in the root directory
# of this source tree or at http://www.apache.org/licenses/LICENSE-2.0.
#
# Any... |
410aefe1ae8555d90561effddddf02199affe04fec68c17e00780626b6bdac6c | Python | 1,971 | 58 | import argparse
import glob
import os
def assembly(input_pathnames, output_pathname):
with open(output_pathname, 'w') as o:
o.write('[')
for p in input_pathnames[:-1]:
with open(p, 'r') as f:
o.write(f.read())
o.write(',\n')
with open(input_pathn... |
88b1331cdc87a8c4ba29f48807b80309faf81964b870621975988f561dc4ca07 | Python | 1,974 | 57 | import torch
from torchvision import models
import numpy as np
from utils import Normalize, load_ground_truth
model_1 = models.resnet50(pretrained=True).eval()
model_2 = models.inception_v3(pretrained=True, transform_input=True).eval()
model_3 = models.densenet121(pretrained=True).eval()
model_4 = models.vgg16_bn(pret... |
f4efe24ed6d4fa08235d40a7ca04d684171bcdf65c7f3890b1146d509f78dea9 | Python | 1,974 | 52 | """ Test Time Pooling (Average-Max Pool)
Hacked together by / Copyright 2020 Ross Wightman
"""
import logging
from torch import nn
import torch.nn.functional as F
from .adaptive_avgmax_pool import adaptive_avgmax_pool2d
_logger = logging.getLogger(__name__)
class TestTimePoolHead(nn.Module):
def __init__(sel... |
2cb5bb6151805f4358f98df66caf8374d153e3577b13b7adacf345ad162e6fec | Python | 1,977 | 73 | from __future__ import division
import numpy as np
import scipy.sparse as sp
import numpy_groupies as npg
def zero_one_scale_adj(adj, scale_invariance=False):
"""Normalize adjacency matrix to interval [0, 1]. Can choose between global
or locale normalization."""
data = adj.data
if data.size == 0:
... |
05fc00f3a56bfb9980c180800a9c88183a454518e11fa2e5cf34cd6fc8f7c435 | Python | 1,978 | 31 | import scipy.ndimage
from typing import Optional, Annotated, Union
from pydantic import validate_call, ConfigDict, Field
from cellprofiler_library.types import ImageAny, ObjectSegmentation, ImageBinary
from cellprofiler_library.opts.findmaxima import BackgroundExclusionMode
from cellprofiler_library.functions.image_pro... |
94de3eaea834f663881fa5608b2cf96fed848637c0e1f5b158b7f194f0890309 | Python | 1,979 | 68 | # Copyright (C) 2014 SWIPO Project
#
# Authors (this file):
# Stefan Schinkel <stefan.schinkel@gmail.com>
"""
Weave tests to check that python and weave implementations give the same
results
"""
import numpy as np
from pyunicorn import ResNetwork
res = ResNetwork.SmallTestNetwork()
resC = ResNetwork.SmallComplexNe... |
f1346cab949c9a87c95ee992f8c11667459ed04a58557e38af32aa2da77db848 | Python | 1,980 | 66 | import torch.nn as nn
import torch.nn.functional as F
class GlobalAveragePooling2D(nn.Module):
"""
Global average pooling operation for 2D tensors.
"""
def __init__(self):
super(GlobalAveragePooling2D, self).__init__()
def forward(self, x):
"""
Forward pass for global ave... |
5b58f442b425e3c0511302f76e6cc3ad3b6a0f8f00116c95dde2c455b061477e | Python | 1,983 | 71 | import os
import shutil
import yaml
from click.testing import CliRunner
from ..cli import main
CSV_FILE_NAME = "HBCD_LORIS.csv"
YAML_FILE_NAME = "hbcd-loris.yml"
CSV_TEST_FILE = os.path.join(
os.path.dirname(__file__), "..", "example", "loris", CSV_FILE_NAME
)
YAML_TEST_FILE = os.path.join(
os.path.dirname(_... |
c1af15249c4cafd333af0ed1f38ef597d5c061bce6eb3259ac121d81d70fa342 | Python | 1,985 | 64 | import numpy as np
from numpy import pi,linspace
import cmath, random
from pylab import *
from exp_errors import *
from exp_forward_backward import *
# hamitonian for H2
g0 = -0.4804 ;
g1 = +0.3435;
g2 = -0.4347;
g3 = +0.5716;
g4 = +0.0910;
g5 = +0.0910;
Hamiltonian = g0 * tensor(qeye(2), qeye(2)) + g1 * tensor(sigma... |
6c9c1094af8b45985a2002020abecd0fc2d5dd64baecc42bbcbf3176edd7da66 | Python | 1,987 | 64 | #####################################################################################################################
