repo_name stringlengths 6 130 | hexsha list | file_path list | code list | apis list | possible_versions list |
|---|---|---|---|---|---|
rafaelcgon/PC | [
"ce5f25c13741c02a19560a57838aec735aac2d88",
"ce5f25c13741c02a19560a57838aec735aac2d88"
] | [
"example_2D.py",
"basisFunctions.py"
] | [
"import numpy as np\nimport PC \nfrom matplotlib import pylab as pl \nimport matplotlib as mpl \nimport matplotlib.pyplot as plt \nimport seaborn as sns #\nimport scipy.io as sio\n\ndef model(X,... | [
[
"matplotlib.pyplot.legend",
"numpy.abs",
"numpy.meshgrid",
"numpy.arange",
"numpy.repeat",
"matplotlib.pyplot.get_cmap",
"matplotlib.colorbar.ColorbarBase",
"numpy.shape",
"matplotlib.pylab.savefig",
"numpy.array",
"matplotlib.pyplot.figure"
],
[
"numpy.polynomi... | [
{
"matplotlib": [],
"numpy": [],
"pandas": [],
"scipy": [],
"tensorflow": []
},
{
"matplotlib": [],
"numpy": [
"1.10",
"1.12",
"1.11",
"1.19",
"1.24",
"1.13",
"1.16",
"1.9",
"1.18",
"1.23",
"1.21",
"1.22",
... |
nailbiter/pyassistantbot2 | [
"00a4171e8359ad4d61fea0bf7e84241ba79708d6"
] | [
"_common/requests_cache.py"
] | [
"\"\"\"===============================================================================\n\n FILE: _common/requests_cache.py\n\n USAGE: (not intended to be directly executed)\n\n DESCRIPTION: \n\n OPTIONS: ---\nREQUIREMENTS: ---\n BUGS: ---\n NOTES: ---\n AUTHOR: Alex Leontiev (aloz... | [
[
"pandas.read_sql_query",
"pandas.DataFrame"
]
] | [
{
"matplotlib": [],
"numpy": [],
"pandas": [
"0.23",
"0.21",
"2.0",
"1.4",
"1.3",
"0.19",
"1.1",
"1.5",
"0.24",
"0.20",
"1.0",
"0.25",
"1.2"
],
"scipy": [],
"tensorflow": []
}
] |
abdel/imdb-sentiment-analysis | [
"f240c6b28cda01c9496fd5e0b02eedd8fbd22b44"
] | [
"notebooks/utils.py"
] | [
"import os\nimport re\nimport bcolz\nimport keras\nimport itertools\nimport numpy as np\nimport _pickle as pickle\n\nfrom itertools import chain\nfrom matplotlib import pyplot as plt\nfrom keras.utils.data_utils import get_file\nfrom numpy.random import normal\n\ndef plot_confusion_matrix(cm, classes, normalize=Fal... | [
[
"matplotlib.pyplot.text",
"matplotlib.pyplot.imshow",
"matplotlib.pyplot.yticks",
"matplotlib.pyplot.tight_layout",
"matplotlib.pyplot.title",
"matplotlib.pyplot.colorbar",
"matplotlib.pyplot.ylabel",
"numpy.random.normal",
"matplotlib.pyplot.xlabel",
"matplotlib.pyplot.xti... | [
{
"matplotlib": [],
"numpy": [],
"pandas": [],
"scipy": [],
"tensorflow": []
}
] |
hawflau/aws-sam-cli-app-templates | [
"47e7100659c1cdf8c1ae1d8eba36de5dbd01623c"
] | [
"python3.9-image/cookiecutter-ml-apigw-pytorch/{{cookiecutter.project_name}}/app/app.py"
] | [
"import torch\nimport torchvision\nimport base64\nimport json\nimport numpy as np\n\nimport torch.nn as nn\nimport torch.nn.functional as F\n\nfrom PIL import Image\nfrom io import BytesIO\n\nimage_transforms = torchvision.transforms.Compose([\n torchvision.transforms.ToTensor(),\n torchvision.transforms.Norm... | [
[
"torch.nn.BatchNorm1d",
"torch.nn.Dropout2d",
"torch.load",
"torch.nn.functional.dropout",
"torch.nn.Conv2d",
"torch.nn.Linear",
"numpy.array",
"torch.argmax"
]
] | [
{
"matplotlib": [],
"numpy": [],
"pandas": [],
"scipy": [],
"tensorflow": []
}
] |
dekuenstle/cnn-review | [
"47600418c0d256d0dfaf2f6feb018f793c1205bc"
] | [
"vectorize.py"
] | [
"#!/usr/bin/env python3\n\nfrom gensim.models import KeyedVectors\nfrom gensim.utils import tokenize\nimport numpy as np\n\nfrom config import random_seed, word2vec_file, word2vec_dim, max_word_num\n\ndef load_word2vec():\n print(\"Load Word2Vec from {} ...\".format(word2vec_file))\n return KeyedVectors.load_... | [
[
"numpy.random.uniform",
"numpy.empty",
"numpy.percentile",
"numpy.random.seed"
]
] | [
{
"matplotlib": [],
"numpy": [],
"pandas": [],
"scipy": [],
"tensorflow": []
}
] |
davidkartchner/rubrix | [
"33faa006d7498a806a9fd594036d4a42c7d70da2"
] | [
"src/rubrix/labeling/text_classification/label_errors.py"
] | [
"# coding=utf-8\n# Copyright 2021-present, the Recognai S.L. team.\n#\n# Licensed under the Apache License, Version 2.0 (the \"License\");\n# you may not use this file except in compliance with the License.\n# You may obtain a copy of the License at\n#\n# http://www.apache.org/licenses/LICENSE-2.0\n#\n# ... | [
[
"numpy.array"
]
] | [
{
"matplotlib": [],
"numpy": [],
"pandas": [],
"scipy": [],
"tensorflow": []
}
] |
feras-oughali/fastai | [
"4052f7adb441ab8a00eaa807b444a4e583b6bcc7"
] | [
"fastai/vision/models/presnet.py"
] | [
"from pdb import set_trace\nimport torch.nn.functional as F\nimport torch.nn as nn\nimport torch\nimport math\nimport torch.utils.model_zoo as model_zoo\n\n__all__ = ['PResNet', 'presnet18', 'presnet34', 'presnet50', 'presnet101', 'presnet152']\n\nact_fn = nn.ReLU\n\ndef init_cnn(m):\n if getattr(m, 'bias', None... | [
[
"torch.nn.Sequential",
"torch.load",
"torch.nn.init.constant_",
"torch.nn.Conv2d",
"torch.nn.MaxPool2d",
"torch.nn.Linear",
"torch.nn.AvgPool2d",
"torch.nn.AdaptiveAvgPool2d",
"torch.nn.BatchNorm2d",
"torch.nn.init.kaiming_normal_"
]
] | [
{
"matplotlib": [],
"numpy": [],
"pandas": [],
"scipy": [],
"tensorflow": []
}
] |
batmanlab/skl-groups | [
"2584c10a413626c6d5f9078cdbf3dcc84e4e9a5b"
] | [
"skl_groups/tests/test_utils.py"
] | [
"from __future__ import division\n\nimport os\nimport sys\n\nimport numpy as np\nfrom sklearn.externals.six import iteritems\nfrom nose.tools import assert_raises\n\nif __name__ == '__main__':\n # make this copy of skl_groups importable\n _this_dir = os.path.dirname(os.path.abspath(__file__))\n sys.path.in... | [
[
"numpy.arange",
"sklearn.externals.six.iteritems",
"numpy.array"
]
] | [
{
"matplotlib": [],
"numpy": [],
"pandas": [],
"scipy": [],
"tensorflow": []
}
] |
moaraccounts/pandas | [
"ebb727e5cd8865a7f5d6cfb4b22d3278b6bf5e6b"
] | [
"pandas/core/arrays/sparse/array.py"
] | [
"\"\"\"\nSparseArray data structure\n\"\"\"\nfrom collections import abc\nimport numbers\nimport operator\nfrom typing import Any, Callable, Union\nimport warnings\n\nimport numpy as np\n\nfrom pandas._libs import lib\nimport pandas._libs.sparse as splib\nfrom pandas._libs.sparse import BlockIndex, IntIndex, Sparse... | [
[
"pandas._libs.sparse.make_mask_object_ndarray",
"pandas.Series",
"numpy.asarray",
"pandas.core.dtypes.common.is_dtype_equal",
"pandas._libs.sparse.IntIndex",
"pandas.compat.numpy.function.validate_cumsum",
"pandas.core.dtypes.missing.notna",
"pandas.core.dtypes.common.is_datetime64... | [
{
"matplotlib": [],
"numpy": [],
"pandas": [],
"scipy": [],
"tensorflow": []
}
] |
gparolin/AEco | [
"5bdc542150cd89581b134418bac5a3bb39fc45d6"
] | [
"Scripts/Model.py"
] | [
"import numpy as np\nimport pandas as pd\nimport warnings\nimport xarray as xr\nimport dask.dataframe as dd\nimport dask.array as da\n\nclass LCI():\n \"\"\"Defines a LCI class based on xr.DataArray.\"\"\"\n \n def __init__(self, name, type, iterations, UP, parameters):\n \"\"\"Initialization with t... | [
[
"numpy.arange"
]
] | [
{
"matplotlib": [],
"numpy": [],
"pandas": [],
"scipy": [],
"tensorflow": []
}
] |
tkondoh1022/deep-learning-from-scratch-3 | [
"240ddab84c50f4c501bd34cd496604892b5bda80"
] | [
"steps/step06.py"
] | [
"import numpy as np\n\n\nclass Variable:\n def __init__(self, data):\n self.data = data\n self.grad = None\n\n\nclass Function:\n def __call__(self, input):\n x = input.data\n y = self.forward(x)\n output = Variable(y)\n self.input = input\n return output\n\n ... | [
[
"numpy.exp",
"numpy.array"
]
] | [
{
"matplotlib": [],
"numpy": [],
"pandas": [],
"scipy": [],
"tensorflow": []
}
] |
Barchid/VISA | [
"1b8842e5985ab3f60580c25c9b9563634d4c8708"
] | [
"TP05/keras-mnist.py"
] | [
"import tensorflow as tf\nimport matplotlib.pyplot as plt\nfrom tensorflow.keras.datasets import cifar10\n\nmnist = tf.keras.datasets.mnist\n\n(x_train, y_train), (x_test, y_test) = cifar10.load_data()\nx_train, x_test = x_train / 255.0, x_test / 255.0\n\nmodel = tf.keras.models.Sequential([\n tf.keras.layers.Fl... | [
[
"matplotlib.pyplot.legend",
"tensorflow.keras.layers.Dropout",
"matplotlib.pyplot.title",
"tensorflow.keras.layers.Dense",
"tensorflow.keras.optimizers.SGD",
"tensorflow.keras.datasets.cifar10.load_data",
"matplotlib.pyplot.plot",
"matplotlib.pyplot.xlabel",
"matplotlib.pyplot.... | [
{
"matplotlib": [],
"numpy": [],
"pandas": [],
"scipy": [],
"tensorflow": [
"1.10",
"2.7",
"2.6",
"2.4",
"2.3",
"2.5",
"2.2"
]
}
] |
zhenghangCN/Local-Connected | [
"a0eae8e2efdb0c34aab2f126f0aa3b849168e27a"
] | [
"3D_QM9.py"
] | [
