sha256 stringlengths 64 64 | language stringclasses 28
values | size int32 1 491k | lines int32 1 23.2k | content stringlengths 1 200k |
|---|---|---|---|---|
0097903f449f2d3f339ea286e314a12b0ba2e4a26fc4f9367ce001a402c759ff | Python | 1,707 | 56 | """
Example for creating a synthetic dataset with compositional labels.
Requirements
------------
seaborn
mpl_toolkits
"""
from smote_cd import dataset_generation
import numpy as np
import matplotlib.pyplot as plt
import seaborn as sns
from mpl_toolkits.axes_grid1 import make_axes_locatable
def display_data():
... |
4e23af7f1f2f3313497e43f751c1cbb81dcaf5f169bc6dd0fb71089e2a03a3fb | Python | 1,707 | 54 | from flair.data import Dictionary, Sentence
from flair.embeddings import (
DocumentLMEmbeddings,
DocumentRNNEmbeddings,
FlairEmbeddings,
)
from flair.models import LanguageModel
from tests.embedding_test_utils import BaseEmbeddingsTest
class TestFlairEmbeddings(BaseEmbeddingsTest):
embedding_cls = Fla... |
155ea6abbdd77381ad7fe5507d4989958debaf440ac6c78a334d988f90b9f577 | Python | 1,708 | 46 | from typing import Any
from flair.trainers.plugins.base import TrainerPlugin
from flair.trainers.plugins.metric_records import MetricRecord
class ClearmlLoggerPlugin(TrainerPlugin):
def __init__(self, task_id_or_task: Any):
if isinstance(task_id_or_task, str):
self.task_id = task_id_or_task
... |
5f70fa486841f0415c1179b1e28da6ea33ae21dbbb4cf332be85a2a75bc71ed8 | Python | 1,709 | 53 | import numpy as np
#import matplotlib
# Force matplotlib to not use any Xwindows backend.
#matplotlib.use('Agg')
import matplotlib.pyplot as plt
class covar_pdf:
"""
Plots the probability density distributions of prediction and observation
for cross-covariances.
"""
def __init__(self, testObj):
... |
b7b2dda03d7a6ac21c9480c2783be7242d424e258d16f02695f07c2d0ca0e1dd | Python | 1,710 | 44 | # 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... |
aff2eb1f09c60e8b3e6dff28cb78ae592eded3eed23654a476b890f96d37bebc | Python | 1,711 | 71 | #!/usr/bin/env python2
__doc__ = """
Loss functions.
Nicholas Turner <nturner.cs@princeton.edu>, 2017
"""
import torch
from torch import nn
import numpy as np
from balance import gunpowder_balance
class BinomialCrossEntropyWithLogits(nn.Module):
"""
A version of BCE w/ logits with the ability to mask
... |
3648af90908df10545ea34ad828d0bbc9f8b231ddfab461bf2cca8841eb2457b | Python | 1,712 | 51 | # 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... |
de6639c77361f96b5fdcd23814309f14c83eebd46352f59bc3a0c790e37e7cdc | Python | 1,713 | 48 | """Script for the direct comparison of the GNN performance compared to DFT.
It works wirth systems containing the following elements:
Adsorbate: C, H, O, N, S
Catalyst slab: Ag, Au, Cd, Co, Cu, Fe, Ir, Ni, Os, Pd, Pt, Rh, Ru, Zn
"""
import argparse
import sys
sys.path.insert(0, "../src")
import matplotlib.pyplot as ... |
57ddead3535c5f740d405ef3e2951cb947fbd2ec8c7427d95f70be045e8d1b40 | Python | 1,715 | 53 | # 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
#
... |
5219058878243ef36515d0d2abe3f54232d1b337bf8b12c21d15c8d25e810df7 | Python | 1,718 | 73 | """Loads NetworkUnit score classes"""
import math
def to_precision(x,p):
"""
returns a string representation of x formatted with a precision of p
Based on the webkit javascript implementation taken from here:
https://code.google.com/p/webkit-mirror/source/browse/JavaScriptCore/kjs/number_object.cpp
... |
61bd2330cdf0bd19525afd2f33db1a5c8b5e4cd966d798f3b5e71fa47b48f25b | Python | 1,718 | 61 | import pytest
import pandas as pd
import scanpy as sc
import numpy as np
from palantir.utils import run_pca
@pytest.fixture
def mock_data():
n_cells = 50
n_genes = 500
rng = np.random.default_rng()
return pd.DataFrame(
rng.random((n_cells, n_genes)),
columns=[f"gene_{i}" for i in rang... |
d2af72fda6241f07605f428e62aae92c048366f979c66a441ec1603e303d0209 | Python | 1,718 | 29 | """This file contains the radius for every element.
Constants:
CORDERO (dict): Covalent radius.
