sha256 stringlengths 64 64 | language stringclasses 28
values | size int32 1 491k | lines int32 1 23.2k | content stringlengths 1 200k |
|---|---|---|---|---|
c3a7e5bc4089fea387540bf8f119795bda5a998889b0ead62a75e506f94b8798 | Python | 3,652 | 88 | """
Author: Mingjian He <mh1@stanford.edu>
Testing functions for the dOsc algorithm in somata/oscillator_search/decomp_osc.py
"""
from somata.oscillator_search import DecomposedOscillatorModel as DecOsc
from somata import OscillatorModel as Osc
from test_load_data import _load_data # type: ignore
import numpy as np
... |
e4ffd0f3053b6a605e54060193d6cff4ad89f5abc5119308524dbb9624818d84 | Python | 3,652 | 111 | # TODO Sep 08 version
from __future__ import print_function
import os
import tarfile
import requests
from warnings import warn
from zipfile import ZipFile
from bs4 import BeautifulSoup
from os.path import abspath, isdir, join, basename
class GetData(object):
"""A Python script for downloading CycleGAN or pix2pix ... |
a5602c8effc5122a27ce89fae54c2513ebf5244331d7a1e766cc07d895b7a70e | Python | 3,654 | 116 | """
pysteps.feature.blob
====================
Blob detection methods.
.. autosummary::
:toctree: ../generated/
detection
"""
import numpy as np
from pysteps.exceptions import MissingOptionalDependency
from scipy.ndimage import gaussian_laplace
try:
from skimage import feature
SKIMAGE_IMPORTED = ... |
89836cf3c2243655bc3d571e752c98d1ac2a80393617df3dab5c04794d82cb98 | Python | 3,656 | 121 | # -*- coding: utf-8 -*-
"""
pysteps.visualization.tstorm
============================
Methods for plotting thunderstorm cells.
Created on Wed Nov 4 11:09:44 2020
@author: mfeldman
.. autosummary::
:toctree: ../generated/
plot_track
plot_cart_contour
"""
import matplotlib.pyplot as plt
import numpy as... |
7d3f602c23984da9444a7195949a2d35b11ff034ba8789f333f2d61e907a481e | Python | 3,658 | 87 | builtin_modules = {
"calculatemath": "CalculateMath",
"calculatestatistics": "CalculateStatistics",
"classifyobjects": "ClassifyObjects",
"closing": "Closing",
"colortogray": "ColorToGray",
"combineobjects": "CombineObjects",
"convertimagetoobjects": "ConvertImageToObjects",
"convertobje... |
83ee0cf3628b44f0ce01a60cab9ec4a1c0ffe830162d482256be73af6f163b7a | Python | 3,661 | 95 | from tempfile import mkdtemp
from shutil import rmtree
import os
import numpy
import h5py
from nose.tools import eq_, ok_
from deeprank.domain.amino_acid import amino_acids
from deeprank.models.variant import PdbVariantSelection, VariantClass
from deeprank.operate import hdf5data
def test_group_name():
variant1... |
4d9329623ccf5c3f24a0e741ee4a242584ad41c7cccd00f4cff372b31beec70a | Python | 3,662 | 124 | #!usr/bin/env python
# -*- coding: utf-8 -*-
import argparse
import os
import yaml
from typing import Optional
import click
from deprecated.classic import deprecated
from GANDLF.cli import copyrightMessage, split_data_and_save_csvs
from GANDLF.entrypoints import append_copyright_to_help
from GANDLF.utils import logg... |
b1120cfd82bcaecfaddea7ebff7d2cad880eafe4f9d864428137b300872c2272 | Python | 3,663 | 126 | import torch
import torch.nn as nn
import torch.nn.functional as F
class InceptionModule(nn.Module):
def __init__(
self,
input_channels,
output_channels,
Conv,
Dropout,
InstanceNorm,
dropout_p=0.3,
leakiness=1e-2,
conv_bias=True,
inst... |
083cb72fad9c53393fd6e789a750bfb4977bf37a936db9eac121b2d2789ba019 | Python | 3,664 | 106 | import csv
import math
import sys
import os
# This program takes in aa acid frequencies at each position from raw CNN output.
'''
1) Calculate the entropy and n-eff for each position
2) Save to csv file
'''
def get_entropy(freq_list):
sum = 0
for freq in freq_list:
freq = float(freq)
sum += freq * (1 if... |
a9a8047d7627d907e3f76226cf27f3b645a02d7580988066202cd4ed227d1560 | Python | 3,666 | 98 | from ._setting import Setting
from ._validation_error import ValidationError
class Joiner(Setting):
"""The joiner setting defines a joining condition between conceptual tables
You might want to join several tables by specifying the columns that match
each other or might want to join images in an image se... |
08dde908b8f4089c208ac17d5411b6763c7f1aa6e945f1ab45d22469be7ad9a3 | Python | 3,671 | 129 | import logging
import pickle
from ._setting import Setting
from ._validation_error import ValidationError
LOGGER = logging.getLogger(__name__)
class ImagePlane(Setting):
"""A setting that specifies an image plane
This setting lets the user pick an image plane. This might be an image
file, a URL, or a p... |
03060eba161e213afa10598489002d3da6bc584b4f8cd1ba48a0f1cfc2e265bd | Python | 3,672 | 79 | """Validate descriptive processing history without applying transformations."""