"import json\nfrom rdkit import Chem\nfrom rdkit.Chem import AllChem\nimport numpy as np\nfrom math import ceil, sqrt\nimport random\nimport os\n\nclass pre(object):\n\tdef __init__(self, path, decimals=1):\n\t\tself.smiles = []\n\t\tself.propertys = []\n\t\tself.path = path\n\t\tself.mols = []\n\t\tself.train_mols... | [
[
"numpy.dot",
"numpy.polyfit",
"numpy.asarray",
"numpy.array",
"numpy.zeros"
]
] | [
{
"matplotlib": [],
"numpy": [],
"pandas": [],
"scipy": [],
"tensorflow": []
}
] |
flymin/Rectified-Rejection | [
"58bfd0ee159cbcbebdda2da068984e6edf8b61ec"
] | [
"adaptiveCWattack/base.py"
] | [
"# Copyright (c) 2018-present, Royal Bank of Canada.\n# All rights reserved.\n#\n# This source code is licensed under the license found in the\n# LICENSE file in the root directory of this source tree.\n#\n\nfrom abc import ABCMeta\n\nimport torch\n\nfrom advertorch.utils import replicate_input\n\n\nclass Attack(ob... | [
[
"torch.no_grad",
"torch.max"
]
] | [
{
"matplotlib": [],
"numpy": [],
"pandas": [],
"scipy": [],
"tensorflow": []
}
] |
salesforce/NeuralBayes | [
"e2f307933abbf124d55763eeb6df536bc47c3e5a"
] | [
"MIM/models.py"
] | [
"__author__ = 'Devansh Arpit'\nimport torch\nimport torch.nn as nn\nimport torch.nn.functional as F\nimport math\nimport torch.nn as nn\nimport torch.nn.init as init\n\n\ndef param_init(module, init='ortho'):\n for m in module.modules():\n if isinstance(m, nn.Conv2d) or isinstance(m, nn.Linear):\n ... | [
[
"torch.nn.Sequential",
"torch.nn.BatchNorm1d",
"torch.nn.Dropout",
"torch.nn.ModuleList",
"torch.nn.Conv2d",
"torch.nn.Linear",
"torch.nn.functional.relu",
"torch.nn.init.orthogonal_",
"torch.nn.BatchNorm2d",
"torch.nn.functional.max_pool2d"
]
] | [
{
"matplotlib": [],
"numpy": [],
"pandas": [],
"scipy": [],
"tensorflow": []
}
] |
rotemgb/spyder | [
"f70735396ce6f4b2f7d920cf7953239bd9504a4f"
] | [
"spyder/plugins/variableexplorer/widgets/tests/test_collectioneditor.py"
] | [
"# -*- coding: utf-8 -*-\n# -----------------------------------------------------------------------------\n# Copyright © Spyder Project Contributors\n#\n# Licensed under the terms of the MIT License\n# (see spyder/__init__.py for details)\n# --------------------------------------------------------------------------... | [
[
"pandas.DateOffset",
"pandas.Series",
"pandas.Categorical",
"pandas.DataFrame",
"pandas.Timedelta",
"pandas.MultiIndex.from_product",
"pandas.Period",
"numpy.array"
]
] | [
{
"matplotlib": [],
"numpy": [],
"pandas": [],
"scipy": [],
"tensorflow": []
}
] |
reedkihaddi/mplsoccer | [
"73705bd269c035a97382eda1166c241bcbee154c"
] | [
"examples/pizza_plots/plot_pizza_different_units.py"
] | [
"\"\"\"\n=====================\nDifferent Units Pizza\n=====================\n\n* ``mplsoccer``, ``py_pizza`` module helps one to plot pizza charts in a few lines of code.\n\n* The design idea is inspired by `Tom Worville <https://twitter.com/Worville>`_, \\\n`Football Slices <https://twitter.com/FootballSlices>`_ ... | [
[
"matplotlib.pyplot.show"
]
] | [
{
"matplotlib": [],
"numpy": [],
"pandas": [],
"scipy": [],
"tensorflow": []
}
] |
ashtonmv/pyiron | [
"99effc008b8a3cc642d1d927f0c712bf9557218a"
] | [
"pyiron/gaussian/gaussian.py"
] | [
"# coding: utf-8\n# Copyright (c) Max-Planck-Institut für Eisenforschung GmbH - Computational Materials Design (CM) Department\n# Distributed under the terms of \"New BSD License\", see the LICENSE file.\n\nimport os,subprocess,re,pandas\nimport numpy as np\nimport matplotlib.pyplot as pt\n\nfrom pyiron.dft.job.gen... | [
[
"numpy.array",
"numpy.zeros",
"pandas.DataFrame"
]
] | [
{
"matplotlib": [],
"numpy": [],
"pandas": [
"0.23",
"0.21",
"2.0",
"1.4",
"0.19",
"1.1",
"1.5",
"1.2",
"0.24",
"0.20",
"1.0",
"0.25",
"1.3"
],
"scipy": [],
"tensorflow": []
}
] |
zvs08/Stark | [
"00ed184e34f8573558b8e27803807ca4cefcf884"
] | [
"lib/train/actors/stark_s.py"
] | [
"from . import BaseActor\nfrom lib.utils.box_ops import box_cxcywh_to_xyxy, box_xywh_to_xyxy\nimport torch\nfrom lib.utils.merge import merge_template_search\n\n\nclass STARKSActor(BaseActor):\n \"\"\" Actor for training the STARK-S and STARK-ST(Stage1)\"\"\"\n def __init__(self, net, objective, loss_weight, ... | [
[
"torch.isnan",
"torch.tensor"
]
] | [
{
"matplotlib": [],
"numpy": [],
"pandas": [],
"scipy": [],
"tensorflow": []
}
] |
SiewLinYap/flair | [
"b0e4cc1a92c4bd56536ed4e09c8ff6cb1a89f08c"
] | [
"flair/trainers/language_model_trainer.py"
] | [
"import time, datetime\nimport random\nimport sys\nimport logging\nfrom pathlib import Path\nfrom typing import Union\n\nfrom torch import cuda\nfrom torch.utils.data import Dataset, DataLoader\nfrom torch.optim.sgd import SGD\n\ntry:\n from apex import amp\nexcept ImportError:\n amp = None\n\nimport flair\nf... | [
[
"torch.utils.data.DataLoader",
"torch.cuda.is_available"
]
] | [
{
"matplotlib": [],
"numpy": [],
"pandas": [],
"scipy": [],
"tensorflow": []
}
] |
Rujaan/Upscale.io | [
"be79e902f008f75de71969f7e01b1577efda20aa",
"be79e902f008f75de71969f7e01b1577efda20aa"
] | [
"upscale.py",
"ModelTrain/codes/models/networks.py"
] | [
"#!/usr/bin/env python3\n# -*- coding: utf-8 -*-\n\nimport logging\nimport sys\nfrom collections import OrderedDict\nfrom enum import Enum\nfrom pathlib import Path\nfrom typing import List, Optional, Union\n\nimport cv2\nimport numpy as np\nimport torch\nimport typer\nfrom rich import print\nfrom rich.logging impo... | [
[
"torch.set_default_tensor_type",
"numpy.expand_dims",
"torch.load",
"numpy.clip",
"numpy.dstack",
"numpy.full",
"numpy.copy",
"numpy.mean",
"numpy.iinfo",
"numpy.transpose",
"torch.device",
"numpy.where"
],
[
"torch.nn.init.constant_",
"torch.nn.init.xav... | [
{
"matplotlib": [],
"numpy": [],
"pandas": [],
"scipy": [],
"tensorflow": []
},
{
"matplotlib": [],
"numpy": [],
"pandas": [],
"scipy": [],
"tensorflow": []
}
] |
ivanvikhrev/open_model_zoo | [
"322e7ac5ed8a17611b56c46e5e56bfef05d8cc2a"
] | [
"tools/accuracy_checker/accuracy_checker/adapters/mask_rcnn_with_text.py"
] | [
"\"\"\"\nCopyright (c) 2018-2020 Intel Corporation\n\nLicensed under the Apache License, Version 2.0 (the \"License\");\nyou may not use this file except in compliance with the License.\nYou may obtain a copy of the License at\n\n http://www.apache.org/licenses/LICENSE-2.0\n\nUnless required by applicable law ... | [
[
"numpy.int0",
"numpy.squeeze",
"numpy.argmax",
"numpy.shape"
]
] | [
{
"matplotlib": [],
"numpy": [],
"pandas": [],
"scipy": [],
"tensorflow": []
}
] |
cptanalatriste/AttnGAN | [
"6b8641cd5eb9c3a0bba73904b5c639784d6c3ec8"
] | [
"featurepred/train.py"
] | [
"import logging\nimport time\nfrom typing import Tuple\n\nimport torch\nimport torch.nn.functional as F\nfrom torch import Tensor\nfrom torch.nn import Module\nfrom torch.optim import Optimizer\nfrom torch.utils.data import DataLoader\nfrom torch.utils.tensorboard import SummaryWriter\n\nfrom featurepred import mod... | [
[
"torch.eq",
"torch.nn.functional.softmax",
"torch.sum"
]
] | [
{
"matplotlib": [],
"numpy": [],
"pandas": [],
"scipy": [],
"tensorflow": []
}
] |
jrs65/radiotools | [
"de8153824d2c394a4ddb850b630028e75ba1afb0"
] | [
"radiotools/estimator.py"
] | [
"# === Start Python 2/3 compatibility\nfrom __future__ import (absolute_import, division,\n print_function, unicode_literals)\nfrom future.builtins import * # noqa pylint: disable=W0401, W0614\nfrom future.builtins.disabled import * # noqa pylint: disable=W0401, W0614\n# === End Python 2/... | [
[
"numpy.dot",
"scipy.linalg.pinv",
"numpy.abs",
"numpy.linspace",
"numpy.random.standard_normal",
"scipy.sparse.linalg.cg",
"scipy.sparse.diags",
"numpy.concatenate",
"scipy.sparse.identity",
"scipy.sparse.linalg.LinearOperator",
"numpy.array",
"numpy.hypot",
"nu... | [
{
"matplotlib": [],
"numpy": [],
"pandas": [],
"scipy": [
"0.13",
"0.12",
"0.14",
"0.15"
],
"tensorflow": []
}
] |
maxzvyagin/mdlearn | [
"30c7f3346f8a2ed3cff0fe7b6b1eead9b61f5310"
] | [
"examples/symmetric_conv2d_vae/sweep/train.py"
] | [
"import time\nimport wandb\nimport torch\nimport random\nimport numpy as np\nfrom pathlib import Path\nfrom collections import defaultdict\nfrom typing import Dict, Tuple\nfrom torchsummary import summary\nfrom mdlearn.utils import (\n log_checkpoint,\n log_latent_visualization,\n get_torch_optimizer,\n ... | [
[
"numpy.random.seed",
"torch.load",
"torch.manual_seed",
"numpy.concatenate",
"torch.set_num_threads",
"numpy.mean",
"torch.no_grad",
"torch.cuda.is_available"
]
] | [
{
"matplotlib": [],
"numpy": [],
"pandas": [],
"scipy": [],
"tensorflow": []
}
] |
reeserich/covid-chicago | [
"88bdc556aebdd7e443e4756e7421160d230f5a01"
] | [
"plotters/process_for_civis_EMSgrp.py"
] | [