# Date created : 10/21/2022
# Date modified: 10/21/2022
# Purpose : To generate features from PSSM
###############################################################################################... |
f27f39b7367b8273e41426baa38deaa0305f6ac5e965ba12ec69faad50329c65 | Python | 1,987 | 77 | #!/usr/bin/python3
import multiprocessing
autocount = multiprocessing.cpu_count
def autopooler_caller(a):
return a[0](*a[1], **a[2])
def autopooler(n,
it,
*a,
chunksize=1,
dummy=False,
return_iter=False,
unordered=False,
**ka):
"""Uses multiprocessing.Pool or multiproce... |
e12e4222187b0b2a857c1e962f446576d7705f043e469acd85e33e3a37b214fc | Python | 1,988 | 42 | from src.models.tabular.widedeep.base import WDBaseModel
from pytorch_widedeep.models import FTTransformer
class WDFTTransformerModel(WDBaseModel):
def __init__(self, **kwargs):
super().__init__(**kwargs)
def build_network(self):
self.model = FTTransformer(
column_idx=self.hparam... |
e8c6b4ad4dbdd44195fe2ab68ab636453254f801ff847003b737f965bb7c3f90 | Python | 1,989 | 55 | import argparse
import os
def get_outdir(path):
with open(path, "r") as c:
for line in c:
if "outdir" in line:
return line[line.index("=")+1:].replace("'", "").rstrip()
def read_names(path, sep="\t"):
names = set()
with open(path, "r") as f:
for line in f:
... |
52d77cfbff084be0e32410d60d1ea3691ff5dd8846a3f37e2ee49a6cbd54eb25 | Python | 1,990 | 62 | # -*- coding: utf-8 -*-
import pytest
from numpy.testing import assert_array_almost_equal
from pysteps.tests.helpers import get_precipitation_fields
from pysteps.verification import spatialscores
R = get_precipitation_fields(num_prev_files=1, return_raw=True)
test_data = [
(R[0], R[1], "FSS", [1], [10], None, 0.... |
ede8685e4c48b89a9ac8befb08eb506021ef0132d3f351bf3c02565c9d0f1a23 | Python | 1,991 | 77 |
from pyControl.utility import *
import hardware_definition as hw
# State machine.
states = ['state1', 'state2','state3', 'state4','state5', 'state6']
events = ['poke_1', 'poke_1_out',
'poke_2', 'poke_2_out',
'poke_3', 'poke_3_out',
'poke_4', 'poke_4_out',
'poke_5'... |
58c7c99284510076b62698ebf197b1fa91ccaa28acccd5279eaf47e17650605b | Python | 1,992 | 64 | import torch
from torch import nn
from .loss_interface import AbstractRegressionLoss
class CrossEntropyLoss(AbstractRegressionLoss):
"""
This class computes the cross entropy loss between two tensors.
"""
def _initialize_loss_function_object(self):
return nn.CrossEntropyLoss(reduction=self.re... |
8f19b10f3e3177b41ca08bb53019edb4cd5dcbea6dd3202e7a61997564e055e6 | Python | 2,000 | 61 | #!/usr/bin/env python3
# -*- coding: utf-8 -*-
"""
Created on Wed May 13 02:24:48 2020
@author: andrey
Code for computing spherical harmonic expansion of a magnetic field. Based on
Taulu and Kajola 2005 doi:10.1063/1.1935742, Hill 1954 doi:10.1119/1.1933682
This is a quick-and-dirty proof-of-concept. It is (a) very c... |
8e0800d5f2cfe9b34698cb16793314ded1e67165c8a1365a696568c3f7f0df52 | Python | 2,001 | 52 | """test_namesubscriber.py - test the name subscriber classes from settings"""
import unittest
from cellprofiler_core.setting.subscriber import (
ImageListSubscriber,
LabelListSubscriber,
)
class TestListNameSubscriber(unittest.TestCase):
def test_load_image_list_empty(self):
s = ImageListSubscri... |
87fc94ff05581392ef1412b1e1038360df3afae8c512c166624cb9c2154c8cc6 | Python | 2,002 | 52 | # -*- coding: utf-8 -*-
"""
@author: bartulem
Run Kilosort2 through Python.
As it stands (spring/summer 2020), to use Kilosort2 one still requires Matlab. To ensure it works,
one needs a specific combination of Matlab, the GPU driver version and CUDA compiler files.
On the lab computer, I set it up to work on Matla... |
c992525eb09c84d3f76067b78ab039ea48a73bcc10fd498fc52cbe8dfe119051 | Python | 2,003 | 74 | from prov import Error
__author__ = "Trung Dong Huynh"
__email__ = "trungdong@donggiang.com"
__all__ = ["get"]
class Serializer:
"""Serializer for PROVONE documents."""
document = None
"""PROVONE document to serialise."""
def __init__(self, document=None):
"""
Constructor.