from __future__ import annotations
import re
from collections.abc import Mapping
from typing import Any
from datamonger._errors import UnsupportedRegistryError
from datamonger._validate import require_array, require_mapping, require_stri... |
c5c9dab02495e9e2f93e105c2418f8c7ac6bc5551509c03c1ac8446adea38887 | Python | 3,681 | 87 | import sys
from argparse import ArgumentParser
import logging
import pytorch_lightning
import torch
workspace_path = '/mnt/netcache/bodyct/experiments/airway_labeling_t7828/bronchial'
print("We add {} into python path for module lookup.".format(workspace_path))
sys.path.append(workspace_path)
from pytorch_lightning.s... |
5d49f11c153a12d74d3d89a6dfcf4059c23f9c23f2ddaaf2322314acd4fda95a | Python | 3,682 | 93 | # -*- 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... |
7a35d42212cd8d1cd379b17eeee098525b8aee3c883433a92dedb284e29a7098 | Python | 3,683 | 106 | from typing import Tuple
import torch
import torchio
def handle_nonempty_batch(subject: dict, params: dict) -> Tuple[dict, int]:
"""
Function to detect batch size from the subject an Opacus loader provides in the case of a non-empty batch, and make any changes to the subject dictionary that are needed for GaN... |
7177ed4e7f9efd7afa17c555e6594aae831f2d8284d65d46ee2f3d36541e4280 | Python | 3,684 | 122 | import numpy as np
from torchio.transforms import (
OneOf,
RandomMotion,
RandomGhosting,
RandomSpike,
RandomAffine,
RandomElasticDeformation,
RandomBiasField,
RandomSwap,
RandomNoise,
RandomAnisotropy,
RandomFlip,
RandomGamma,
)
from .blur_enhanced import RandomBlurEnhan... |
26e65b72c83d1984e72cee2549fb70aee6a4cbe44a744dfd76b8eecd2627b077 | Python | 3,685 | 98 | """
ClinicalASL - Clinical Arterial Spin Labeling processing pipeline
ASL T1-from-M0 computation module.
Repository: https://github.com/JSIERO/ClinicalASL
Author: Jeroen Siero
Institution: UMCU (University Medical Center Utrecht), The Netherlands
Contact: j.c.w.siero@umcutrecht.nl
Description:
Functions for bra... |
45d05ee0db2ca5ce53120ea9119a4dbcff0b6c87c44943afae41a6ba9c04b158 | Python | 3,685 | 143 |
from __future__ import division
from numpy import *
from matplotlib.mlab import *
from circ_stats import *
from scipy.stats import *
from scikits.bootstrap import ci
from scikits import bootstrap
from scikits.bootstrap import bootstrap_indexes
import statsmodels.nonparametric.smoothers_lowess as loess
from constants i... |
ab97ed1fbe17137e7e2fe1f934066cb5d2180bc9682ebf4ae991a76abfd0150c | Python | 3,687 | 109 | import pytest
from click.testing import CliRunner
from GANDLF.entrypoints.optimize_model import new_way, old_way
from . import CliCase, run_test_case, TmpDire, TmpFile, TmpNoEx
# This function is a place where a real logic is executed.
# For tests, we replace it with mock up, and check if this function is call... |
fb71f37b4b616848298c1e656c61edb126cb62371b523b0768c5b237dbcb4c02 | Python | 3,688 | 112 | """ Split Attention Conv2d (for ResNeSt Models)
Paper: `ResNeSt: Split-Attention Networks` - /https://arxiv.org/abs/2004.08955
Adapted from original PyTorch impl at https://github.com/zhanghang1989/ResNeSt
Modified for torchscript compat, performance, and consistency with timm by Ross Wightman
"""
from typing import... |
94a9961903532188f6ff5df300a7958a18c8186f8a1f0dda6a0ee36afd0fd2a3 | Python | 3,689 | 117 | """
pysteps.nowcasts.extrapolation
==============================
Implementation of extrapolation-based nowcasting methods.
.. autosummary::
:toctree: ../generated/
forecast
"""
import time
import numpy as np
from pysteps import extrapolation
def forecast(
precip,
velocity,
timesteps,
ext... |
fc5c40c06fe54845111cc76779b39f4236a288b485d925004500085c34799e64 | Python | 3,692 | 68 | from torch.utils.data.sampler import Sampler
import numpy as np
from sklearn.utils.class_weight import compute_class_weight
import time
import logging
class SubtypingStratifiedSampler(Sampler):
def __init__(self, data_source, balance_label_count):
super(SubtypingStratifiedSampler, self).__init__(data_sourc... |
66b47f054fbf4a9f8fa9d19f3edab322c2e3828f783e00471f004641ff300568 | Python | 3,700 | 140 | # -*- coding: utf-8 -*-
"""
pysteps.utils.fft
=================
Interface module for different FFT methods.
.. autosummary::
:toctree: ../generated/
get_numpy
get_scipy
get_pyfftw
"""
from pysteps.exceptions import MissingOptionalDependency
from types import SimpleNamespace
def get_numpy(shape, ff... |
7de1d485bcc286697774d126835706c15b81635a6ac4a796c312286ebf734033 | Python | 3,705 | 139 | # -*- coding: utf-8 -*-
import pytest
import numpy as np
from pysteps import downscaling
from pysteps.tests.helpers import get_precipitation_fields
from pysteps.utils import aggregate_fields_space, square_domain, aggregate_fields
@pytest.fixture(scope="module")
def data():
precip, metadata = get_precipitation_fi... |
ddec986d024c3dc819cfa343645a4969d6e051d9cc17a721b9d44aaa605a2781 | Python | 3,712 | 112 | #!usr/bin/env python
# -*- coding: utf-8 -*-
import argparse
from typing import Optional
import click
from deprecated import deprecated
from GANDLF.cli import copyrightMessage, recover_config
from GANDLF.entrypoints import append_copyright_to_help
from GANDLF.utils import logger_setup
def _recover_config(model_dir... |
22c4c295a3987e0a190ab1b59d2e9135ef5ce8380fc06e806731aa303c1f937e | Python | 3,717 | 115 | import numpy as np
import os.path as osp
import scipy
import matplotlib.pyplot as plt
import seaborn as sns
import sys
sys.path.append('..')