Beatriz Cordero; Verónica Gómez; Ana E. Platero-Prats; Marc Revés;
Jorge Echeverría; Eduard Cremades; Flavia Barragán; Santiago Alvarez
(2008). "Covalent radii revisited". Dalton Trans. (21): 283... |
bf1c82b00dba39c30c158d8f4e76cf9c7c777098ac341bcc8b1a23d25ea94df7 | Python | 1,720 | 57 | # roifile_demo.py
"""Demonstrate the roifile module.
Use the roifile and tifffile modules to read and write the results of image
segmentation from/to ImageJ TIFF files.
"""
import numpy
from matplotlib import pyplot
from skimage.measure import find_contours, label, regionprops
from tifffile import TiffFile, imwrite... |
4775599e695af0ada96389bacc09f288db602ea1cdae11da0a755d018c8fe2bd | Python | 1,721 | 52 | from __future__ import print_function
import sys
import numpy as np
from scipy import signal
import matplotlib.pyplot as plt
from parameterSetup import ParameterSetup
from statistics import recompMean, recompVariance
args = sys.argv
if len(args) > 1:
option = args[1]
else:
option = ''
# get params shared by p... |
597782389951a3a09a0635a2661e70659a36b537ffe2cd62163ffda808788e40 | Python | 1,722 | 49 | # 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 MeanVarianceNormalization(Base):
@staticmethod
def export() ->... |
7aabefb2a4cbeae126f4cb646599ca636fd19d251039ad4d6a448054da0d20d4 | Python | 1,722 | 52 | """Unit tests for sklearn classifiers."""
__author__ = ["MatthewMiddlehurst"]
import platform
import pytest
from sklearn.linear_model import LogisticRegression
from sklearn.utils.estimator_checks import parametrize_with_checks
from sktime.classification.sklearn import ContinuousIntervalTree, RotationForest
from skt... |
91235d1dfacc55ae1672e386e2c67445bba92bd95cb0f4492f672ad3500e515d | Python | 1,723 | 56 | # 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 IsInf(Base):
@staticmethod
def export_infinity() -> None:
... |
f47fab7b7d1646f5d2cbad8ead6056b2415c0dbb78b16bc68d2e24520e17c50d | Python | 1,723 | 50 | # 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
#
# ... |
41e07877af48b243ed55f69c2f91c91b6adac4daf775a8d05a22528be38432a2 | Python | 1,724 | 47 | # 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... |
44b2124d7d0756fcf49a2a681a3cd61162df19365f4c8548c0ea8498abcca580 | Python | 1,726 | 61 | from __future__ import print_function
"""
"""
import sys
import subprocess
if len(sys.argv) < 2: # if no argument, print helpful message
print("Plot selected figures from paper, Manis and Campagnola, Hearing Research. 2018")
print("Usage: figures.py [2a | 2b | 2c | 3 | 4 | 5 | 6a | 6d | 7]")
exit(1)
... |
61efdbf82a097f6503a02ec874b98ea8c9a9a768fde23eeb519da750eaf13330 | Python | 1,728 | 46 | from expert.src.model import Model
import os
os.environ['TF_CPP_MIN_LOG_LEVEL'] = '2'
import tensorflow as tf, pandas as pd, numpy as np
from expert.CLI.CLI_utils import find_pkg_resource
def search(cfg, args):
# Basic configurations for GPU and CPU
os.environ["CUDA_DEVICE_ORDER"] = "PCI_BUS_ID"
os.envi... |
bb402fa753f509705b01b3f1677cdc60d9d14c2db12fb9e8e2fd0320cb43b2e1 | Python | 1,730 | 42 | # Copyright 2019 The TensorFlow 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 applica... |
302da229f7cd76849bfea55ef30b4dbbf72525b34f7567274aa67655b7fc0c94 | Python | 1,731 | 47 | # Copyright (c) ONNX Project Contributors
# SPDX-License-Identifier: Apache-2.0
from __future__ import annotations
import numpy as np
from onnx.reference.ops.aionnxml._op_run_aionnxml import OpRunAiOnnxMl
class DictVectorizer(OpRunAiOnnxMl):
def _run(self, x, int64_vocabulary=None, string_vocabulary=None):
... |
3e10931f7f96ef35456cf89e05b47c73fd62d69a5b6a0435911276132b1c9680 | Python | 1,731 | 52 | # 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... |
d03afd6705c8d0d7328de00fc6c6fe3a18e8619faaebd59eaa0f2168f5746d3e | Python | 1,731 | 51 | # SPDX-License-Identifier: LGPL-3.0-or-later
"""PyTorch extras keep Vesin bindings within their supported versions."""
