sha256 stringlengths 64 64 | language stringclasses 28
values | size int32 1 491k | lines int32 1 23.2k | content stringlengths 1 200k |
|---|---|---|---|---|
4c95ba0ba8877d6861ee8cea9c985366b93ae59d3860480d98881aecb5545f53 | Python | 1,274 | 44 | # Copyright (c) ONNX Project Contributors
#
# SPDX-License-Identifier: Apache-2.0
from __future__ import annotations
import numpy as np
import onnx
from onnx.backend.test.case.base import Base
from onnx.backend.test.case.node import expect
class GlobalAveragePool(Base):
@staticmethod
def export() -> None:
... |
fce1e82dc26516cd6e4f8ad9729ab1711c6d5f501cc6de8b3abd909447d1587f | Python | 1,274 | 33 | def train_model(config, DataHandler, model, callback_list, verbose=2, final_models=False, return_model=False):
if verbose > 0:
print('Start training')
train_input, y_train = [DataHandler['X_train'], DataHandler['dg_train']], DataHandler['y_train']
valid_input, y_val = [DataHandler['X_valid'], Da... |
52bbfcaa1875d3c838055abb493ba69124045f3918d972db2f85abe607e69232 | Python | 1,275 | 48 | #! /usr/bin/env python3
import os
import csv
import json
from pathlib import Path
from pyontutils.utils import async_getter
from pyontutils.scigraph import Cypher, Vocabulary
current_file = Path(__file__).absolute()
gitf = current_file.parent.parent.parent
c = Cypher()
v = Vocabulary(cache=True)
def main():
cur... |
389bc8467b270484cfa1eb43bcf503d9eeb59088d0a4cab1d0f48d003dade193 | Python | 1,276 | 39 | # Copyright (c) ONNX Project Contributors
#
# SPDX-License-Identifier: Apache-2.0
from __future__ import annotations
import numpy as np
import onnx
from onnx.backend.test.case.base import Base
from onnx.backend.test.case.node import expect
class LeakyRelu(Base):
@staticmethod
def export() -> None:
n... |
0309efa8c554614a0db7a3ecc08ae8311a3cbef480795ddfa0819efc62efcbc9 | Python | 1,278 | 42 | """Plotting examples for DBA."""
from sktime.clustering.metrics.averaging import dba
from sktime.datasets import load_arrow_head
from sktime.datatypes import convert_to
def plot_dba_example():
"""Plot dba."""
import matplotlib.pyplot as plt
X_train, y_train = load_arrow_head(split="train")
X_train =... |
3771e2fb5f834e74c19074e3ad084cbf37117377fb4c30ddf847bc89497499d4 | Python | 1,279 | 32 | """Unit tests for all time series regressors."""
__author__ = ["felipeangelimvieira"]
from sktime.tests.test_all_estimators import BaseFixtureGenerator, QuickTester
class RegressionDatasetFixtureGenerator(BaseFixtureGenerator):
"""Fixture generator for classifier tests.
Fixtures parameterized
---------... |
06fe2b3ac3fd8f6ed91eecf21cecf28da5133441de3c5a75bd03a27d271ff619 | Python | 1,280 | 40 | from torchvision import datasets
from torch.utils.data import Dataset
from .loader import pil_loader
class CustomizedImageFolder(datasets.ImageFolder):
def __init__(self, root, transform=None, target_transform=None, loader=pil_loader):
super(CustomizedImageFolder, self).__init__(root, transform, target_t... |
9f5c0cb3a2f64b2ba234072b163937a8ecb70dd2a0a99efd39c80f280af7cb97 | Python | 1,280 | 44 | from scipy.spatial.distance import pdist, squareform
from scipy.optimize import linear_sum_assignment
import pandas as pd
def _standardize(x):
return (x - x.min()) / (x.max() - x.min())
def _matchmaker(metadata, status, match_columns, types):
""" Computes matching ids.
Parameters
----------
met... |
0856dac1a6a121e7e856b286247800676b8b5742005dd5b13fb551df411f01ef | Python | 1,282 | 41 | #!/usr/bin/env python
"""
AQDnet setup script
"""
from setuptools import setup, find_packages
with open('README.md', 'r', encoding='utf-8') as f:
long_description = f.read()
setup(
name='aqdnet',
version='0.1.0',
author='AQDnet Authors',
description='Deep Neural Network for Protein-Ligand Docking... |
dbd70043d149b308f3e09c4f467c18f4574284a0e69dd4a76a7385b8e0286175 | Python | 1,282 | 43 | # ---
# jupyter:
# jupytext:
# cell_metadata_filter: -all
# formats: ipynb,py:light
# text_representation:
# extension: .py
# format_name: light
# format_version: '1.5'
# jupytext_version: 1.13.8
# kernelspec:
# display_name: Python 3 (ipykernel)
# language: python
# ... |
5a7396346ae7f124b7d97bc3d28a3c7112fa441015918f03968274b5e7dec8bb | Python | 1,283 | 50 | from __future__ import annotations
from dataclasses import dataclass
import numpy as np
import pandas as pd
from seaborn._stats.base import Stat
@dataclass
class PolyFit(Stat):
"""
Fit a polynomial of the given order and resample data onto predicted curve.