"import argparse\nimport numpy as np\nimport pandas as pd\nimport matplotlib.pyplot as plt\nimport os\nimport seaborn as sns\nimport matplotlib as mpl\nimport matplotlib.dates as mdates\nfrom datetime import date, timedelta, datetime\nimport sys\nsys.path.append('../')\nfrom processing_helpers import *\nfrom load_p... | [
[
"matplotlib.dates.DateFormatter",
"pandas.merge",
"pandas.concat",
"numpy.min",
"pandas.DataFrame",
"numpy.max",
"matplotlib.pyplot.figure"
]
] | [
{
"matplotlib": [],
"numpy": [],
"pandas": [
"0.23",
"0.21",
"2.0",
"1.4",
"1.3",
"0.19",
"1.1",
"1.5",
"0.24",
"0.20",
"1.0",
"0.25",
"1.2"
],
"scipy": [],
"tensorflow": []
}
] |
gjoseph92/pangeo-forge-recipes | [
"6dda95778bcae551bed1e79d76a20867e237097f"
] | [
"tests/conftest.py"
] | [
"\"\"\"\nObjects in this module belong to the following groups, delimited by inline comments:\n - Helper functions:\n Functions used in the creation of fixtures\n - Dataset + path fixtures:\n Create a dataset or a path to dataset(s)\n - FilePattern fixtures:\n Create `pangeo_forge_reci... | [
[
"numpy.random.seed",
"numpy.arange",
"numpy.random.rand",
"pandas.date_range",
"numpy.random.randint"
]
] | [
{
"matplotlib": [],
"numpy": [],
"pandas": [
"0.23",
"0.21",
"2.0",
"1.4",
"0.19",
"1.1",
"1.5",
"1.2",
"0.24",
"0.20",
"1.0",
"0.25",
"1.3"
],
"scipy": [],
"tensorflow": []
}
] |
anDoer/PoseTrack21 | [
"25c8412feca57319404a0c48565f9a264d648bd1"
] | [
"eval/mot/motmetrics/mot.py"
] | [
"# py-motmetrics - Metrics for multiple object tracker (MOT) benchmarking.\n# https://github.com/cheind/py-motmetrics/\n#\n# MIT License\n# Copyright (c) 2017-2020 Christoph Heindl, Jack Valmadre and others.\n# See LICENSE file for terms.\n\n\"\"\"Accumulate tracking events frame by frame.\"\"\"\n\nfrom __future__ ... | [
[
"pandas.concat",
"pandas.Series",
"numpy.isfinite",
"pandas.MultiIndex",
"numpy.asarray",
"pandas.Categorical",
"numpy.unique",
"numpy.arange",
"numpy.isnan",
"pandas.MultiIndex.from_arrays",
"numpy.atleast_2d",
"numpy.zeros_like",
"numpy.where"
]
] | [
{
"matplotlib": [],
"numpy": [],
"pandas": [
"0.23",
"0.21",
"2.0",
"1.4",
"1.3",
"0.19",
"1.1",
"1.5",
"0.24",
"0.20",
"1.0",
"0.25",
"1.2"
],
"scipy": [],
"tensorflow": []
}
] |
otherm/gshp-analysis | [
"746070b10a05985c31f06acd5e052ac3a7bf4924"
] | [
"utilities/csv_to_yaml.py"
] | [
"import yaml\nimport pandas as pd\nimport model_dict_templates as mdt\n\n\ninputfile = '../temp_files/NWS_stations_2.csv'\n\nstation_data = pd.read_csv(inputfile, header=0)\n\nstation_dict_list = station_data.set_index('model').to_dict('records')\n\nweather_station_list = []\nfor data in station_dict_list:\n if ... | [
[
"pandas.read_csv"
]
] | [
{
"matplotlib": [],
"numpy": [],
"pandas": [
"2.0",
"1.4",
"1.1",
"1.5",
"1.2",
"1.3"
],
"scipy": [],
"tensorflow": []
}
] |
vision7820/BMN-Boundary-Matching-Network | [
"bb13368245b5079a6be156cc065abd6599412cbe"
] | [
"post_processing.py"
] | [
"# -*- coding: utf-8 -*-\nimport numpy as np\nimport pandas as pd\nimport json\nimport multiprocessing as mp\n\nfrom utils import iou_with_anchors\n\n\ndef load_json(file):\n with open(file) as json_file:\n data = json.load(json_file)\n return data\n\n\ndef getDatasetDict(opt):\n df = pd.read_cs... | [
[
"numpy.square",
"numpy.array",
"pandas.read_csv",
"pandas.DataFrame"
]
] | [
{
"matplotlib": [],
"numpy": [],
"pandas": [
"2.0",
"1.4",
"1.3",
"1.1",
"1.5",
"1.2"
],
"scipy": [],
"tensorflow": []
}
] |
tosseto/robosat.pink | [
"81b891a5a21a531b66a9834bed73b0da6baa9867"
] | [
"robosat_pink/tools/tile.py"
] | [
"import os\nimport sys\nimport math\nfrom tqdm import tqdm\nimport concurrent.futures as futures\n\nimport numpy as np\n\nimport shutil\nimport mercantile\n\nfrom rasterio import open as rasterio_open\nfrom rasterio.vrt import WarpedVRT\nfrom rasterio.enums import Resampling\nfrom rasterio.warp import transform_bou... | [
[
"numpy.all",
"numpy.zeros",
"numpy.sum",
"numpy.moveaxis"
]
] | [
{
"matplotlib": [],
"numpy": [],
"pandas": [],
"scipy": [],
"tensorflow": []
}
] |
shibing624/textgen | [
"0a9d55f1f61d5217b8e06f1f23904e49afa84370",
"0a9d55f1f61d5217b8e06f1f23904e49afa84370"
] | [
"textgen/question_answering/question_answering_model.py",
"textgen/language_generation/language_generation_model.py"
] | [
"# -*- coding: utf-8 -*-\n\"\"\"\n@author:XuMing(xuming624@qq.com)\n@description: refer https://github.com/ThilinaRajapakse/simpletransformers\n\"\"\"\nimport json\nimport math\nimport os\nimport random\nimport warnings\nfrom dataclasses import asdict\n\nimport numpy as np\nimport pandas as pd\nimport torch\nfrom t... | [
[
"numpy.random.seed",
"torch.load",
"torch.manual_seed",
"torch.utils.data.SequentialSampler",
"torch.utils.data.TensorDataset",
"torch.utils.data.DataLoader",
"torch.utils.data.RandomSampler",
"pandas.DataFrame",
"torch.tensor",
"torch.cuda.amp.autocast",
"torch.cuda.am... | [
{
"matplotlib": [],
"numpy": [],
"pandas": [
"0.23",
"0.21",
"2.0",
"1.4",
"0.19",
"1.1",
"1.5",
"1.2",
"0.24",
"0.20",
"1.0",
"0.25",
"1.3"
],
"scipy": [],
"tensorflow": []
},
{
"matplotlib": [],
"nump... |
mcdobe100/arkouda | [
"499ecb502da214ee71e9923fda9487c65ec4d616"
] | [
"tests/operator_tests.py"
] | [
"import numpy as np\nimport warnings\nfrom itertools import product\nfrom base_test import ArkoudaTest\nfrom context import arkouda as ak\nSIZE = 10\nverbose = ArkoudaTest.verbose\n\ndef run_tests(verbose):\n # ignore numpy warnings like divide by 0\n np.seterr(all='ignore')\n global pdarrays\n pdarrays... | [
[
"numpy.allclose",
"numpy.linspace",
"numpy.arange",
"numpy.seterr",
"numpy.int64",
"numpy.uint64",
"numpy.float64"
]
] | [
{
"matplotlib": [],
"numpy": [],
"pandas": [],
"scipy": [],
"tensorflow": []
}
] |
hjyjh/wechat_articles_spider | [
"38da6cde565f8d6e09a5822b25b0dcfb1a8cb239"
] | [
"test/test_GetUrls.py"
] | [
"# coding: utf-8\nimport json\nimport os\nimport random\nimport time\nfrom pprint import pprint\n\nimport pandas as pd\nfrom wechatarticles import ArticlesInfo\nfrom wechatarticles.utils import get_history_urls, verify_url\n\n# 快速获取大量文章urls（利用历史文章获取链接）\n\n\ndef save_xlsx(fj, lst):\n df = pd.DataFrame(lst, column... | [
[
"pandas.DataFrame"
]
] | [
{
"matplotlib": [],
"numpy": [],
"pandas": [
"0.23",
"0.21",
"2.0",
"1.4",
"0.19",
"1.1",
"1.5",
"1.2",
"0.24",
"0.20",
"1.0",
"0.25",
"1.3"
],
"scipy": [],
"tensorflow": []
}
] |
crochat/exareme | [
"94c0ab79b0096a2bac65b13bdf975ff6bbebfea2",
"94c0ab79b0096a2bac65b13bdf975ff6bbebfea2"
] | [
"Exareme-Docker/src/mip-algorithms/LOGISTIC_REGRESSION/init/1/global.py",
"Exareme-Docker/src/mip-algorithms/LOGISTIC_REGRESSION/step/1/local.py"
] | [
"from __future__ import division\nfrom __future__ import print_function\nfrom __future__ import unicode_literals\n\nimport sys\nfrom os import path\nfrom argparse import ArgumentParser\nimport numpy as np\n\nsys.path.append(path.dirname(path.dirname(path.dirname(path.dirname(path.abspath(__file__))))) + '/utils/')\... | [
[
"numpy.log",
"numpy.zeros"
],
[
"numpy.diag",
"numpy.dot",
"numpy.log",
"scipy.special.expit",
"numpy.multiply",
"numpy.transpose",
"numpy.divide"
]
] | [
{
"matplotlib": [],
"numpy": [],
"pandas": [],
"scipy": [],
"tensorflow": []
},
{
"matplotlib": [],
"numpy": [],
"pandas": [],
"scipy": [],
"tensorflow": []
}
] |
onsiteiq/OpenSfM | [
"77335de7fe5ae30a2af6b23ff4488a8ef18738d1"
] | [
"opensfm/features.py"
] | [
"\"\"\"Tools to extract features.\"\"\"\n\nimport time\nimport logging\nimport numpy as np\nimport sys\nimport cv2\n\nfrom opensfm import context\nfrom opensfm import csfm\n\nlogger = logging.getLogger(__name__)\n\n\ndef resized_image(image, config):\n \"\"\"Resize image to feature_process_size.\"\"\"\n max_s... | [
[
"numpy.sqrt",
"numpy.abs",
"numpy.arange",
"numpy.linalg.norm",
"numpy.sign",
"numpy.load",
"numpy.array",
"numpy.sum"
]
] | [
{
"matplotlib": [],
"numpy": [],
"pandas": [],
"scipy": [],
"tensorflow": []
}
] |
hungcao0402/PaddleOCR-Vietnamese | [
"fae0985c902a7a6e541b08c9c708a55593a89b64"
] | [
"tools/infer/predict_system.py"
] | [
"# Copyright (c) 2020 PaddlePaddle Authors. All Rights Reserved.\n#\n# Licensed under the Apache License, Version 2.0 (the \"License\");\n# you may not use this file except in compliance with the License.\n# You may obtain a copy of the License at\n#\n# http://www.apache.org/licenses/LICENSE-2.0\n#\n# Unless re... | [
[
"numpy.random.uniform",
"numpy.array"
]
] | [
{
"matplotlib": [],
"numpy": [],
"pandas": [],
"scipy": [],
"tensorflow": []
}
] |
cod3licious/simec | [
"45392475debc37883a79eddb0e90f2669ce0a44e"
] | [
"utils_datasets.py"
] | [