from pathlib import (
Path,
)
import pytest
from packaging.requirements import (
Requirement,
)
@pytest.mark.parametrize("version", ["2.1.0", "2.2.0", "2.3.0", ""])
def test_vesin_requireme... |
e7cd77d847ff536424e2c40ac2eb5e9f1015daf2b7f4fc03b34eeab6e1295f61 | Python | 1,731 | 49 | from setuptools import setup, find_packages
import setuptools
import os, shutil
import os
path = os.path.join(os.path.dirname(__file__), 'cnmodel')
version = None
for line in open(os.path.join(path, '__init__.py'), 'r').readlines():
if line.startswith('__version__'):
version = line.partition('=')[2].stri... |
0aa8e1547f4d444ea38f193e9f361698566c1e22d91c397f4909359e790d626f | Python | 1,732 | 52 | import numpy as np
import os
from matplotlib import pyplot as plt
from .helper import run_shell_command
from ..io import save_nifti
def show_brain_side_by_side(im1, im2, num=10, savename=None):
# merge two images along x axis
merged = np.concatenate((im1, im2), axis=2)
start = int(im1.shape[0]*0.05)
e... |
0aaf95832460628ce85ef4953c6dc47dbf9c3f2e82c6082ef42fcb40952046c6 | Python | 1,732 | 41 | import torch
import os
class Config(object):
"""args in model and trainer"""
def __init__(self):
self.device = torch.device('cuda:0' if torch.cuda.is_available() else 'cpu')
self.num_fold = 10
self.num_classes = 5
self.num_epochs = 200 # Because early stopping is ... |
13bc435b880b9a33f4c3cdb517af76ee31731844e23ad7e1d5106ae335ac4d67 | Python | 1,732 | 45 | # 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... |
746b507b8cee2c63781642341dafd161eed6883fb87f1bdf3097de93dddffe20 | Python | 1,732 | 63 | #!/usr/bin/env python
import click
import pandas as pd
import sys
CONTEXT_SETTINGS = {
"help_option_names": ["-h", "--help"],
}
@click.command(no_args_is_help=True, context_settings=CONTEXT_SETTINGS)
@click.argument(
"bed_file",
type=click.Path(exists=True, resolve_path=True),
)
@click.argument(
"chr... |
1f1962a9662214d073e98a2a5fd1fc053ef2e3adcb8f12905ef3cf9a012066a2 | Python | 1,735 | 63 | """Euclidean distances implemented in pytorch.
This module was copied from the repository the following repository:
https://github.com/asappresearch/dynamic-classification
It contains the code from the paper "Metric Learning for Dynamic Text
Classification".
https://arxiv.org/abs/1911.01026
In case this file is mod... |
2f7319197283535fbc38156a6899e5a099aab0fadda06adda8ad510d5c65138d | Python | 1,735 | 46 | import scipy.stats
import numpy as np
from .population import Population
from .. import cells
class TStellate(Population):
type = 'tstellate'
def __init__(self, species='mouse', **kwds):
# Note that `cf` is the mean value used when selecting SGCs to connect;
# it is NOT the measured CF o... |
1cb5fc9c646c0441b50f795cab4680c07098d93acbfb198eda6fc251c50afa67 | Python | 1,736 | 52 | from setuptools import setup
from setuptools import find_packages
# change this.
NAME = "expert-mst"
AUTHOR = "Hui Chong"
EMAIL = "huichong.me@gmail.com"
URL = "https://github.com/HUST-NingKang-Lab/EXPERT"
LICENSE = "MIT"
DESCRIPTION = "Exact and pervasive expert model for source tracking based on transfer le... |
8415bd8504e669b2f41bada83244e74cf2cdcbe54a3a39493599573e11ee6191 | Python | 1,736 | 51 | """JapaneseVowels dataset."""
from sktime.datasets._single_problem_loaders import load_japanese_vowels
from sktime.datasets.classification._base import _ClassificationDatasetFromLoader
class JapaneseVowels(_ClassificationDatasetFromLoader):
"""JapaneseVowels time series classification problem.
Example of a ... |
c459c8a91569d5f927b950cb874600eacfed06703ef64445aa0fbdca7de3a8b8 | Python | 1,736 | 52 | import re
from setuptools import setup
def find_version(filename):
_version_re = re.compile(r"__version__ = '(.*)'")
for line in open(filename):
version_match = _version_re.match(line)
if version_match:
return version_match.group(1)
__version__ = find_version('htmlfn/__init__.py'... |
10db143e7068bddbf0bf7612fa277b52192368d2ebcf37cd929b0ec57f86484a | Python | 1,738 | 52 | from setuptools import setup
from setuptools import find_packages
# change this.
NAME = "expert-mst"
AUTHOR = "Hui Chong"
EMAIL = "huichong.me@gmail.com"
URL = "https://github.com/HUST-NingKang-Lab/EXPERT"
LICENSE = "MIT"
DESCRIPTION = "Exact and pervasive expert model for source tracking based on transfer le... |
13f2c192ace5d1e5d6afa8c89002d671ca27c1e65fbeaccb475903e8dc1f5e0f | Python | 1,738 | 48 | """GunPoint dataset."""
from sktime.datasets._single_problem_loaders import load_gunpoint
from sktime.datasets.classification._base import _ClassificationDatasetFromLoader
class GunPoint(_ClassificationDatasetFromLoader):
"""GunPoint time series classification problem.