"""
# This is a provisional class that is u... |
f9aa25f2b49935dc79eb5e8202aa54ae4fbd7796093f587b973992c94ca3f28b | Python | 1,283 | 38 | import numpy as np
import pandas as pd
import matplotlib.pyplot as plt
import seaborn as sns
import matplotlib.pyplot as plt
def load_data_HCSC(spss_file):
data = pd.read_spss(spss_file)
#Change numeric identifiers to objects
data['NHC'] = data['NHC'].astype('object')
data['NHC_LCR'] = data['NHC_LCR'... |
a27d3a279b2d9d980caab171cdb98361c5e77dac6b79cc633abde9b74f552230 | Python | 1,284 | 42 | from pathlib import Path as p
from ilxutils.interlex_sql import IlxSql
from ilxutils.tools import create_pickle
import os
sql = IlxSql(db_url=os.environ.get('SCICRUNCH_DB_URL_PRODUCTION'))
terms = sql.get_terms()
create_pickle(terms, p.home() / 'Dropbox/interlex_backups/ilx_db_terms_backup.pickle')
print('=== terms... |
e4db7858043e15f77182e44847a6860b9adc6b15e260339196d24d86decea310 | Python | 1,284 | 44 | """
Creates a stimulus with an auto-generated sweep order then replaces it with a
custom one.
"""
from camstim import SweepStim, Stimulus, Window
from psychopy import visual
window = Window(fullscr=True, monitor="GammaCorrect20")
stim = Stimulus(visual.GratingStim(window,
pos=(0, 0),
... |
76284260bd671f82c8e8b77b9dd0cfb4e2b3cf8d858932d3a5ecfd89458656c4 | Python | 1,285 | 50 | # Copyright (c) OpenMMLab. All rights reserved.
import pytest
import torch
from torch.nn.modules.batchnorm import _BatchNorm
from mmcls.models.backbones import TNT
def check_norm_state(modules, train_state):
"""Check if norm layer is in correct train state."""
for mod in modules:
if isinstance(mod, _... |
784631f29d47dc18c8e61a8966750dc7d0b1021969cb8b67505960c5f30152ff | Python | 1,286 | 45 | # coding: utf-8
# several data readers need optional dependencies. There's no
# appropriate builtin exception
class MissingDependencyException(Exception):
pass
class DataReaderBase(object):
"""Read data from file system and yield as dicts.
Raises:
onmt.inputters.datareader_base.MissingDependenc... |
bc8433f39dc6e2b6f17a88a6a128657b714cda573203ee436673e8d324b8271d | Python | 1,286 | 44 | from anlffr.helper import biosemi2mne as bs
import mne
import numpy as np
from anlffr import spectral
import pylab as pl
# Adding Files and locations
# This below is just an example
# You have to edit this to supply your own data
fpath = '/home/hari/Documents/MNEforBiosemi/'
edfname = 'I13_depth_01.bdf'
# Load data a... |
6965ec0959adcf466d5f927e7ff5dec9e192023f576ee4108ca273febbcf56d6 | Python | 1,287 | 44 | # Copyright 2018-2025
# Institute of Neuroscience and Medicine (INM-1), Forschungszentrum Jülich GmbH
# 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/LICE... |
cbff06fe3cba3d331081fc343932e3673e2c5373bbc5f33bc33e3d8e9f37ae75 | Python | 1,287 | 44 | """
Read and prepare paths for the data and other input files.
All
"""
from pathlib import Path
import toml
def get_data_paths():
"""get the full path for a the data files
Reads the "wheres_my_data.toml" file, prepends the disk,
and returns the configuration.
(A call to this functions should replac... |
0565975263d4f9a3d02036ac61da600f3d485a95b1c35234673607d17cc64db1 | Python | 1,288 | 25 | """The package :mod:`pyfilterbank` provides tools for acousticians and audiologists/engineers working with python.
A fractional octave filter bank is provided in the module :mod:`octbank`. You can use it to split your signals into many bands of constant relative fractional octave band width. The output signals stay in... |
1e0183da65ef08644bf5717cce0d50bd45d8347759ed8cf384d024b3cee45347 | Python | 1,288 | 48 | # Copyright (c) ONNX Project Contributors
#
# SPDX-License-Identifier: Apache-2.0
from __future__ import annotations
import numpy as np
import onnx
from onnx.backend.test.case.base import Base
from onnx.backend.test.case.node import expect
class HammingWindow(Base):
@staticmethod
def export() -> None:
... |
654e8bfeb35538dcb6adedfe6659bdbb034ddb477e5205c9c7cd392ff4e9a365 | Python | 1,288 | 43 | #
# # Highlight Parcels
#
# One possble use of netplotbrain is to highlight a seed region used. Here we will highlight two regions of interest.
# +
# Load imports
import netplotbrain
import pandas as pd
import numpy as np
# Get 100 node atlas from templateflow
node_dict = {'atlas': 'Schaefer2018',
... |
6c1e1e2fcf24c09fb955b2346a787a2e254351f4a0318a3138b567fbb01e9f86 | Python | 1,288 | 45 | # Copyright 2023 DeepMind Technologies Limited
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agr... |
7db3493b438c6ffc86c2586be8a335057eb06617f6118dc187aa646e5c9fb0de | Python | 1,290 | 42 | import pytest
from typing import Tuple
import siibra
@pytest.mark.parametrize("space", siibra.spaces)
def test_space(space: siibra.core.space.Space):
for vol in space.volumes:
print(vol.providers)
should_have_desc = [siibra.spaces["big brain"]]
@pytest.mark.parametrize("space", should_have_desc)
def t... |
2f8e2887f466506b9aff54c4a0f93573331f3b906dde0c5331d7276c1ab19644 | Python | 1,291 | 49 | """
Merge PDF files
This module is part of *vcnmodel*.
