repo_name stringlengths 6 130 | hexsha list | file_path list | code list | apis list |
|---|---|---|---|---|
m30m/dgl | [
"2190c39d674f76c65db9ee8da7b43d3021f19c29"
] | [
"python/dgl/backend/pytorch/tensor.py"
] | [
"from __future__ import absolute_import\n\nfrom distutils.version import LooseVersion\n\nimport scipy # Weird bug in new pytorch when import scipy after import torch\nimport torch as th\nimport builtins\nfrom torch.utils import dlpack\n\nfrom ... import ndarray as nd\nfrom ... import kernel as K\nfrom ...function.b... | [
[
"torch.cat",
"torch.stack",
"torch.ones",
"torch.narrow",
"torch.squeeze",
"torch.sparse_coo_tensor",
"torch.transpose",
"torch.exp",
"torch.reshape",
"torch.sum",
"torch.topk",
"torch.argsort",
"torch.unsqueeze",
"torch.tensor",
"torch.zeros_like",
... |
echaussidon/desispec | [
"8a8bd59653861509dd630ffc8e1cd6c67f6cdd51",
"8a8bd59653861509dd630ffc8e1cd6c67f6cdd51",
"8a8bd59653861509dd630ffc8e1cd6c67f6cdd51",
"8a8bd59653861509dd630ffc8e1cd6c67f6cdd51"
] | [
"py/desispec/pipeline/db.py",
"py/desispec/scripts/humidity_corrected_fiberflat.py",
"py/desispec/qa/qa_quicklook.py",
"py/desispec/workflow/timing.py"
] | [
"#\n# See top-level LICENSE.rst file for Copyright information\n#\n# -*- coding: utf-8 -*-\n\"\"\"\ndesispec.pipeline.db\n===========================\n\nPipeline processing database\n\"\"\"\n\nfrom __future__ import absolute_import, division, print_function\n\nimport os\n\nimport re\nfrom collections import Ordered... | [
[
"numpy.array",
"numpy.isnan",
"numpy.sum",
"numpy.where",
"numpy.unique"
],
[
"numpy.allclose",
"numpy.abs",
"numpy.isnan",
"numpy.mean"
],
[
"numpy.median",
"numpy.genfromtxt",
"numpy.mean",
"numpy.where",
"numpy.gradient",
"numpy.concatenate",
... |
IRC-SPHERE/SklearnHyperStream | [
"7799e0ea15135fe5cb2935bdd39b471c53ccf0ff"
] | [
"online_learning_plugins/sklearn/tools/dataset/2017-08-22_v0.0.1.py"
] | [
"# The MIT License (MIT)\n# Copyright (c) 2014-2017 University of Bristol\n#\n# Permission is hereby granted, free of charge, to any person obtaining a copy\n# of this software and associated documentation files (the \"Software\"), to deal\n# in the Software without restriction, including without limitation the rig... | [
[
"sklearn.model_selection.train_test_split",
"numpy.unique",
"sklearn.preprocessing.label_binarize"
]
] |
AHammoudeh/Flow_AH | [
"16c5641be3e9e85511756f75efd002478edaee9b"
] | [
"flow/visualize/time_space_diagram.py"
] | [
"\"\"\"Generate a time space diagram for some networks.\n\nThis method accepts as input a csv file containing the sumo-formatted emission\nfile, and then uses this data to generate a time-space diagram, with the x-axis\nbeing the time (in seconds), the y-axis being the position of a vehicle, and\ncolor representing... | [
[
"numpy.where",
"matplotlib.pyplot.xticks",
"numpy.concatenate",
"matplotlib.pyplot.colorbar",
"numpy.logical_and",
"matplotlib.pyplot.Normalize",
"matplotlib.colors.LinearSegmentedColormap",
"matplotlib.pyplot.axes",
"matplotlib.use",
"numpy.array",
"matplotlib.pyplot.t... |
jonassagild/Track-to-Track-Fusion | [
"6bb7fbe6a6e2d9a2713c47f211899226485eee79"
] | [
"scripts/plot_results_kf_dependence.py"
] | [
"\"\"\"plot_stuff script to plot things\n\nJust temporary code to plot things. Not for producing results, but for testing code.\n\"\"\"\nimport numpy as np\nimport scipy\nfrom stonesoup.types.state import GaussianState\nfrom matplotlib import pyplot as plt\nfrom matplotlib.patches import Ellipse\n\n\nfrom trackers.... | [
[
"numpy.argmin",
"numpy.rad2deg",
"matplotlib.pyplot.figure",
"matplotlib.patches.Ellipse",
"numpy.argmax",
"numpy.arctan2",
"numpy.sqrt",
"numpy.diag"
]
] |
gkuling/BIRADS_BERT | [
"f218d05283df90e536b210efbb4fab1d6dff082d"
] | [
"examples/MLM_Training_transformers.py"
] | [
"'''\nCopyright (c) 2020, Martel Lab, Sunnybrook Research Institute\nCodes inspired by Hugging Face Transformers package code run_mlm.py\nhttps://github.com/huggingface/transformers/blob/main/examples/pytorch/\nlanguage-modeling/run_mlm.py\n\nDescription: Training code used to train a BERT embedding in Masked Langu... | [
[
"torch.utils.data.RandomSampler",
"torch.cuda.manual_seed_all",
"numpy.random.seed",
"torch.no_grad",
"torch.utils.data.SequentialSampler",
"torch.cuda.device_count",
"torch.manual_seed",
"torch.cuda.is_available",
"torch.tensor",
"torch.utils.data.DataLoader",
"torch.n... |
PurplePean/AIX360 | [
"0a71cfe372b91078dd7887d7597371e09d84f968",
"4037d6347c40405f342b07da5d341fcd21081cfa"
] | [
"aix360/data/ted_data/GenerateData.py",
"tests/rbm/test_Logistic_Rule_Regression.py"
] | [
"# This file will generate a synthetic dataset to predict employee attrition\r\n# Like most datasets it will have a feature vector and a Y label for each instance.\r\n# However, unlike most datasets it will also have an Explanation (E) for each instance, encoded as an non-negative integer.\r\n# This is motivated by... | [
[
"pandas.DataFrame"
],
[
"numpy.array",
"pandas.util.testing.assert_frame_equal",
"sklearn.datasets.load_breast_cancer",
"pandas.DataFrame",
"sklearn.metrics.accuracy_score",
"sklearn.model_selection.train_test_split",
"sklearn.metrics.precision_score",
"sklearn.metrics.f1_s... |
asadziach/CarND-Semantic-Segmentation | [
"c3431ab5dc3878b82bfc66e7384005f7a93fcb16"
] | [
"main.py"
] | [
"import os.path\nimport tensorflow as tf\nimport helper\nimport ImageProcessor\nimport warnings\nfrom distutils.version import LooseVersion\nimport project_tests as tests\nimport scipy.misc\nfrom glob import glob\nfrom moviepy.editor import VideoFileClip\nimport time\nimport timeit\n\n# Check TensorFlow Version\nas... | [
[
"tensorflow.nn.softmax_cross_entropy_with_logits",
"tensorflow.reshape",
"tensorflow.nn.softmax",
"tensorflow.local_variables_initializer",
"tensorflow.global_variables_initializer",
"tensorflow.train.latest_checkpoint",
"tensorflow.get_default_graph",
"tensorflow.argmax",
"ten... |
huilin16/PaddleRS | [
"ca0d6223d8e56cd3bd3cbd3a033c89f1718ce26a",
"b6f7033f3c0ca7bc6952456c0a0f53eef6c1c07f"
] | [
"tools/mask2geojson.py",
"paddlers/models/ppdet/utils/colormap.py"
] | [
"# Copyright (c) 2022 PaddlePaddle Authors. All Rights Reserved.\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#... | [
[
"numpy.zeros_like",
"numpy.unique"
],
[
"numpy.array"
]
] |
Lufeifeina/models | [
"d7d260d4c690e5163070e21d75df372ab559ea23",
"d7d260d4c690e5163070e21d75df372ab559ea23",
"d7d260d4c690e5163070e21d75df372ab559ea23",
"d7d260d4c690e5163070e21d75df372ab559ea23"
] | [
"official/core/train_lib.py",
"official/vision/tasks/maskrcnn.py",
"official/nlp/modeling/layers/reuse_transformer.py",
"official/vision/modeling/backbones/resnet_deeplab_test.py"
] | [
"# Copyright 2022 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.train.CheckpointManager"
],
[
"tensorflow.keras.metrics.Mean",
"tensorflow.shape",
"tensorflow.train.latest_checkpoint",
"tensorflow.GradientTape",
"tensorflow.distribute.get_strategy",
"tensorflow.reduce_any",
"tensorflow.io.gfile.isdir",
"tensorflow.cast",
... |
szabi-luxonis/openvino | [
"c8dd831fc3ba68a256ab47edb4f6bf3cb5e804be"
] | [
"model-optimizer/extensions/middle/UpsampleToResample.py"
] | [
"\"\"\"\n Copyright (C) 2018-2020 Intel Corporation\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 required by applicable... | [
[
"numpy.array"
]
] |
Pandinosaurus/gala | [
"975ed783a6cb3c0afe24a921afdacf2f27184fcf",
"975ed783a6cb3c0afe24a921afdacf2f27184fcf"
] | [