"from __future__ import unicode_literals, division, print_function, absolute_import\nfrom builtins import range\nimport numpy as np\nfrom sklearn.datasets import make_circles, make_blobs, make_swiss_roll, make_s_curve\nfrom sklearn.utils import check_random_state\n\n\ndef make_3_circles(n_samples, random_state=1):\... | [
[
"sklearn.datasets.make_s_curve",
"sklearn.datasets.make_swiss_roll",
"numpy.cos",
"numpy.ones",
"numpy.sin",
"sklearn.datasets.make_circles",
"numpy.array",
"sklearn.utils.check_random_state",
"sklearn.datasets.make_blobs"
]
] | [
{
"matplotlib": [],
"numpy": [],
"pandas": [],
"scipy": [],
"tensorflow": []
}
] |
chao9527/PaddleBox | [
"1cb68eb8227096c3d269e7f6ba5075f7157add86"
] | [
"python/paddle/fluid/dataset.py"
] | [
"# Copyright (c) 2018 PaddlePaddle Authors. All Rights Reserved.\n#\n# Licensed under the Apache License, Version 2.0 (the \"License\");\n# you may not use this file except in compliance with the License.\n# You may obtain a copy of the License at\n#\n# http://www.apache.org/licenses/LICENSE-2.0\n#\n# Unless ... | [
[
"numpy.array"
]
] | [
{
"matplotlib": [],
"numpy": [],
"pandas": [],
"scipy": [],
"tensorflow": []
}
] |
Vishal-V/Hack-Submission | [
"677d8d6a19ae63d3aa2ddd74e9ce8ae7a06b71df"
] | [
"Flask/cancer_classification.py"
] | [
"#!/usr/bin/env python\n# coding: utf-8\n\n# In[1]:\n\n\nimport numpy as np \nimport pandas as pd\nimport seaborn as sns\nimport matplotlib.pyplot as plt\n\n\n# In[2]:\n\n\nfrom sklearn.datasets import load_breast_cancer\n\n\n# In[3]:\n\n\ndata = load_breast_cancer()\n\n\n# In[4]:\n\n\ndata\n\n\n# In[5]:\n\n\ndata.... | [
[
"sklearn.datasets.load_breast_cancer",
"matplotlib.pyplot.figure",
"sklearn.model_selection.train_test_split",
"sklearn.metrics.confusion_matrix",
"numpy.append",
"sklearn.svm.SVC",
"sklearn.metrics.classification_report",
"sklearn.metrics.accuracy_score"
]
] | [
{
"matplotlib": [],
"numpy": [],
"pandas": [],
"scipy": [],
"tensorflow": []
}
] |
aimagelab/RefiNet | [
"aedd551df78b265bff4de9610df077473d07166c"
] | [
"src/Datasets/transforms.py"
] | [
"import numpy as np\n\n\nclass Compose(object):\n def __init__(self, transforms):\n self.transforms = transforms\n\n def __call__(self, inputs):\n for t in self.transforms:\n inputs = t(inputs)\n\n return inputs\n\n\nclass GaussianNoise(object):\n def __init__(self, image_si... | [
[
"numpy.random.normal"
]
] | [
{
"matplotlib": [],
"numpy": [],
"pandas": [],
"scipy": [],
"tensorflow": []
}
] |
ds-wook/Final-NeuralFBProphet | [
"40caac12a1805da6a061452ea5571b48d6f2bb8f"
] | [
"src/Final-NeuralFBProphet/two_optim.py"
] | [
"import argparse\n\nimport joblib\nimport optuna\nfrom neuralprophet import NeuralProphet\nfrom optuna import Trial\nfrom optuna.samplers import TPESampler\nfrom sklearn.metrics import mean_squared_error\n\nfrom data.dataset import two_seconds_dataset\n\nparse = argparse.ArgumentParser(\"Optimize\")\nparse.add_argu... | [
[
"sklearn.metrics.mean_squared_error"
]
] | [
{
"matplotlib": [],
"numpy": [],
"pandas": [],
"scipy": [],
"tensorflow": []
}
] |
MICCoMpy/PyCCE | [
"b24a311f54d04ce452ef4b75f52a61a35d502563"
] | [
"pycce/utilities.py"
] | [
"import numpy as np\r\nfrom pycce.sm import _smc\r\nfrom numba import jit\r\nfrom numba.typed import List\r\nimport warnings\r\n\r\ndef rotmatrix(initial_vector, final_vector):\r\n r\"\"\"\r\n Generate 3D rotation matrix which applied on initial vector will produce vector, aligned with final vector.\r\n\r\n ... | [
[
"numpy.diag",
"numpy.dot",
"numpy.sqrt",
"numpy.linspace",
"numpy.asarray",
"numpy.eye",
"numpy.matmul",
"numpy.linalg.norm",
"numpy.delete",
"numpy.any",
"numpy.moveaxis",
"numpy.cross",
"numpy.array",
"numpy.zeros",
"numpy.trace",
"numpy.empty"
]... | [
{
"matplotlib": [],
"numpy": [],
"pandas": [],
"scipy": [],
"tensorflow": []
}
] |
zhuohaoyu/TextBox | [
"bc44c51902fa9b3392c022b4cba5ff8757355869"
] | [
"textbox/model/Seq2Seq/rnnencdec.py"
] | [
"# @Time : 2020/11/14\n# @Author : Junyi Li\n# @Email : lijunyi@ruc.edu.cn\n\n# UPDATE:\n# @Time : 2020/12/25\n# @Author : Tianyi Tang\n# @Email : steventang@ruc.edu.cn\n\nr\"\"\"\nRNNEncDec\n################################################\nReference:\n Sutskever et al. \"Sequence to Sequence Learning wit... | [
[
"torch.nn.CrossEntropyLoss",
"torch.nn.Dropout",
"torch.LongTensor",
"torch.nn.Embedding",
"torch.nn.Linear",
"torch.ne"
]
] | [
{
"matplotlib": [],
"numpy": [],
"pandas": [],
"scipy": [],
"tensorflow": []
}
] |
varun-affinsys/Monocular-Depth-Estimation-with-Transfer-Learning-pretrained-MobileNetV2 | [
"9b20c5b3d7a9f90e1dc6f40e17ee31d9b3dee684"
] | [
"UtilityTest.py"
] | [
"import os\nimport glob\nimport time\nfrom PIL import Image\nimport numpy as np\nimport PIL\nimport random\nimport torch\nimport matplotlib.pyplot as plt\nfrom torch.utils.data import Dataset, DataLoader\nfrom torchvision import transforms, utils\n\ndef _is_pil_image(img):\n return isinstance(img, Image.Image)\n... | [
[
"numpy.array"
]
] | [
{
"matplotlib": [],
"numpy": [],
"pandas": [],
"scipy": [],
"tensorflow": []
}
] |
noogel/xyzDeepLearning | [
"5cfb477b317202b4d09850ae9602bc99cfc9f90c"
] | [
"machine_learning/show_pic_location.py"
] | [
"#! /usr/bin/python\n# -*- coding:utf-8 -*-\n\"\"\"\n@author: abc\n@file: euclidean_distance.py\n@date: 2016-12-09\n@desc: 差分矩阵求和/均值\n\"\"\"\n__author__ = \"abc\"\n\nimport cv2\nimport numpy as np\n\n\ndef show_pic_location(img, findimg):\n \"\"\"\n show_pic_location\n :param img:\n :param findimg:\n ... | [
[
"numpy.random.uniform",
"numpy.mean",
"numpy.random.rand"
]
] | [
{
"matplotlib": [],
"numpy": [],
"pandas": [],
"scipy": [],
"tensorflow": []
}
] |
shravan20/mycaptain-ai-certification | [
"d8a700d3bb2059fc7e359e8e1ff23ed0c154299e"
] | [
"ImageClassification/test.py"
] | [
"from train import load_data, batch_size\nfrom tensorflow.keras.models import load_model\nimport matplotlib.pyplot as plt\nimport numpy as np\n\n# CIFAR-10 classes\ncategories = {\n 0: \"airplane\",\n 1: \"automobile\",\n 2: \"bird\",\n 3: \"cat\",\n 4: \"deer\",\n 5: \"dog\",\n 6: \"frog\",\n ... | [
[
"tensorflow.keras.models.load_model",
"matplotlib.pyplot.imshow",
"matplotlib.pyplot.show",
"matplotlib.pyplot.axis"
]
] | [
{
"matplotlib": [],
"numpy": [],
"pandas": [],
"scipy": [],
"tensorflow": [
"1.10",
"2.7",
"2.2",
"2.3",
"2.4",
"2.5",
"2.6"
]
}
] |
DedSec-1/Idiot-Boxx | [
"de41bb0ace787f34ba8100dc1f33b570f24315b4"
] | [
"openCV.py"
] | [
"import cv2\nimport mediapipe as mp\nfrom tensorflow.keras.models import load_model\nimport numpy as np\nimport pyttsx3 \n\nCLASSIFICATION = {\n 0: \"A\",\n 1: \"B\",\n 2: \"C\",\n 3: \"D\",\n 4: \"E\",\n 5: \"F\",\n 6: \"G\",\n 7: \"H\",\n 8: \"I\",\n 9: \"J\",\n 10: \"K\",\n 11... | [
[
"tensorflow.keras.models.load_model",
"numpy.array",
"numpy.argmax"
]
] | [
{
"matplotlib": [],
"numpy": [],
"pandas": [],
"scipy": [],
"tensorflow": [
"1.10",
"2.7",
"2.2",
"2.3",
"2.4",
"2.5",
"2.6"
]
}
] |
anandrajasekar18/spinningup | [
"c14daf6579e0341a387358adf4230de36d6e7cd4"
] | [
"spinup/algos/tf1/cvi/cvi_ad.py"
] | [
"import numpy as np\nimport tensorflow as tf\nimport gym\nimport time\nimport math\nfrom spinup.algos.cvi import core\nfrom spinup.algos.cvi.core import get_vars\nfrom spinup.utils.logx import EpochLogger\n\n\n\nclass ReplayBuffer:\n \"\"\"\n A simple FIFO experience replay buffer for SAC agents.\n \"\"\"\... | [
[
"tensorflow.sign",
"numpy.random.seed",
"tensorflow.reduce_mean",
"tensorflow.control_dependencies",
"tensorflow.minimum",
"tensorflow.assign",
"tensorflow.placeholder",
"tensorflow.global_variables_initializer",
"tensorflow.variable_scope",
"tensorflow.train.AdamOptimizer"... | [
{
"matplotlib": [],
"numpy": [],
"pandas": [],
"scipy": [],
"tensorflow": [
"1.10"
]
}
] |
davidtea/CIFAR-10 | [
"38f58d9888c321974f434fc26e3037def4669f2c"
] | [
"cifar10_train.py"
] | [
"# Copyright 2015 The TensorFlow Authors. All Rights Reserved.\n#\n# Licensed under the Apache License, Version 2.0 (the \"License\");\n# you may not use this file except in compliance with the License.\n# You may obtain a copy of the License at\n#\n# http://www.apache.org/licenses/LICENSE-2.0\n#\n# Unless requ... | [
[
"tensorflow.Graph",
"tensorflow.gfile.DeleteRecursively",
"tensorflow.train.StopAtStepHook",
"matplotlib.pyplot.title",
"tensorflow.train.NanTensorHook",
"tensorflow.gfile.Exists",
"matplotlib.use",
"tensorflow.train.SessionRunArgs",
"tensorflow.app.flags.DEFINE_integer",
"... | [
{
"matplotlib": [],
"numpy": [],
"pandas": [],
"scipy": [],
"tensorflow": []
}
] |
mlrun/frameworks | [
"3b046710102af00baac9a5c2fdeceb7fc1f8838a"
] | [
"frameworks/keras/mlrun_interface.py"
] | [
