repo_name stringlengths 6 130 | hexsha list | file_path list | code list | apis list |
|---|---|---|---|---|
koelling/amplimap | [
"cbd5b7b8c2f703982d8964a3c77bd350a47f08a6"
] | [
"amplimap/coverage.py"
] | [
"# -*- coding: utf-8 -*-\n\"\"\"\nThis module contains methods for processing and aggregating coverage files generated by ``bedtools``.\n\"\"\"\n\nimport pandas as pd\nimport numpy as np\nimport re\nimport os\n\nfrom .reader import read_sample_info\n\ncov_cols = ['Target', 'min_coverage', 'sum_coverage', 'basepairs... | [
[
"pandas.read_csv"
]
] |
joey12300/Paddle | [
"59102c6dcd2def3091f5c37816354ac69d669809"
] | [
"python/paddle/fluid/tests/unittests/xpu/test_softmax_with_cross_entropy_op_xpu.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 ... | [
[
"numpy.log",
"numpy.full",
"numpy.apply_along_axis",
"numpy.zeros_like",
"numpy.prod",
"numpy.random.uniform",
"numpy.sum",
"numpy.random.randint"
]
] |
computationalartist/tensorflow | [
"b89cf636c412abdff53b3e8f201bde671c92209d",
"b89cf636c412abdff53b3e8f201bde671c92209d",
"b89cf636c412abdff53b3e8f201bde671c92209d"
] | [
"tensorflow/python/kernel_tests/math_ops/argmax_op_test.py",
"tensorflow/compiler/mlir/tfrt/python_tests/tf_const_test.py",
"tensorflow/lite/testing/op_tests/multinomial.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.python.ops.math_ops.argmax",
"numpy.arange",
"numpy.random.shuffle",
"tensorflow.python.ops.array_ops.zeros",
"tensorflow.python.platform.test.main",
"numpy.random.randn",
"tensorflow.python.framework.test_util.is_xla_enabled",
"numpy.array",
"numpy.zeros",
"ten... |
QuESt-Calculator/pyscf | [
"0ed03633b699505c7278f1eb501342667d0aa910",
"0ed03633b699505c7278f1eb501342667d0aa910",
"0ed03633b699505c7278f1eb501342667d0aa910",
"0ed03633b699505c7278f1eb501342667d0aa910",
"0ed03633b699505c7278f1eb501342667d0aa910",
"0ed03633b699505c7278f1eb501342667d0aa910",
"0ed03633b699505c7278f1eb501342667d0aa91... | [
"pyscf/grad/casci.py",
"pyscf/symm/test/test_Dmatrix.py",
"pyscf/ao2mo/test/test_incore.py",
"pyscf/lib/test/test_misc.py",
"pyscf/mp/test/test_ump2.py",
"pyscf/pbc/cc/eom_kccsd_rhf_ip.py",
"pyscf/scf/_response_functions.py",
"pyscf/dft/uks.py",
"pyscf/gw/gw_exact.py",
"pyscf/agf2/mpi_helper.py"
] | [
"#!/usr/bin/env python\n# Copyright 2014-2020 The PySCF Developers. 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/LIC... | [
[
"numpy.dot",
"numpy.einsum",
"numpy.arange",
"numpy.zeros_like",
"numpy.zeros"
],
[
"numpy.dot",
"numpy.random.random",
"numpy.linalg.norm",
"numpy.random.seed"
],
[
"numpy.random.random",
"numpy.allclose",
"numpy.random.seed"
],
[
"numpy.all",
"... |
tsheaff/keras | [
"ee227dda766d769b7499a5549e8ed77b5e88105b",
"ee227dda766d769b7499a5549e8ed77b5e88105b",
"ee227dda766d769b7499a5549e8ed77b5e88105b",
"ee227dda766d769b7499a5549e8ed77b5e88105b",
"ee227dda766d769b7499a5549e8ed77b5e88105b",
"ee227dda766d769b7499a5549e8ed77b5e88105b",
"ee227dda766d769b7499a5549e8ed77b5e88105... | [
"keras/utils/layer_utils_test.py",
"keras/optimizers/optimizer_v2/rmsprop.py",
"keras/layers/preprocessing/hashing_test.py",
"keras/engine/base_layer_test.py",