from numpy.random import seed
from sklearn.metrics import jaccard_score
from functions.def_ROIs_EarlyVisualAreas import roi as ROI
from functions.def_ROIs_DorsalEarlyVisualCorte... |
22cfa9ae32b33854f906ad10d52e209fa8b8564876f7b8f789a8aafff1e66c84 | Python | 3,717 | 109 | import pytest
from click.testing import CliRunner
from GANDLF.entrypoints.recover_config import new_way, old_way
from . import CliCase, run_test_case, TmpDire, TmpFile, TmpNoEx
# This function is a place where a real logic is executed.
# For tests, we replace it with mock up, and check if this function is call... |
951bd10cac8fa84b3e092f4ba602a39a111ae28c34e7a6ef7798f9e38f972912 | Python | 3,718 | 82 | import numpy as np
import meshes as ms
import matplotlib.pyplot as plt
from scipy.stats import unitary_group
from numba import njit
class EOIntensityModulation:
def __init__(self, alpha=0.1, g=np.pi, phi_b=np.pi):
self.alpha = alpha; self.g = g; self.phi_b = phi_b
def __call__(self, inputs):
(a... |
f929717d915fe22ebc7b61e71dc97c99abe28edce6673585ee0e02c25a0cd8eb | Python | 3,718 | 109 | from __future__ import annotations
import numpy as np
from scipy.signal import resample
import traits.api
from ptsa.data.timeseries import TimeSeries
from ptsa.data.filters import BaseFilter
class ResampleFilter(BaseFilter):
"""Resample a time series to a new sample rate.
Parameters
----------
resa... |
3239457aad443f885b74633d561c28b6733b0a1675b35d72d28285cab79b81a9 | Python | 3,719 | 88 | from functools import partial
from typing import Any, Optional
import torch
import torch.nn as nn
import torch.nn.init as init
class Fire(nn.Module):
def __init__(self, inplanes: int, squeeze_planes: int, expand1x1_planes: int, expand3x3_planes: int) -> None:
super().__init__()
self.inplanes = in... |
4a09ce6bc34f76fb8eff63a192e78b06744a05bcc1a44af73d8af4aa396f1bdc | Python | 3,729 | 142 | from __future__ import annotations
import sys
from typing import Dict, Optional
from imctools.data.slide import Slide
if sys.version_info >= (3, 8):
from typing import TypedDict # pylint: disable=no-name-in-module
else:
from typing_extensions import TypedDict
class PanoramaDict(TypedDict):
slide_id: i... |
890c605cb811391d72a512e9b9e06c758aba79107f9fa603c6e5703be8fb31a8 | Python | 3,729 | 219 | class TestModule:
def test_create_settings(self):
pass
def test_create_from_handles(self):
pass
def test_prepare_settings(self):
pass
def test_set_settings_from_values(self):
pass
def test_upgrade_settings(self):
pass
def test_post_pipeline_load(self)... |
9f9da1fac6b33ca0c50f6f2abfbfab836680ed7620b808ffc8d5bf0ca93bcbc7 | Python | 3,732 | 114 | # -*- coding: utf-8 -*-
import numpy as np
import pytest
from pysteps.tracking.tdating import dating
from pysteps.utils import to_reflectivity
from pysteps.tests.helpers import get_precipitation_fields
arg_names = ("source", "dry_input", "output_splits_merges")
arg_values = [
("mch", False, False),
("mch", ... |
512312869c5faf6ea723cb88b2f863dfde06601c9320e16c034486ccc36ec5f0 | Python | 3,735 | 116 | #!/usr/bin/env python
# coding: utf-8
"""Code for Figures 2, 5"""
# In[ ]:
get_ipython().run_line_magic('Sort', 'by Substrate')
import numpy as np
import pandas as pd
from sklearn.preprocessing import MinMaxScaler, RobustScaler, QuantileTransformer
from sklearn.model_selection import train_test_split, StratifiedKFol... |
5d6d656c7472536e21b41c82d6a48216307afcc73623113dba62509a0120fdaa | Python | 3,735 | 130 | from __future__ import annotations
import sys
from typing import TYPE_CHECKING, Dict, Optional
import imctools.io.mcd.constants as const
if sys.version_info >= (3, 8):
from typing import TypedDict # pylint: disable=no-name-in-module
else:
from typing_extensions import TypedDict
if TYPE_CHECKING:
from ... |
1d6895c3c2c0a89c97b19230e628ac802481fb619a04e7b3cec4ef1bc5fd8629 | Python | 3,738 | 82 | # -*- coding: utf-8 -*-
"""
------------------------------------------------------------------------------
Copyright (C) 2019 Université catholique de Louvain (UCLouvain), Belgium.