Support::
NIH grants:
DC R01 DC015901 (Spirou, Manis, Ellisman),
DC R01 DC004551 (Manis, 2013-2019, Early development)
DC R01 DC019053 (Manis, 2020-2025, Later development)
Copyright 2020 Paul B. Manis
Distributed under MIT/X11 license. See lice... |
cf2cd67c44796ac101fd04ad3b6acc4229a08ffa0f27bed225f3a8ac6ab5482c | Python | 1,291 | 42 | # Mocapy: A parallelized Dynamic Bayesian Network toolkit
#
# Copyright (C) 2004 Thomas Hamelryck
#
# This library is free software: you can redistribute it and/or
# modify it under the terms of the GNU General Public License as
# published by the Free Software Foundation, either version 3 of the
# License... |
1a52738bf27aff4f189e02c78dd249190bfbd811e6ea85519d6037a5382b9e9a | Python | 1,292 | 36 | # Copyright (c) ONNX Project Contributors
# SPDX-License-Identifier: Apache-2.0
from __future__ import annotations
import re
import numpy as np
from onnx.reference.op_run import OpRun
_acceptable_str_dtypes = ("U", "O")
class RegexFullMatch(OpRun):
def _run(self, x, pattern=None):
# Note: The ONNX sp... |
513d171d71284639f39baf2b087e1585fc9062b6f775d06200e03ea2cbdbd71e | Python | 1,292 | 40 | # Copyright 2026 DeepMind Technologies Limited
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agr... |
54bf361363c6e2e063ad49a069a0582e0c262bb4608857c61e54046ed8aaec5e | Python | 1,292 | 42 | """Isolated numba imports for _ddtw."""
__author__ = ["chrisholder", "TonyBagnall"]
import numpy as np
from sktime.utils.numba.njit import njit
@njit(cache=True, fastmath=True)
def average_of_slope(q: np.ndarray) -> np.ndarray:
r"""Compute the average of a slope between points.
Computes the average of the... |
be3ce424d9bb0d85cb79de8869d2400a40a49afaba088dedce7f38d56799f49d | Python | 1,293 | 45 | import io
import setuptools
try:
import numpy as np
except ImportError:
print("Please install Numpy first. e.g. pip install numpy")
exit(1)
from glob import glob
module_utils = setuptools.extension.Extension('ssam.utils', sources=["c/utils.cpp"], extra_compile_args=["-fopenmp"], extra_link_args=["-fopenmp"... |
f350ca4234be9fc4eeb79f561e85535cbf9748b93df449ee098467e15dbdf71e | Python | 1,293 | 55 | """Isolated numba imports for _euclidean."""
__author__ = ["chrisholder", "TonyBagnall"]
import numpy as np
from sktime.utils.numba.njit import njit
@njit(cache=True, fastmath=True)
def _local_euclidean_distance(x, y):
"""Compute the local euclidean distance.
Parameters
----------
x: np.ndarray (1... |
470823a89c289db0d56ab5f88c0335227569d1154bdc66e657ad496a5c22c39d | Python | 1,294 | 42 | """#---------------------------------#---------------------------------#-------------
This script helps estimate the full range of values for a given feature type
""" #
# ---------------------------------#---------------------------------#-------------
from os.path import join as pjoin
import numpy as np
from gra... |
034f2894958dd183e8b3e31b4b4a9251f2b12a022e461c15bdba9dfea0db3420 | Python | 1,296 | 41 | import random
import numpy as np
def binary_tournament(trial_runner, trial, states):
"""Selects a candidate to replace the current trial.
Parameters
----------
trial_runner : ray.tune.trial_runner.TrialRunner
The trial runner for the PBT run.
trial : ray.tune.trial.Trial
The tria... |
491b5ce5c33f06b297d239eb89183c5a8e892513bc0385a292db8426f8d426f1 | Python | 1,296 | 39 | """
Filtering functions for protein sequences.
"""
import pandas as pd
import atom3d.protein.sequence as seq
def form_seq_filter_against(dataset, cutoff):
"""
Create filter that removes remove structures with too much sequence identity to a chain in supplied dataset.