"from abc import ABC\nfrom typing import Union, List, Dict, Tuple, Any\nimport os\nimport importlib\n\nimport tensorflow as tf\nfrom tensorflow import keras\nfrom tensorflow.keras.callbacks import (\n Callback,\n ModelCheckpoint,\n TensorBoard,\n ProgbarLogger,\n CSVLogger,\n BaseLogger,\n)\nfrom ... | [
[
"tensorflow.config.experimental.list_physical_devices",
"tensorflow.config.experimental.set_memory_growth"
]
] | [
{
"matplotlib": [],
"numpy": [],
"pandas": [],
"scipy": [],
"tensorflow": []
}
] |
SNUHDR2018/ConSSL | [
"c7d406d0224e38895986c8fb7281a189e493c982"
] | [
"ConSSL/datamodules/vocdetection_datamodule.py"
] | [
"from typing import Any, Callable, Dict, List, Optional, Tuple, Union\n\nimport torch\nfrom pytorch_lightning import LightningDataModule\nfrom torch.utils.data import DataLoader\n\nfrom ConSSL.utils import _TORCHVISION_AVAILABLE\nfrom ConSSL.utils.warnings import warn_missing_pkg\n\nif _TORCHVISION_AVAILABLE:\n ... | [
[
"torch.utils.data.DataLoader",
"torch.as_tensor"
]
] | [
{
"matplotlib": [],
"numpy": [],
"pandas": [],
"scipy": [],
"tensorflow": []
}
] |
awesome-archive/detectron2 | [
"4fe0d8f10a13016c2a802e5e47af67ebe5576fc3"
] | [
"demo/predictor.py"
] | [
"# Copyright (c) Facebook, Inc. and its affiliates. All Rights Reserved\nimport atexit\nimport bisect\nimport multiprocessing as mp\nfrom collections import deque\nimport cv2\nimport torch\n\nfrom detectron2.data import MetadataCatalog\nfrom detectron2.engine.defaults import DefaultPredictor\nfrom detectron2.utils.... | [
[
"torch.device",
"torch.cuda.device_count"
]
] | [
{
"matplotlib": [],
"numpy": [],
"pandas": [],
"scipy": [],
"tensorflow": []
}
] |
gustasvs/AI | [
"23360a8865e8211568594c2b2ced11dcdc9b0006",
"23360a8865e8211568594c2b2ced11dcdc9b0006"
] | [
"DiRT AI/DiRT NeuralNetworks/functions/grabscreen.py",
"Tensorflow-master/experiments/2D_car/car_env.py"
] | [
"import win32gui, win32ui, win32con, win32api\nimport cv2\nimport numpy as np\n\n\ndef grab_screen(region=None):\n hwin = win32gui.GetDesktopWindow()\n\n left,top,x2,y2 = region\n width = x2 - left + 1\n height = y2 - top + 1\n\n hwindc = win32gui.GetWindowDC(hwin)\n srcdc = win32ui.CreateDCFromHa... | [
[
"numpy.fromstring"
],
[
"numpy.random.seed",
"numpy.linspace",
"numpy.min",
"numpy.clip",
"numpy.cos",
"numpy.linalg.norm",
"numpy.sin",
"numpy.argmin",
"numpy.cross",
"numpy.random.uniform",
"numpy.array",
"numpy.zeros",
"numpy.vstack"
]
] | [
{
"matplotlib": [],
"numpy": [],
"pandas": [],
"scipy": [],
"tensorflow": []
},
{
"matplotlib": [],
"numpy": [],
"pandas": [],
"scipy": [],
"tensorflow": []
}
] |
mtzgroup/ChemPixCH | [
"0f2763eb8989904d11eb3486f101a50173723ed4"
] | [
"im2smiles/model/utils/general.py"
] | [
"import os\nimport numpy as np\nimport time\nimport logging\nimport sys\nimport subprocess, shlex\nfrom shutil import copyfile\nimport json\nfrom threading import Timer\nfrom os import listdir\nfrom os.path import isfile, join\n\n\ndef minibatches(data_generator, minibatch_size):\n \"\"\"\n Args:\n dat... | [
[
"numpy.log10"
]
] | [
{
"matplotlib": [],
"numpy": [],
"pandas": [],
"scipy": [],
"tensorflow": []
}
] |
sharat910/datacube-iirs | [
"1b7e2d192d969609756def8923c20899733e695d"
] | [
"build/lib/datacube/ndexpr/__init__.py"
] | [
"# ------------------------------------------------------------------------------\n# Name: ndexpr.py\n# Purpose: ndarray Math Expression evaluator\n#\n# Author: Peter Wang\n#\n# Created: 7 October 2015\n# Copyright: 2015 Commonwealth Scientific and Industrial Research Organisation\n# (C... | [
[
"scipy.ndimage.binary_erosion",
"numpy.random.randn",
"matplotlib.pyplot.subplots_adjust",
"matplotlib.pyplot.show",
"numpy.zeros",
"matplotlib.pyplot.figure"
]
] | [
{
"matplotlib": [],
"numpy": [],
"pandas": [],
"scipy": [
"1.7",
"1.0",
"0.10",
"1.2",
"0.14",
"0.19",
"1.5",
"0.12",
"0.17",
"0.13",
"1.6",
"1.4",
"1.9",
"1.3",
"1.10",
"0.15",
"0.18",
"0.16"... |
michaels10/pydec | [
"738c3d9cf1cedc95a61be63fae36073e038d08bc"
] | [
"pydec/io/tests/test_arrayio.py"
] | [
"from pydec.testing import *\n\nfrom scipy import arange, prod, reshape, rand, random, allclose, rank, zeros\nfrom scipy.sparse import csr_matrix, csc_matrix, coo_matrix\n\nfrom pydec.io.arrayio import write_array, read_array\n\n\n#TODO replace with tempfile\n\nfilename = '/tmp/pydec_arrayio_testfile.dat'\n\nclass ... | [
[
"scipy.sparse.csc_matrix",
"scipy.sparse.coo_matrix",
"scipy.random.seed",
"scipy.prod",
"scipy.zeros",
"scipy.sparse.csr_matrix",
"scipy.rand",
"scipy.rank"
]
] | [
{
"matplotlib": [],
"numpy": [],
"pandas": [],
"scipy": [],
"tensorflow": []
}
] |
guilhermesilveira/marked_card_detector | [
"03a81171b7625cbef0c3968ad881c09c4b384d08"
] | [
"marked_card_detector/card.py"
] | [
"import cv2\nimport numpy as np\n\nfrom marked_card_detector.graphics import flattener\n\nfont = cv2.FONT_HERSHEY_SIMPLEX\n\n# based on https://github.com/EdjeElectronics/OpenCV-Playing-Card-Detector/blob/master/Cards.py\n# Width and height of card corner, where rank and suit are\nCORNER_WIDTH = 32\nCORNER_HEIGHT =... | [
[
"numpy.sum",
"numpy.float32"
]
] | [
{
"matplotlib": [],
"numpy": [],
"pandas": [],
"scipy": [],
"tensorflow": []
}
] |
laigm/rcnn | [
"37bd2f3ea460353efbccd17ccd02045ee6a442d2"
] | [
"frcnn.py"
] | [
"import colorsys\nimport copy\nimport math\nimport os\nimport pickle\n\nimport cv2\nimport numpy as np\nimport tensorflow as tf\nfrom PIL import Image, ImageDraw, ImageFont\nfrom tensorflow import keras\nfrom tensorflow.keras import backend as K\nfrom tensorflow.keras.applications.imagenet_utils import preprocess_i... | [
[
"numpy.expand_dims",
"tensorflow.function",
"numpy.shape",
"numpy.zeros_like",
"numpy.floor",
"numpy.array"
]
] | [
{
"matplotlib": [],
"numpy": [],
"pandas": [],
"scipy": [],
"tensorflow": [
"2.7",
"2.6",
"2.2",
"2.3",
"2.4",
"2.9",
"2.5",
"2.8",
"2.10"
]
}
] |
mandanasmi/torch-rl | [
"0f195945070fde80db0876b61a5f800ce1494619"
] | [
"torch_rl/torch_rl/algos/new_algo.py"
] | [
"import numpy as np\nfrom comet_ml import Experiment\nimport torch\nfrom torch_rl.format import default_preprocess_obss\nfrom abc import ABC\nfrom collections import deque\nimport random\nfrom matplotlib import pyplot as plt\nimport math\nimport json, os, csv\nimport torch.nn.functional as F\n\nhyper_params = {\n ... | [
[
"matplotlib.pyplot.legend",
"torch.LongTensor",
"numpy.expand_dims",
"numpy.save",
"numpy.concatenate",
"torch.FloatTensor",
"torch.save",
"torch.nn.functional.smooth_l1_loss",
"matplotlib.pyplot.close",
"torch.cuda.is_available",
"torch.no_grad",
"numpy.mean",
... | [
{
"matplotlib": [],
"numpy": [],
"pandas": [],
"scipy": [],
"tensorflow": []
}
] |
Parry-Parry/Level-4-Project | [
"ea2d6be2b7964fe21a8e1a92d79e89fcab8b6b74"
] | [
"code2text/models/baseline/baseline_weak.py"
] | [
"from tensorflow.keras.models import Model\nfrom tensorflow.keras.layers import Input\nfrom tensorflow.keras.layers import LSTM\nfrom tensorflow.keras.layers import Dense\n\n# configure\nnum_encoder_tokens = 71\nnum_decoder_tokens = 93\nlatent_dim = 256\n# Define an input sequence and process it.\nencoder_inputs = ... | [
[
"tensorflow.keras.layers.Dense",
"tensorflow.keras.layers.LSTM",
"tensorflow.keras.models.Model",
"tensorflow.keras.layers.Input"
]
] | [
{
"matplotlib": [],
"numpy": [],
"pandas": [],
"scipy": [],
"tensorflow": [
"2.7",
"2.2",
"2.3",
"2.4",
"2.5",
"2.6"
]
}
] |
asparc/acados | [
"fe353023814cdfc47ae84eaeef1fcb0b3fa7b687"
] | [
"interfaces/acados_template/acados_template/utils.py"
] | [
"#\n# Copyright 2019 Gianluca Frison, Dimitris Kouzoupis, Robin Verschueren,\n# Andrea Zanelli, Niels van Duijkeren, Jonathan Frey, Tommaso Sartor,\n# Branimir Novoselnik, Rien Quirynen, Rezart Qelibari, Dang Doan,\n# Jonas Koenemann, Yutao Chen, Tobias Schöls, Jonas Schlagenhauf, Moritz Diehl\n#\n# This file is pa... | [
[
"numpy.nonzero",
"numpy.array",
"numpy.zeros",
"numpy.prod"
]
] | [
{
"matplotlib": [],
"numpy": [],
"pandas": [],
"scipy": [],
"tensorflow": []
}
] |
dchou1618/MST-DecisionTree-Phishing | [
"6443b07dc425a3b58cf88e9092284fb7e082bfc2"
] | [
"c45/c45.py"
] | [
"import math\r\nfrom xml.dom import minidom\r\nfrom xml.etree import ElementTree as ET\r\n\r\nfrom sklearn.base import BaseEstimator, ClassifierMixin\r\nfrom sklearn.utils.validation import check_array, check_is_fitted, check_X_y\r\n\r\nfrom .c45_utils import decision, grow_tree\r\n\r\nclass C45(BaseEstimator, Clas... | [
[
"sklearn.utils.validation.check_is_fitted",
"sklearn.utils.validation.check_X_y",
"sklearn.utils.validation.check_array"
]
] | [
{
"matplotlib": [],
"numpy": [],
"pandas": [],
"scipy": [],
"tensorflow": []
}
] |
allocateam/opendc | [
"8ee3067c40c2e94d504c9a663d1df174f289ba8e"