"tests/test_watershed.py",
"gala/imio.py"
] | [
"import os\nimport time\nimport numpy as np\nfrom scipy import ndimage as nd\nfrom numpy.testing import assert_array_equal, assert_array_less\n\nfrom gala import morpho\n\nrundir = os.path.dirname(__file__)\n\ndef time_me(function):\n def wrapped(*args, **kwargs):\n start = time.time()\n r = functi... | [
[
"numpy.array",
"numpy.testing.run_module_suite",
"scipy.ndimage.label",
"numpy.testing.assert_array_equal",
"numpy.ones",
"numpy.testing.assert_array_less",
"numpy.loadtxt"
],
[
"numpy.concatenate",
"numpy.max",
"numpy.array",
"numpy.zeros_like",
"numpy.uint8",
... |
xiangruhuang/OpenPCDet | [
"d82d9594a0629ffed0c457aedc304e0805e93221",
"d82d9594a0629ffed0c457aedc304e0805e93221"
] | [
"pcdet/models/backbones_3d/pfe/voxel_set_abstraction.py",
"pcdet/ops/torch_hash/test_torch_hash.py"
] | [
"import math\nimport numpy as np\nimport torch\nimport torch.nn as nn\n\nfrom ....ops.pointnet2.pointnet2_stack import pointnet2_modules as pointnet2_stack_modules\nfrom ....ops.pointnet2.pointnet2_stack import pointnet2_utils as pointnet2_stack_utils\nfrom ....utils import common_utils\n\n\ndef bilinear_interpolat... | [
[
"torch.zeros",
"torch.nn.Linear",
"torch.cat",
"torch.nn.ModuleList",
"torch.clamp",
"torch.nn.ReLU",
"torch.nn.BatchNorm1d",
"torch.tensor",
"torch.t",
"torch.floor",
"torch.atan2"
],
[
"torch.randint",
"torch.randn"
]
] |
dxs/neighbour-analyser | [
"609c220b1352f9c3e64ea96ff43007584712efb0"
] | [
"testing/car_record.py"
] | [
"import cv2 as cv\nimport argparse\nimport sys\nimport numpy as np \nimport os.path \n\n#set constants\nFRONT_CAMERA = 1\nBACK_CAMERA = 0\ni = 0\n\nconfThreshold = 0.5 #Confidence threshold\nnmsThreshold = 0.4 #Non-maximum suppression threshold\ninpWidth = 416 #Width of network's input image\ninpHeight = 416 #Hei... | [
[
"numpy.argmax"
]
] |
Thomas-Schatz/scone-phobia | [
"55577d150ff71fd1f1c52073143c64e242b28600"
] | [
"scone_phobia/utils/apply_analyses.py"
] | [
"# -*- coding: utf-8 -*-\n\"\"\"\nCreated on Wed Jun 20 10:59:28 2018\n\n@author: Thomas Schatz\n\nCode for managing the analysis of a set of ABXpy minimal-pair scores \nfor ABX tasks with the following structure:\n ON phone BY speaker, previous and following phonetic context)\n\nThe main function is apply_analysi... | [
[
"pandas.concat"
]
] |
mwittgen/rogue | [
"4be0e9a4d17bdd3987a268f54ad195ee1093190d"
] | [
"tests/test_list_memory.py"
] | [
"#!/usr/bin/env python3\n#-----------------------------------------------------------------------------\n# This file is part of the rogue software platform. It is subject to\n# the license terms in the LICENSE.txt file found in the top-level directory\n# of this distribution and at:\n# https://confluence.slac.st... | [
[
"numpy.array"
]
] |
event-driven-robotics/models | [
"a8b6e2a83d4842eb99878d3fa53cd92f4c6b3db8"
] | [
"nxsdk_modules_ncl/dnn/composable/composable_dnn.py"
] | [
"# \n# Copyright © 2020 Intel Corporation.\n# \n# This software and the related documents are Intel copyrighted\n# materials, and your use of them is governed by the express \n# license under which they were provided to you (License). Unless\n# the License provides otherwise, you may not use, modify, copy, \n# publ... | [
[
"numpy.zeros_like",
"numpy.prod",
"numpy.unique"
]
] |
sixhobbits/prefect | [
"bf7a6b95ab592ad4808415f295163a64e38f1419"
] | [
"src/prefect/engine/serializers.py"
] | [
"import base64\nimport bz2\nimport gzip\nimport io\nimport json\nimport lzma\nfrom typing import TYPE_CHECKING, Any, Callable, Dict, Tuple\nimport zlib\n\nimport cloudpickle\nimport pendulum\n\nif TYPE_CHECKING:\n import pandas as pd\n\n__all__ = (\n \"Serializer\",\n \"PickleSerializer\",\n \"JSONSeria... | [
[
"pandas.DataFrame"
]
] |
seekindark/helloworld | [
"00fe439fdbd98add53f3bec7eac2b1ba1dc817a7"
] | [
"python/matplotlib/ee.py"
] | [
"import matplotlib.pyplot as plt\r\nx = [1, 2, 3, 4, 5]\r\ny = [2.3, 3.4, 1.2, 6.6, 7.0]\r\nplt.scatter(x, y, color='r', marker='+')\r\nplt.show()"
] | [
[
"matplotlib.pyplot.scatter",
"matplotlib.pyplot.show"
]
] |
Adib234/AugLy | [
"35a6a5de07e64f465b8979e3257218551929e57a"
] | [
"augly/video/helpers/ffmpeg.py"
] | [
"#!/usr/bin/env python3\n# Copyright (c) Facebook, Inc. and its affiliates.\n\nimport io\nimport math\nimport os\nimport shutil\nfrom typing import Any, Dict, Optional, Union\n\nimport augly.audio.utils as audutils\nimport ffmpeg\nimport numpy as np\nfrom augly.utils import pathmgr, SILENT_AUDIO_PATH\nfrom augly.ut... | [
[
"numpy.frombuffer"
]
] |
ueshin/mars | [
"0b542974243be4e0ff239eaf49ab0fb2935f3361",
"0b542974243be4e0ff239eaf49ab0fb2935f3361",
"0b542974243be4e0ff239eaf49ab0fb2935f3361",
"0b542974243be4e0ff239eaf49ab0fb2935f3361"
] | [
"mars/lib/sparse/matrix.py",
"mars/dataframe/arithmetic/tests/test_arithmetic.py",
"mars/learn/decomposition/pca.py",
"mars/learn/neighbors/tests/test_nearest_neighbors.py"
] | [
"#!/usr/bin/env python\n# -*- coding: utf-8 -*-\n# Copyright 1999-2020 Alibaba Group Holding Ltd.\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/li... | [
[
"numpy.arange",
"numpy.dtype"
],
[
"numpy.random.rand",
"pandas.Int64Index",
"pandas.RangeIndex",
"pandas.testing.assert_series_equal",
"numpy.arange",
"numpy.random.randint",
"pandas.concat",
"numpy.random.bytes"
],
[
"scipy.special.gammaln",
"sklearn.utils... |
iwangjian/ByteCup2018 | [
"348bdee3215c146ef7d6e4fe1fecbe4598798c8a",
"348bdee3215c146ef7d6e4fe1fecbe4598798c8a"
] | [
"model/dropout.py",
"model/copy_summ.py"
] | [
"import torch\nimport torch.nn as nn\nfrom torch.autograd import Variable\n\n\nclass LockedDropout(nn.Module):\n def __init__(self):\n super().__init__()\n\n def forward(self, x, dropout=0.5, seq_lens=None):\n if not self.training or not dropout:\n return x\n if seq_lens == Non... | [
[
"torch.autograd.Variable",
"torch.nn.functional.dropout",
"torch.nn.Parameter",
"torch.nn.utils.rnn.pad_packed_sequence",
"torch.nn.utils.rnn.pack_padded_sequence"
],
[
"torch.zeros",
"torch.cat",
"torch.stack",
"torch.autograd.Variable",
"torch.mm",
"torch.matmul",... |
kkelchte/pilot | [
"e3c3b753351efac30323af57465abe360973653a"
] | [
"pilot/models/alex_net_v4.py"
] | [
"\"\"\"\nVersion of Alexnet with smaller input size and less weights\n\"\"\"\n\nimport tensorflow as tf\nimport numpy as np\n\n# input downscaled to 128x128x1\ndef alexnet(inputs,\n num_outputs=1,\n dropout_rate=0,\n reuse=None,\n is_training=False,\n verbose=F... | [
[
"tensorflow.layers.dropout",
"tensorflow.nn.relu",
"tensorflow.contrib.layers.xavier_initializer",
"tensorflow.layers.max_pooling2d",
"tensorflow.layers.batch_normalization",
"tensorflow.reshape",
"tensorflow.squeeze"
]
] |
goldnimrod/IML.HUJI | [
"4fe39f597e1fc9eb188ca12daa2b3111bae92ee9",
"4fe39f597e1fc9eb188ca12daa2b3111bae92ee9"
] | [
"IMLearn/learners/classifiers/decision_stump.py",
"IMLearn/learners/classifiers/gaussian_naive_bayes.py"
] | [
"from __future__ import annotations\nfrom typing import Tuple, NoReturn\nfrom ...base import BaseEstimator\nimport numpy as np\nfrom ...metrics import misclassification_error\nfrom itertools import product\n\n\nclass DecisionStump(BaseEstimator):\n \"\"\"\n A decision stump classifier for {-1,1} labels accord... | [
[
"numpy.vectorize",
"numpy.argmin",
"numpy.ones",
"numpy.where",
"numpy.sign",
"numpy.arange",
"numpy.abs"
],
[
"numpy.array",
"numpy.count_nonzero",
"numpy.log",
"numpy.linalg.det",
"numpy.where",
"numpy.apply_along_axis",
"numpy.argmax",
"numpy.inv"... |