Example of a univariate problem with e... |
916e2cf18541cb07d252dc9d69fa68254841efb6ae72ac6c01b0a11b1164a470 | Python | 1,738 | 51 | # 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... |
a2edc1b7fbf69f973acdbdef69f5565656accbf7a0805b0115a92626fd4e4bdd | Python | 1,738 | 57 | # 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... |
19681173ba2f7969b1453b3164987b690d8365c6ebcc9aea94d6c42eba312e01 | Python | 1,739 | 54 | # -*- coding: utf-8 -*-
#
# Copyright © 2013 Charles E. Vejnar
#
# This Source Code Form is subject to the terms of the Mozilla Public
# License, v. 2.0. If a copy of the MPL was not distributed with this
# file, You can obtain one at https://www.mozilla.org/MPL/2.0/.
#
import json
import os
import re
all_exts = ['.... |
cd7c1e90a8fa81768f8dc049dcea43604452eefda07ec19e1b655ee3b8dfafd0 | Python | 1,739 | 39 | # Copyright (c) OpenMMLab. All rights reserved.
from .alexnet import AlexNet
from .lenet import LeNet5
from .mobilenet_v2 import MobileNetV2
from .mobilenet_v3 import MobileNetV3
from .regnet import RegNet
from .resnest import ResNeSt
from .resnet import ResNet, ResNetV1d
from .resnet_cifar import ResNet_CIFAR
from .re... |
f03a9bddee07acd3655fba44eeaa944454c6ff38cca7fa6fe5779db922d39f65 | Python | 1,739 | 58 | """
Rename import paths for pickle load after restructuring data
Approach taken From stack overflow:
https://stackoferflow.com/questions/2121874/python-pickling-after-changing-a-modules-directory
This module is part of *vcnmodel*.
Support::
NIH grants:
DC R01 DC015901 (Spirou, Manis, Ellisman),
DC R01 ... |
7f887874cce085ca88f0399afe51e4ae2618af38446754ec004df385f0db69b1 | Python | 1,741 | 52 | import face_recognition
import cv2
# This is a demo of blurring faces in video.
# PLEASE NOTE: This example requires OpenCV (the `cv2` library) to be installed only to read from your webcam.
# OpenCV is *not* required to use the face_recognition library. It's only required if you want to run this
# specific demo. If ... |
9224819aadcf24417ede83f501173929bc155a46c6831ef184668b521b27152f | Python | 1,741 | 56 | params = {'font.size': 14,
'font.weight': 'bold',
'axes.labelsize':14,
'axes.titlesize':14,
'axes.labelweight':'bold',
'axes.titleweight':'bold',
'legend.fontsize': 12,
# 'legend.fontweight': 'bold',
}
# Global parameters
ext='.mp4' # '.avi'... |
eae7ac29cb4c18eeb176a007bbe8796da7c562f59374cf9aa70a370d10b0cb9e | Python | 1,741 | 66 | # 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
# Reference implementation of shape op
def shape_reference_impl(
x: np.n... |
406edb2d96fd2b3d42d1d714bad73c83b31d3425228c79e013a0231612fbdacb | Python | 1,743 | 62 | import pytest
import pandas as pd
import scanpy as sc
from anndata import AnnData
import numpy as np
from palantir.utils import run_pca
@pytest.fixture
def mock_data():
n_cells = 50
n_genes = 500
rng = np.random.default_rng()
return pd.DataFrame(
rng.random((n_cells, n_genes)),
column... |
82258bc7cfa8832606b216b7b41eb451d69e49caa1ca3f4f4b62384193b1c76d | Python | 1,743 | 49 | # Copyright 2022 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... |
98bf959ff79c35305f66581ce38b053bf3575fd3dbb0bf3c0bc3dc129183accf | Python | 1,743 | 50 | from ctypes import byref
import numpy as np
import socket
import datetime
import threading
import tqdm
import time
import math
import pickle
from parameterSetup import ParameterSetup
params = ParameterSetup()
pickledDir = params.pickledDir
classifierType = params.classifierType
classifierParams = params.classifierPar... |
359209197b9465c90127a2b70f17cc17cab100a3eeac3d189d10defae0d5fd8c | Python | 1,745 | 51 | from setuptools import find_packages, setup
with open("README.md", "r", encoding="utf-8") as fh:
long_description = fh.read()
setup(
name="genomic_benchmarks",
version="1.0.0",
description="Genomic Benchmarks",
long_description=long_description,
long_description_content_type="text/markdown",
... |
4f67e1112f01ef0eabe52c83ffa2e113f6f7eea68200dba060a99fac156426af | Python | 1,745 | 44 | # 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... |
301ab2c9098820960eaa538745e60c162d7020bb3d307871986e50829cbc0d05 | Python | 1,746 | 55 | # Copyright (c) OpenMMLab. All rights reserved.