We consider each chain in each stru... |
eb33f60453137faaf87e25f619b7943f2197574e407f54b586a70a2daf76166d | Python | 1,296 | 59 | import sentencepiece
from translation_tokenize import TOKEN_DIR
def source(line):
if len(line) < 1:
return False
if line[0] == 'S':
return True
return False
def translation(line):
if len(line) < 1:
return False
if line[0] == 'D':
return True
return False
... |
5ce6a1e96ff77cb6e2c19db13033df5e96989c1982f8ced45a4ac9e7101b63e0 | Python | 1,298 | 41 | # Copyright (c) ONNX Project Contributors
#
# SPDX-License-Identifier: Apache-2.0
from __future__ import annotations
import numpy as np
import onnx
from onnx.backend.test.case.base import Base
from onnx.backend.test.case.node import expect
class ThresholdedRelu(Base):
@staticmethod
def export() -> None:
... |
6a1cd6aa25f154f81ad496b586329eabe2938991c4b1f559e8445ab12d33d901 | Python | 1,298 | 46 | # Copyright (c) ONNX Project Contributors
# SPDX-License-Identifier: Apache-2.0
from __future__ import annotations
import numpy as np
from onnx.reference.op_run import OpRun
class DepthToSpace(OpRun):
def _run(self, data, blocksize=None, mode=None):
if len(data.shape) != 4:
raise RuntimeErr... |
7393dd928af18b8ef754c7fa8f4826b0bd7343986a1f0a02103332ccbaa2a848 | Python | 1,298 | 51 | fa=open('/home/disk/database/data/ICS_scHIC/f03_atlas/eQTL/ALL_EQTL_1k_merged.bed.detail.bed')
snp2tag={}
for line in fa:
seq=line.rstrip().split('\t')
this_tag=seq[0]+'\t'+seq[1]+'\t'+seq[2]
this_snp=seq[3]+'\t'+seq[4]+'\t'+seq[5]
snp2tag[this_snp]=this_tag
import numpy as np
from scipy.stats impor... |
27643efed9c74892228026be8f5194f3021b3f68047703d5d94d6ff4596f5db8 | Python | 1,301 | 57 | # Copyright (c) ONNX Project Contributors
# SPDX-License-Identifier: Apache-2.0
from __future__ import annotations
import sys
import atheris
with atheris.instrument_imports():
import onnx
from onnx import version_converter
def _default_opset_version(model):
for opset in model.opset_import:
if o... |
b76ec1ed55603b70f4702acad1a19ab6ef5151c2d19727d3c4decebbd4a81d28 | Python | 1,301 | 45 | import numpy as np
import pandas as pd
from keras.models import load_model
from sklearn.preprocessing import LabelEncoder
from sklearn.model_selection import train_test_split
from keras.utils import to_categorical
from sklearn.metrics import confusion_matrix, classification_report
import seaborn as sns
import matplotli... |
3307f424130838e510ba1e527252a3b0b811ebb911f944a53404b3dd2bd6f670 | Python | 1,303 | 44 | #!/usr/bin/env python
# -*- coding: utf-8 -*-
""" read datasets from existing files"""
import numpy as np
from sklearn.preprocessing import StandardScaler
class DataGenerator(object):
def __init__(self, file_path, solution_path=None, normalize_flag=False, transpose_flag=False):
self.inputdata = np.lo... |
2efa27c7976aecb9612348a0038c4c7b8f05de7b5533e41e06429f4f90483675 | Python | 1,304 | 37 | import matplotlib.pyplot as plt
import seaborn as sns
import numpy as np
def sample_histogram(sample1, sample2=None, ax=None, bins=100, palette=None,
sample_names=['observation', 'prediction'], density=True,
var_name='Measured Parameter', **kwargs):
if ax is None:
... |
6f49292cfe350d9b269e27d3c030fe166c77f8ecd3ea01ba063e56844ae335e5 | Python | 1,304 | 36 | # coding=utf-8
# Copyright (C) 2021. Huawei Technologies Co., Ltd. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# ... |
38a079cb25e5a28b9bb50c3c0fa652e1ba55eb4935853aea28e427022b5528fc | Python | 1,305 | 43 | # Copyright 2019 DeepMind Technologies Ltd. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by appl... |
4da58e0deef311384bce8b97d7a5265338648dd04143cad3351f81699b39a195 | Python | 1,307 | 43 | # Copyright (c) OpenMMLab. All rights reserved.
import torch
from torch.nn.modules.batchnorm import _BatchNorm
from mmcls.models.backbones import DistilledVisionTransformer
def check_norm_state(modules, train_state):
"""Check if norm layer is in correct train state."""
for mod in modules:
if isinsta... |
9622db895f46adb4035e6ed4bb46fb1afd099af235f136ee4e097220c7ef34db | Python | 1,308 | 67 | # SPDX-License-Identifier: LGPL-3.0-or-later
# Import to register converters. ``dpa4_nn`` registers the dpmodel -> pt_expt
# converters for the DPA4 interaction block, initial embedding, grid nets,
# SO(2) modules and radial MLP (activation checkpointing, accelerated inference
# kernels and trainable-weight promotion),... |
17dcc419e397fc62273dcc388994ba8b0be3dd18e07279f565488cc339aba7ba | Python | 1,310 | 60 | from pyontutils import sheets
from pyontutils.sheets import Sheet
from pyontutils.namespaces import ilxtr
from neurondm.sheets import CutsV1, Row as RowBase
from neurondm.core import Config, NeuronEBM
from neurondm.phenotype_namespaces import Species
class NeuronNerves(NeuronEBM):
owlClass = ilxtr.NeuronNerves
... |
4066f33584833f517a7ecd52c3f22b135f45074e6db96cecbea38c6ca0913ed7 | Python | 1,311 | 37 | # Copyright 2019 DeepMind Technologies Limited
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agr... |
7574374f7f7bf3305cf63df47a75e30c66a2edc533c8a19ffd7d68c968c26677 | Python | 1,312 | 45 | import unittest