dataubc/number_-of_clicks_prediction | [
"738c2e15dc627b247ad5692ab80d3713fe5c8f3e"
] | [
"xgboost_model.py"
] | [
"import pandas as pd\nimport numpy as np\nimport xgboost\n\n# reading data\nhotel_data = pd.read_csv('cleaned_train.csv')\nX = hotel_data.drop(columns=['n_clicks', 'hotel_id'])\n# let's also add the new feature avg_saving_cash\nX['avg_saving_cash'] = X['avg_price'] * X['avg_saving_percent']\ny = hotel_data['n_click... | [
[
"numpy.where",
"pandas.read_csv"
]
] |
PacktPublishing/Machine-Learning-Algorithms-Second-Edition | [
"b25d3607e9d5cc388bcf5f1a029bae39bb2b837b"
] | [
"Chapter10/birch.py"
] | [
"from __future__ import print_function\n\nimport numpy as np\nimport matplotlib.pyplot as plt\n\nfrom sklearn.datasets import make_blobs\nfrom sklearn.cluster import Birch\nfrom sklearn.metrics import adjusted_rand_score\n\n\n# Set random seed for reproducibility\nnp.random.seed(1000)\n\n\nnb_samples = 2000\nbatch_... | [
[
"sklearn.datasets.make_blobs",
"numpy.random.seed",
"sklearn.cluster.Birch",
"matplotlib.pyplot.subplots",
"matplotlib.pyplot.show"
]
] |
rniranjan93/tensorflow | [
"2d22f93b04cd137d2480528a80b45ea5306ca9b3"
] | [
"tensorflow/python/compat/compat.py"
] | [
"# Copyright 2018 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.python.platform.tf_logging.warning",
"tensorflow.python.util.tf_export.tf_export"
]
] |
quantify-os/quantify-scheduler | [
"9dee17ca9345560b998b52f956c23b79a9ab287f"
] | [
"tests/scheduler/test_waveforms.py"
] | [
"# pylint: disable=missing-function-docstring\n\n\nimport numpy as np\nimport numpy.testing as npt\nimport pytest\nfrom quantify_scheduler.waveforms import (\n square,\n drag,\n staircase,\n modulate_wave,\n rotate_wave,\n)\n\n\ndef test_square_wave():\n amped_sq = square(np.arange(50), 2.44)\n ... | [
[
"numpy.max",
"numpy.array",
"numpy.sin",
"numpy.zeros",
"numpy.testing.assert_array_equal",
"numpy.ones",
"numpy.exp",
"numpy.mean",
"numpy.testing.assert_array_almost_equal",
"numpy.arange",
"numpy.linspace"
]
] |
surchs/lab-documentation | [
"9d71a4710b66da5341e7c3c67108d175f8a9fe0d"
] | [
"source/tutorials/files/mnist.py"
] | [
"import tensorflow as tf\n\n(x_train, y_train), (x_test, y_test) = tf.keras.datasets.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.Conv2D(filters=16, kernel_size=(3, 3), activation='relu'),\n tf.keras.layers.MaxPool2D(),\n t... | [
[
"tensorflow.keras.layers.Flatten",
"tensorflow.keras.layers.MaxPool2D",
"tensorflow.keras.layers.Dense",
"tensorflow.keras.layers.Conv2D",
"tensorflow.keras.losses.SparseCategoricalCrossentropy",
"tensorflow.keras.datasets.cifar10.load_data"
]
] |
kahilah/hpc-python | [
"5d2efa08076ed2706c81ca255c7e4574c937557c"
] | [
"demos/mpi-collective.py"
] | [
"from mpi4py import MPI\nfrom numpy import arange, empty\n\ncomm = MPI.COMM_WORLD\nrank = comm.Get_rank()\nsize = comm.Get_size()\n\nn = 10\ndata = empty(n, float)\nif rank == 0:\n data = arange(n, dtype=float)\n\ncomm.Bcast(data, 0)\n\nif rank == 1:\n print(\"Received: \" + str(data))\n\n"
] | [
[
"numpy.arange",
"numpy.empty"
]
] |
yangyuethz/qutip | [
"7f5682b5edfd4c906b2e89f69cf0a8be4bfd529b",
"7f5682b5edfd4c906b2e89f69cf0a8be4bfd529b"
] | [
"qutip/propagator.py",
"qutip/tests/test_qobjevo.py"
] | [
"# This file is part of QuTiP: Quantum Toolbox in Python.\n#\n# Copyright (c) 2011 and later, Paul D. Nation and Robert J. Johansson.\n# All rights reserved.\n#\n# Redistribution and use in source and binary forms, with or without\n# modification, are permitted provided that the following conditions are... | [
[
"scipy.sparse.coo_matrix",
"numpy.zeros_like",
"numpy.ones_like",
"numpy.argmin",
"numpy.unravel_index",
"numpy.sqrt",
"numpy.abs",
"scipy.sparse.csr_matrix"
],
[
"numpy.testing.assert_allclose",
"numpy.sin",
"numpy.array",
"numpy.random.rand",
"numpy.testin... |
dfarrow0/flu-contest | [
"8356cf48910a76d2643d105651342288076a9377"
] | [
"src/epicast/fc_epicast_analysis.py"
] | [
"from statistics import median_low\nimport mysql.connector\nimport numpy as np\nimport scipy.stats\nfrom ..forecasters.fc_abstract import Forecaster\nfrom delphi.epidata.client.delphi_epidata import Epidata\nimport delphi.operations.secrets as secrets\nimport delphi.utils.epiweek as flu\nfrom ..utils.forecast_type ... | [
[
"numpy.median",
"numpy.std",
"numpy.array"
]
] |
C3RV1/LaytonEditor | [
"51e1a9a372a8acdaa4183ae008235a721dc56cdc"
] | [
"formats/sound/sample_transform.py"
] | [
"import math\nimport numpy as np\n\n\ndef change_sample_rate(buffer: np.ndarray, current, target) -> np.ndarray:\n shape = [0, 0]\n shape[0] = buffer.shape[0]\n\n # RATEo = SAMPLESo\n # RATEm = (SAMPLESo / RATEo) * RATEm\n extend = target / current\n shape[1] = int(math.ceil(buffer.shape[1] * exte... | [
[
"numpy.ndarray",
"numpy.zeros"
]
] |
sunmengnan/city_brain | [
"478f0b974f4491b4201956f37b83ce6860712bc8"
] | [
"algorithms/02-edge-subdivision/osmnx_hz/district.py"
] | [
"import pandas as pd\nimport osmnx\nimport numpy as np\n\nfix = {'西湖区,杭州市,浙江省,中国': 2}\ncity_query = [\n '杭州市,浙江省,中国',\n]\ndistrict_query = [\n '上城区,杭州市,浙江省,中国',\n '下城区,杭州市,浙江省,中国',\n '江干区,杭州市,浙江省,中国',\n '西湖区,杭州市,浙江省,中国',\n '拱墅区,杭州市,浙江省,中国',\n '滨江区,杭州市,浙江省,中国',\n]\n\n\ndef query_str_to_dic(query... | [
[
"pandas.DataFrame"
]
] |
shun60s/impulse-response | [
"4bdf8ef671ed0b55afd452a12b43f6fde6cdf3ac"
] | [
"ola_convolve.py"
] | [
"#coding:utf-8\r\n\r\n# overlap-add convolve with impulse response waveform\r\n\r\n\r\nimport sys\r\nimport os\r\nimport argparse\r\nimport numpy as np\r\nfrom scipy import signal\r\nfrom scipy.io.wavfile import read as wavread\r\nfrom scipy.io.wavfile import write as wavwrite\r\n\r\n# Check version\r\n# Python 3.... | [
[
"numpy.array",
"scipy.io.wavfile.read",
"numpy.abs",
"scipy.signal.oaconvolve",
"numpy.hstack",
"numpy.iinfo",
"numpy.average"
]
] |
erikolofsson/scrypted | [
"39016a617464003cac13719a426eefcc2421e51a"
] | [
"plugins/opencv/src/opencv/__init__.py"
] | [
"from __future__ import annotations\nfrom time import sleep\nfrom detect import DetectionSession, DetectPlugin\nfrom typing import Any, List\nimport numpy as np\nimport cv2\nimport imutils\nfrom gi.repository import GLib, Gst\nfrom scrypted_sdk.types import ObjectDetectionModel, ObjectDetectionResult, ObjectsDetect... | [
[
"numpy.ndarray",
"numpy.floor"
]
] |
tbhuwan14/ga-learner-dsb-repo | [
"1d2271037214e6203a0ff92bae75aff32964263e"
] | [
"Banking-Inference/code.py"
] | [
"# --------------\nimport pandas as pd\r\nimport scipy.stats as stats\r\nimport math\r\nimport numpy as np\r\nimport warnings\r\n\r\nwarnings.filterwarnings('ignore')\r\n#Sample_Size\r\nsample_size=2000\r\n\r\n#Z_Critical Score\r\nz_critical = stats.norm.ppf(q = 0.95) \r\n\r\n\r\n# path [File location varia... | [
[
"numpy.array",
"scipy.stats.norm.ppf",
"matplotlib.pyplot.subplots",
"scipy.stats.chi2_contingency",
"pandas.Series",
"matplotlib.pyplot.show",
"pandas.read_csv",
"scipy.stats.chi2.ppf"
]
] |
And1210/SRGAN | [
"200731d6249c674d0ed556ba287ad7a7698f88b5"
] | [
"datasets/Pedestron_dataset.py"
] | [
"import os\n\nimport cv2\nimport numpy as np\nimport pandas as pd\nfrom torchvision.transforms import transforms\nfrom torch.utils.data import Dataset\nfrom datasets.base_dataset import BaseDataset\nfrom utils.augmenters.augment import seg\nimport xml.etree.ElementTree as ET\nfrom PIL import Image\nimport matplotli... | [
[
"numpy.dstack",
"numpy.asarray"
]
] |
ORNL-BSEC/morph-net | [
"eb1a493ca07ba4992af1f91ab3b73a6c4fb9cca8"
] | [