import argparse
import datetime
import subprocess
from pathlib import Path
import torch
from mmcv import digit_version
def parse_args():
parser = argparse.ArgumentParser(
description='Process a checkpoint to be published')
parser.add_argument('in_file',... |
926ba4523f75b010b59c4906607616905f0577042c2467b77221d6475f85b30b | Python | 1,746 | 53 | '''
Inference of inception-v3 model with pretrained parameters on ImageNet
'''
import tensorflow.compat.v1 as tf
# To make tf 2.0 compatible with tf1.0 code, we disable the tf2.0 functionalities
tf.disable_eager_execution()
import tensorflow_hub as hub
import numpy as np
import cv2
import pandas as pd
# Load saved ... |
b95dfa7b1fc3c0b89c0d395870e46bd2dd0d84d396729b7fcb99bf659b6ea627 | Python | 1,746 | 58 | import pytest
from itertools import repeat
from time import time
import os
import numpy as np
import siibra
from siibra.features.image.image import Image
from siibra.volumes.volume import Volume
TEST_ALL_PRECONF_BBOXES = os.getenv("TEST_ALL_PRECONF_BBOXES", "False").strip().lower() in ("1", "true", "yes", "on")
RANDO... |
5894d0ccf2a3b72d43ab5b96e3b1849832b604d9833727af1b9feaf2f3acf9b3 | Python | 1,747 | 54 | import torch
from torch import nn
from scipy.spatial import distance
import numpy as np
class DiceCoefficient:
"""
Standard DICE coefficient
"""
def __init__(self, smooth=1.0, epsilon=1e-06, **kwargs):
self.smooth = 1.0
self.epsilon = epsilon
def __call__(self, y_pred, y_true, ma... |
e87246f44e8f0b1624db717ed0da62b196ba164f14682549418f8cc1e0782bda | Python | 1,747 | 56 | import torch
class LockedDropout(torch.nn.Module):
"""Implementation of locked (or variational) dropout.
Randomly drops out entire parameters in embedding space.
"""
def __init__(self, dropout_rate=0.5, batch_first=True, inplace=False) -> None:
super().__init__()
self.dropout_rate = ... |
ee4094c787e6241d60a202848fbdb59a3af667eee06d8aa58d2aa6c236f7cf20 | Python | 1,749 | 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 EyeLike(Base):
@staticmethod
def export_without_dtype() -> Non... |
c625ae29ab665d09349d620a3fe7926c1c9bbb40c07cadf8305704011d4d0d85 | Python | 1,750 | 65 | 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
fpath = '/home/hari/Documents/MNEforBiosemi/'
# List of files stems, each will be appended by run number
# Use list [] and enumerate over if filenames are weird
names... |
870377e260044d9cf86cdabb281e9b11610f3c019973efdceb7e7fcb6e2490cc | Python | 1,751 | 57 | #!/usr/bin/env python
import argparse
import torch
def average_models(model_files, fp32=False):
vocab = None
opt = None
avg_model = None
avg_generator = None
for i, model_file in enumerate(model_files):
m = torch.load(model_file, map_location='cpu')
model_weights = m['model']
... |
b858d1cf3b2a9e08b5938aea12e0fc6218a63d90bb50be816a8ace61241f9b39 | Python | 1,751 | 68 | """
Module to collect system metrics for front-end
"""
import logging
import types
from builtins import str
import psutil
from ts.metrics.dimension import Dimension
from ts.metrics.metric import Metric
system_metrics = []
dimension = [Dimension('Level', 'Host')]
def cpu_utilization():
data = psutil.cpu_percent... |
19506a8b80e35147efe27d300aacf931a6f4d8863c85f82f3b87cc340ef7732d | Python | 1,752 | 56 | # 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... |
36983fb4f85ea8fc8ae51362b060546eb40299e8c264d43dd15eb37ad833a428 | Python | 1,752 | 64 | #!/usr/bin/env python
# -*- coding: utf-8 -*-
from setuptools import setup
with open('README.rst') as readme_file:
readme = readme_file.read()
with open('HISTORY.rst') as history_file:
history = history_file.read()
requirements = [
'face_recognition_models>=0.3.0',
'Click>=6.0',
'dlib>=19.7',
... |
9193553502906ccc487f21af826722f555bf556545d30f3e24d28906b724e13b | Python | 1,752 | 63 | # Author: Behrad Soleimani <behrad@umd.edu>
"Statistical tests"
import numpy as np
from scipy.stats import chi2, ncx2
def fdr_control(d, k, alpha):
"""CFDR control based on BY procedure
Parameters
----------
d: ndarray of shape (n_sources, n_sources)
devianc... |
54f735aef6005917826ee9163f322799619e6825b8efdcf6838f05ad55d963a3 | Python | 1,756 | 41 | import tensorflow as tf
from tensorflow.keras import Model
from tensorflow.keras.layers import Input, Dropout, Activation, Convolution2D, Convolution3D
from tensorflow.keras.layers import BatchNormalization
"""
adapted from https://github.com/okason97/DenseNet-Tensorflow2
"""
def conv_block(x, stage, bra... |