Licensed under the Apache License, Version 2.0 (the "License");
you may not use this file except in compliance with the License.... |
467b4ce5d193116b1e241fb2efc11521fed7afe3bbce660039f5021a0834872a | Python | 3,739 | 111 |
from sklearn import svm
import pickle
import numpy as np
# import matplotlib.pyplot as plt
# from scipy import stats
### PARAMETERS
# output file prefix
out_file_pref = 'res_5fold_split_1'
# SVM kernel (RBF or Polynomial)
# kern_func = 'rbf'
kern_func = 'poly'
# Polynomial degree for 'poly' ker... |
e65c1cc607c6363ac27990ac09f65e1ab9837b97c9ab6ffcdfcf01897a5a4020 | Python | 3,743 | 101 | # -*- 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... |
a923461c9fd2325e48e7bc46c86c173b9ac695ab1822555d27e2b09604aa85ae | Python | 3,746 | 94 | import os.path
import pytest
from click.testing import CliRunner
from GANDLF.entrypoints.split_csv import new_way, old_way
from . import CliCase, run_test_case, TmpDire, TmpFile, TmpNoEx
# This function is a place where a real logic is executed.
# For tests, we replace it with mock up, and check if this fun... |
888221afc582466adf64f3047feddfc9d7d258c2d25651822a54b27a2468c439 | Python | 3,747 | 125 | #!/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
... |
95a8d2a5af94c4818858b0272faeef39caf5508f8ee5292393e6366ff1705a06 | Python | 3,755 | 147 | from matplotlib.pylab import *
from joblib import Parallel, delayed
import multiprocessing
import sys
sys.path.insert(0, '../../helpers/')
from circ_stats import *
from pickle import dump,load
import scikits.bootstrap as bootstrap
import difflib
import seaborn as sns
from scipy.stats import circmean
from joblib impor... |
c4896f9aa276585dd30476d42c4a1b534e2838f17fcde01c5924fa932e357660 | Python | 3,760 | 101 | from __future__ import absolute_import
import numpy as np
import scipy.linalg
def smooth_with_noise(image, bits):
"""Smooth the image with a per-pixel random multiplier
image - the image to perturb
bits - the noise is this many bits below the pixel value
The noise is random with normal distr... |
1a944bd28a96292a870cfd47004c32ea9616f0caf4f18f39b2759f686dbe1e16 | Python | 3,763 | 105 | # -*- 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... |
e4449b7e6e9f33132ac06a5c23cb4d95f9bf15404561182176598984ea7d0032 | Python | 3,764 | 94 | #### Master Script 2: Partition CENTER-TBI for stratified k-fold cross-validation ####
#
# Shubhayu Bhattacharyay
# University of Cambridge
# email address: sb2406@cam.ac.uk
#
### Contents:
# I. Initialisation
# II. Resampling of dataset for training/testing splits
# III. Resampling of training sets to set assign valid... |
92553830392cc715de44a1ed5335c53f5cb8f27cb27d178d7d519855189c84d0 | Python | 3,766 | 116 | import scipy.io as scio
import numpy as np
import pandas as pd
import matplotlib.pyplot as plt
from scipy.fftpack import fft,ifft
from scipy import signal
from scipy.fft import fftshift
data = [np.array(scio.loadmat(f'./propofol_circle/cortical_thalamus_simulationpropofol_circle__16000ms_{i}.mat')['Isubregion'... |
b1d97916fa94513b71e8b38ca2d1e921fe5598004a1e52e113c3fc0f255b8548 | Python | 3,767 | 84 | """
ClinicalASL - Clinical Arterial Spin Labeling processing pipeline
ASL data preparation module.
Repository: https://github.com/JSIERO/ClinicalASL
Author: Jeroen Siero
Institution: UMCU (University Medical Center Utrecht), The Netherlands
Contact: j.c.w.siero@umcutrecht.nl
Description:
Perform motion correcti... |
53046c8528aec6ffa145b7e58ca61d5c6cdc2e1f8a8b132c8db4f26d593be4bc | Python | 3,768 | 96 | from setuptools import setup, find_packages
from setuptools.command.install import install
import os.path
import sys
VERSION='2.3.3'
here = os.path.abspath(os.path.dirname(__file__))
readme_file = os.path.join(os.path.dirname(os.path.abspath(__file__)), 'README.md')
try:
from m2r import parse_from_file
read... |
a4087f35c80ca443e1c7a765110bc2e1fb36609b00423bb246e827a73f73580d | Python | 3,773 | 91 | # -*- coding: utf-8 -*-
"""
molvs.resonance
~~~~~~~~~~~~~~~
Resonance (mesomeric) transformations.
"""
from __future__ import absolute_import
from __future__ import division
from __future__ import print_function
from __future__ import unicode_literals
import logging
from rdkit import Chem
log = logging.getLogger(... |
8aa4f88ab84be2247525115e67e312ebad8ab5df299103b081bda265d1c5ae98 | Python | 3,779 | 113 | import numpy as np
import scipy.io
import os.path as osp
import sys
import argparse
sys.path.append('..')
from nilearn import plotting
from functions.def_ROIs_EarlyVisualAreas import roi as ROI
from functions.def_ROIs_DorsalEarlyVisualCortex import roi
def polarAngle_plot(subject_id, path, cluster, binarize=False):
... |
e188d4f0e3b69483cdaa7ed7a59a50e0b292a1c5febd5890580a4a9a4cd995b5 | Python | 3,779 | 82 | """
ClinicalASL - Clinical Arterial Spin Labeling processing pipeline
DICOM to NIfTI conversion module.