"morph_net/network_regularizers/cost_calculator.py"
] | [
"\"\"\"CostCalculator that computes network cost or regularization loss.\"\"\"\n\nfrom __future__ import absolute_import\nfrom __future__ import division\nfrom __future__ import print_function\n\nimport tensorflow as tf\n\n\nCONV2D_OPS = ('Conv2D', 'Conv2DBackpropInput', 'DepthwiseConv2dNative')\nFLOP_OPS = CONV2D_... | [
[
"tensorflow.logging.info",
"tensorflow.constant",
"tensorflow.reduce_sum",
"tensorflow.logging.warning",
"tensorflow.cast"
]
] |
timwillhack/dm-haikuBah2 | [
"b76a3db3a39b82c8a1ae5a81a8a0173c23c252e5"
] | [
"haiku/_src/layer_norm_test.py"
] | [
"# Copyright 2019 DeepMind Technologies Limited. 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# Unle... | [
[
"numpy.full",
"numpy.random.normal",
"numpy.nditer",
"numpy.testing.assert_array_equal",
"numpy.ones",
"numpy.random.uniform"
]
] |
unbun/snake.ai | [
"0c017357608dc7c06af0ca3ca57d870641461207",
"0c017357608dc7c06af0ca3ca57d870641461207",
"0c017357608dc7c06af0ca3ca57d870641461207",
"0c017357608dc7c06af0ca3ca57d870641461207",
"0c017357608dc7c06af0ca3ca57d870641461207"
] | [
"venv/Lib/site-packages/scipy/fftpack/tests/test_basic.py",
"venv/Lib/site-packages/numpy/core/tests/test_indexing.py",
"venv/Lib/site-packages/scipy/interpolate/interpolate.py",
"venv/Lib/site-packages/numpy/distutils/tests/test_system_info.py",
"venv/Lib/site-packages/numpy/core/records.py"
] | [
"# Created by Pearu Peterson, September 2002\n\nfrom __future__ import division, print_function, absolute_import\n\n__usage__ = \"\"\"\nBuild fftpack:\n python setup_fftpack.py build\nRun tests if scipy is installed:\n python -c 'import scipy;scipy.fftpack.test()'\nRun tests if fftpack is not installed:\n python... | [
[
"numpy.random.rand",
"numpy.exp",
"numpy.fft.fft",
"numpy.issubdtype",
"numpy.dtype",
"numpy.linalg.norm",
"scipy.fftpack.fftn",
"numpy.take",
"numpy.testing.assert_array_almost_equal",
"scipy.fftpack.fft",
"numpy.arange",
"numpy.swapaxes",
"scipy.fftpack.fft2",... |
snowcoding/justice40-tool | [
"b6a6813bb5d617abf400cafc97da891618541558"
] | [
"data/data-pipeline/data_pipeline/etl/sources/michigan_ejscreen/etl.py"
] | [
"import pandas as pd\n\nfrom data_pipeline.etl.base import ExtractTransformLoad\nfrom data_pipeline.utils import get_module_logger\nfrom data_pipeline.score import field_names\nfrom data_pipeline.config import settings\n\nlogger = get_module_logger(__name__)\n\n\nclass MichiganEnviroScreenETL(ExtractTransformLoad):... | [
[
"pandas.read_csv"
]
] |
jiwoncpark/lens-classification | [
"c1faf4dbbd4a16f2df74a34fd593ec7128750252"
] | [
"magnificat/drw_dataset.py"
] | [
"import os\nimport os.path as osp\nimport numpy as np\nimport torch\nfrom torch.utils.data import Dataset\nfrom tqdm import tqdm\nfrom torch.utils.data import DataLoader\nfrom magnificat import drw_utils\nfrom magnificat.cadence import LSSTCadence\n\n\nclass DRWDataset(Dataset):\n\n bp_to_int = dict(zip(list('ug... | [
[
"numpy.array",
"torch.arange",
"numpy.random.seed",
"numpy.random.randn",
"torch.log10",
"torch.from_numpy",
"torch.ones",
"torch.tensor",
"numpy.arange",
"torch.utils.data.DataLoader"
]
] |
jld23/sasoptpy | [
"f96911f04d6c0c01fce902f1f995935583df69a8"
] | [
"examples/client_side/decentralization.py"
] | [
"import sasoptpy as so\nimport pandas as pd\n\n\ndef test(cas_conn):\n\n m = so.Model(name='decentralization', session=cas_conn)\n\n DEPTS = ['A', 'B', 'C', 'D', 'E']\n CITIES = ['Bristol', 'Brighton', 'London']\n\n benefit_data = pd.DataFrame([\n ['Bristol', 10, 15, 10, 20, 5],\n ['Bright... | [
[
"pandas.DataFrame"
]
] |
kingsj0405/Explorable-Super-Resolution | [
"6582477ec1e2b0c6f4bd781552ac880fabdb4496"
] | [
"codes/models/modules/architecture.py"
] | [
"import math\nimport torch\nimport torch.nn as nn\nimport torch.nn.init as init\nimport torchvision\nfrom . import block as B\nfrom . import spectral_norm as SN\nimport functools\nimport numpy as np\nimport os\nimport models.modules.archs_util as arch_util\nimport torch.nn.functional as F\nimport re\n\n############... | [
[
"torch.nn.Linear",
"torch.cat",
"torch.nn.ModuleList",
"torch.nn.LeakyReLU",
"torch.nn.BatchNorm2d",
"torch.nn.init.kaiming_normal_",
"torch.load",
"matplotlib.pyplot.colorbar",
"torch.nn.LayerNorm",
"torch.nn.MaxPool2d",
"torch.nn.init.constant_",
"matplotlib.pyplo... |
L-Net-1992/TensorRT | [
"34b664d404001bd724cb56b52a6e0e05e1fd97f2",
"34b664d404001bd724cb56b52a6e0e05e1fd97f2"
] | [
"samples/python/network_api_pytorch_mnist/model.py",
"samples/python/efficientdet/create_onnx.py"
] | [
"#\n# SPDX-FileCopyrightText: Copyright (c) 1993-2022 NVIDIA CORPORATION & AFFILIATES. All rights reserved.\n# SPDX-License-Identifier: Apache-2.0\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 t... | [
[
"torch.nn.Linear",
"torch.autograd.Variable",
"torch.no_grad",
"torch.nn.functional.log_softmax",
"torch.nn.Conv2d",
"torch.nn.functional.nll_loss"
],
[
"numpy.concatenate",
"numpy.asarray",
"tensorflow.Graph",
"tensorflow.import_graph_def",
"numpy.squeeze"
]
] |
mlweilert/bpnet | [
"dcc9e8d805f9de774ae9dcc62c20504915be614f",
"dcc9e8d805f9de774ae9dcc62c20504915be614f",
"dcc9e8d805f9de774ae9dcc62c20504915be614f"
] | [
"bpnet/samplers.py",
"bpnet/data.py",
"bpnet/metrics.py"
] | [
"\"\"\"\nModule implementing different samplers for the chipnexus data\n\"\"\"\nimport pandas as pd\nimport numpy as np\nfrom kipoi_utils.external.torch.sampler import Sampler\nfrom kipoi_utils.data_utils import iterable_cycle\nimport warnings\nimport gin\n\n\ndef get_batch_sizes(p_vec, batch_size, verbose=True):\n... | [
[
"numpy.round",
"numpy.array",
"numpy.random.permutation",
"pandas.Series"
],
[
"numpy.arange"
],
[
"scipy.stats.pearsonr",
"numpy.apply_along_axis",
"sklearn.metrics.average_precision_score",
"numpy.unique",
"sklearn.metrics.f1_score",
"sklearn.metrics.accuracy_... |
ankitdipto/sumo-rl | [
"70d75d463fa09d0ecfc10589b66955c22c8df41b"
] | [
"sumo_rl/environment/env.py"
] | [
"import os\nimport sys\nfrom pathlib import Path\nfrom typing import Optional, Union, Tuple\nimport sumo_rl\nif 'SUMO_HOME' in os.environ:\n tools = os.path.join(os.environ['SUMO_HOME'], 'tools')\n sys.path.append(tools)\nelse:\n sys.exit(\"Please declare the environment variable 'SUMO_HOME'\")\nimport tra... | [
[
"pandas.DataFrame",
"numpy.array",
"numpy.where"
]
] |
nick-parker/trimesh | [
"a7bc1e0489ec98e3a3516088a7e64c8beca8b41a"
] | [
"trimesh/remesh.py"
] | [
"\"\"\"\nremesh.py\n-------------\n\nDeal with re- triangulation of existing meshes.\n\"\"\"\n\nimport numpy as np\n\nimport collections\n\nfrom . import util\nfrom . import grouping\n\n\ndef subdivide(vertices, faces, face_index=None):\n \"\"\"\n Subdivide a mesh into smaller triangles.\n\n Parameters\n ... | [
[
"numpy.logical_not",
"numpy.diff",
"numpy.column_stack",
"numpy.asanyarray",
"numpy.vstack"
]
] |
Murat-Karadag/nlu | [
"6a2b5995ea543e63c40baaca1bf9ad8a9db36757"
] | [
"nlu/pipe/viz/streamlit_viz/viz_building_blocks/word_similarity.py"
] | [
"import nlu\nfrom nlu.discovery import Discoverer\nfrom nlu.pipe.utils.storage_ref_utils import StorageRefUtils\nfrom typing import List, Tuple, Optional, Dict, Union\nimport streamlit as st\nfrom nlu.utils.modelhub.modelhub_utils import ModelHubUtils\n\nimport numpy as np\nimport pandas as pd\nfrom nlu.pipe.viz.st... | [
[
"numpy.array",
"numpy.linalg.norm",
"pandas.DataFrame",
"numpy.sum",
"sklearn.metrics.pairwise.distance_metrics"
]
] |
joannetruong/habitat-api | [