... |
5d8d1f4daf09a10855ee77e5755a124b34c55b2ca77f629dc45c23bf11f34efd | Python | 2,005 | 62 | import matplotlib.pyplot as plt
parameters = [1, 8, 35, 150, 650, 300000] # M
relation = {'gvp': [0.6875, 0.7183, 0.7820, 0.8267, 0.8544, 0.8703],
'egnn': [0.7336, 0.7532, 0.7968, 0.8205, 0.8456, 0.8637],
'molformer': [0.3921, 0.4228, 0.4773, 0.5546, 0.6210, 0.6683]}
def ablation_cu... |
57975f5a7191791db0311440821be1cee6796eb1963f90a1a3ae7aff08bacb21 | Python | 2,006 | 61 | # -*- coding: utf-8 -*-
# (C) Copyright 2020, 2021, 2022, 2023 IBM. All Rights Reserved.
#
# This code is licensed under the Apache License, Version 2.0. You may
# obtain a copy of this license in the LICENSE.txt file in the root directory
# of this source tree or at http://www.apache.org/licenses/LICENSE-2.0.
#
# Any... |
898bd2dd3139f4d2088d727f0f8a23be99d78ba5541b85a797fa5538736c968b | Python | 2,007 | 81 | """
MedianFilter
============
**MedianFilter** reduces salt-and-pepper noise in an image while preserving
borders.
|
============ ============ ===============
Supports 2D? Supports 3D? Respects masks?
============ ============ ===============
YES YES NO
============ ============ ===============
"""... |
7ec41b26caf8d6f4de6411644af65d4c5058e7c071e3f185d33c8da3ab7264ed | Python | 2,008 | 67 | import os
from itertools import product
import numpy as np
import pkg_resources
from etspredict.job_submission import HTCSubmissionTemplate
def load_subject_list(dataset):
path = os.path.join("..", "etspredict", "data", f"{dataset}_subjects.txt")
stream = pkg_resources.resource_stream(__name__, path)
... |
f870f58bfe3719d7c0d2c4e5cdbf2d6557f08cfbbe7988f905743052f108fc8f | Python | 2,018 | 73 | """Semantic errors exposed by the Datamonger client."""
class DatamongerError(Exception):
"""Base class for expected Datamonger failures."""
class RegistryError(DatamongerError):
"""Base class for registry failures."""
class RegistryIntegrityError(RegistryError):
"""The registry bytes do not match the... |
b8c81ce4c1354a841fef3383faba8d52cdefbeff96dc2ba4371175063de62bad | Python | 2,020 | 58 | import numpy as np
from PIL import Image
import pickle
import os.path as osp
class LoadData(object):
'''
Class to laod the data
'''
def __init__(self, data_dir, dataset, cached_data_file):
'''
:param data_dir: directory where the dataset is kept
:param cached_data_file: locatio... |
b89e55b61b8f2f6ddac8462dd68168a981414a34da9995ce1c356d6617483f3b | Python | 2,023 | 49 | import os
from typing import Optional
from .reader_image_folder import ReaderImageFolder
from .reader_image_in_tar import ReaderImageInTar
def create_reader(
name: str,
root: Optional[str] = None,
split: str = 'train',
**kwargs,
):
kwargs = {k: v for k, v in kwargs.items() if v is... |
20f1866d6c19024b126447af069e522bc620ced714935a699821d00849886106 | Python | 2,024 | 67 | import os.path
from data.base_dataset import BaseDataset, get_transform
from data.image_folder import make_dataset
from skimage import io
import re
def numericalSort(value):
numbers = re.compile(r'(\d+)')
parts = numbers.split(value)
parts[1::2] = map(int, parts[1::2])
return parts
class CubeDataset... |
27f5202e1ddf7db789442616c57717862909f90fac451709c384d0eaa48ed4a6 | Python | 2,024 | 69 | import os
import glob
import shutil
from tqdm import tqdm
import pydoc
import numpy as np
import omegaconf
def flatten_dict(d, top_level_key="", sep="_"):
flat_d = {}
for k, v in d.items():
if isinstance(v, (dict, omegaconf.DictConfig)):
flat_d.update(flatten_dict (v, top_level_key=(k + sep... |
2ade2401d415b35c06b684bf704539c07b156deb1412fd0115cb90a1f4aae7ab | Python | 2,025 | 63 | # -*- coding: utf-8 -*-
# (C) Copyright 2020, 2021, 2022, 2023 IBM. All Rights Reserved.
#
# This code is licensed under the Apache License, Version 2.0. You may
# obtain a copy of this license in the LICENSE.txt file in the root directory
# of this source tree or at http://www.apache.org/licenses/LICENSE-2.0.
#
# Any... |
bcc39abbb3b5f9c8d4de2d12b1b8804bfbf25fad35e9347fffe9a5603fc166a4 | Python | 2,026 | 58 | # -*- coding: utf-8 -*-
import pytest
import numpy as np
from pysteps.utils import pca
pca_arg_values = (
(10, 10),
(20, 20),
(10, 5),
(20, 15),
)
pca_arg_names = ("len_y", "n_components")
@pytest.mark.parametrize(pca_arg_names, pca_arg_values)
def test_pca(len_y, n_components):
pytest.importo... |
3dc75a68c7f75914a5d2d68aaca64d02530c39985e712719b5e059b470133565 | Python | 2,029 | 62 | from unittest import TestCase
import numpy as np
from numpy.testing import assert_equal, assert_almost_equal
from .augment import (flip_left_right_image, random_flip_left_right_image,
adjust_brightness, random_brightness, adjust_contrast,
random_contrast)
class AugmentTes... |
56bed9cc2039dd8ce5965f75dfef71a0196690ca704415725e08fbc89b02866c | Python | 2,029 | 65 | import pandas as pd
import matplotlib.pyplot as plt
import matplotlib as mpl
import numpy as np
'''
This script generates Fig 8C from the paper.