Repository: https://github.com/JSIERO/ClinicalASL
Author: Jeroen Siero
Institution: UMCU (University Medical Center Utrecht), The Netherlands
Contact: j.c.w.siero@umcutrecht.nl
Description:
Function for regis... |
242af0051628efdff30e4ab0cc3ff0573e2c9bd496bb4f758cacd58671362eb0 | Python | 3,780 | 114 | '''
JHK
Python script for computing occlusion sensitivity
'''
import numpy as np
import os
from cdo import Cdo
#==========================================================
# Set main directory
#==========================================================
hdir = '/home/jhkim/task/ccd_anom_backup'
cdo = Cdo()
f_name_lis... |
5d4b8be2ef338487e1b51be905f0efb065bfe6aed9afc15fc5b9b66026980456 | Python | 3,780 | 90 | #!/usr/bin/env python2
# -*- coding: utf-8 -*-
"""
Created on Thu Apr 12 09:36:18 2018
@author: saskiad
"""
# dataset
# get spontanoues stim table
# get L0
# spontaneous rate
# table cell id, cre, area, depth, cre_depth, spontaneous rate
import numpy as np
import pandas as pd
#import os, h5py
#import scipy.stats as ... |
81298f7129d0aab94f1456b1a9d25d12a5509f690e818820847bc0d07bd6869a | Python | 3,780 | 114 | '''
JHK
Python script for computing occlusion sensitivity
'''
import numpy as np
import os
from cdo import Cdo
#==========================================================
# Set main directory
#==========================================================
hdir = '/home/jhkim/task/ccd_anom_backup'
cdo = Cdo()
f_name_lis... |
40fbd376b22d1a1bb85151f91e2c3e56c7e875afb66540fba589e2e06004c705 | Python | 3,782 | 99 | """
ClinicalASL - Clinical Arterial Spin Labeling processing pipeline
ASL Look-Locker correction module.
Repository: https://github.com/JSIERO/ClinicalASL
Author: Jeroen Siero
Institution: UMCU (University Medical Center Utrecht), The Netherlands
Contact: j.c.w.siero@umcutrecht.nl
Description:
Function for comp... |
68b6e0716cc0b4258695e810f7dfffdbdf491ea78c83172d0c3366cb1ce0899a | Python | 3,783 | 94 | #------------------------------poke_habituation protcol--------------------
#Task file for 5-CSRTT habituation, task starts with reward and trial starts by presenting all light
#...of the five-choice light on for undefined time any poke at five_choice give reward
# important note:- Do not change any print stings if you... |
f2d7d6549fe5946c7747299f7be1790f5e7bbdd4597518d1329ac03e59923130 | Python | 3,790 | 109 | """ Tools for working with NIDM-Experiment files """
from argparse import ArgumentParser
import os.path
from rdflib import Graph, util
from nidm.experiment.Utils import read_nidm
def main():
parser = ArgumentParser(
description="This program contains various NIDM-Experiment utilities"
)
sub = par... |
fecf93cb0b9d3a1db572821eeae6ae0448e2c94ced907f38cdf311057a0b904e | Python | 3,791 | 81 | import torch
import os
import logging
import argparse
import random
import numpy as np
def parse_args():
parser = argparse.ArgumentParser()
# set data and method
parser.add_argument('--data', type=str, default='qm7', choices=['qm7', 'qm8', 'qm9', 'hamiltonian', 'newtonian', 'md'])
parser.add_argument(... |
bda8d0e62927d22ea1c3c3e4a8019cb888c90837731d8bf402d3ff0394d5ffe5 | Python | 3,792 | 111 | # coding=utf-8
"""
ErodeObjects
=============
**ErodeObjects** shrinks objects based on the structuring element provided.
This function is similar to the "Shrink" function of **ExpandOrShrinkObjects**,
with two major distinctions-
1. **ErodeObjects** supports 3D objects, unlike **ExpandOrShrinkObjects**.
2. In **Exp... |
324fd10a8f0fa9a9a14323f6f15e5aac1c976e1d1577ba4dc069dd77211b5c6d | Python | 3,793 | 105 | from typing import Optional
import torch
import torch.nn.functional as F
from skimage.measure import label
import numpy as np
from scipy.ndimage import binary_fill_holes, binary_closing
from GANDLF.utils.generic import get_array_from_image_or_tensor
def torch_morphological(
input_image, kernel_size: Optional[int]... |
a6be05355d377ff5697bb23f94b621ddbbb90573916d3757d610f50d3b2ef9ab | Python | 3,796 | 109 | import pandas as pd
import numpy as np
import argparse
import matplotlib.pylab as plt
from rdkit import Chem
import rdkit.Chem.Descriptors
import os
def pref_split(smiles_string):
"""
splits a string on '|' into a list with two elements, starting from the right
the prefix token must be in '<pref... |
1f7fa7ba320de168004a7b2a05d0ee8a8b90d8cf9401c5ddaf72d08a6689a7d1 | Python | 3,797 | 142 | from typing import Literal, cast
import numpy as np
import pytest
import xgboost as xgb
from xgboost import testing as tm