342cf1153d0f3d57ce24c88bee740e8aa210327bc4b5ea779dfa8ff6e331ce46 | Python | 1,758 | 38 | import numpy as np
import nibabel as nib
from nilearn import image, signal, plotting, masking
from scipy import stats
import seaborn as sns
import nilearn
## Taking HCP resting-state fMRI data as an example
## Volume pipeline
gradients_vol = image.load_img('$PATH_SOURCE/principal_gradient_MNI.nii.gz')
nii_img_demo = i... |
557ef27f5fbf1dbedf88006ed7a1695bfa2d52c5f71d2b13ff2330e7e68c68f5 | Python | 1,761 | 46 | # 这是一个在树莓派上运行人脸识别的案例
# 本案例会在命令行控制面板上输出识别出的人脸数量和身份结果。
# 你需要一个2代以上的树莓派，并在树莓派上安装face_recognition，并连接上picamera摄像头
# 并确保picamera这个模块已经安装（树莓派一般会内置安装）
# 你可以参考这个教程配制你的树莓派：
# https://gist.github.com/ageitgey/1ac8dbe8572f3f533df6269dab35df65
import face_recognition
import picamera
import numpy as np
# 你需要在sudo raspi-config中把c... |
c15dbc0199bf154fc3f284421afaa53ecb0ad1d53ac4ca83e26cbf251f67322c | Python | 1,763 | 59 | # 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... |
db04aeb1b9e85c900880baf7780b97ca7344b3522bd0ef3c2cedb8403dfa43f1 | Python | 1,763 | 53 | # 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... |
edc25951e6c604b23354c071a5d7b9ac0851d67d8eb5537e12d9c211d89208ad | Python | 1,763 | 57 | """Dummy segment detector which detects no segments."""
from sktime.detection.base import BaseDetector
class ZeroSegments(BaseDetector):
"""Dummy segments detector which detects no segments.
Naive method that can serve as benchmarking pipeline or API test.
Detects no segments.
Examples
-------... |
fe395cd9be1f6b23e5dd4bbf370ead31a7725786b598b26235afb9593e288828 | Python | 1,763 | 58 | """Intended purpose it to convert every ontology in NIF-Ontology and picklize it in a new folder
Usage:
picklize.py [-h | --help]
picklize.py [-v | --version]
picklize.py [-f=<paths>...] [-o=<path>]
Options:
-h --help Display this help message
-v --version Current version ... |
82f9d63354154e9a856925775380b9e1b3b5b37ebbd56a14e85f999ad4c333be | Python | 1,764 | 47 | # 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
#
# ... |
84de9f0f79f57eccc9eb65ae3b068b06a8e0a2eae33be99802654030805132dc | Python | 1,764 | 51 | # 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... |
eba67e51a73279da6ec8bb86bbd9ef8c02b87ff163c8bcee20fb6ced1c222693 | Python | 1,767 | 53 | # 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... |
f9e8e55970a23baaf9ab78b7b3cf0d090939a6d96d7352e39bc9219930a577c8 | Python | 1,767 | 58 | import pytest
import numpy as np
from scipy.sparse import csr_matrix
from scipy.sparse.linalg import eigs
from pytest import approx
from palantir.utils import diffusion_maps_from_kernel, determine_multiscale_space
@pytest.fixture
def mock_kernel():
size = 50
rng = np.random.default_rng()
A = rng.random((... |
435c1378044586af1ca3fe6c33f9f0c767f480c40978a3a05d181b372cacb55d | Python | 1,768 | 52 | import unittest
import os
import numpy as np
import shutil
from ddt import ddt, data
from SPHARM.classes.ellipsoid import Ellipsoid
@ddt
class TestEllipsoidClass(unittest.TestCase):
@data(
([10, 10], [1, 3, 2], (0, 0)),
([10, 30], [3, 3, 2], (np.pi/4, 0)),
([100, 100], [1, 3, 2], (np.pi... |
91b0d98c12d2003a445c788db7038e6cd5a4ca94a60f2b9ae5f5b6770ff21cd5 | Python | 1,768 | 43 | # Code adapted from tensorflow to pytorch from https://github.com/google-research/graph-attribution/tree/main/graph_attribution
import torch
from torch_geometric.data import Data
from molucn.feat_attribution.explainer_base import Explainer
class CAM(Explainer):
"""CAM: Decompose output as a linear sum of nodes ... |
d2655b604a8640216df1d692ae88adec89e7a663a78bc446a6adc1ea5d1f01ea | Python | 1,768 | 50 | # 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... |
47b0457f2c697c82a46cc17bfccc8b30aaf6f63a4cacb53ed472e168a52376d5 | Python | 1,769 | 49 | # 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... |
c4d79576ecc4059bba34fb44a27b448f52d67d913cc9758d2d9cf0672a3f4cb3 | Python | 1,770 | 72 | '''
what does this do?
printMoleculeInfo
@author: Nicholas Browning
'''
from __future__ import print_function
# Use this to print residue information
from builtins import range
import argparse
from src import MoleculeInfo as mi
import openbabel
import numpy as np
def printResidueInfo(mol):
print("Num Atoms:",... |
406aab9f68dc949c21ac0d454239e11394211a3f87aced5c5e4542186402918f | Python | 1,771 | 60 | import rdflib
from IPython import embed
from ilxutils.ilx_graph_comparator import IlxGraphComparator
tdata = """
@prefix skos: <http://www.w3.org/2004/02/skos/core#> .