8.11.23
GCG
'''
params = {'axes.labelsize': 8,
'axes.titlesize': 8,
'legend.fontsize': 8,
'xtick.labelsize': 8,
'ytick.labelsize'... |
652bd2b7400f4eaa80b2cc3cb65aae80f0a977819fac2ad34884c50d1e4bd5b4 | Python | 2,029 | 58 | """
ClinicalASL - Clinical Arterial Spin Labeling processing pipeline
Main pipeline script for processing ASL MRI data.
Repository: https://github.com/JSIERO/ClinicalASL
Author: Jeroen Siero
Institution: UMC Utrecht (University Medical Center Utrecht), The Netherlands
Contact: j.c.w.siero@umcutrecht.nl
Description:
... |
bbd91e6cedfde69b5c376bbb984859b10bbaab743be09ff6fd69ca793c515d78 | Python | 2,031 | 65 | # coding=utf-8
"""CellProfilerGUI package
The CellProfilerGUI package holds the viewer and controller portions
of the cell profiler program
"""
import sys
BV_DOWN = "down"
BV_UP = "up"
def draw_item_selection_rect(window, dc, rect, flags):
"""Replacement for RendererNative.DrawItemSelectionRect
window - d... |
317f5b87295967d40e5204fda9c20f99b39367db40643444b6fc11653c40f282 | Python | 2,032 | 42 | ## Run:
# python preprocess_raw_data.py -n_jobs 40 -data db5 -graph_nodes residues -graph_cutoff 30 -graph_max_neighbor 10 -graph_residue_loc_is_alphaC -pocket_cutoff 8
# If you want to use less DIPS data, then: python preprocess_raw_data.py -n_jobs 60 -data dips -graph_nodes residues -graph_cutoff 30 -graph_max_neighb... |
b2dc6c12b52cba5dd12a238285e6b2f841a2334c9feb8d8642c1659f098cab47 | Python | 2,033 | 65 | import os
import numpy as np
import pkg_resources
from ptpython.ipython import embed
from etspredict.data.hcp_aging_pheno.load import load_hcp_aging_pheno
from etspredict.data.hcp_ya_pheno.get_data import load_behavioural_data
def load_subject_list(dataset, sc=False):
path = os.path.join("..", "etspredict", "d... |
adc334c7337875e54dce2af695f60363ef8f139c0268eb2048f9dde774bbcbd5 | Python | 2,036 | 82 | import numpy
import numpy.random
import pytest
import cellprofiler_core.image
import cellprofiler_core.measurement
from cellprofiler_core.constants.measurement import M_LOCATION_CENTER_X, FF_COUNT, M_LOCATION_CENTER_Y, \
M_LOCATION_CENTER_Z, M_NUMBER_OBJECT_NUMBER
import cellprofiler.modules.convertimagetoobjects... |
6ff9a9322529d1c7409f2bf8c38d21ecb0cd8557d8190b91359212c118aa66ae | Python | 2,037 | 48 | class Config:
def __init__(self):
#################################################################
# settings for train and eval
#################################################################
# set the npy or csv data path here
self.patho_path = ''
self.no... |
b123302388de67762755b76786b571591175a83101512b6746534780097649ff | Python | 2,037 | 88 | # 20 standard amino acids
# https://www.ncbi.nlm.nih.gov/Class/MLACourse/Modules/MolBioReview/iupac_aa_abbreviations.html
_aa_standard = [
('ALA', 'A'),
('ARG', 'R'),
('ASN', 'N'),
('ASP', 'D'),
('CYS', 'C'),
('GLN', 'Q'),
('GLU', 'E'),
('GLY', 'G'),
('HIS', 'H'),
('ILE', 'I'),
... |
bffc6cc49086fa8f296077150ece85538586851cc1977758b9b112c2d7736a07 | Python | 2,038 | 82 | #