from xgboost._data_utils import ArrayInf, from_array_interface, pd_cat_inf
from xgboost.testing.ordinal import (
run_cat_container,
run_cat_container_iter,
run_cat_container_mixed,
... |
079f6c2703f515ab354bfb67f5c2c403dcbdcd4804b3085e8afd907621c66ea3 | Python | 3,799 | 94 | from . GenomeTrack import GenomeTrack
from .. utilities import get_optimal_fontsize, change_chrom_names
import numpy as np
import pyfaidx
import os
# Color code for seqs
seq_color = {'A': 'red',
'T': 'green',
'G': 'blue',
'C': 'black',
'N': 'grey'
}
cl... |
82a6f22a3758e83f3a8a0f7fee7997b7d88607969d8f072dd9f9243cb1086bfb | Python | 3,800 | 108 | # -*- 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... |
9b3f8f1194a034714d711dfd57bdcf392c15b57554784f6e201aacf27605dea2 | Python | 3,808 | 85 | import numpy as np
import pandas as pd
from dragen.utilities.generateExodus import NetCDFWrapper
from dragen.utilities.PvGridGeneration import MeshingHelper
from dragen.utilities.InputInfo import RveInfo
class MooseMesher(MeshingHelper):
def __init__(self, rve_shape: tuple, rve: pd.DataFrame, grains_df: pd.Data... |
378680947b0ea64704903e54d8e07d082c3b5c39281338b2ad1f85140f4252d9 | Python | 3,811 | 138 | """ adapted from https://github.com/TissueImageAnalytics/tiatoolbox/blob/master/tiatoolbox/tools/stainextract.py """
from typing import Optional
import numpy as np
from skimage import exposure
import cv2
def contrast_enhancer(
img: np.ndarray, low_p: Optional[int] = 2, high_p: Optional[int] = 98
) -> np.ndarray:... |
905790304d38f39589e9ae0fbc2279846cf67351785aabfb7c0dff6bc5c97607 | Python | 3,813 | 98 | from __future__ import absolute_import
import unittest
import numpy as np
import scipy.ndimage
import centriole.smooth as cpms
class TestSmoothWithNoise(unittest.TestCase):
def test_01_smooth_zero(self):
"""Make sure smooth doesn't crash on all zeros"""
out = cpms.smooth_with_noise(np.zeros((3, 3)... |
b883dc8b5d32605e0498b7f9ee6e030903a96f8cdcf95ead3a9bf2095ff3286b | Python | 3,813 | 112 | import cupy as cp
import rvt.vis
import rasterio as rio
import time
import numpy as np
def slope_aspect_gpu(dem, resolution_x, resolution_y, ve_factor=1, output_units="radian"):
"""
Procedure can return terrain slope and aspect in radian units (default) or in alternative units (if specified).
Slope is def... |
70c76f3bc13cae39ccfebe18e5c2a66e6e08defc7fd2382d36f7055de5219c18 | Python | 3,818 | 92 | """
Author: Mingjian He <mh1@stanford.edu>
Testing functions for the iOsc algorithm in somata/oscillator_search/iter_osc.py
"""
from somata.oscillator_search import IterativeOscillatorModel as IterOsc
from somata.oscillator_search.helper_functions import innovations_wrapper
from somata import OscillatorModel as Osc
f... |
340a48fb055762dca960f0b87f35e4aa5ed0a49a81fde2ac45b2b3ad62d2cb6a | Python | 3,823 | 111 | import os
import logging
import numpy
from deeprank.models.forcefield.param import VanderwaalsParam
from deeprank.models.forcefield.patch import PatchActionType
from deeprank.parse.forcefield.top import TopParser
from deeprank.parse.forcefield.patch import PatchParser
from deeprank.parse.forcefield.residue import Res... |
9fb7b98b2130884fcd9b1d0f99dd3fbfb9791d0aad05b64175d1055d12f1a4e8 | Python | 3,826 | 123 | #!/usr/bin/env python3
# -*- coding: utf-8 -*-
"""
Created on Mon Oct 29 15:27:11 2018
@author: Nikolai M Chapochnikov
"""
file_hdf = 'results/act3.hdf'
n_cells = 21
n_conc = 5
n_odors_EC = 34
# this is the order based on the 2nd loading vector of the PCA of ORN activity
# when the full activity data (all concent... |
9adfe55332945deb3f9b19c9a592bdba54be0fae4f2a8c11ea503776a5c04d8c | Python | 3,829 | 96 | import pyb
import math
from . import hardware as hw
_sine_len = 100 # Number of points in sine wave.
_sine_buf = bytearray([128+int(127*math.sin(2*math.pi*i/_sine_len)) for i in range(_sine_len)])
_sqr_buf = bytearray([255,0])
_click_buf = bytearray([255,0,255,255,0,0]+4*[255]+4*[0]+8*[255]+8*[0]
... |
f0214f5327a22921e92e6bc0f06c21fa55a568b3e88a2c05600a6ca9b51d2e17 | Python | 3,832 | 120 | import logging
from sklearn import svm, linear_model
from sklearn.ensemble import AdaBoostRegressor, RandomForestRegressor
from sklearn.ensemble import RandomForestClassifier, AdaBoostClassifier
from sklearn.gaussian_process import GaussianProcessClassifier
from sklearn.linear_model import Ridge, ElasticNet, Lasso, SG... |
31ed82f5d3803c33d65f34340a12fc92ec8fc348f2a8514cf0a943746b9d7b55 | Python | 3,835 | 114 | """ TanH Scheduler
TanH schedule with warmup, cycle/restarts, noise.