@prefix owl: <http://www.w3.org/2002/07/owl#> .
@prefix rdfs: <http://www.w3.org/2000/01/rdf-schema#> .
@prefix xsd: <http://www.w3.org/2001/XMLSche... |
b6887b93a964b74ff8bdea2e101e220d83ab34ef87b027b0b19183d444e79e09 | Python | 1,771 | 55 | # Copyright (c) ONNX Project Contributors
# SPDX-License-Identifier: Apache-2.0
from __future__ import annotations
import numpy as np
from onnx.helper import tensor_dtype_to_np_dtype
from onnx.reference.op_run import OpRun
class _CommonRandom(OpRun):
def __init__(self, onnx_node, run_params):
OpRun.__i... |
3176b28b867334642cfc331f4f200cdea718ffa729d15c33172cdbacc7323be2 | Python | 1,772 | 46 | """Unit tests for all time series regressors."""
__author__ = ["felipeangelimvieira"]
import numpy as np
import pandas as pd
from sktime.tests.test_all_estimators import BaseFixtureGenerator, QuickTester
class ClassificationDatasetFixtureGenerator(BaseFixtureGenerator):
"""Fixture generator for classifier tests... |
4ac18dd23e405fb02d4c70cad0bbc1d65469cd217075efc499d7e4965e421af7 | Python | 1,772 | 57 | #!/usr/bin/env python
# arima_mapping 0.0.1 test suite
# Generated by dx-app-wizard.
import json, os, time, unittest
import dxpy
import dxpy.app_builder
from dxpy.exceptions import DXAPIError
src_dir = os.path.join(os.path.dirname(__file__), "..")
test_resources_dir = os.path.join(src_dir, "test", "resources")
def... |
021011c24046b7bf1a982b1c812c0261240bffd39fd6dd3c9ad98a94fe602810 | Python | 1,773 | 68 | """Utilities to handle checks and conversions between output formats of detectors."""
import pandas as pd
def _get_example_segments_0():
"""Generate example 0 for segmentation output.
- non-overlapping
- non-exhaustive
- no labels
"""
segs = pd.IntervalIndex.from_tuples([(1, 2), (3, 6), (7, ... |
c9a0737e3c0152649d98806b8f3c7dc239023139d99e3d42fbcc55d16928e3cf | Python | 1,773 | 56 | from __future__ import division
import numpy as np
import sciunit
import matplotlib.pyplot as plt
class effect_size(sciunit.Score):
"""
Calculates the effect size between samples.
"""
score = np.nan
@classmethod
def compute(self, observation, prediction, **kwargs):
def s_pooled(sampl... |
31a8ef241068abac871a32e95de4da6abbc3f2b712ea6f81abd7bbb29f404c7a | Python | 1,774 | 61 | # 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... |
5db4d8fcf0e3084b6a3cacb90cba3a9447d1644eb60f71ffdea6cd764f4ff248 | Python | 1,774 | 65 | ##+++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++
## Created by: Yaoyao Liu
## Modified from: https://github.com/Sha-Lab/FEAT
## Tianjin University
## liuyaoyao@tju.edu.cn
## Copyright (c) 2019
##
## This source code is licensed under the MIT-style license found in the
## LICENSE file in the r... |
786192717ac88832502e73a0a14a96a3db062f2de5f21f7be88e9083aa391b39 | Python | 1,774 | 57 | #!/usr/bin/env python
# bcftools_merge 0.0.1 test suite
# Generated by dx-app-wizard.
import json, os, time, unittest
import dxpy
import dxpy.app_builder
from dxpy.exceptions import DXAPIError
src_dir = os.path.join(os.path.dirname(__file__), "..")
test_resources_dir = os.path.join(src_dir, "test", "resources")
de... |
870ee2673cebfc8060079384f897bfb075f798dd5a55d03c5175a2cc0558c74e | Python | 1,774 | 57 | #!/usr/bin/env python
# rename_contigs 0.0.1 test suite
# Generated by dx-app-wizard.
import json, os, time, unittest
import dxpy
import dxpy.app_builder
from dxpy.exceptions import DXAPIError
src_dir = os.path.join(os.path.dirname(__file__), "..")
test_resources_dir = os.path.join(src_dir, "test", "resources")
de... |
24186ccc0d623f51c46c0f6363509122f961041e43cf966b59a86f277f6acde1 | Python | 1,775 | 60 | '''
Functions for computing abnormalities and abnormality-based measures from
continuous iEEG data.