"aad2fd7b8545dce44daefd4b7b3941672eb96ee3",
"aad2fd7b8545dce44daefd4b7b3941672eb96ee3"
] | [
"evaluation/evaluate_simulation_coda_gan.py",
"test/test_pyrobot.py"
] | [
"import matplotlib.pyplot as plt\nimport argparse\nimport os\nfrom collections import defaultdict\n\nimport habitat\nimport numpy as np\nimport quaternion\nimport torch\nfrom evaluate_reality import load_model\nfrom gym.spaces.dict_space import Dict as SpaceDict\nfrom habitat.tasks.utils import cartesian_to_polar\n... | [
[
"torch.zeros",
"torch.device",
"numpy.sin",
"numpy.array",
"numpy.savetxt",
"numpy.zeros",
"torch.no_grad",
"numpy.save",
"numpy.diff",
"torch.cuda.is_available",
"torch.tensor",
"numpy.subtract",
"numpy.cos",
"numpy.squeeze",
"numpy.vstack"
],
[
... |
casperg92/MaSIF_colab | [
"f030061276cc21b812bb3be652124b75dcdf7e5b"
] | [
"data.py"
] | [
"import torch\nfrom torch_geometric.data import InMemoryDataset, Data, DataLoader\nfrom torch_geometric.transforms import Compose\nimport numpy as np\nfrom scipy.spatial.transform import Rotation\nimport math\nimport urllib.request\nimport tarfile\nfrom pathlib import Path\nimport requests\nfrom data_preprocessing.... | [
[
"torch.stack",
"torch.save",
"numpy.load",
"torch.clamp",
"numpy.save",
"scipy.spatial.transform.Rotation.random",
"torch.load",
"torch.matmul",
"torch.mean",
"torch.sum"
]
] |
DaoiestFire/self-supervised-learning-of-object-movement | [
"4db59bf352efd946661feffc7afc4630c6731852"
] | [
"data/datasets.py"
] | [
"import os\r\nimport glob\r\nimport random\r\n\r\nimport numpy as np\r\nimport pandas as pd\r\nfrom imageio import mimread\r\nfrom skimage.color import gray2rgb\r\nfrom skimage import io, img_as_float32\r\nfrom sklearn.model_selection import train_test_split\r\n\r\nfrom torch.utils.data import Dataset\r\nfrom data.... | [
[
"numpy.array",
"numpy.random.choice",
"numpy.random.seed",
"sklearn.model_selection.train_test_split",
"numpy.moveaxis",
"pandas.read_csv"
]
] |
liuhanyao98/nums_gpu_draft | [
"48df59afe605f02ea2bd609c5f9e0006fbc27a5d"
] | [
"nums/core/array/application.py"
] | [
"# coding=utf-8\n# Copyright (C) 2020 NumS Development 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# Unless requir... | [
[
"numpy.product",
"numpy.zeros_like",
"numpy.array",
"numpy.__getattribute__",
"numpy.ceil",
"numpy.ones_like",
"numpy.sum",
"numpy.exp",
"numpy.eye",
"numpy.diff",
"numpy.finfo",
"numpy.argmax",
"numpy.iinfo",
"numpy.dtype",
"numpy.floor"
]
] |
caglasozen/wilds | [
"db2ff095304891244962509459ee48e2fc5fd5e6",
"db2ff095304891244962509459ee48e2fc5fd5e6",
"db2ff095304891244962509459ee48e2fc5fd5e6"
] | [
"examples/pretraining/swav/src/logger.py",
"wilds/common/data_loaders.py",
"wilds/datasets/waterbirds_dataset.py"
] | [
"# Copyright (c) Facebook, Inc. and its affiliates.\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\nimport os\nimport logging\nimport time\nfrom datetime import timedelta\nimport pandas as pd\n\n\nclass LogFor... | [
[
"pandas.read_pickle",
"pandas.DataFrame"
],
[
"numpy.concatenate",
"torch.utils.data.DataLoader"
],
[
"torch.LongTensor"
]
] |
yugangzhang/pyFAI | [
"e0453b279dac1f165f637e2a2ed1d4ddf57d31ba",
"e0453b279dac1f165f637e2a2ed1d4ddf57d31ba",
"e0453b279dac1f165f637e2a2ed1d4ddf57d31ba",
"e0453b279dac1f165f637e2a2ed1d4ddf57d31ba",
"e0453b279dac1f165f637e2a2ed1d4ddf57d31ba"
] | [
"pyFAI/opencl/OCLFullSplit.py",
"pyFAI/units.py",
"pyFAI/test/test_pickle.py",
"pyFAI/test/test_convolution.py",
"pyFAI/gui/widgets/CalibrantPreview.py"
] | [
"# -*- coding: utf-8 -*-\n#\n# Project: Azimuthal integration\n# https://github.com/silx-kit/pyFAI\n#\n#\n# Copyright (C) 2014-2018 European Synchrotron Radiation Facility, Grenoble, France\n#\n# Principal author: Jérôme Kieffer (Jerome.Kieffer@ESRF.eu)\n# Giann... | [
[
"numpy.ndarray",
"numpy.empty",
"numpy.dtype",
"numpy.finfo"
],
[
"numpy.sqrt"
],
[
"numpy.random.random"
],
[
"numpy.allclose"
],
[
"numpy.histogram",
"numpy.rad2deg"
]
] |
seib2/PypeIt | [
"4c68b38cb907345a480d7afee58200a05ecd4556"
] | [
"pypeit/tests/test_save.py"
] | [
"\"\"\"\nModule to run tests on arsave\n\"\"\"\nimport os\n\nimport numpy as np\nimport pytest\n\nfrom astropy import units\nfrom astropy.io import fits\n\nfrom pypeit import specobjs\nfrom pypeit.core import save\n\nfrom pypeit.tests.tstutils import dummy_fitstbl\nfrom pypeit.spectrographs import util\n\ndef data_... | [
[
"numpy.ones",
"numpy.arange"
]
] |
gskdhiman/zomato-recommendation | [
"76d050d654f5ae4db4801eadb065db324baacf5e"
] | [
"backend_code.py"
] | [
"# -*- coding: utf-8 -*-\n\"\"\"\nCreated on Fri Oct 2 00:14:39 2020\n\n@author: Gursewak\n\"\"\"\n\nimport pandas as pd\nimport re\nimport string\nfrom nltk.corpus import stopwords\nfrom sklearn.feature_extraction.text import TfidfVectorizer\nfrom sklearn.neighbors import NearestNeighbors\nfrom datetime import da... | [
[
"pandas.read_csv",
"sklearn.neighbors.NearestNeighbors",
"sklearn.feature_extraction.text.TfidfVectorizer"
]
] |
Weilory/python-matplotlib-graphs | [
"4578c184daba587417becc6df1ad4566e881343a"
] | [
"graph/hist_bin.py"
] | [
"import pandas as pd\r\nfrom matplotlib import pyplot as plt\r\n\r\nplt.style.use(\"fivethirtyeight\")\r\n\r\npath = input(\"please input the age.csv file path here: \")\r\ndata = pd.read_csv(path)\r\nids = data[\"Responder_id\"]\r\nages = data[\"Age\"]\r\n\r\nbins = [10, 20, 30, 40, 50, 60, 70, 80, 90, 100]\r\n\r\... | [
[
"matplotlib.pyplot.xlabel",
"matplotlib.pyplot.title",
"matplotlib.pyplot.legend",
"matplotlib.pyplot.hist",
"matplotlib.pyplot.show",
"matplotlib.pyplot.tight_layout",
"matplotlib.pyplot.style.use",
"matplotlib.pyplot.ylabel",
"matplotlib.pyplot.axvline",
"pandas.read_csv"... |
hellomoto-ai/splatoon2-ml | [
"4bd24eed527d6b56ce4369b70d24f20058962383"
] | [
"spml/trainer/vae_gan.py"
] | [
"\"\"\"Training mechanism for VAE-GAN\"\"\"\nimport os\nimport time\nimport logging\n\nimport numpy as np\nimport torch\nimport torch.nn.functional as F\n\nfrom spml import (\n image_util,\n loss_utils,\n)\nfrom . import (\n misc_utils,\n saved_model_manager,\n)\n\n_LG = logging.getLogger(__name__)\n\n\... | [
[
"numpy.concatenate",
"numpy.max",
"torch.no_grad",
"numpy.min",
"numpy.mean",
"torch.nn.functional.mse_loss",
"torch.randn_like",
"torch.load",
"numpy.var"
]
] |
BOSS-Danuphan/coralinedb | [
"23458c82528ac7ceb78c17e23163d542ad96b79a"
] | [
"coralinedb/coralinedb.py"
] | [
"\"\"\"\n Coraline DB Manager - This will take care of reading and saving tables to SQL database\n\"\"\"\n\n# import python packages\nimport pandas as pd\nimport time\n\n\nclass BaseDB:\n \"\"\"\n Base class for all DB\n These functions must be inherited by sub-class\n - create_connection\n ... | [
[
"pandas.read_sql"
]
] |
yonesuke/prax | [
"6957776b11c297d4463fba6d15cd06671dfbd45f"
] | [
"examples/hodgkinhuxley.py"
] | [
"import jax.numpy as jnp\nfrom prax import Oscillator\nfrom jax.config import config; config.update(\"jax_enable_x64\", True)\n\nimport matplotlib.pyplot as plt\n\nclass HodgkinHuxley(Oscillator):\n def __init__(self, input_current, C=1.0, G_Na=120.0, G_K=36.0, G_L=0.3, E_Na=50.0, E_K=-77.0, E_L=-54.4, dt=0.01, ... | [
[
"matplotlib.pyplot.xlabel",
"matplotlib.pyplot.savefig",
"matplotlib.pyplot.title",
"matplotlib.pyplot.plot",
"matplotlib.pyplot.legend",
"matplotlib.pyplot.figure",
"matplotlib.pyplot.ylabel",
"matplotlib.pyplot.subplot"
]
] |
LukiBa/zybo_face | [
"5f229818727b65ffa82efee2f63522234364fbe2"
] | [
"PC/application_pc.py"
] | [