"keras/layers/reshaping/up_sampling3d.py",
"keras/preprocessing/dataset_utils.py",
"keras/layers/reshaping/permute.py",
"keras/layers/pooling/... | [
"# Copyright 2020 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.compat.v2.io.gfile.exists",
"numpy.random.random",
"tensorflow.compat.v2.test.main",
"tensorflow.compat.v2.__internal__.tf2.enabled"
],
[
"tensorflow.compat.v2.compat.v1.assign",
"tensorflow.compat.v2.raw_ops.ResourceApplyCenteredRMSProp",
"tensorflow.compat.v2.control_... |
systemquant/book-pandas-for-finance | [
"90b7eb9be1de20a12ae72b9bb5d51424a979b174",
"90b7eb9be1de20a12ae72b9bb5d51424a979b174"
] | [
"old/03/08.py",
"old/02/28.py"
] | [
"from pandas import Series\n\ndata = [1000, 2000, 3000]\nindex = [\"메로나\", \"구구콘\", \"하겐다즈\"]\ns = Series(data=data, index=index)\n\nprint(s.loc['메로나':'구구콘'])\n",
"import numpy as np\n\ndata = [1, 2, 3]\narr = np.array(data)\ndata2 = arr * 10\nprint(data2)"
] | [
[
"pandas.Series"
],
[
"numpy.array"
]
] |
vidursatija/SongWCT | [
"c892c2833ff9f85cfb31788babf016699c5eec8f"
] | [
"models.py"
] | [
"import torch\nimport torch.nn as nn\ntry:\n from torch.hub import load_state_dict_from_url\nexcept ImportError:\n from torch.utils.model_zoo import load_url as load_state_dict_from_url\nfrom torchsummary import summary\nimport numpy as np\n\n\nclass X_Enc(nn.Module):\n def __init__(self, layers, num_class... | [
[
"torch.nn.Sequential",
"torch.load",
"torch.nn.init.constant_",
"torch.nn.MaxPool1d",
"torch.nn.init.normal_",
"torch.cuda.is_available",
"torch.nn.Conv1d",
"torch.nn.ConvTranspose1d",
"torch.nn.ReLU",
"torch.nn.MaxUnpool1d",
"numpy.zeros",
"torch.nn.init.kaiming_no... |
eembees/solar_flares | [
"9022f92c0577efaf06d7425002995e4fa4df74b4"
] | [
"reading_data.py"
] | [
"from pathlib import Path\nimport ijson\nimport numpy as np # linear algebra\nimport pandas as pd # data processing, CSV file I/O (e.g. pd.read_csv)\nfrom json import JSONDecoder, JSONDecodeError # for reading the JSON data files\nimport re # for regular expressions\nimport os # for os related operations\nfrom... | [
[
"pandas.concat",
"numpy.savez",
"pandas.Series",
"numpy.isnan",
"numpy.arange",
"numpy.nan_to_num",
"pandas.Index",
"pandas.read_json",
"pandas.DataFrame.from_dict",
"numpy.load",
"numpy.array"
]
] |
geoffreynyaga/ostrich-project | [
"157cd7a3c3d9014e31ef21ca21de43f04d039997"
] | [
"CORE/engines/constraint.py"
] | [
"#!/usr/bin/env python3\r\n# -*- coding:utf-8 -*-\r\n##################################################################################\r\n# File: c:\\Projects\\KENYA ONE PROJECT\\CORE\\engines\\constraint.py #\r\n# Project: c:\\Projects\\KENYA ONE PROJECT\\CORE\\engines #... | [
[
"matplotlib.pylab.show",
"numpy.sqrt",
"numpy.abs",
"numpy.arange",
"numpy.cos",
"matplotlib.pylab.plot",
"matplotlib.pylab.legend",
"numpy.array",
"matplotlib.pylab.axvline"
]
] |
nkuxx161/baseline-SR | [
"c4caf06c5a5a88d7f8e27069018316b319f0913b"
] | [
"plot.py"
] | [
"import pandas as pd\nimport os\n\ncurve_name = '5_k7'\n\ndata = pd.read_csv(os.path.join('result', curve_name+'.csv'))\ntimestamp = data['timestamp']\nvalue = data['value']\nmag = data['mag']\nisAnomaly = data['isAnomaly']\n\nimport matplotlib\nmatplotlib.use(\"Agg\")\nimport matplotlib.pyplot as plt \n\nplt.subpl... | [