Gabrielle M. Schroeder
CNNP Lab, Newcastle University
May 2023
'''
import numpy as np
import sklearn.metrics as sk_metrics
def compute_d_rs(roi_data,roi_is_resect):
'''
Compute D_RS (AUC) of resected vs. spar... |
6f23230edf4bca00aae1170f1afd6a5b17a3d6ad78fd1453a2a13d0955bdc818 | Python | 1,775 | 73 | """Turn the examples section of a function docstring into a notebook."""
import re
import sys
import pydoc
import seaborn
from seaborn.external.docscrape import NumpyDocString
import nbformat
def line_type(line):
if line.startswith(" "):
return "code"
else:
return "markdown"
def add_cell... |
fe37d44ac3f2d1e151c92c819248803ecf7ec4c0c22b1293696a2e5184b542b3 | Python | 1,775 | 51 | import pytest
import os
from time import time
import numpy as np
import siibra
from siibra.volumes import Map
from siibra.exceptions import NoneCoordinateSuppliedError
TEST_ALL_MAPS = os.getenv("TEST_ALL_MAPS", "False").strip().lower() in ("1", "true", "yes", "on")
preconfiugres_maps = list(siibra.maps)
BLACKLIST =... |
a2946b9113322bbb7d3e707d818b7b88cee4ce1f06f9ce66bade3d8dcf157af6 | Python | 1,776 | 57 | #!/usr/bin/env python
# workstation1404 0.0.1 test suite
# Generated by dx-app-wizard.
import json, os, time, unittest
import dxpy
import dxpy.app_builder
from dxpy.exceptions import DXAPIError
src_dir = os.path.join(os.path.dirname(__file__), "..")
test_resources_dir = os.path.join(src_dir, "test", "resources")
d... |
89465ecbfa2f357898a232d9c922816c7e661a5c60d39c9573ed468cd6c6592e | Python | 1,778 | 48 | import numpy as np
from scipy.stats import ttest_ind
import sciunit
from networkunit.scores import to_precision
class students_t(sciunit.Score):
"""
Student's T-test
"""
score = np.nan
# TODO: should be named ttest only because if equal_var=False -> Welch's t-test
# The computation is perform... |
f0efd945e4b5eb6ba5c97b4486d92405aaeb0b763d15f7d553ba378434916e68 | Python | 1,778 | 74 | # 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... |
46ac075435b46941041233eed4647fc95b3895bb0a3bc9e5ad03b85a4a8d6af3 | Python | 1,779 | 66 | # Copyright (c) ONNX Project Contributors
# SPDX-License-Identifier: Apache-2.0
from __future__ import annotations
import numpy as np
from numpy.random import RandomState
from onnx.reference.op_run import OpRun
def _dropout(
X: np.ndarray,
drop_probability: float = 0.5,
seed: int | None = None,
tra... |
f03235e77e48a39b5ded4ce6b2d05347d5a8b26ee199e89e62ba666c4bc4780f | Python | 1,779 | 48 | # 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... |
8464b9617cecaa66006e7bf628a4e61edfeda2470ee41299b1254efb42dc0da4 | Python | 1,781 | 45 |
def _add_subplot_title(ax, azim=None, elev=None, subtitle_frame='auto', hemisphere='both', viewtype='b', **kwargs):
subtitlefont = kwargs.get('font')
subtitlecolor = kwargs.get('fontcolor')
subtitle_fontsize = kwargs.get('subtitle_fontsize')
subtitle_loc = kwargs.get('subtitle_loc')
subtitle_weigh... |
3229ebdcc57ec5060be42ead3ad47cf16330402d01f6db78ba876ea0e6aa30cf | Python | 1,782 | 55 | import logging
import os
import sys
import pytest
from ts.context import Context
from ts.service import Service
from ts.service import emit_metrics
logging.basicConfig(stream=sys.stdout, format="%(message)s", level=logging.INFO)
# noinspection PyClassHasNoInit
class TestService:
model_name = 'testmodel'
m... |
768aabe46d17523da48e746e4bd2a01080ff51899709cb066830d06fcdaf4caa | Python | 1,784 | 63 | """Functions and utilities for downloading example data for bycycle."""
import os
from urllib.request import urlretrieve
import numpy as np
from neurodsp.utils.download import check_data_folder, check_data_file
###################################################################################################
#####... |
1a69688e57e108f02579a5da43722c2acd2f5dee50251a0719942cc9e5c1cb5c | Python | 1,786 | 55 | import re
from setuptools import setup
def find_version(filename):
_version_re = re.compile(r"__version__ = '(.*)'")
for line in open(filename):
version_match = _version_re.match(line)
if version_match:
return version_match.group(1)
__version__ = find_version('clifn/__init__.py')... |
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