"# -*- coding: utf-8 -*-\n\"\"\"\nCreated on Wed Dec 1 18:09:27 2021\n\n@author: lukas\n\"\"\"\n\nimport cv2\nimport dlib\nimport numpy as np\nimport timeit\nimport utils\nimport queue\nimport multiprocessing\nimport pathlib\nimport argparse\nimport time\n\n\ndef _create_parser():\n parser = argparse.ArgumentPa... | [
[
"numpy.array",
"numpy.linalg.norm",
"numpy.zeros",
"numpy.abs"
]
] |
tasx0823/BBN | [
"7992e908842f5934f0d1ee3f430d796621e81975",
"7992e908842f5934f0d1ee3f430d796621e81975"
] | [
"lib/utils/utils.py",
"main/valid.py"
] | [
"import logging\r\nimport time\r\nimport os\r\n\r\nimport torch\r\nfrom utils.lr_scheduler import WarmupMultiStepLR\r\nfrom net import Network\r\n\r\n\r\ndef create_logger(cfg):\r\n dataset = cfg.DATASET.DATASET\r\n net_type = cfg.BACKBONE.TYPE\r\n module_type = cfg.MODULE.TYPE\r\n log_dir = os.path.joi... | [
[
"torch.optim.lr_scheduler.CosineAnnealingLR",
"torch.optim.Adam",
"torch.optim.SGD",
"torch.optim.lr_scheduler.MultiStepLR",
"torch.nn.DataParallel"
],
[
"torch.device",
"torch.nn.Softmax",
"numpy.sum",
"torch.no_grad",
"torch.utils.data.DataLoader",
"torch.nn.DataP... |
dwhu/pandas | [
"283fa07e723fac091685366ba83727624748fddb"
] | [
"pandas/core/internals/blocks.py"
] | [
"from datetime import datetime, timedelta\nimport functools\nimport inspect\nimport re\nfrom typing import Any, List\nimport warnings\n\nimport numpy as np\n\nfrom pandas._libs import NaT, algos as libalgos, lib, tslib, writers\nfrom pandas._libs.index import convert_scalar\nimport pandas._libs.internals as libinte... | [
[
"pandas.core.indexers.is_scalar_indexer",
"pandas.core.dtypes.cast.infer_dtype_from",
"pandas.core.construction.extract_array",
"pandas.core.dtypes.common.is_float_dtype",
"pandas.core.dtypes.common.is_datetime64_dtype",
"numpy.empty",
"pandas.core.computation.expressions.where",
"... |
zhonglihanzhu/tensorflow-objectDetection | [
"aa3d1b754d5c78b8401ce86d4c20f45741fc2b77",
"aa3d1b754d5c78b8401ce86d4c20f45741fc2b77",
"aa3d1b754d5c78b8401ce86d4c20f45741fc2b77"
] | [
"builders/losses_builder_test.py",
"utils/shape_utils_test.py",
"models/faster_rcnn_nas_feature_extractor.py"
] | [
"# Copyright 2017 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.constant",
"tensorflow.test.main"
],
[
"numpy.zeros",
"tensorflow.get_default_graph",
"tensorflow.constant",
"tensorflow.placeholder",
"tensorflow.reduce_sum",
"tensorflow.test.main",
"tensorflow.slice",
"tensorflow.contrib.framework.is_tensor"
],
[
... |
nicola144/auxiliary-particle-filters | [
"61d72e9163abb73007c0fbd30f68d4cc6d7ab4e9"
] | [
"src/utils.py"
] | [
"import re\nimport sys\n\nimport matplotlib.pyplot as plt\nimport numpy as np\nfrom matplotlib import rcParams\nfrom scipy.integrate import simps\nfrom scipy.special import logsumexp\nfrom scipy.optimize import minimize\n# from sklearn.cluster import DBSCAN\n# from sklearn.preprocessing import StandardScaler\nimpor... | [
[
"numpy.min",
"numpy.mean",
"numpy.random.normal",
"numpy.count_nonzero",
"scipy.special.logsumexp",
"numpy.log",
"numpy.eye",
"numpy.sqrt",
"scipy.optimize.minimize",
"numpy.expand_dims",
"numpy.linalg.eigvals",
"scipy.integrate.simps",
"numpy.zeros",
"numpy... |
fredshentu/public_model_based_controller | [
"9301699bc56aa49ba5c699f7d5be299046a8aa0c",
"9301699bc56aa49ba5c699f7d5be299046a8aa0c"
] | [
"railrl/predictors/state_action_network.py",
"railrl/planner/forward_planner/choose_init_goal_pairs_pushing_active_sampling.py"
] | [
"import abc\nimport tensorflow as tf\n\nfrom railrl.core.neuralnet import NeuralNetwork\nfrom rllab.misc.overrides import overrides\n\n\nclass StateActionNetwork(NeuralNetwork, metaclass=abc.ABCMeta):\n \"\"\"\n A map from (state, action) to a vector\n \"\"\"\n\n def __init__(\n self,\n ... | [
[
"tensorflow.variable_scope",
"tensorflow.placeholder"
],
[
"numpy.concatenate",
"numpy.random.rand",
"tensorflow.ConfigProto",
"numpy.random.randint",
"numpy.clip",
"tensorflow.GPUOptions"
]
] |
topolphukhanh/xam | [
"3fa958ba8b0c8e8e266cac9997b7a7d0c309f55c"
] | [
"xam/preprocessing/binning/mdlp.py"
] | [
"\"\"\"\nMinimum Description Length Principle (MDLP) binning\n\n- Original paper: http://sci2s.ugr.es/keel/pdf/algorithm/congreso/fayyad1993.pdf\n- Implementation inspiration: https://www.ibm.com/support/knowledgecenter/it/SSLVMB_21.0.0/com.ibm.spss.statistics.help/alg_optimal-binning.htm\n\"\"\"\n\nimport collecti... | [
[
"scipy.stats.entropy",
"sklearn.utils.check_X_y",
"numpy.unique"
]
] |
ezeddin/random_forest | [
"07a23af1764fbf7a54a27e79d5ac68c69a64f0b1"
] | [
"bin/AdaBoost.py"
] | [
"from sklearn.ensemble import AdaBoostClassifier\nfrom sklearn.tree import DecisionTreeClassifier\nfrom sklearn.datasets import make_gaussian_quantiles\nfrom sklearn.ensemble import RandomForestClassifier\n\ndef AdaBoost(X_train, y_train, X_test, DEPTH, N_ESTIMATORS):\n\t# Create and fit an AdaBoosted decision tree... | [
[
"sklearn.ensemble.RandomForestClassifier",
"sklearn.tree.DecisionTreeClassifier"
]
] |
BioSystemsUM/biotmpy | [
"f981d58cf7f53a2aa09708e13d6561533c164e1f"
] | [
"pipelines/cv_biobert_lstm_ft.py"
] | [
"model_name= 'cv_biobert_lstm_ft'\r\n\r\nimport sys \r\nsys.path.append('../')\r\nimport os\r\nimport tensorflow \r\nimport numpy as np\r\nimport random\r\n\r\n\r\nseed_value = 123123\r\n#seed_value = None\r\n\r\nenvironment_name = sys.executable.split('/')[-3]\r\nprint('Environment:', environment_name)\r\nos.envir... | [
[
"tensorflow.distribute.MirroredStrategy",
"tensorflow.test.gpu_device_name",
"sklearn.model_selection.StratifiedKFold",
"numpy.random.seed",
"tensorflow.random.set_seed",
"tensorflow.compat.v1.ConfigProto",
"tensorflow.compat.v1.InteractiveSession",
"sklearn.metrics.accuracy_score"... |
johnfmaddox/kilojoule | [
"b4c146ded82e3ef51a0252ff48b1066a076e9aeb"
] | [
"kilojoule/humidair.py"
] | [
"from .units import Quantity, units\nfrom .common import (\n invert_dict,\n CP_symbUpper_to_units,\n preferred_units_from_type,\n preferred_units_from_symbol,\n)\nfrom .realfluid import Properties as rfprop\nfrom .plotting import PropertyPlot, plt\nimport CoolProp\nfrom CoolProp.CoolProp import HAPropsS... | [
[
"numpy.log10",
"numpy.arange"
]
] |
Dongzhou-1996/tf_learning | [
"fe764e78cc1a934707ae01d0847f901cb6fbb8b9"
] | [
"tf_mnist.py"
] | [
"#!/usr/bin/env python\n# coding=utf-8\nimport tensorflow as tf\nimport os\nimport numpy as np\nimport argparse\nimport shutil\nfrom tensorflow.examples.tutorials.mnist import input_data\n\nparser = argparse.ArgumentParser('MNIST Softmax')\nparser.add_argument('--data_dir', type=str, default='/tmp/mnist-data', \n ... | [
[
"tensorflow.nn.softmax_cross_entropy_with_logits",
"tensorflow.constant_initializer",
"tensorflow.argmax",
"tensorflow.examples.tutorials.mnist.input_data.read_data_sets",
"tensorflow.train.Saver",
"tensorflow.Session",
"tensorflow.matmul",
"tensorflow.variable_scope",
"tensorf... |
MalayAgr/DeepNeuralNetworksFromScratch | [
"ded75b148d9bb497014c016bfd2d7d0280c007ab",
"ded75b148d9bb497014c016bfd2d7d0280c007ab"
] | [
"dnn/loss.py",
"dnn/training/optimizers/sgd.py"
] | [
"from __future__ import annotations\n\nfrom abc import ABC, abstractmethod\n\nimport numpy as np\nfrom numba import njit\n\n\n@njit(cache=True)\ndef _clip(a: np.ndarray, epsilon: float) -> np.ndarray:\n if ((a == 1) | (a <= 0)).any():\n a = np.maximum(a, epsilon).astype(np.float32)\n a = np.minimum... | [
[
"numpy.log",
"numpy.minimum",
"numpy.sum",
"numpy.arange",
"numpy.squeeze",
"numpy.maximum"