import htmlfn as hfn
doc_expect ='''<!DOCTYPE HTML PUBLIC "-//W3C//DTD HTML 4.01//EN"
"http://www.w3.org/TR/html4/loose.dtd">
<html>
<head>
<title>test page</title>
<meta charset="UTF-8">
<meta test="meta">
<style>
body { font-family: Dejavu Sans Mono; font-size: 11pt }
</style>
<script>
console.log("l... |
3472a3883e13306a747cc601e4e2caef706689e92f9fb694fc597820af5ba52c | Python | 1,317 | 33 | # Code adapted from tensorflow to pytorch from https://github.com/google-research/graph-attribution/tree/main/graph_attribution
import torch
from torch.autograd import Variable
from torch_geometric.data import Data
from molucn.feat_attribution.explainer_base import Explainer
class GradInput(Explainer):
def __init... |
7549e1781f00ef027df81d9fc368fb00b7fe483e00ca675a164f800fdd02dbae | Python | 1,317 | 43 | # An extension to: Mocapy
#
# Copyright (C) 2007 Jes Frellsen, Ida Moltke and Martin Thiim
#
# This library is free software: you can redistribute it and/or
# modify it under the terms of the GNU General Public License as
# published by the Free Software Foundation, either version 3 of the
# License, or (at... |
2eb3444af8d3bce9c235d8bd3c6e4f5997103d2ae4a649a31cf87c6b3c3156fb | Python | 1,319 | 42 | #!/usr/bin/env python
from setuptools import setup, find_packages
from os import path
this_directory = path.abspath(path.dirname(__file__))
with open(path.join(this_directory, 'README.md'), encoding='utf-8') as f:
long_description = f.read()
setup(
name='OpenNMT-py',
description='A python implementation o... |
62d9f32b5959954837e4692d0deeb7d9d3b02c8f878af1c60423c185881ab1db | Python | 1,320 | 31 | import time
_this_year = time.strftime("%Y")
__name__ = "vp-suite"
_version = 0, 0, 9
__version__ = ".".join(map(str, _version))
__author__ = "Andreas Boltres"
__author_email__ = "andreas.boltres@posteo.de"
__license__ = "MIT"
__copyright_short__ = f"2021-{_this_year}, {__author__}"
__copyright__ = f"Copyright (c) {__... |
7106da2c0fad568517eb7b9d982a010760e303d30b0edc7f2805e187e724e3b4 | Python | 1,321 | 50 | # Copyright (c) ONNX Project Contributors
# SPDX-License-Identifier: Apache-2.0
from __future__ import annotations
from typing import TYPE_CHECKING, Any
import pytest
from onnx.backend.test.report.coverage import Coverage
if TYPE_CHECKING:
from collections.abc import Sequence
import _pytest
_coverage = C... |
3a50cfef92c655b580916913a5822e046ca7d1724039de990a9090feaa65bbb2 | Python | 1,322 | 62 | # Copyright (c) ONNX Project Contributors
#
# SPDX-License-Identifier: Apache-2.0
from __future__ import annotations
import numpy as np
import onnx
from onnx.backend.test.case.base import Base
from onnx.backend.test.case.node import expect
class Round(Base):
@staticmethod
def export() -> None:
node ... |
a99ef68cbfb437345dd02681439f882c5ce221141ae98dc33bfa9d2047d641b9 | Python | 1,322 | 39 | from ..preprocessing import preprocess
def basic_preprocessing(data):
"""
Call each of the listed preprocessing functions on <data> and return the result.
Preprocessing functions:
- cast_to_typed_array
- normalize_by_MAD
- center_to_mean
Args:
data (np.ndarray, list): ... |
3567877b222f7e18003ae3d3e8864f1f0fdad0cbd9622810df19b1390fbfc9e2 | Python | 1,325 | 48 | import unittest
import os
import shutil
import numpy as np
from ddt import ddt
from SPHARM.classes.surface import Surface
from SPHARM.classes.moving_surface import MovingSurface
@ddt
class TestMovingSurfaceCass(unittest.TestCase):
def test_add_spectrum_and_plotting(self):
ms = MovingSurface()
... |
35000014586203bf960a10ab33b93e42916b68b08c4870ef2e3a0bb6bf017845 | Python | 1,326 | 36 | # qtlib.py
#
# Utiliti functions for training CNN in DeepDTI.
#
# (c) Qiyuan Tian, Harvard, 2021
import numpy as np
import keras.backend as K
def extract_block(data, inds):
xsz_block = inds[0, 1] - inds[0, 0] + 1
ysz_block = inds[0, 3] - inds[0, 2] + 1
zsz_block = inds[0, 5] - inds[0, 4] + 1
ch_block ... |
4180d427cdb9a976df4b2add02d8e2528e8f5736ce34787c9630284d40c863c6 | Python | 1,326 | 41 | import numpy as np
from tensorflow import keras
import tensorflow as tf
from tensorflow.keras.models import Sequential
from tensorflow.keras.layers import Dense, Dropout, Activation, Flatten
from tensorflow.keras.layers import Convolution2D, MaxPooling2D
from tensorflow.keras import layers
from tensorflow.keras.preproc... |
72537a0c63086075277c57737e3b00a0251d3138cd9b127ee91b33541252612a | Python | 1,326 | 42 | # ----------------------------------------------------------------------------
# Copyright (c) 2017-2026, QIIME 2 development team.
#
# Distributed under the terms of the Modified BSD License.
#
# The full license is in the file LICENSE, distributed with this software.
# ------------------------------------------------... |
b6124249bc2cc01e62385dfda3bf4ee1ca9f999b393bb378b8cfd42c80f85508 | Python | 1,326 | 42 | # Copyright (c) OpenMMLab. All rights reserved.
import torch.nn as nn
from ..builder import BACKBONES
from .base_backbone import BaseBackbone
@BACKBONES.register_module()
class LeNet5(BaseBackbone):
"""`LeNet5 <https://en.wikipedia.org/wiki/LeNet>`_ backbone.