Hacked together by / Copyright 2021 Ross Wightman
"""
import logging
import math
import numpy as np
import torch
from typing import List, Tuple, Union
from .scheduler import Scheduler
_logger = logging.getLogger(__name__)
class TanhLRScheduler(... |
5c3d08d6c32539569ca50580335bff6ccd760035b9e604bad9fda6d9cf70b173 | Python | 3,848 | 109 | # 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
# -- Path setup --------------------------------------------------------------
# If ex... |
7cd99a6b39c4098929e95e76c8905abc2d790b4bb5496e02080670e73d114410 | Python | 3,849 | 93 | import numpy as np
import torch
import torch.nn as nn
from torch.autograd import Variable
from torch_geometric.utils import to_dense_adj, degree
from scipy import sparse as sp
def Laplacian_position_encoding(edge_index, num_nodes, pos_enc_dim):
"""
from https://github.com/graphdeeplearning/benchmark... |
14d50142ac9960abaa8f718382cedfb9a962fa6ed5c796c9f3eb707c84620e6e | Python | 3,850 | 94 | # -*- coding: utf-8 -*-
import numpy as np
from . BedGraphTrack import BedGraphTrack
from . GenomeTrack import GenomeTrack
class BedGraphMatrixTrack(BedGraphTrack):
# this track class extends a BedGraphTrack that is already part of
# pyGenomeTracks. The advantage of extending this class is that
# we can r... |
732b813b3ce135c55da59583bb6daf82d33ee63aed0bc1a32e16054166e62fcf | Python | 3,852 | 147 | import pdb
import wntr
import torch
import networkx as nx
from DT_for_WDN_leak_localization.network import WDN
def get_prior(net, data_path):
epanet_data_path = f"EPANET_input_files/net_{str(net)}.inp"
if net == 1:
return get_prior_net_1(data_path, epanet_data_path)
elif net == 2:
... |
59ebf6afff2c5798552d3dc061635f20a82869e55e768a56e96830186741b923 | Python | 3,853 | 120 | import hashlib
import numpy
from ..image import Image
from ..module import Module
from ..setting.text import Name
class InjectImage(Module):
"""This module is intended for testing. It injects an image into the
image set.
"""
module_name = "InjectImage"
variable_revision_number = 1
def __in... |
66617edd8eee1f1260c037b39647773544bc66ffc4e09b15c1dc96ff341d1385 | Python | 3,856 | 162 | import numpy
import pytest
import skimage.data
import skimage.color
import skimage.filters
import skimage.measure
import cellprofiler_core.image
import cellprofiler_core.measurement
import cellprofiler_core.object
import cellprofiler_core.pipeline
import cellprofiler_core.workspace
@pytest.fixture(
scope="modul... |
fa4e7b07f933dc1adeccc24cca82f4b5ac462b5418a1c9e3f34f905fbc6121a9 | Python | 3,856 | 113 | import sys
import torch
sys.path.append("..")
import utils
spike_args = {}
spike_args['thresh'] = utils.args.thresh
spike_args['lens'] = utils.args.lens
spike_args['decay'] = utils.args.decay
class Net(torch.nn.Module):
def __init__(self, args, inputsize, taskcla, labsize, nhid,nlayers=1):
... |
183aa8670651d5fba8f6eda8a779979bd21e36dadcf929824c5ac4f7c622a997 | Python | 3,862 | 116 | """
created by: Donghyeon Won
"""
from __future__ import print_function
import os
import argparse
import numpy as np
import pandas as pd
import time
import shutil
from PIL import Image
from tqdm import tqdm
import torch
from torch.utils.data import Dataset, DataLoader
from torch.autograd import Variab... |
2d50879305ea260722e537da1e8951d1cebcad159d64f25a9cc2a1fe08f30d31 | Python | 3,864 | 115 | """
FillObjects
===========
**FillObjects** fills holes within all objects in an image.
**FillObjects** can be run *after* any labeling or segmentation module (e.g.,
**ConvertImageToObjects** or **Watershed**). Labels are preserved and, where possible, holes
entirely within the boundary of labeled objects are filled ... |
7c73cfb124ac785118596410a06c57f0327025a7fc1f301b27480b6d07bde3db | Python | 3,864 | 133 | # -*- coding: utf-8 -*-
"""
pysteps.io.archive
==================
Utilities for finding archived files that match the given criteria.
.. autosummary::
:toctree: ../generated/
find_by_date
"""
from datetime import datetime, timedelta
import fnmatch
import os
def find_by_date(
date,
root_path,
p... |
f5c44a3e636099e5dafef4672f982473a830e313d9e487ce71aadef9c2b336a5 | Python | 3,866 | 143 | import torch
import torch.nn as nn
# sub-parts of the U-Net model
import torch
import torch.nn as nn
import torch.nn.functional as F
from torchfcn.models import FCN8s
class double_conv(nn.Module):
'''(conv => BN => ReLU) * 2'''
def __init__(self, in_ch, out_ch):
super(double_conv, self).__init__()
... |
30782659d41f887a852e94e882f2e2c09fec0a68075b2fcb4b129532a837263d | Python | 3,867 | 104 | import numpy as np
from functools import partial
from scipy.stats import beta, expon
import bayesflow as bf
from priors import sample_random_walk, sample_scale
from likelihoods import sample_poisson_process
class RandomWalkPoissonModel:
"""A wrapper for a non-stationary Poisson process with a random walk transi... |
540706480af74d330d58bc887104c1fe42f7ae4e5f730503bca184870c5f4a68 | Python | 3,869 | 113 | #!/usr/bin/env python3
# -*- coding: utf-8 -*-
"""
Created on Tue Oct 5 15:58:38 2021
@author: filtsem
"""
from pathlib import Path
import numpy as np
import eelbrain
import re
import os
import mne
import pandas as pd
from mne.stats import (spatio_temporal_cluster_test, f_threshold_mway_rm, f_mway_rm)
from mne impo... |
6f218baa5863b826663ee28683617f2a3703ba3d33a70e8bdd314bc0b8d92f88 | Python | 3,869 | 129 | """
This file implements functions to simulate and analyze
Fitzhugh-Nagumo type differential equations with Brian2.
Relevant book chapters:
- http://neuronaldynamics.epfl.ch/online/Ch4.html
- http://neuronaldynamics.epfl.ch/online/Ch4.S3.html.