],
[
"numpy.zeros_like"
]
] |
dmuraco3/CompuTradePython | [
"5c2bc4d1d3baabd68677b8c3d78b8caeed52ba28"
] | [
"build/lib/Quantuiti/_ema.py"
] | [
"import numpy as np\ndef ema(self, N):\n \"\"\"\n Simple Moving Average = (N - PeriodSum) / N\n N = number of days in a given period\n PeriodSum = sum of stock closing prices in that period\n \"\"\"\n name = 'ema_' + str(N)\n dependent = 'sma_' + str(N)\n try:\n return self.data[name]... | [
[
"numpy.isnan"
]
] |
debowin/pytext | [
"91126bb34bd689f3513f25ca0d356ad374e004ab",
"91126bb34bd689f3513f25ca0d356ad374e004ab"
] | [
"pytext/metrics/__init__.py",
"pytext/models/semantic_parsers/rnng/rnng_data_structures.py"
] | [
"#!/usr/bin/env python3\n# Copyright (c) Facebook, Inc. and its affiliates. All Rights Reserved\n\nimport itertools\nfrom collections import defaultdict\nfrom json import dumps as json_dumps\nfrom typing import (\n Any,\n DefaultDict,\n Dict,\n List,\n NamedTuple,\n Optional,\n Sequence,\n T... | [
[
"numpy.square",
"numpy.append",
"numpy.array",
"numpy.extract",
"numpy.sum",
"numpy.logical_and",
"numpy.any",
"numpy.argsort",
"numpy.cumsum"
],
[
"torch.nn.Linear",
"torch.cat",
"torch.nn.LSTM",
"torch.stack",
"torch.nn.Tanh",
"torch.Tensor"
]
] |
Seb-Park/tensorflow-for-poets-2 | [
"1ef4112553b25f1c687b40b6872d4a97b9d44762"
] | [
"scripts/label_image_flask.py"
] | [
"# Copyright 2017 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.image.resize_bilinear",
"tensorflow.io.gfile.GFile",
"tensorflow.expand_dims",
"tensorflow.read_file",
"tensorflow.Graph",
"tensorflow.GraphDef",
"tensorflow.Session",
"tensorflow.import_graph_def",
"tensorflow.subtract",
"tensorflow.ConfigProto",
"tensorflo... |
sanweiliti/HMP | [
"abb37a553c9ebeccf746225331bd90ccc0e33df9"
] | [
"utils/Quaternions.py"
] | [
"import numpy as np\r\n\r\nclass Quaternions:\r\n \"\"\"\r\n Quaternions is a wrapper around a numpy ndarray\r\n that allows it to act as if it were an narray of\r\n a quaternion data type.\r\n \r\n Therefore addition, subtraction, multiplication,\r\n division, negation, absolute, are all defin... | [
[
"numpy.concatenate",
"numpy.array",
"numpy.arccos",
"numpy.empty",
"numpy.sin",
"numpy.zeros",
"numpy.sum",
"numpy.copy",
"numpy.linalg.eigh",
"numpy.ones",
"numpy.core.umath_tests.matrix_multiply",
"numpy.sign",
"numpy.where",
"numpy.arctan2",
"numpy.sq... |
RingoIngo/gluon-ts | [
"62fb20c36025fc969653accaffaa783671709564",
"62fb20c36025fc969653accaffaa783671709564"
] | [
"src/gluonts/nursery/tsbench/src/tsbench/surrogate/deepset.py",
"src/gluonts/nursery/SCott/test/evaluation/test_evaluator.py"
] | [
"# Copyright 2018 Amazon.com, Inc. or its affiliates. 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# A copy of the License is located at\n#\n# http://www.apache.org/licenses/LICENSE-2.0\n#\n# or ... | [
[
"numpy.concatenate",
"numpy.array",
"torch.nn.MSELoss",
"torch.from_numpy",
"torch.cuda.is_available",
"torch.as_tensor"
],
[
"numpy.array",
"pandas.date_range",
"numpy.ones",
"pandas.Timestamp",
"numpy.arange",
"numpy.isfinite",
"pandas.Series"
]
] |
Wayne-Mai/DynSLAM | [
"7b62e13d2a33ff58ca888a346433a4891a228a20"
] | [
"preprocessing/MaskRCNN/MaskRCNN_TUM.py"
] | [
"#!/usr/bin/env python3\n#\n# This file is part of https://github.com/martinruenz/maskfusion\n#\n# This program is free software: you can redistribute it and/or modify\n# it under the terms of the GNU General Public License as published by\n# the Free Software Foundation, either version 3 of the License, or\n# (at ... | [
[
"matplotlib.pyplot.ion",
"numpy.empty",
"matplotlib.pyplot.figure"
]
] |
AropJoe/milvus | [
"35612881e33ce19a7407628769f6b51a7518bfe9"
] | [
"tests/benchmark/milvus_benchmark/runners/utils.py"
] | [
"import os\nimport logging\nimport numpy as np\nimport sklearn.preprocessing\nimport h5py\nimport random\nfrom itertools import product\n\nfrom pymilvus import DataType\nfrom milvus_benchmark import config\n\nlogger = logging.getLogger(\"milvus_benchmark.runners.utils\")\n\nDELETE_INTERVAL_TIME = 2\n\nVECTORS_PER_F... | [
[
"numpy.packbits",
"numpy.load",
"numpy.fromfile"
]
] |
gonzrubio/ML_Papers | [
"562f85c81b0afb8771708ff31063f722d838b9d2"
] | [
"GANs/WGANGP_Gulrajani_et_al_2017/driver.py"
] | [
"\"\"\"Improved Training of Wasserstein GANs.\n\nPapers:\n https://arxiv.org/abs/1701.07875\n https://arxiv.org/abs/1704.00028\n\nCreated on Tue Oct 26 15:17:08 2021\n\n@author: gonzo\n\"\"\"\n\n\nimport torch\nimport torch.nn as nn\nimport torch.optim as optim\n\n\nfrom torch.optim.lr_scheduler import Cosine... | [
[
"torch.utils.data.ConcatDataset",
"torch.rand",
"torch.utils.tensorboard.SummaryWriter",
"torch.optim.lr_scheduler.CosineAnnealingLR",
"torch.no_grad",
"torch.cuda.is_available",
"torch.utils.data.DataLoader",
"torch.ones_like",
"torch.mean",
"torch.randn"
]
] |
KireinaHoro/Ax | [
"16cb868911eecba323759e2e129df8833361e614"
] | [
"ax/modelbridge/factory.py"
] | [
"#!/usr/bin/env python3\n# Copyright (c) Facebook, Inc. and its affiliates.\n#\n# This source code is licensed under the MIT license found in the\n# LICENSE file in the root directory of this source tree.\n\nfrom logging import Logger\nfrom typing import Any, Dict, List, Optional, Type\n\nimport torch\nfrom ax.core... | [
[
"torch.device",
"torch.cuda.is_available"
]
] |
maximilian-hoffmann/FINE | [
"62828f5feefefc2208dde0133435979d63398cc1"
] | [
"FINE/storage.py"
] | [
"from FINE.component import Component, ComponentModel\nfrom FINE import utils\nimport pyomo.environ as pyomo\nimport warnings\nimport pandas as pd\n\n\nclass Storage(Component):\n \"\"\"\n A Storage component can store a commodity and thus transfers it between time steps.\n \"\"\"\n def __init__(self, e... | [
[
"pandas.DataFrame",
"pandas.MultiIndex.from_tuples",
"pandas.concat"
]
] |
yzR1991/Copulas | [
"72c0d9c398f7fe3eb075b56591911fea377cdc33",
"72c0d9c398f7fe3eb075b56591911fea377cdc33"
] | [
"tests/unit/multivariate/test_gaussian.py",
"tests/unit/univariate/test_selection.py"
] | [
"from unittest import TestCase\nfrom unittest.mock import Mock, patch\n\nimport numpy as np\nimport pandas as pd\n\nfrom copulas import get_qualified_name\nfrom copulas.multivariate.gaussian import GaussianMultivariate\nfrom copulas.univariate import GaussianUnivariate\n\n\nclass TestGaussianMultivariate(TestCase):... | [
[
"pandas.isnull",
"numpy.testing.assert_allclose",
"numpy.array",
"pandas.testing.assert_frame_equal",
"numpy.isclose",
"numpy.zeros",
"numpy.testing.assert_equal",
"pandas.DataFrame",
"numpy.mean",
"numpy.std",
"pandas.Series"
],
[
"numpy.random.seed",
"nump... |
Cheol-H-Jeong/Doridori-Counter | [
"c16da56dbbcccdc24033ddb9435d13506feb8b99"
] | [
"doridori.py"
] | [
"import cv2\nimport mediapipe as mp\nimport numpy as np\nimport pandas as pd\nimport seaborn as sns\nimport matplotlib.pyplot as plt\nfrom scipy.spatial import distance\nfrom scipy.signal import find_peaks\nfrom celluloid import Camera\nfrom tqdm import tqdm\n\nclass Doridori:\n def __init__(self,filepath):\n ... | [
[
"numpy.concatenate",
"numpy.array",
"numpy.delete",
"numpy.empty",
"scipy.spatial.distance.euclidean",
"matplotlib.pyplot.plot",
"matplotlib.pyplot.close",
"matplotlib.pyplot.subplots",
"matplotlib.pyplot.figure",
"scipy.signal.find_peaks"
]
] |
MobTgZhang/CIAlgorithms | [
"3aa1b249f526d75fb8e9bf7f37516f18a025d50a"
] | [
"ACO/ACO.py"
] | [