[
"matplotlib.pyplot.title",
"matplotlib.use",
"matplotlib.pyplot.plot",
"matplotlib.pyplot.subplot",
"matplotlib.pyplot.close",
"matplotlib.pyplot.show"
]
] |
catniplab/ML-music-analysis | [
"793d54ed16166fbcd9acf4eec24998892334e064",
"793d54ed16166fbcd9acf4eec24998892334e064"
] | [
"models/_sources/model_trainer_c4d127b7cc8008ff2c0c849733ead6e1.py",
"models/_sources/logistic_regression_207b05cd2ed83ee471bd1fd9fb4270d4.py"
] | [
"\"\"\"\nThis script creates an instance of a sacred experiment and defines default configurations for training a neural network or a regression model.\n\"\"\"\n\nfrom src.neural_nets.models import get_model\nfrom src.neural_nets.load_data import get_loader\nfrom src.neural_nets.metrics import MaskedBCE, Accuracy, ... | [
[
"torch.optim.lr_scheduler.LambdaLR",
"numpy.random.seed",
"numpy.linspace",
"torch.autograd.set_detect_anomaly",
"torch.manual_seed",
"torch.cuda.device",
"numpy.save",
"torch.cuda.is_available",
"torch.device",
"torch.distributions.Uniform",
"numpy.zeros",
"torch.s... |
dutxubo/nni | [
"c16f4e1c89b54b8b80661ef0072433d255ad2d24",
"c16f4e1c89b54b8b80661ef0072433d255ad2d24",
"c16f4e1c89b54b8b80661ef0072433d255ad2d24",
"c16f4e1c89b54b8b80661ef0072433d255ad2d24",
"c16f4e1c89b54b8b80661ef0072433d255ad2d24",
"c16f4e1c89b54b8b80661ef0072433d255ad2d24",
"c16f4e1c89b54b8b80661ef0072433d255ad2d2... | [
"test/ut/tools/annotation/testcase/usercode/mnist.py",
"nni/algorithms/feature_engineering/gradient_selector/gradient_selector.py",
"examples/trials/mnist-keras/mnist-keras.py",
"test/ut/sdk/test_networkmorphism_tuner.py",
"test/ut/compression/v1/test_transformer_pruners.py",
"test/ut/compression/v2/test_... | [
"# -*- encoding:utf8 -*-\n\n\"\"\"A deep MNIST classifier using convolutional layers.\n\"\"\"\n\nfrom __future__ import absolute_import\nfrom __future__ import division\nfrom __future__ import print_function\n\nimport logging\nimport math\nimport tempfile\nimport tensorflow as tf\n\nfrom tensorflow.examples.tutoria... | [
[
"tensorflow.nn.softmax_cross_entropy_with_logits",
"tensorflow.nn.max_pool",
"tensorflow.cast",
"tensorflow.train.AdamOptimizer",
"tensorflow.get_default_graph",
"tensorflow.nn.conv2d",
"tensorflow.Variable",
"tensorflow.name_scope",
"tensorflow.Session",
"tensorflow.argmax... |
jessehui/occlum | [
"8a5f3033881c090340d678f2aecdca4ac6355bf4"
] | [
"demos/python/python_musl/demo.py"
] | [
"import pandas as pd\nimport numpy as np\nfrom sklearn.datasets import dump_svmlight_file\n\ndf1 = pd.read_csv(\"./dataset/input_label.csv\")\ndf2 = pd.read_csv(\"./dataset/input.csv\")\nres = pd.merge(df1, df2, how='left', left_on='id', right_on='id')\n\nX = res[np.setdiff1d(res.columns,['label','id'])]\ny = res.l... | [
[
"pandas.merge",
"pandas.read_csv",
"sklearn.datasets.dump_svmlight_file",
"numpy.setdiff1d"
]
] |
adrenadine33/graphvite | [
"34fc203f96ff13095073c605ecfcae32213e7f6a"
] | [
"python/graphvite/application/application.py"
] | [