] | [
"simulator/opendc-experiments/opendc-experiments-allocateam/tools/plot/plot.py"
] | [
"#!/usr/bin/env python3\n\nimport argparse\nfrom datetime import datetime\nfrom pathlib import Path\nfrom typing import List, Dict, Type\n\nimport pandas as pd\nimport seaborn as sns\n\nfrom metrics import Metric, Plot\nfrom metrics.plot import MetricWorkloadBarPlot as bar_plot\nfrom metrics.plot import MetricWorkl... | [
[
"pandas.read_parquet",
"pandas.concat"
]
] | [
{
"matplotlib": [],
"numpy": [],
"pandas": [
"0.23",
"0.21",
"2.0",
"1.4",
"1.3",
"1.1",
"1.5",
"0.24",
"1.0",
"0.25",
"1.2"
],
"scipy": [],
"tensorflow": []
}
] |
EnergyModels/BLIS | [
"514577a99a16804894019b4ee53d48eda0c6c313"
] | [
"examples/storage_sizing/test_create_inputs.py"
] | [
"# ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~#\n\"\"\"\nBLIS - Balancing Load of Intermittent Solar:\nA characteristic-based transient power plant model\n\nCopyright (C) 2020. University of Virginia Licensing & Ventures Group (UVA LVG). All Rights Reserved.\n\nPermission is hereby... | [
[
"numpy.random.lognormal",
"pandas.read_excel",
"pandas.DataFrame",
"numpy.append",
"numpy.random.normal",
"numpy.random.triangular",
"numpy.random.uniform"
]
] | [
{
"matplotlib": [],
"numpy": [],
"pandas": [
"0.23",
"0.21",
"2.0",
"1.4",
"1.3",
"0.19",
"1.1",
"1.5",
"0.24",
"0.20",
"1.0",
"0.25",
"1.2"
],
"scipy": [],
"tensorflow": []
}
] |
conan7882/tmp | [
"669161ff20770c5698f2e4f5acc3c366a4cd7151"
] | [
"src/utils/utils.py"
] | [
"#!/usr/bin/env python\r\n# -*- coding: utf-8 -*-\r\n# File: utils.py\r\n# Author: Qian Ge <geqian1001@gmail.com>\r\n\r\n\r\nimport numpy as np\r\n\r\ndef make_list(inputs):\r\n if not isinstance(inputs, list):\r\n return [inputs]\r\n else:\r\n return inputs\r\n\r\ndef get_shape4D(in_val):\r\n ... | [
[
"numpy.array"
]
] | [
{
"matplotlib": [],
"numpy": [],
"pandas": [],
"scipy": [],
"tensorflow": []
}
] |
symbench/scm | [
"8e40d3549dd605b1822156216684a28cc027a8e8"
] | [
"circuit_recognizer/circuit_recognizer/test/connect/test_line.py"
] | [
"from itertools import chain\n\nimport numpy as np\n\nfrom circuit_recognizer.connect.line import DirectedLine, detect_intersection_rect\n\n\nclass TestLine:\n def test_detect_intersection(self):\n image = np.array(\n [\n [False, False, True, False, False, False, False],\n ... | [
[
"numpy.array",
"numpy.zeros"
]
] | [
{
"matplotlib": [],
"numpy": [],
"pandas": [],
"scipy": [],
"tensorflow": []
}
] |
fl42/frigate | [
"d7460d9c3606267b36a2ba5efccde395f6e05064"
] | [
"frigate/config.py"
] | [
"import base64\nimport json\nimport logging\nimport os\nfrom typing import Dict\n\nimport cv2\nimport matplotlib.pyplot as plt\nimport numpy as np\nimport voluptuous as vol\nimport yaml\n\nfrom frigate.const import RECORD_DIR, CLIPS_DIR, CACHE_DIR\nfrom frigate.util import create_mask\n\nlogger = logging.getLogger(... | [
[
"numpy.array",
"numpy.zeros"
]
] | [
{
"matplotlib": [],
"numpy": [],
"pandas": [],
"scipy": [],
"tensorflow": []
}
] |
thvasilo/autogluon | [
"49eb617cd324cdc758a2a7b74bfef5e34d7f96d7"
] | [
"autogluon/utils/tabular/ml/models/lr/lr_model.py"
] | [
"import logging\nimport re\n\nimport numpy as np\nfrom pandas import DataFrame\nfrom sklearn.feature_extraction.text import TfidfVectorizer\nfrom sklearn.impute import SimpleImputer\nfrom sklearn.pipeline import FeatureUnion, Pipeline\nfrom sklearn.preprocessing import StandardScaler, QuantileTransformer\n\nfrom .h... | [
[
"sklearn.pipeline.FeatureUnion",
"sklearn.preprocessing.QuantileTransformer",
"sklearn.impute.SimpleImputer",
"sklearn.preprocessing.StandardScaler",
"sklearn.feature_extraction.text.TfidfVectorizer"
]
] | [
{
"matplotlib": [],
"numpy": [],
"pandas": [],
"scipy": [],
"tensorflow": []
}
] |
jbofill10/COIVID-19-EDA | [
"816a4b4d75bbdbcbcaaf17fb844d1524ec614ca1"
] | [
"EDA/task1_transmission_incubation/Transmission.py"
] | [
"import spacy\nimport pandas as pd\nimport os\nimport json\nimport matplotlib.pyplot as plt\nimport matplotlib.style as style\nfrom spacy.matcher import Matcher\n\nfrom tqdm import tqdm\n\n\ndef transmission(df):\n style.use('seaborn-poster')\n style.use('ggplot')\n\n if not os.path.exists('Data/pickles/tr... | [
[
"matplotlib.pyplot.title",
"matplotlib.style.use",
"matplotlib.pyplot.savefig",
"pandas.DataFrame",
"pandas.read_pickle",
"matplotlib.pyplot.show"
]
] | [
{
"matplotlib": [],
"numpy": [],
"pandas": [
"0.23",
"0.21",
"2.0",
"1.4",
"1.3",
"0.19",
"1.1",
"1.5",
"0.24",
"0.20",
"1.0",
"0.25",
"1.2"
],
"scipy": [],
"tensorflow": []
}
] |
Tomoya-K-0504/deepSELF | [
"0e5a7d0169b3e9edcb5c8d9802140a84ce5cb69a"
] | [
"deepself/models/nn_models/rnn.py"
] | [
"from __future__ import print_function, division\n\nfrom collections import OrderedDict\n\nimport torch\nimport torch.nn as nn\n\nfrom deepself.models.nn_models.nn_utils import initialize_weights\n\nsupported_rnns = {\n 'lstm': nn.LSTM,\n 'rnn': nn.RNN,\n 'gru': nn.GRU\n}\n\n\nfrom dataclasses import datac... | [
[
"torch.nn.Linear",
"torch.nn.BatchNorm1d",
"torch.nn.LogSoftmax"
]
] | [
{
"matplotlib": [],
"numpy": [],
"pandas": [],
"scipy": [],
"tensorflow": []
}
] |
sujanabasnet/Hackflight | [
"98d0f0dee07dbddd81c63bd1997e845ca244106f"
] | [
"extras/python/hackflight.py"
] | [
"\"\"\"\nHackflight class in python\n\nCopyright (C) 2021 S.Basnet, N. Manaye, N. Nguyen, S.D. Levy\n\nMIT License\n\"\"\"\n\n\nimport numpy as np\n# from debugging import debug\n\n\nclass Hackflight(object):\n\n def __init__(self, board, receiver, actuator):\n self.board = board\n self.receiver = ... | [
[
"numpy.zeros"
]
] | [
{
"matplotlib": [],
"numpy": [],
"pandas": [],
"scipy": [],
"tensorflow": []
}
] |
BrisaDavis/visclaw | [
"2ad7217502ce4df2b2452dcbb3eb010d567a2eca"
] | [
"src/python/visclaw/animation_tools.py"
] | [
"\"\"\"\nThis animation_tools module contains tools to create animations in Python and\nJupyter notebooks.\n\nThree types of animations are supported: \n - using the ipywidget interact to create a figure with a slider bar, \n - using JSAnimation to create Javascript code that loops over a set of \n images and add... | [
[
"matplotlib.pyplot.imshow",
"matplotlib.animation.writers.is_available",
"matplotlib.pyplot.imread",
"matplotlib.pyplot.savefig",
"matplotlib.pyplot.draw",
"matplotlib.pyplot.axes",
"matplotlib.image.imread",
"matplotlib.pyplot.close",
"matplotlib.pyplot.figure"
]
] | [
{
"matplotlib": [],
"numpy": [],
"pandas": [],
"scipy": [],
"tensorflow": []
}
] |
lionelxhub/electra_japanese | [
"105d3e42edf84e66d5288939cd73546748eec73a"
] | [
"pretrain/pretrain_data.py"
] | [
"# coding=utf-8\r\n# Copyright 2020 The Google Research Authors.\r\n#\r\n# Licensed under the Apache License, Version 2.0 (the \"License\");\r\n# you may not use this file except in compliance with the License.\r\n# You may obtain a copy of the License at\r\n#\r\n# http://www.apache.org/licenses/LICENSE-2.0\r\n... | [
[
"tensorflow.compat.v1.io.FixedLenFeature",
"tensorflow.compat.v1.io.parse_single_example",
"tensorflow.compat.v1.data.experimental.parallel_interleave",
"tensorflow.compat.v1.io.gfile.glob",
"numpy.zeros_like",
"tensorflow.compat.v1.cast",
"tensorflow.compat.v1.constant"
]
] | [
{
"matplotlib": [],
"numpy": [],
"pandas": [],
"scipy": [],
"tensorflow": []
}
] |
aced-differentiate/dft-input-gen | [
"14bee323517714c433682bad2dcb897b223dd5ec"
] | [
"src/dftinputgen/utils.py"
] | [
"import re\nimport six\nimport numpy as np\n\nfrom ase import io as ase_io\n\nfrom dftinputgen.data import STANDARD_ATOMIC_WEIGHTS\n\n\nclass DftInputGeneratorUtilsError(Exception):\n \"\"\"Base class for errors associated with the helper utilities.\"\"\"\n\n pass\n\n\ndef get_elem_symbol(species_label):\n ... | [
[
"numpy.linalg.inv",
"numpy.linalg.norm"
]
] | [
{
"matplotlib": [],
"numpy": [
"1.11",
"1.10",
"1.12",
"1.19",
"1.24",
"1.13",
"1.16",
"1.9",
"1.18",
"1.23",
"1.21",
"1.22",
"1.20",
"1.7",
"1.15",
"1.14",
"1.17",
"1.8"
],
"pandas": [],
... |
Daikon-Sun/AdjustAutocorrelation | [
"e57264d5d13a471ad5873062d88be7d81912a229"
] | [
"main.py"
] | [
"import logging\nimport numpy as np\nimport sys\nimport os\nimport importlib\n\n\nimport torch\nimport torch.nn as nn\n\n\nfrom args import args\nfrom utils import create_dir, ForecastingData\n\n\ndef run():\n\n if args.task_type == 'forecasting':\n data = ForecastingData()\n\n # datasets = []\n # f... | [
[
"torch.nn.init.xavier_uniform_",
"torch.nn.init.uniform_",
"numpy.ones",
"torch.tensor"
]
] | [
{
"matplotlib": [],
"numpy": [],
"pandas": [],
"scipy": [],
"tensorflow": []
}
] |
MainRo/deep-speaker | [
"48ff6c503bd15eab23ef46911fe48c88cab4058d",