"\nimport numpy as np\nimport matplotlib.pyplot as plt\nimport urllib.request\nimport os\nimport time\ndef download(root_path,filename):\n if not os.path.exists(root_path):\n os.mkdir(root_path)\n if not os.path.exists(os.path.join(root_path,filename)):\n url = \"http://elib.zib.de/pub/mp-testda... | [
[
"numpy.square",
"numpy.array",
"numpy.random.rand",
"numpy.zeros",
"matplotlib.pyplot.arrow",
"numpy.sum",
"numpy.ones",
"matplotlib.pyplot.plot",
"numpy.min",
"matplotlib.pyplot.title",
"matplotlib.pyplot.close",
"numpy.mean",
"numpy.where",
"numpy.power",
... |
uwe-iben/torchphysics | [
"775d9aca71752a568f1fca972c958b99107f3b7c"
] | [
"src/torchphysics/utils/user_fun.py"
] | [
"\"\"\"Contains a class which extracts the needed arguments of an arbitrary \nmethode/function and wraps them for future usage. E.g correctly choosing \nthe needed arguments and passing them on to the original function.\n\"\"\"\nimport inspect\nimport copy \nimport torch\n\nfrom ..problem.spaces.points import Point... | [
[
"torch.tensor"
]
] |
DevRx28/pokemon-type | [
"2f62d4b88856dcd9aff79bdda993a4ddc093d7b7"
] | [
"prepro.py"
] | [
"import numpy as np\nfrom scipy.optimize import fmin_l_bfgs_b\nimport time\nimport argparse\nimport cv2\nfrom tensorflow.keras.models import load_model\nimport numpy as np\nimport csv \nimport sys\nfrom matplotlib import pyplot as plt\nfrom PIL import Image\nfrom keras.preprocessing.image import img_to_array\n\n\ni... | [
[
"numpy.where",
"numpy.zeros"
]
] |
vishalbelsare/lasso-python | [
"319bf590599b4a4d50d9345e83e8030afe044aec"
] | [
"lasso/dyna/FemzipMapper.py"
] | [
"\r\nimport logging\r\nimport re\r\nimport traceback\r\nfrom typing import Dict, List, Set, Tuple, Union\r\n\r\nimport numpy as np\r\nfrom lasso.dyna.ArrayType import ArrayType\r\nfrom lasso.femzip.femzip_api import FemzipAPI, FemzipFileMetadata, VariableInfo\r\nfrom lasso.femzip.fz_config import (FemzipArrayType, ... | [
[
"numpy.empty"
]
] |
rewin123/NNPreprocessingTomography | [
"b630f4c2cb9705c3c8432480498e4307ed511edf"
] | [
"open_test.py"
] | [
"import torch\nfrom torch import nn\nfrom torch.nn import Sequential\n\n#model definition\nclass Unet1D(nn.Module):\n def __init__(self):\n super(Unet1D, self).__init__()\n \n ch = 32\n self.maxpool = nn.MaxPool2d((1,2))\n self.unpool = nn.Upsample(scale_factor=(1,2))\n ... | [
[
"torch.nn.MaxPool2d",
"numpy.load",
"matplotlib.pyplot.subplots",
"torch.nn.Upsample",
"torch.nn.Conv2d",
"numpy.abs",
"torch.load",
"matplotlib.pyplot.show",
"numpy.linspace"
]
] |
rran9235/GazePal-Application | [
"88d6a74daeddd18ab37c0f2953a118f1f59e06a5"
] | [
"src/python/GazePal_PC.py"
] | [
"\"\"\"\nGazePal Application\nAuthor: Rishi Rangarajan\nYear: 2021 \n\nFile: GazePal_PC.py\nInfo: GazePal_PC class definition\n\"\"\"\n\n# Imports\nimport csv\nimport os\nimport pyautogui\nimport time\nimport torch\nimport torchvision\nimport cv2 as cv\nimport numpy as np\nimport torchvision.transforms as transform... | [
[
"torch.max",
"torch.tensor",
"numpy.size",
"torch.load"
]
] |
ICRC-BME/PySigView | [
"8ac60960dea0e5c70757c76545a896c76a95f68d"
] | [
"pysigview/widgets/transforms/filters.py"
] | [
"#!/usr/bin/env python3\n# -*- coding: utf-8 -*-\n\"\"\"\nCreated on Thu Jun 29 09:23:17 2017\n\nAnnotations plugin for pysigview\n\nIng.,Mgr. (MSc.) Jan Cimbálník\nBiomedical engineering\nInternational Clinical Research Center\nSt. Anne's University Hospital in Brno\nCzech Republic\n&\nMayo systems electrophysiolo... | [
[
"scipy.signal.filtfilt",
"scipy.signal.butter"
]
] |
monferrand/pandas | [
"a3477c769b3d2ea4950ae69f8867e3b291b743c1"
] | [
"pandas/core/arrays/datetimes.py"
] | [
"from datetime import datetime, time, timedelta\nfrom typing import Union\nimport warnings\n\nimport numpy as np\nfrom pytz import utc\n\nfrom pandas._libs import lib, tslib\nfrom pandas._libs.tslibs import (\n NaT,\n Timestamp,\n ccalendar,\n conversion,\n fields,\n iNaT,\n normalize_date,\n ... | [
[
"pandas.core.dtypes.common.is_string_dtype",
"pandas.core.dtypes.dtypes.DatetimeTZDtype.construct_from_string",
"pandas._libs.tslibs.timezones.is_utc",
"pandas.core.arrays.datetimelike.validate_inferred_freq",
"pandas.core.arrays.datetimelike.maybe_infer_freq",
"pandas.core.dtypes.common.i... |
steventan0110/multiDDS | [
"b77d0ad7b8f38d5b3b1b0e63e2671e0de0e3da00"
] | [
"fairseq/optim/lr_scheduler/inverse_square_root_decay_schedule.py"
] | [
"# Copyright (c) Facebook, Inc. and its affiliates.\n#\n# This source code is licensed under the MIT license found in the\n# LICENSE file in the root directory of this source tree.\n\nfrom . import FairseqLRScheduler, register_lr_scheduler\nimport torch\n\n@register_lr_scheduler('inverse_sqrt_decay')\nclass Inverse... | [
[
"torch.optim.lr_scheduler.ReduceLROnPlateau"
]
] |
mariogeiger/jax | [
"7098088f4eb15cf750398889e4341dbc15cda1b3"
] | [
"tests/lax_numpy_indexing_test.py"
] | [
"# Copyright 2018 Google LLC\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# https://www.apache.org/licenses/LICENSE-2.0\n#\n# Unless required by applicable law or agreed ... | [
[
"numpy.max",
"numpy.full",
"numpy.zeros_like",
"numpy.array",
"numpy.isposinf",
"numpy.zeros",
"numpy.asarray",
"numpy.minimum",
"numpy.ones",
"numpy.isneginf",
"numpy.arange",
"numpy.int32",
"numpy.issubdtype",
"numpy.iinfo",
"numpy.maximum"
]
] |
archman/python-mpl4qt | [
"f84fefb95113492407899206269ff82b609279b2"
] | [
"mpl4qt/widgets/mplbasewidget.py"
] | [
"# -*- coding: utf-8 -*-\n\"\"\"\nmplbasewidget.py\n\nBase class for matplotlib widget for PyQt.\n\nCopyright (C) 2018 Tong Zhang <zhangt@frib.msu.edu>\n\nThis program is free software; you can redistribute it and/or modify\nit under the terms of the GNU General Public License as published by\nthe Free Software Fou... | [
[
"matplotlib.ticker.AutoMinorLocator",
"matplotlib.figure.Figure",
"matplotlib.ticker.NullLocator",
"numpy.linspace",
"numpy.vstack",
"matplotlib.backends.backend_qt5agg.FigureCanvasQTAgg"
]
] |
msusicky/ockovani-covid | [
"2835943b5796b04a3542782ecda125b6766cd317"
] | [
"app/fetcher/used_fetcher.py"
] | [
"import pandas as pd\n\nfrom app import db, app\nfrom app.fetcher.fetcher import Fetcher\nfrom app.models import OckovaniSpotreba, OckovaciMisto\n\n\nclass UsedFetcher(Fetcher):\n \"\"\"\n Class for updating used vaccines table.\n \"\"\"\n\n USED_CSV = 'https://onemocneni-aktualne.mzcr.cz/api/v2/covid-1... | [
[
"pandas.read_csv"
]
] |
rodrigodelazcano/AerialRobotics | [
"44d7929721eaf3c817cf7f70966e805b36f66981"
] | [
"assignment1/src/offboard_UMD/script/plot_position.py"
] | [
"import numpy as np\nimport rosbag\nimport matplotlib.pyplot as plt\nfrom mpl_toolkits.mplot3d import Axes3D\nfrom tf.transformations import euler_from_quaternion\n\n# Read bag file\nbag = rosbag.Bag('2021-09-21-19-57-22.bag')\n\nx = []\ny = []\nz = []\nroll = []\npitch = []\nyaw = []\ntime = []\ncycles = []\ncycle... | [
[
"matplotlib.pyplot.show",
"numpy.stack",
"matplotlib.pyplot.subplots",
"matplotlib.pyplot.figure"
]
] |
kizill/coremltools | [
"11e143089a66ee219ce3a2ed98aa1aae794d4794"
] | [
"coremltools/models/_graph_visualization.py"
] | [
"# Copyright (c) 2017, Apple Inc. All rights reserved.\n#\n# Use of this source code is governed by a BSD-3-clause license that can be\n# found in the LICENSE.txt file or at https://opensource.org/licenses/BSD-3-Clause\n\n\"\"\"\nFunctions related to graph visualization of mlmodels\n\"\"\"\n\nimport ast as _ast\nim... | [
[
"numpy.random.randint"
]
] |
Subsets and Splits
No community queries yet
The top public SQL queries from the community will appear here once available.