# nate berry
# 2023-04-01
#
# ---------------------------------------------------------
# NOTES:
# - this file contains a variety of parameters needed
# throughout the processing of the EEG and COM data.
#
# ---------------------------------------------------------
import numpy as np
# smapling frequency ... |
dbc4e7e925e9888cac9ea273c8eb9cfcbfe98ca1b6b4a00a711608f720ecc1e1 | Python | 2,042 | 63 | from packaging.version import Version
import cellprofiler_core.constants.pipeline
import cellprofiler_core.measurement
import cellprofiler_core.pipeline
import cellprofiler_core.utilities.core.pipeline
from cellprofiler_core import __version__ as core_version
def dump(pipeline, fp, save_image_plane_details, sanitize... |
66833d8df37a69d1c7a7a264536a91efb98a8ee350ee0a3c63ec5196caf239a9 | Python | 2,045 | 65 | import cellprofiler_core.setting
from ._does_not_predicate import DoesNotPredicate
from ._does_predicate import DoesPredicate
from ._filter import CONTAINS_PREDICATE
from ._filter import CONTAINS_REGEXP_PREDICATE
from ._filter import ENDSWITH_PREDICATE
from ._filter import EQ_PREDICATE
from ._filter import STARTS_WITH_... |
3ce2780af9ad949c0e4694667c7b03847c64c2b26d704300cb006d46fb9d6cb3 | Python | 2,046 | 79 | """
GaussianFilter
==============
**GaussianFilter** will blur an image and remove noise. Filtering an
image with a Gaussian filter can be helpful if the foreground signal is
noisy or near the noise floor.
|
============ ============ ===============
Supports 2D? Supports 3D? Respects masks?
============ ============... |
e32970f776bfd7dd476e4f1319ebaa9198eb3043b209672c79d24d3bf231d374 | Python | 2,046 | 64 | from pathlib import Path
from rdflib.namespace import RDF, RDFS
from nidm.core import Constants
from nidm.experiment.Utils import _rdflib_graph_from_prov_graph, read_nidm
def _fixture_path(*names):
base = Path(__file__).resolve().parent / "data" / "read_nidm"
for name in names:
p = base / name
... |
78cc5db5f4db806d7c996f1206853b014f9f99a016ceb1d4be7f35916b437604 | Python | 2,047 | 54 | import subprocess
import shutil
import os
"""
Versions are built from PyPi rvt-py.
First from PyPi we build win-64 for each python version.
Then from win-64 version we create versions for other platforms (for each python version).
"""
BUILDS_DIR = "./rvt-py_builds" # Builds for each python version
PLATFORM_BUILDS_DI... |
f9ed125490496a74f667710d9709944b1feb9ac323254975ca7e651680d03b1c | Python | 2,047 | 62 | import torch.nn as nn
class DownsamplingModule(nn.Module):
def __init__(
self,
input_channels,
output_channels,
conv=nn.Conv2d,
conv_kwargs=None,
norm=nn.BatchNorm2d,
norm_kwargs=None,
act=nn.LeakyReLU,
act_kwargs=None,
):
"""
... |
7ec586646874bb1ee5063a0dd04ad340bbf0464620fc8a2d74cac5ec69fddc24 | Python | 2,052 | 66 | """
"""
import subprocess
import psutil
import shutil
import os
tmp_input_dir = 'tmp_inputs'
tmp_output_dir = 'tmp_outputs'
cfmid4_folder = '$HOME/cfmid4'
def split_file(mfile, num):
with open(mfile) as infp:
if os.path.exists(tmp_input_dir):
shutil.rmtree(tmp_input_dir... |
cd93fba1e710de62c808570456c4fc4ad235b206bd3b6cdb7002cf8adf2074e0 | Python | 2,052 | 65 | from qutip import*
import numpy as np
from qutip.qip.circuit import QubitCircuit, Gate
from qutip.qip.operations import phasegate, rx, gate_sequence_product, cnot, sqrtswap, csign
from scipy import optimize,integrate
list = [ [[1,3], [2,3], [1,4], [2,4]],
[[3,5], [4,5], [3,6], [4,6]] ] ;
depth = 3 ;
width =... |
13a82873a56ebb22c03c1197f0e8117ba4e46cbb71d1888eec0944e49ec695cc | Python | 2,053 | 81 | from Bio import SeqIO
import os
import sys
box_size = "12"
# this code aligns a protein sequence alignment reference to the wild type sequence in the CNN output
def get_reference_from_CNN_data(name):
aaCodes = {'ALA':'A', 'ARG':'R', 'ASN':'N', 'ASP':'D', 'CYS':'C', 'GLN':'Q', 'GLU':'E', 'GLY':'G', 'HIS':'H', 'ILE'... |
cef151fb57c762f2742926fb47d191c63e6c2ccc430e0cc3eb661a21b78e7d0f | Python | 2,057 | 65 | """ Tools for working with NIDM-Experiment files """
import os.path
import click
from nidm.experiment.Utils import read_nidm
from nidm.experiment.tools.click_base import cli
# adding click argument parsing
@cli.command()
@click.option(
"--nidm_file_list",
"-nl",
required=True,
help="A comma-separated... |
11571a75e03ec5c5a86e43af257afabbfbcaa73b473aa6156fd44eee43521dbe | Python | 2,058 | 69 | from pathlib import Path
from typing import Union
import tifffile
from imctools.data import Session
from imctools.data.acquisitiondata import AcquisitionData
from imctools.io.utils import OME_TIFF_SUFFIX, SCHEMA_XML_SUFFIX, SESSION_JSON_SUFFIX
class ImcParser:
"""IMC folder parser."""