"48ff6c503bd15eab23ef46911fe48c88cab4058d"
] | [
"deep_speaker/do_train.py",
"deep_speaker/toolbox/audio_features.py"
] | [
"import asyncio\nimport argparse\nimport pickle\nimport yaml\nfrom deep_speaker.toolbox import import_function\nfrom makinage.data import pull\n\n\nimport numpy as np\nimport torch\nfrom torch.utils.tensorboard import SummaryWriter\n\n\ndef load_config(config_file):\n with open(config_file, 'r') as f:\n r... | [
[
"numpy.expand_dims",
"torch.from_numpy",
"numpy.stack",
"torch.utils.tensorboard.SummaryWriter",
"numpy.zeros"
],
[
"numpy.dot",
"numpy.abs",
"numpy.linspace",
"numpy.fft.rfft",
"numpy.arange",
"numpy.finfo",
"numpy.sin",
"scipy.fftpack.dct",
"numpy.appe... | [
{
"matplotlib": [],
"numpy": [],
"pandas": [],
"scipy": [],
"tensorflow": []
},
{
"matplotlib": [],
"numpy": [],
"pandas": [],
"scipy": [
"1.7",
"1.0",
"0.10",
"1.2",
"0.14",
"0.19",
"1.5",
"0.12",
"0.17",
"0.13",
... |
Nightwalker495/SiamFC | [
"3813f80c907c87f67f6937e489d3cf452f7d96db"
] | [
"src/test_tracking.py"
] | [
"#!/usr/bin/env python\n# -*- coding: utf-8 -*-\n\n# Author: Milan Ondrasovic <milan.ondrasovic@gmail.com>\n\nimport sys\nimport pathlib\nfrom typing import Iterable, Optional, cast\n\nimport click\nimport cv2 as cv\nimport numpy as np\nimport torch\n\nfrom sot.cfg import TrackerConfig\nfrom sot.tracker import Trac... | [
[
"numpy.asarray",
"torch.cuda.is_available"
]
] | [
{
"matplotlib": [],
"numpy": [],
"pandas": [],
"scipy": [],
"tensorflow": []
}
] |
irwanmazlin/Object-Detection | [
"943a08cd142ebe6b841910cac1a0ae85a6e4b23a"
] | [
"vehicle detection/tensorflow-yolov4-tflite/core/utils.py"
] | [
"import cv2\nimport random\nimport colorsys\nimport numpy as np\nimport tensorflow as tf\nfrom core.config import cfg\n\ndef load_freeze_layer(model='yolov4', tiny=False):\n if tiny:\n if model == 'yolov3':\n freeze_layouts = ['conv2d_9', 'conv2d_12']\n else:\n freeze_layouts ... | [
[
"numpy.fromfile",
"tensorflow.concat",
"numpy.product",
"tensorflow.maximum",
"tensorflow.minimum",
"numpy.full",
"numpy.concatenate",
"numpy.argmax",
"numpy.float32",
"numpy.exp",
"numpy.array",
"tensorflow.math.divide_no_nan"
]
] | [
{
"matplotlib": [],
"numpy": [],
"pandas": [],
"scipy": [],
"tensorflow": []
}
] |
wenbingl/keras-onnx | [
"2dd93301024b1e296a8d77be72483f35506478be"
] | [
"keras2onnx/main.py"
] | [
"###############################################################################\n# Copyright (c) Microsoft Corporation. All rights reserved.\n# Licensed under the MIT License. See License.txt in the project root for\n# license information.\n##########################################################################... | [
[
"tensorflow.python.summary.summary.FileWriter"
]
] | [
{
"matplotlib": [],
"numpy": [],
"pandas": [],
"scipy": [],
"tensorflow": [
"1.10",
"2.7",
"1.12",
"2.6",
"2.2",
"1.13",
"2.3",
"2.4",
"1.4",
"2.9",
"1.5",
"1.7",
"2.5",
"0.12",
"1.0",
"2.8",
"1... |
mvoofan/pct_code | [
"89bba63cc7c6c0f49a552a7d00ca87ef124f8bed"
] | [
"train.py"
] | [
"import time\nfrom options.train_options import TrainOptions\nfrom data.data_loader import CreateDataLoader\nfrom models.models import create_model\nfrom util.visualizer import Visualizer\nfrom tqdm import tqdm\nimport numpy as np\nimport os\nimport torch\n\nopt = TrainOptions().parse()\ndata_loader = CreateDataLoa... | [
[
"torch.load"
]
] | [
{
"matplotlib": [],
"numpy": [],
"pandas": [],
"scipy": [],
"tensorflow": []
}
] |
xmnfw/pywim | [
"5d8b1ca467af80444551082588c2c713c3074e77",
"5d8b1ca467af80444551082588c2c713c3074e77"
] | [
"pywim/utils/dsp/baseline.py",
"pywim/utils/stats/iqr.py"
] | [
"\"\"\"\nNmrglue is a module for working with NMR data in Python.\nWhen used with the NumPy, SciPy, and matplotlib packages nmrglue provides a\nrobust environment for rapidly developing new methods for processing,\nanalyzing, and visualizing NMR data. Nmrglue also provides a\nframework for connecting existing NMR s... | [
[
"numpy.linspace",
"scipy.ndimage.median_filter",
"numpy.atleast_2d",
"numpy.zeros_like",
"numpy.ma.masked_array",
"scipy.signal.boxcar",
"numpy.array",
"scipy.signal.convolve",
"scipy.signal.gaussian"
],
[
"numpy.all",
"scipy.stats.scoreatpercentile"
]
] | [
{
"matplotlib": [],
"numpy": [],
"pandas": [],
"scipy": [
"0.13",
"0.14",
"0.15",
"0.10",
"0.19",
"0.18",
"0.12",
"1.0",
"0.17",
"0.16"
],
"tensorflow": []
},
{
"matplotlib": [],
"numpy": [],
"pandas": [],
"scipy... |
mkduong-ai/grAdapt | [
"94c2659b0f6ff9a2984a9dc58e3c83213313bf90"
] | [
"grAdapt/utils/math/linalg.py"
] | [
"import scipy.linalg\nimport numpy as np\n\n\ndef inv_stable(A):\n \"\"\"Inverts a quadratic matrix with non-negative eigenvalues\n Inverts using cholesky decomposition if matrix is positive semi-definite.\n If not, inverts matrix using eigenvalue decomposition.\n If eigendecomposition does not succeed ... | [
[
"numpy.diag",
"numpy.allclose",
"numpy.linalg.inv",
"numpy.linalg.eig",
"numpy.eye"
]
] | [
{
"matplotlib": [],
"numpy": [],
"pandas": [],
"scipy": [],
"tensorflow": []
}
] |
theshanky/Fingerprint-Liveness | [
"4a303cc5043e8aef1bea59b581cf2943b773b97f"
] | [
"config.py"
] | [
"# coding: utf8\nimport torch\nimport warnings\n\nclass DefaultConfig(object):\n model = 'MyMobilenet' # 使用的模型，名字必须与models/__init__.py中的名字一致\n env = model #\n ATTACK = 1\n GENUINE = 0\n # train_filelists=[\n # ['/home/shashank/Desktop/Fingerprint/dataset/colored','/home/shashank/Desktop/Fingerprint/dat... | [
[
"torch.cuda.is_available"
]
] | [
{
"matplotlib": [],
"numpy": [],
"pandas": [],
"scipy": [],
"tensorflow": []
}
] |
mikeludemann/python-data-visualization | [
"e5317505d41ae79389f6eec61cefeca1690935b0"
] | [
"src/default/slider/index.py"
] | [
"import numpy as np\nimport matplotlib.pyplot as plt\nfrom matplotlib.widgets import Slider, Button, RadioButtons\n\nfig, ax = plt.subplots()\nplt.subplots_adjust(left=0.25, bottom=0.25)\nt = np.arange(0.0, 1.0, 0.001)\na0 = 5\nf0 = 3\ndelta_f = 5.0\ns = a0 * np.sin(2 * np.pi * f0 * t)\nl, = plt.plot(t, s, lw=2)\na... | [
[
"matplotlib.widgets.Button",
"numpy.arange",
"matplotlib.pyplot.subplots",
"numpy.sin",
"matplotlib.pyplot.plot",
"matplotlib.pyplot.axes",
"matplotlib.widgets.Slider",
"matplotlib.pyplot.subplots_adjust",
"matplotlib.pyplot.show",
"matplotlib.widgets.RadioButtons"
]
] | [
{
"matplotlib": [],
"numpy": [],
"pandas": [],
"scipy": [],
"tensorflow": []
}
] |
semaphoreP/EXOSIMS | [
"9b2c25ff0bf1e6378af08a95b04c9e51ef4f1340"
] | [
"EXOSIMS/SurveySimulation/SLSQPSchedulerF.py"
] | [
"from EXOSIMS.Prototypes.SurveySimulation import SurveySimulation\nimport astropy.units as u\nimport numpy as np\nfrom ortools.linear_solver import pywraplp\nfrom scipy.optimize import minimize,minimize_scalar\nimport os\ntry:\n import cPickle as pickle\nexcept:\n import pickle\n\nclass SLSQPSchedulerF(SurveySi... | [
[
"numpy.log",
"numpy.arange",
"scipy.optimize.minimize_scalar",
"scipy.optimize.minimize",
"numpy.argmin",
"numpy.where",
"numpy.sum"
]
] | [
{
"matplotlib": [],
"numpy": [],
"pandas": [],
"scipy": [
"0.13",
"1.6",
"0.14",
"1.10",
"0.15",
"1.4",
"1.3",
"1.9",
"0.19",
"1.5",
"0.18",
"1.2",
"1.7",
"0.12",
"1.0",
"0.17",
"0.16",
"1.8"
... |
AjayThorve/cuxfilter | [
"537ff67de80439a43e0bad7373558f5e25dcb112"
] | [
"python/cuXfilter/assets/numba_kernels/gpu_histogram.py"
] | [
"import numpy as np\nfrom numba import cuda\nimport cudf\nimport numba\nimport pyarrow as pa\nimport pandas as pd\nimport io\nimport gc\nfrom typing import Type\n\nfrom ...charts.core.core_chart import BaseChart\n\n@numba.jit(nopython=True,parallel=True)\ndef compute_bin(x, n, xmin, xmax):\n '''\n description... | [
[
"numpy.asarray",
"numpy.issubdtype",
"numpy.int32",
"numpy.finfo",
"numpy.iinfo",
"numpy.float32",
"numpy.float64",
"numpy.array",
"numpy.zeros"
]
] | [
{
"matplotlib": [],
"numpy": [],
"pandas": [],
"scipy": [],
"tensorflow": []
}
] |
BiomedicalMachineLearning/HEMnet | [
"e9b49f09055f8af8f1a46e6645585eb42d296631"
] | [
"HEMnet/train.py"
] | [
"# Example command:\n# python /scratch/imb/Xiao/HEMnet/HEMnet/train.py -b /scratch/imb/Xiao/HE_test/10x/ -t train_dataset_10x_19_12_19_strict_Reinhard/tiles_10x/ -l valid_Reinhard/tiles_10x -o HEMnet_14_01_2020 -g 2 -e 10 -s -m vgg16 -a 64 -v\nimport argparse\nimport numpy as np\nimport os\nimport time\nfrom pathli... | [
[
"tensorflow.keras.preprocessing.image.ImageDataGenerator",
"numpy.unique"
]
] | [
{
"matplotlib": [],
"numpy": [],
"pandas": [],
"scipy": [],
"tensorflow": [
"1.10",
"2.7",
"2.2",
"2.3",
"2.4",
"2.5",
"2.6"
]
}
] |
mouradbelo/pytorch_connectomics | [
"bbed3a879ba2b4bcfa215eb2aba04b59533e180a"
] | [