"""
# This file is part of the exercise code repository accompanying
# t... |
79406f6802dbdfe51571e69a3859d6b7de8349c8b6a965359d8bfc3f93e56ca9 | Python | 3,869 | 116 | # -*- 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... |
01063d9d6fbb49fd03a5135263cfd4682fb581d69484fc6446806fec67ad7d72 | Python | 3,872 | 62 | import argparse
import ast
class Options:
def __init__(self):
self.parser = argparse.ArgumentParser()
# logging options
self.parser.add_argument('--config_file', default='config.yaml', type=str, help='path to config file')
self.parser.add_argument('--data_config', type=str, help='... |
6b3d5627f6cc250bb982a144955fb2de3ce7bb9f7e354081ddfeb987a443fff4 | Python | 3,875 | 95 | import sklearn.metrics
import matplotlib.pyplot as plt
import numpy as np
import tensorflow as tf
import itertools
def numeric_metrics(model,dataset,threshold=0.5,drop_carbon=True):
for data, labels in dataset.take(1):
y_pred = model.predict(data,verbose=0)
y_true = labels
for data, l... |
982ef2509b044f84c3d1770543e35e2b6461622db38669a4de35df6964aac6f8 | Python | 3,875 | 110 | import glob
import logging
import os
import re
import shutil
from pathlib import Path
from typing import Sequence, Union
from imctools.data import Session
from imctools.io.mcd.mcdxmlparser import McdXmlParser
from imctools.io.ometiff.ometiffparser import OmeTiffParser
from imctools.io.utils import OME_TIFF_SUFFIX, SCH... |
026afbe74caab8f5a6c0e429bc86508673a3b9f0242aadb9996211fbfe36d4a5 | Python | 3,876 | 106 | import numpy as np
from scipy.ndimage import (binary_closing, binary_dilation, binary_erosion,
binary_opening)
a = np.array([[1, 0, 0, 1, 1, 0, 0],
[1, 1, 0, 0, 0, 0, 0],
[1, 1, 0, 0, 0, 0, 0],
[1, 1, 0, 0, 0, 1, 0],
[1, 1, 0, 0, 0, 0, ... |
03db9e67dd9d62f593cdfea9b831782faf73df04e744b89b93620fb18f830e42 | Python | 3,876 | 62 | import argparse
import ast
class Options:
def __init__(self):
self.parser = argparse.ArgumentParser()
# logging options
self.parser.add_argument('--config_file', default='config.yaml', type=str, help='path to config file')
self.parser.add_argument('--data_config', type=str, help='... |
7f23f5aa46522a4b3df526c2b840570b2a4e09f4a429ce2e627a5f72d0f33558 | Python | 3,877 | 102 | from typing import Sequence, Type, Union
import numpy as np
import torch
import torch.nn as nn
import torch.nn.functional as F
from torch.nn import LayerNorm
from monai.networks.layers import Conv, trunc_normal_
from monai.utils import ensure_tuple_rep, optional_import
from monai.utils.module import look_up_option
R... |
a81dcf8618a4064489d10d83b3ccff2bc97f48c9d56936f79f4d598261bbc338 | Python | 3,878 | 108 |
import keras
from keras.models import Sequential
from keras.layers import Dense, Dropout, Activation, Flatten
from keras.layers import Conv2D, AveragePooling2D, BatchNormalization
from keras.callbacks import EarlyStopping, ModelCheckpoint
from keras.models import load_model
import numpy as np
import matplotl... |
161a3e96f7465ebdc5a66b857effa3041a00d817e0c08a0aa23164cd68a97eda | Python | 3,887 | 44 | from .base_options import BaseOptions
class TrainOptions(BaseOptions):
"""This class includes training options.
It also includes shared options defined in BaseOptions.
"""
def initialize(self, parser):
parser = BaseOptions.initialize(self, parser)
# HTML and tensorboard visualization... |
4d0302753785ed362d5a6f435882bdcf7a4246a4f043c96528cfb616ef5cffc3 | Python | 3,890 | 88 | import tensorflow as tf
from .layer import GradientLayer,BoundaryGradientLayer
class PINN:
def __init__(self, network):
self.network = network
self.grads = GradientLayer(self.network)
self.boundaryGrad = BoundaryGradientLayer(self.network)
def build(self,NO_FLUX_BND,RADIALDIFFUSI... |
70fb4c20282680c242fdd1205b6bafd1e6dbe79b9a2016d69aa96fac03ec55cf | Python | 3,891 | 160 | """
Top-level trial data bandpower export
Authored by Eric Easthope
"""
import numpy as np
from pathlib import Path
DATA = "data"
DERIVED = "derived"
fs = 3052
MIN_REST_LEN = 1 / 2
bandnames = [
"beta1",
"beta2",
"gamma1",
"gamma2",
"highgamma1",
"highgamma2",
"beta",
"gamma",
"h... |
2547e79fe476c295d800cc039fbc7e8c3bb81523b29ac06850cc636e0ec84105 | Python | 3,892 | 104 | import os
import scyjava
import numpy as np
import logging
from . import omexml
from ..utilities.java import jimport
LOGGER = logging.getLogger(__name__)
p2j = lambda v: scyjava.to_java(v)
def write_image(
pathname,
pixels,
pixel_type,
c,
z,
t,
size_c,
size_z,
size_t,
channe... |
626e9dc0ca775bb863063cf5f0dfdd08ede215fbd73747a0f2479fbf3f5bc567 | Python | 3,900 | 110 | # -*- 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... |
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