def __init__(self, in... |
9ed7c5163a306f10365e51e473aceffbf866c4346278c71eb9d43d380f6733b7 | Python | 2,058 | 66 | from qutip import*
import numpy as np
from qutip.qip.circuit import QubitCircuit, Gate
from qutip.qip.operations import phasegate, rx, gate_sequence_product, cnot, sqrtswap, csign
from scipy import optimize,integrate
list = [ [[1,3], [2,3], [1,4], [2,4]],
[[3,5], [4,5], [3,6], [4,6]] ] ;
depth = 3 ;
width =... |
8242377afac827d04007c41d664456c32d4ae0bbe40e1e071f619e032a6b9242 | Python | 2,059 | 56 | # -*- coding: utf-8 -*-
import numpy as np
import pytest
from pysteps.tests.helpers import get_precipitation_fields
from pysteps.verification.salscores import sal
from pysteps.utils import to_rainrate, to_reflectivity
test_data = [
(to_rainrate, 1 / 15),
(to_reflectivity, None),
]
@pytest.mark.parametrize(... |
8e153485173d8d3d0ab340dd5850bf096486f6e16fc1f87664fcf266d1c03266 | Python | 2,060 | 60 | import os
import sys
import numpy as np
sys.path.insert(0, os.path.dirname(__file__))
from PIL import Image
from handlers import model_builder
from utils import utils
# config
_BASE_MODEL_NAME = 'MobileNet'
_ROOT = os.path.dirname(__file__)
_AESTHETIC_WEIGHTS_FILE = os.path.join(
_ROOT, 'models', _BASE_MODEL_N... |
b16797d65aa792f26357822eb8a0649dc7e8aa6e6f9bc032f9755b2ec4ec00b1 | Python | 2,060 | 45 | from src.models.tabular.pytorch_tabular.base import PTBaseModel
from src.models.tabular.pytorch_tabular.repository.models.autoint.autoint import AutoIntModel
from omegaconf import DictConfig
class PTAutoIntModel(PTBaseModel):
def __init__(self, **kwargs):
super().__init__(**kwargs)
def build_network... |
dc6b18cacf04b3716a87a67eb00ea45d894555832298d07b4e0dbbcf94291f74 | Python | 2,060 | 44 | from src.models.tabular.pytorch_tabular.base import PTBaseModel
from src.models.tabular.pytorch_tabular.repository.models.node.node_model import NODEModel
from omegaconf import DictConfig
class PTNODEModel(PTBaseModel):
def __init__(self, **kwargs):
super().__init__(**kwargs)
def build_network(self)... |
fe540d7462a2e9031b3c3a941a5fa9ad37c1a89043e65d71109b3044336ac156 | Python | 2,062 | 81 | """ Norm Layer Factory
Create norm modules by string (to mirror create_act and creat_norm-act fns)
Copyright 2022 Ross Wightman
"""
import functools
import types
from typing import Type
import torch.nn as nn
from .norm import (
GroupNorm,
GroupNorm1,
LayerNorm,
LayerNorm2d,
LayerNormFp32,
La... |
26a63bff6b8573e1826d8679214c49940348151eb1d219dd805dd4acbeab32e0 | Python | 2,063 | 59 | import numpy as np
class HH:
def __init__(self, v_init=-65.0, n_init=0.3177, m_init=0.0529, h_init=0.5961):
self.v = v_init
self.n = n_init
self.m = m_init
self.h = h_init
self.C = 1.0
self.g_Na = 120.0
self.g_K = 36.0
self.g_L = 0.3
self.E_Na... |
81ee575238405b8b92f5ead4f841f6af00719375751cec774abc791b7bb23c10 | Python | 2,063 | 78 | import numpy as np
from coeff import Coeff
from grid import Grid
from scipy import sparse
from scipy.sparse import linalg
from matplotlib import pyplot as plt
import time
import pandas as pd
from concurrent.futures import ProcessPoolExecutor
import os
bulk_A = 1.0
def simulation(sigma):
#start and end poten... |
01df67d271d480c427d27f5048c1df22f0e4b809116f9457f69a61b7a12e7e67 | Python | 2,068 | 64 | import tempfile
import os
import h5py
import numpy
from deeprank.domain.amino_acid import cysteine, serine
from deeprank.features.gnomad import __compute_feature__, AF_FEATURE_NAME
from deeprank.models.environment import Environment
from deeprank.models.variant import PdbVariantSelection
def test_dbnsfp():
env... |
aa9863885f753a42dcda9cb43114b4c2cf39f64c2634627e9dd59fdf5d4b9f23 | Python | 2,070 | 53 | #!/usr/bin/env python
from rgbmatrix import RGBMatrix, RGBMatrixOptions
from PIL import Image
import urllib2 as urllib
import io
from samplebase import SampleBase
class StillViewer(SampleBase):
def __init__(self, *args, **kwargs):
super(StillViewer, self).__init__(*args, **kwargs)
self.parser.add_a... |
14dbf1bee9ae59d4ed4789d5375817941929a8735fcc52c3fcb7e7c7651eeab0 | Python | 2,071 | 41 | import glob
import cv2 as cv
import numpy as np
from models.epu import EPUNet
from models.subnetworks import Subnet
from tensorflow.keras.optimizers import SGD
from tensorflow.keras.callbacks import LearningRateScheduler, EarlyStopping
train = [cv.imread(img) for img in glob.glob("../data/banapple/train/*.jpg")]
trai... |
04a357eec86b115e3a12420f144c37e418a7eb5e4e2f6bb4356c17703b92d7d4 | Python | 2,072 | 75 | """Instantiate Flask and set up plugins."""