The input for LeNet-5 is a 32×32 grayscale image... |
ed2b643cb170f75b1b17c6b070c2dbed8d520e85a2ed250100d09ac93cfbbf6e | Python | 1,326 | 43 | """Code to generate pair ensembles."""
import click
import pandas as pd
import parallel as par
import neighbors as nb
import atom3d.util.log as log
logger = log.get_logger('shard_pairs')
def _gen_pairs_per_ensemble(x, cutoff, cutoff_type):
pairs = []
if len(x['subunit'].unique()) > 1:
raise RuntimeE... |
582b5c05d20787ab64791d8e6f3afa2f2c1e7f22bf856470a035d8306028fdbc | Python | 1,327 | 42 | """HIVE-COTE v2 test code."""
import pytest
from sktime.classification.hybrid import HIVECOTEV2
from sktime.classification.sklearn import RotationForest
from sktime.datasets import load_unit_test
from sktime.tests.test_switch import run_test_for_class
@pytest.mark.skipif(
not run_test_for_class(HIVECOTEV2),
... |
80c6ebdbcf7ea9a37c7c2b820303ab6b557a28d10055d86168bf5cfd5aeca360 | Python | 1,327 | 42 | #
# # Template from TemplateFlow: WHS
#
# [Open interactive notebook in Binder](https://mybinder.org/v2/gh/wiheto/netplotbrain/main?filepath=docs/gallery/whs.ipynb)
#
# To plot different templtes from templateflow, you just need to change the template specification:
#
# `template='WHS',`
#
# The example nodes are sca... |
a6aef0438c15b209c508600cadfa32cf8eb4aa44372a227f1f3228a99e0116e1 | Python | 1,327 | 36 | # Copyright 2019-2021 The ASReview Authors. All Rights Reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by appl... |
61089e6d354d120f69dbc9e12fb5e73d2d6616b6494ce6c7d35e294694d7464e | Python | 1,328 | 47 | """train_precipitation"""
"""
Author: Yimin Yang
Last revision date: Jan 18, 2022
Function: Run this to train the model on cloud cover dataset
"""
import torch
from Models.AA_TransUNet import AA_TransUnet
import pytorch_lightning as pl
if __name__ == "__main__":
args = {
'vit_blocks': 1,
'vit_he... |
699be6a0e90a912e6428041b7bcdf8c7ce8d43bca61a9280402a1d73b9196e98 | Python | 1,330 | 43 | import numpy as np
from scipy import io
import os, subprocess
def define_initial_transformation(aff, transl, outname):
"""
generates a .mat file defining the initial transformation
INPUTS:
aff: 3x3 numpy matrix
transl: 3x1 vector
outname: .mat file name
"""
aff = aff.reshape((9,1))
transl = transl.reshape((3... |
a1f353609ac53a7aba7d10426f3741e1dc08956b47f411319c42dcad7005e202 | Python | 1,330 | 42 | # Copyright (c) ONNX Project Contributors
#
# SPDX-License-Identifier: Apache-2.0
from __future__ import annotations
import numpy as np
import onnx
from onnx.backend.test.case.base import Base
from onnx.backend.test.case.node import expect
class Where(Base):
@staticmethod
def export() -> None:
node ... |
53de065abf1b5c09878c95a1dc5d82f5569226efc17295a86eccd4dd5aa88537 | Python | 1,331 | 40 | import logging
import os
from abc import ABC, abstractmethod
from typing import Dict, List
class Processor(ABC):
"""Base class for processor"""
@abstractmethod
def __init__(self,
model_name: str,
model_args, # let's enforce everythi... |
734566f927d3ed4199cc015c48804a65d8c77809dbc0e664a28a5ec48218df73 | Python | 1,331 | 60 | # Copyright (c) ONNX Project Contributors
#
# SPDX-License-Identifier: Apache-2.0
from __future__ import annotations
import numpy as np
import onnx
from onnx.backend.test.case.base import Base
from onnx.backend.test.case.node import expect
class MatMulInteger(Base):
@staticmethod
def export() -> None:
... |
76d3249ba12539cb1a1cd0630e033845694bf7a5d618edceb19b4b0f253421ea | Python | 1,334 | 33 | #------------------------------------------------------------------------------
# elftools tests
#
# Anders Dellien (anders@andersdellien.se)
# This code is in the public domain
#------------------------------------------------------------------------------
import os
import unittest
from elftools.elf.elffile import EL... |
790c43699c54f398f1c3d35776bcfe7cd4e69c479ed1732959520610359c77d7 | Python | 1,334 | 45 | import numpy as np
import matplotlib as mpl
import matplotlib.pyplot as plt
import matplotlib.ticker as ticker
__all__ = ["palplot", "dogplot"]
def palplot(pal, size=1):
"""Plot the values in a color palette as a horizontal array.
Parameters
----------
pal : sequence of matplotlib colors
col... |
6aa936728e06d1cadb5417ac3b37b6e3081a976c578f3fe839fc217c5f99e664 | Python | 1,335 | 33 | """Fetch official comparator repositories at the experiment's pinned revisions."""
import argparse
from pathlib import Path
import subprocess
from short2long.published_models import ROOT, UPSTREAM
URLS = {
"rtdl": "https://github.com/yandex-research/rtdl-revisiting-models.git",
"babel": "https://github.com/wu... |
b42078e17ba742b070d2a339a7a4a1ee74ae5bc610ad3900a980358629e2e86b | Python | 1,337 | 43 | # Configuration file for the Sphinx documentation builder.
#
# For the full list of built-in configuration values, see the documentation:
# https://www.sphinx-doc.org/en/master/usage/configuration.html
import os
import sys
sys.path.insert(0, os.path.abspath('../..'))