"connectomics/data/dataset/__init__.py"
] | [
"import os,sys\nimport numpy as np\nfrom scipy.ndimage import zoom\n\nimport torch\nimport torch.nn as nn\nimport torch.utils.data\nimport torchvision.utils as vutils\n\nfrom .dataset_volume import VolumeDataset\nfrom .dataset_tile import TileDataset\nfrom ..utils import collate_fn_target, collate_fn_test, seg_wide... | [
[
"scipy.ndimage.zoom",
"numpy.array",
"torch.utils.data.DataLoader",
"numpy.pad"
]
] | [
{
"matplotlib": [],
"numpy": [],
"pandas": [],
"scipy": [
"1.7",
"1.0",
"0.10",
"1.2",
"0.14",
"0.19",
"1.5",
"0.12",
"0.17",
"0.13",
"1.6",
"1.4",
"1.9",
"1.3",
"1.10",
"0.15",
"0.18",
"0.16"... |
YyongXin/tf-mets | [
"dacd9398170f5135feb7135b635d4cc3f6869369",
"dacd9398170f5135feb7135b635d4cc3f6869369"
] | [
"machinelearning-benchmark/dl/bert/gpu_movie_reviews.py",
"benchmark/mlp/swap-module.py"
] | [
"import math\nimport datetime\nfrom tqdm import tqdm\nimport pandas as pd\nimport numpy as np\n\nimport tensorflow as tf\n\nimport bert\nfrom bert import BertModelLayer\nfrom bert.loader import StockBertConfig, map_stock_config_to_params, load_stock_weights\nfrom bert.tokenization.bert_tokenization import FullToken... | [
[
"pandas.concat",
"tensorflow.keras.metrics.SparseCategoricalAccuracy",
"tensorflow.keras.layers.Lambda",
"tensorflow.keras.losses.SparseCategoricalCrossentropy",
"tensorflow.io.gfile.GFile",
"tensorflow.keras.layers.Dense",
"tensorflow.keras.callbacks.LearningRateScheduler",
"tenso... | [
{
"matplotlib": [],
"numpy": [],
"pandas": [
"0.23",
"0.21",
"2.0",
"1.4",
"1.3",
"0.19",
"1.1",
"1.5",
"0.24",
"0.20",
"1.0",
"0.25",
"1.2"
],
"scipy": [],
"tensorflow": [
"2.7",
"2.2",
"2.3",
... |
aloctavodia/Theano-PyMC | [
"6d39faafdc3182ee232461b36ed66407b08b5c05"
] | [
"theano/tensor/basic.py"
] | [
"\"\"\"A `Type` and `Op` classes to work with numpy.ndarrays symbolically.\"\"\"\n\nimport builtins\nimport logging\nimport numbers\nimport warnings\nfrom collections.abc import Sequence\nfrom functools import partial\n\nimport numpy as np\n\nimport theano\nimport theano.scalar.sharedvar\nfrom theano import compile... | [
[
"numpy.dot",
"numpy.minimum",
"numpy.asarray",
"numpy.dtype",
"numpy.concatenate",
"numpy.max",
"numpy.all",
"numpy.mean",
"numpy.tri",
"numpy.iinfo",
"numpy.allclose",
"numpy.may_share_memory",
"numpy.reshape",
"numpy.arange",
"numpy.eye",
"numpy.ch... | [
{
"matplotlib": [],
"numpy": [],
"pandas": [],
"scipy": [],
"tensorflow": []
}
] |
jasonyuan97/angle-first-gait-recognition | [
"d99c8717cac488b858b4a2b8e26a66d6b12c2c1f"
] | [
"inference.py"
] | [
"__author__ = 'jason'\n\nimport tensorflow as tf \nimport sys\nfrom tool import NUM_PARTS\n\nINPUT_CHANNEL = 1\nCONV1_DEEP = 16\nCONV1_SIZE = 7\nCONV2_DEEP = 64\nCONV2_SIZE = 7\nCONV3_DEEP = 256\nCONV3_SIZE = 7\nDROP_RATE = 0.5\nWEIGHT_DECAY=0.0005\n\ndef weightVariable(shape, weight_decay):\n\tinit = tf.Variable(t... | [
[
"tensorflow.matmul",
"tensorflow.concat",
"tensorflow.Variable",
"tensorflow.nn.max_pool",
"tensorflow.reshape",
"tensorflow.random_normal",
"tensorflow.contrib.layers.l2_regularizer",
"tensorflow.nn.dropout",
"tensorflow.nn.local_response_normalization",
"tensorflow.nn.con... | [
{
"matplotlib": [],
"numpy": [],
"pandas": [],
"scipy": [],
"tensorflow": [
"1.10"
]
}
] |
Quiet-Clicking-Sounds/StringCalculator | [
"cd06759d214aa00b69182f42bf66e0393d127b29"
] | [
"interface/visualization.py"
] | [
"from __future__ import annotations\n\nimport tkinter as tk\nfrom tkinter import ttk\n\nfrom matplotlib.backends.backend_tkagg import FigureCanvasTkAgg\n\nfrom interface.instrument_class import Instrument\nfrom interface.visualization_plotting import plot_type_dict, plot_func_type\n\n\nclass PlotFrame(ttk.Frame):\n... | [
[
"matplotlib.backends.backend_tkagg.FigureCanvasTkAgg"
]
] | [
{
"matplotlib": [],
"numpy": [],
"pandas": [],
"scipy": [],
"tensorflow": []
}
] |
wikicoo/spot-trend-grid | [
"b631145db73e18cc35077c56c63a3bacc400d674"
] | [
"run.py"
] | [
"# -*- coding: utf-8 -*-\nfrom app.BinanceAPI import BinanceAPI\nfrom app.authorization import api_key,api_secret\nfrom data.runBetData import RunBetData\nfrom app.dingding import Message\nfrom data.calcIndex import CalcIndex\nimport time\n\nimport mplfinance as mpf\nimport matplotlib as mpl# 用于设置曲线参数\nfrom cycler ... | [
[
"pandas.to_datetime",
"pandas.read_json"
]
] | [
{
"matplotlib": [],
"numpy": [],
"pandas": [
"0.23",
"0.21",
"2.0",
"1.4",
"1.3",
"0.19",
"1.1",
"1.5",
"0.24",
"0.20",
"1.0",
"0.25",
"1.2"
],
"scipy": [],
"tensorflow": []
}
] |
AiNoTsubasa/tic-tac-toe | [
"71a1e3bbffbdc2e1a7acbc8f0f86b44c85a4071f"
] | [
"src/TicTacToe.py"
] | [
"import numpy as np\nimport random\n\nclass TicTacToe:\n def __init__(self):\n self.__O_MOVES = []\n self.__X_MOVES = []\n self.__o_player = \"human\"\n self.__x_player = \"ai\"\n self.__WIN_PATTERNS = [\n [0, 3, 6],\n [1, 4, 7],\n [2, 5, 8],\n [0, 1, 2],\n [3, 4, 5],\n ... | [
[
"numpy.array",
"numpy.setdiff1d"
]
] | [
{
"matplotlib": [],
"numpy": [],
"pandas": [],
"scipy": [],
"tensorflow": []
}
] |
sanderslab/magellanmapper | [
"16d55df6dc1f0e5baf3938a30edcdd634e0ffd85",
"16d55df6dc1f0e5baf3938a30edcdd634e0ffd85"
] | [
"magmap/stats/clustering.py",
"magmap/cv/segmenter.py"
] | [
"# Cluster measurement.\n# Author: David Young, 2019\n\"\"\"Clustering measurements.\"\"\"\n\nimport os\n\nimport numpy as np\nimport pandas as pd\nfrom sklearn import cluster\nfrom sklearn import neighbors\n\nfrom magmap.cv import chunking, detector\nfrom magmap.settings import config\nfrom magmap.io import libmag... | [
[
"numpy.amax",
"numpy.multiply",
"numpy.unique",
"numpy.median",
"numpy.save",
"numpy.percentile",
"sklearn.cluster.DBSCAN",
"numpy.argsort",
"sklearn.neighbors.NearestNeighbors",
"numpy.sum",
"numpy.divide"
],
[
"numpy.amax",
"numpy.abs",
"numpy.unique",... | [
{
"matplotlib": [],
"numpy": [],
"pandas": [],
"scipy": [],
"tensorflow": []
},
{
"matplotlib": [],
"numpy": [],
"pandas": [],
"scipy": [
"1.7",
"1.0",
"0.10",
"1.2",
"0.14",
"0.19",
"1.5",
"0.12",
"0.17",
"0.13",
... |
myelinio/SpectralNet | [
"9366942b7b98f6c2abf7159101feddbcc7c1bee5"
] | [
"src/core/pairs.py"
] | [
"\"\"\"\npairs.py: contains functions used for creating pairs from labeled and unlabeled data (currently used only for the siamese network)\n\"\"\"\n\nfrom __future__ import absolute_import\nfrom __future__ import print_function\n\nimport pickle\nimport random\nfrom collections import defaultdict\nfrom random impor... | [
[
"numpy.logical_and",
"sklearn.metrics.confusion_matrix",
"sklearn.neighbors.NearestNeighbors",
"numpy.prod",
"numpy.array",
"numpy.empty"
]
] | [
{
"matplotlib": [],
"numpy": [],
"pandas": [],
"scipy": [],
"tensorflow": []
}
] |
stjordanis/QMLT | [
"fc9487f89bf894576d2001abe5a5d07f35f19d7a"
] | [
"examples/numerical/supervised_num.py"
] | [
"#!/usr/bin/env python3\n# -*- coding: utf-8 -*-\n# Copyright 2018 Xanadu Quantum Technologies Inc.\n\n# Licensed under the Apache License, Version 2.0 (the \"License\");\n# you may not use this file except in compliance with the License.\n# You may obtain a copy of the License at\n\n# http://www.apache.org/lic... | [
[
"numpy.array"
]
] | [
{
"matplotlib": [],
"numpy": [],
"pandas": [],
"scipy": [],
"tensorflow": []
}
] |
developer0hye/AS-MLP | [
"a18569e61e1a0ffe4635ba149d5f3d19bbe74831"
] | [
"main.py"
] | [
"\nimport os\nimport time\nimport argparse\nimport datetime\nimport numpy as np\n\nimport torch\nimport torch.backends.cudnn as cudnn\nimport torch.distributed as dist\n\nfrom timm.loss import LabelSmoothingCrossEntropy, SoftTargetCrossEntropy\nfrom timm.utils import accuracy, AverageMeter\n\nfrom config import get... | [
[
"torch.nn.CrossEntropyLoss",
"torch.cuda.synchronize",
"torch.distributed.init_process_group",
"torch.cuda.set_device",
"numpy.random.seed",
"torch.manual_seed",
"torch.distributed.barrier",
"torch.cuda.max_memory_allocated",
"torch.no_grad",
"torch.distributed.get_rank",
... | [
{
"matplotlib": [],
"numpy": [],
"pandas": [],
"scipy": [],
"tensorflow": []
}
] |
juarolsal/derinkuyu | [
"fbba3e57ee43f68caf06c6f13202b0292ad47418"
] | [
"generation/MapGenerator.py"
] | [
"from argparse import Action, ArgumentParser\nfrom os.path import isdir\nfrom os import access, R_OK\nfrom logging import debug, info, warning, error, basicConfig, DEBUG, getLogger\nfrom datetime import datetime\nimport BSPTree, Cellautomata, Togetherness, BiomeRenderer\nfrom numpy import zeros\n\ndef check_range(m... | [
[
"numpy.amax"
]
] | [
{
"matplotlib": [],
"numpy": [],
"pandas": [],
"scipy": [],
"tensorflow": []
}
] |
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