import os
from flask import Flask
from flask_migrate import Migrate
from afidsvalidator.config import (
DevelopmentConfig,
ProductionConfig,
TestingConfig,
)
from afidsvalidator.model import db, login_manager
from afidsvalidator.orcid import orcid_blueprint
fro... |
b1cce62f9bf6a9631108e1b76751548408b30dc4c71233a38c5d19a5089cac5c | Python | 2,072 | 66 |
"""
MIT License
Copyright (c) 2022 Pawan Goyal
Permission is hereby granted, free of charge, to any person obtaining a copy
of this software and associated documentation files (the "Software"), to deal
in the Software without restriction, including without limitation the rights
to use, copy, modify, merge, publish, ... |
4e9abbde166c133fda385c65b1a72e8f7f65d49a439e51ecf25499ed97680799 | Python | 2,074 | 74 |
from torch.utils.data import DataLoader
from torch.utils.data import Dataset
import torch
import pdb
from typing import Any
class WDNDataset(Dataset[Any]):
"""Dataset for processed WDN data."""
def __init__(
self,
data_path: str,
sample_ids: int,
include_leak_area: bool = F... |
2a4563dbf37e5c3afd9a3857e08f2e03d9e58f87d6a9b1f38baf2099d289069c | Python | 2,077 | 73 | import torch
import torch.nn as nn
import os
import tifffile
import numpy as np
from model import UNet
from dataset import *
from config import *
from torchvision import transforms
from collections import OrderedDict
dirc_data = args.dirc_data
dirc_ckpt = args.dirc_ckpt
dirc_result = args.dirc_result
if not os.path.ex... |
d3859c692ce098fa51a91289146b89c8212e0c75febe25a827e2b4fe3c337e8b | Python | 2,077 | 78 | import numpy as np
from coeff import Coeff
from grid import Grid
from scipy import sparse
from scipy.sparse import linalg
from matplotlib import pyplot as plt
import time
import pandas as pd
from concurrent.futures import ProcessPoolExecutor
import os
bulk_A = 1.0
def simulation(sigma):
#start and end poten... |
db9e501fef859d7c974a8b40c79888f70fbda2c502d03c36dd0e90cf3e99a199 | Python | 2,078 | 75 | #!/usr/bin/env python
from evaluate_results import pearson_confidence
from matplotlib import pyplot as plt
from math import sqrt
import numpy as np
plt.switch_backend("agg")
# Generate a figure showing the relationship between correlation, number of datapoints and
# the confidence interval
def generate_points(r_s... |
dff26e415e33482f1a4a453d1e495322e02747bbf1efc8c8dfbb3b020e82e4a3 | Python | 2,081 | 58 | import numpy as np
from numpy import pi,linspace
import cmath, random
from pylab import *
from training_data import *
from forward_backward import *
eps = 0.15 ; iters = 60;
def mean_fidelity(X):
total_fidelity = 0 ;
for i in range(size_train):
phiout, _ = forward_th(X, train_psi[i]) ;
t... |
f5ae43cdd465b192ca4316c86a06df3ab02adfe6a1a6304972619c477f9c135d | Python | 2,081 | 52 | ### list of npy file
import glob
import random
import numpy as np
import os
train_flist_main1 = []
valid_flist_main1 = []
test_flist_main1 = []
random.seed(259)
save_path = "./five_cross_valid"
nii_path = "data_prepro"
npy_path = "./five_cross_valid"
subj_ad = glob.glob(os.path.join(nii_path,"FLAI... |
8ad576ec1ce1edaf5eaf75ac7a79edbe59f308cd192c1c355de9edb38fb0b807 | Python | 2,084 | 58 | import torch.nn as nn
import sys
import torchvision
import traceback
def brainage(parameters):
"""
This function creates a VGG16-based neural network model for brain age prediction.