# -- Project information --------------------... |
f528303ca75f18c7a708936c61ac99701a0dc8251353e9600da6bacd3187ed25 | Python | 1,337 | 45 | # coding=utf-8
# Copyright (C) 2022. Huawei Technologies Co., Ltd. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# ... |
75c6844f4080748a9b673068778e826004a5221fe3690f8cc4a3f01df4272c8c | Python | 1,338 | 53 | import sys
import torch
from tqdm import tqdm
from PIL import Image
from torchvision import transforms
sys.path.insert(0, '..')
from utils.func import load_config
from modules.builder import generate_model
def define_preprocess(cfg):
input_size = cfg.data.input_size
mean = cfg.data.mean
std = cfg.data.st... |
dbd3c877716e4ab2c7c1fc83bcf808c8045c1cfc5d22d9f4adfeac513d2ed53a | Python | 1,338 | 45 | """Utilities for detection tasks."""
import numpy as np
import pandas as pd
def seg_middlepoint(seg_df):
"""Convert segmentation data frame to midpoint detections.
Parameters
----------
seg_df : pd.DataFrame
data frame in segmentation format, with columns:
* ``ilocs`` - IntervalInde... |
7d0b85c780c15f05f50ed6a34f684ec7173faf396d4613495afc5b11d5c8551f | Python | 1,339 | 48 | import numpy as np
from tensorflow.keras.initializers import Constant, RandomNormal, VarianceScaling
def ones_zeros(hidden_dim):
"""Creates a custom initializer for GRU cell bias.
GRU bias initializer sets gate bias (upper 2/3 of matrix)
to 1 and candidate bias (bottom 1/3 of matrix) to 0
Parameters... |
e29d4202d36d36b0d42bef95d91468ddbcd27f77c935bdf7645a771acd59748e | Python | 1,339 | 43 | # Copyright (c) OpenMMLab. All rights reserved.
from collections.abc import Sequence
from mmcv.utils import build_from_cfg
from ..builder import PIPELINES
@PIPELINES.register_module()
class Compose(object):
"""Compose a data pipeline with a sequence of transforms.
Args:
transforms (list[dict | call... |
8d5f2f24eca56235bef5edb6d17c5d13f1e52cdb1e2f724beedc203c0ad04fa9 | Python | 1,340 | 41 | import numpy as np
from tensorflow import keras
import tensorflow as tf
from tensorflow.keras.models import Sequential
from tensorflow.keras.layers import Dense, Dropout, Activation, Flatten
from tensorflow.keras.layers import Convolution2D, MaxPooling2D
from tensorflow.keras import layers
from tensorflow.keras.preproc... |
79f7593a3df9be8baa8ba19be22f5290002a458125a62528500d17fade2964e1 | Python | 1,341 | 36 | # ----------------------------------------------------------------------------
# Copyright (c) 2017-2026, QIIME 2 development team.
#
# Distributed under the terms of the Modified BSD License.
#
# The full license is in the file LICENSE, distributed with this software.
# ------------------------------------------------... |
cb41b4231ae221e8b811268df890934a9b2c9cae2bc09549dc39d2e06a2f7c4a | Python | 1,342 | 46 | import numpy as np
import matplotlib.pyplot as plt
import seaborn as sns
import anndata as ad
import scanpy as sc
from matplotlib.colors import ListedColormap
sns.set_context("poster")
sns.set_palette("colorblind")
sc.settings.figdir = "./figures/"
seed = 1029 # set randomness for dim. reduction and clustering
data_d... |
ec32f1f6dec9c8fa0656449a067c034a44476f97fd76ce481f7d4f52af4a901d | Python | 1,342 | 48 | """
utility to copy the ORIGINAL VCN hoc files to a new name only if the new name
does not already exist (prevent overwrite)
This module is part of *vcnmodel*.
Support::
NIH grants:
DC R01 DC015901 (Spirou, Manis, Ellisman),
DC R01 DC004551 (Manis, 2013-2019, Early development)
DC R01 DC019053 (Manis... |
98ae326bd84044ec27d3defd89fb40c630b04a797c6e0e59113787303ccc9b46 | Python | 1,343 | 44 | # Copyright (c) ONNX Project Contributors
# SPDX-License-Identifier: Apache-2.0
"""onnx version converter
This enables users to convert their models between different opsets within the
default domain ("" or "ai.onnx").
"""
from __future__ import annotations
import onnx
import onnx.onnx_cpp2py_export.version_convert... |
a21c4be60b12e47f5ffb45aff276859d10dbd9157046bed4686063baeb80697b | Python | 1,343 | 40 | from typing import Dict, List
from rxnebm.proposer.proposer_base import Proposer
from rxnebm.proposer.retrosim_model import Retrosim
class RetrosimProposer(Proposer):
""" Retrosim proposer """
def __init__(self, retrosim_config: Dict) -> None:
super().__init__()
self.model = self.build_mode... |
c74ae56869f84d30cc1e22bb2c3b2372488c644532c730a310f22308a8170633 | Python | 1,343 | 43 | # Copyright 2019-2020 The ASReview Authors. All Rights Reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by appl... |
ecaa8ed8d29019694d4c2a8ba515c856bd0be38f47e7ef96fbd18d11d9978f20 | Python | 1,344 | 41 | from collections.abc import Iterable
import torch
from flair.models import MultitaskModel
from flair.nn import DeepNCMDecoder
from flair.trainers.plugins.base import TrainerPlugin
class DeepNCMPlugin(TrainerPlugin):
"""Plugin for training DeepNCMClassifier.
Handles both multitask and single-task scenarios.... |
509f3f706cb9df9df28f4343095c6a371909a8e91ff6e2480764c2312efb7990 | Python | 1,345 | 47 | # Copyright (c) ONNX Project Contributors
#
# SPDX-License-Identifier: Apache-2.0
from __future__ import annotations
import numpy as np
import onnx
from onnx.backend.test.case.base import Base
from onnx.backend.test.case.node import expect
class Sum(Base):
@staticmethod
def export() -> None:
data_0 ... |
213aa3442ca93c3f7e7c604f00777253892d55044bbe5b20c9721b875ab472e9 | Python | 1,346 | 47 | # Copyright 2019-2020 The ASReview Authors. All Rights Reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by appl... |
63f4fd496c7684a35a910a4a67d06432d71d540d2fc11b661f029f6df0682d03 | Python | 1,346 | 45 | #%%
import pandas as pd
import numpy as np
import netplotbrain
import templateflow.api as tf
import itertools
import pytest
import matplotlib.pyplot as plt
#%%
@pytest.mark.mpl_image_compare
def test_labels():
#%%
atlas = {'template': 'MNI152NLin2009cAsym',
'atlas': 'Schaefer2018',
... |
c7db32babb1457ad57a647df92fd9d84d65adebf9cead7babe1511df06774325 | Python | 1,346 | 72 | """Shared pytest fixtures for the corset-tools test suite."""
from pathlib import Path
import pytest
@pytest.fixture(scope='session')
def data_dir() -> Path:
"""
Directory holding the checked-in test fixtures.
Returns
-------
pathlib.Path
Path to ``tests/data``.
"""
return Path(... |
da70748b956192ae86d14d784eecdeea8c54b790bcb3a13d0d03c6bb227d4717 | Python | 1,346 | 38 | #------------------------------------------------------------------------------
# elftools tests
#
# Seva Alekseyev (sevaa@sprynet.com)
# This code is in the public domain
#------------------------------------------------------------------------------
import os
import sys
import unittest
sys.path.insert(1, os.getcwd(... |
1615982bde76f164a1546e570969012c1dd1d73748dbdbf20a90fc64c26d0a17 | Python | 1,347 | 48 | # Copyright (c) ONNX Project Contributors
# SPDX-License-Identifier: Apache-2.0
from __future__ import annotations
import numpy as np
from onnx.reference.op_run import OpRun
def _rms_normalization(
X: np.ndarray,
W: np.ndarray,
axis: int = -1,
epsilon: float = 1e-5,
) -> np.ndarray:
shape = X.s... |
23ced2a63b5fcf116e944d1938c391352f47e3ad5be3aaee4cbbab2af1d69064 | Python | 1,348 | 47 | from __future__ import annotations
from typing import TYPE_CHECKING
if TYPE_CHECKING:
from typing import Self
# Map an integer in the inclusive range 0-255 to its string byte representation
_printable = {i: chr(i) if 32 <= i < 128 else "." for i in range(256)}
def hexdump(data: bytes, linesize: int) -> list[s... |
6ce28edd95b7d0a1619ec3079d03391982297abdf808ddbdcc400cb2a8d0098c | Python | 1,349 | 62 | """
plot_pareto_front
=================
.. autofunction:: optuna.visualization.plot_pareto_front
:no-index:
The following code snippet shows how to plot the Pareto front of a study.
.. _visualization-plot-pareto-front-plotly-content:
"""
import optuna
def objective(trial):
x = trial.suggest_float("x", 0... |
994c19e034f9ad2e8e1f4dacbf03be593c55faea63fef48feb0697691ae8a2fd | Python | 1,349 | 43 | """Compute medoids from time series."""
__author__ = ["chrisholder", "TonyBagnall"]
import numpy as np
from sktime.dists_kernels._numba_distances import pairwise_distance
def medoids(
X: np.ndarray,
precomputed_pairwise_distance: np.ndarray = None,
distance_metric: str = "dtw",
):
"""Compute the me... |
f179b246901e64663c4012a474d6cd0f683b9ba76e8b9bb74a67a3b05fbeeda5 | Python | 1,349 | 30 | import numpy as np
class ResultWriter():
def __init__():
pass
def write():
#-----
# show the summary (average) of the result
print('classifier type = ' + str(classifierType))
print('classifier parameter = ' + str(classifierParams[paramID]))
print('pastStageLo... |
956375bc6c7039bf3431966621d00ab906bd63a1286f565e1b6c3db5d02a30d6 | Python | 1,350 | 40 | # Copyright 2019 DeepMind Technologies Ltd. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by appl... |
13d4fcddec7951273bdee881507a24182c5a33b0c23301b99e3a01afafb62eef | Python | 1,352 | 32 | # Copyright (c) ONNX Project Contributors
# SPDX-License-Identifier: Apache-2.0
from __future__ import annotations
import numpy as np
from onnx.reference.op_run import OpRun
class SwiGLU(OpRun):
def _run(self, a, b, alpha=None):
# SwiGLU requires identical shapes and dtypes for A and B: broadcasting is... |
af1c78ad2e6ecf0aee503cf0d4e5451a56f4287a8eb19342fa3de330e069f93a | Python | 1,352 | 42 | #
# # Template from TemplateFlow: MNIInfant
#
# [Open interactive notebook in Binder](https://mybinder.org/v2/gh/wiheto/netplotbrain/main?filepath=docs/gallery/infant.ipynb)
#
# To plot different templtes from templateflow, you just need to change the template specification:
#
# `template='MNIInfant',`
#
# The exampl... |
Subsets and Splits
No community queries yet
The top public SQL queries from the community will appear here once available.