Args:
parameters (dict): A dictionary containing the model parameters, including:
- model: a sub-dictio... |
f1b642dc09d0bf7be952b3529cbbdc73fb3413e3fadd76eb7f032fece64d8ede | Python | 2,084 | 40 | from typing import Annotated, Optional
from pydantic import Field, validate_call, ConfigDict
from cellprofiler_library.opts.correctilluminationapply import Method
from ..types import Image2D
from ..functions.image_processing import apply_divide, apply_subtract, clip_low, clip_high
@validate_call(config=ConfigDict(arb... |
81cb88d77e11f9ccb48d34295da6f289999367cc392b19574162aa3475c90966 | Python | 2,085 | 59 | import matplotlib.pyplot as plt
import torch
def strength_order_training(data='qm7', n_sample=10, fontsize=28):
J_ = []
for data in ['qm7', 'qm8', 'hamiltonian', 'newtonian']:
J_.append(torch.load(f'../save/J_{data}_egnn.pt'))
fig, ax = plt.subplots(1, 4, figsize=(32, 7))
plt.rcParams.updat... |
3a9d48133cb2d742d62c9bfd8bf7cf09df073274f8a6a3d170e7545138918a73 | Python | 2,091 | 65 | import os
from collections import namedtuple
import torch
import torch.nn as nn
from sklearn.metrics import classification_report
from torch.optim import Adam
from tqdm import tqdm
from data import DataIterator
from loss import FocalLoss
from model import CNN
from torchtext import data, vocab
from args import get_ar... |
bf0b1e061360563cf442521508c951c42fb7bc2b850c47bbd66162c2a837ada8 | Python | 2,095 | 38 | from torch.utils.data import DataLoader
from asteroid.data import LibriMix, WhamDataset
from .utils import MultiTaskDataLoader
def make_dataloaders(corpus, train_dir, val_dir, train_enh_dir=None, task="sep_clean",
sample_rate=8000, n_src=2, segment=4.0, batch_size=4, num_workers=None,):
if c... |
6da65deae4d16442907648ae05a5f379a534d05ac7f7f65f289fe02ebe17174c | Python | 2,096 | 60 | '''
behavior for Barbosa, Stein et al. (Nat Neuro, 2020)
created by H Stein, Mar 2020
input: ../data/behavior.pkl
output: ./serial_bias.pkl
'''
import numpy as np
import scikits.bootstrap as boot
import pandas as pd
import pickle
import sys
sys.path.insert(0, '../../helpers/')
import heike_helpers as hf
#########... |
23980fb66cff450dc23e59690798813b4c0be5e078f91d9a86fa030a6d8b81e8 | Python | 2,105 | 72 | """
Convert TIFs of selected markers into pixel x markers matrix
Author: Candace Liu
Date: 3/18/21
"""
import pandas as pd
import numpy as np
import os
import matplotlib.pyplot as plt
from PIL import Image
import scipy.ndimage as ndimage
# sigma for Gaussian blur
s = 2
# Markers for clustering
markers = ["Abeta","A... |
bf6f18ad22db287e4f8d03377c4df5b7f0928729252222d1d85ad342e7e2b1ac | Python | 2,105 | 63 | """
Generate a plot of noise vs R and number of sensors for regularly-spaced barbutes
"""
import numpy as np
from mayavi import mlab
import matplotlib.pyplot as plt
from megsimutils.arrays import BarbuteArraySL, noise_max
N_SENS_RANGE = np.arange(135, 241, 5)
R_RANGE = np.linspace(0.15, 0.25, 20)
#N_SENS_RANGE = np.... |
d04b97fa42b4664fde108943cd0c464f06b6b033103c9a5d4bfc6ccbbefc4455 | Python | 2,107 | 82 | from ._module import Module
from ..image import Image
from ..setting.subscriber import ImageSubscriber
from ..setting.text import ImageName
class ImageProcessing(Module):
category = "Image Processing"
def create_settings(self):
self.x_name = ImageSubscriber(
"Select the input image", doc=... |
8c30dcab453af3458bd61daad0853cebad9ee861a8da764e87be46e3a45b70c0 | Python | 2,109 | 51 | import numpy as np
import torch
class EarlyStopping:
"""Early stops the training if validation loss doesn't improve after a given patience."""
def __init__(self, patience=7, verbose=False, delta=0, path='checkpoint.pt', trace_func=print):
"""
Args:
patience (int): How long to wait a... |
72e3ea506ac571321f853ebb940c699f2c2df2df72ae5ab21d497ac23af5f2aa | Python | 2,111 | 56 | import os
from pathlib import Path
from typing import Optional
from GANDLF.compute import create_pytorch_objects
from GANDLF.config_manager import ConfigManager
from GANDLF.utils import version_check, load_model, optimize_and_save_model
def post_training_model_optimization(
model_path: str, config_path: Optional[... |
88c8b784bb9948ef51e3d617f8b2d20b1b266b52b775f1314b9a135f0984d83d | Python | 2,112 | 62 | import os
from manifest import prepare_manifest, test_json_files
from allensdk.core.brain_observatory_cache import BrainObservatoryCache
def get_boc_json_files(manifest_file):
# We need 'base_uri' until all of the data is publicly released
boc = BrainObservatoryCache(manifest_file=manifest_file, base_uri="ht... |
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