"# Copyright 2019 MilaGraph. 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 required by appli... | [
[
"numpy.linspace",
"numpy.asarray",
"torch.sum",
"numpy.concatenate",
"numpy.all",
"torch.set_grad_enabled",
"numpy.mean",
"torch.topk",
"numpy.where",
"torch.ones",
"numpy.ones_like",
"numpy.uint32",
"numpy.unique",
"numpy.arange",
"numpy.std",
"nump... |
zhoudoufu/lingvo | [
"bd0f89809942fd0508ff43bd4b6bca1b598220cb",
"bd0f89809942fd0508ff43bd4b6bca1b598220cb",
"bd0f89809942fd0508ff43bd4b6bca1b598220cb",
"bd0f89809942fd0508ff43bd4b6bca1b598220cb",
"bd0f89809942fd0508ff43bd4b6bca1b598220cb"
] | [
"lingvo/core/test_utils_test.py",
"lingvo/tasks/asr/model_test.py",
"lingvo/core/conv_layers_with_time_padding.py",
"lingvo/core/base_model.py",
"lingvo/tasks/asr/frontend.py"
] | [
"# Lint as: python2, python3\n# 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/... | [
[
"tensorflow.test.main"
],
[
"tensorflow.Graph",
"tensorflow.all_variables",
"tensorflow.test.main",
"tensorflow.trainable_variables",
"tensorflow.global_variables_initializer",
"tensorflow.set_random_seed"
],
[
"tensorflow.nn.l2_normalize",
"tensorflow.nn.convolution",
... |
garaytc/reinforcement | [
"e6af258bf2ac3b45c20e0ed3d2f58ca7bc2b232f"
] | [
"tests/agents/test_agent_interface.py"
] | [
"import pytest\nimport torch\nfrom gym.spaces import Discrete, MultiDiscrete, MultiBinary, Dict, Tuple, Box\n\nfrom blobrl.agents import AgentInterface\n\n\nclass MOCKAgentInterface(AgentInterface):\n def __init__(self, observation_space, action_space, device):\n super().__init__(observation_space, action... | [
[
"torch.device",
"torch.cuda.is_available"
]
] |
ivary43/pandas | [
"46adc5b1c2aacb312d72729af72bc0ad600917c0",
"46adc5b1c2aacb312d72729af72bc0ad600917c0",
"46adc5b1c2aacb312d72729af72bc0ad600917c0"
] | [
"pandas/tests/series/test_alter_axes.py",
"pandas/tests/plotting/common.py",
"pandas/tests/plotting/test_hist_method.py"
] | [
"from datetime import datetime\n\nimport numpy as np\nimport pytest\n\nfrom pandas import DataFrame, Index, MultiIndex, RangeIndex, Series\nimport pandas.util.testing as tm\n\n\nclass TestSeriesAlterAxes:\n\n def test_setindex(self, string_series):\n # wrong type\n msg = (r\"Index\\(\\.\\.\\.\\) mu... | [
[
"pandas.util.testing.assert_numpy_array_equal",
"pandas.Series",
"pandas.MultiIndex",
"pandas.RangeIndex",
"numpy.arange",
"pandas.util.testing.assert_produces_warning",
"pandas.util.testing.assert_series_equal",
"pandas.DataFrame",
"pandas.MultiIndex.from_arrays",
"pandas.... |
Hemankita/refarch-kc-container-ms | [
"c2e85eacabe8a194782835b04f3410c2d7956a9b"
] | [
"tools/generateData_sensor_malfunction.py"
] | [
"import csv\nimport json\nfrom random import gauss\nimport random\nimport datetime\nimport numpy as np\nimport sys\nimport pandas as pd\n\ndf = pd.DataFrame(columns=['Timestamp', 'ID', 'Temperature(celsius)', 'Target_Temperature(celsius)', 'Amp', 'CumulativePowerConsumption', 'ContentType', 'Humidity', 'CO2', 'Time... | [
[
"pandas.DataFrame",
"numpy.linspace"
]
] |
xvinay28x/cat_dog_classifier_library | [
"4d56f90f9d3e91051dba71dcdea78930c4ac0e52"
] | [
"animal-classifier/__init__.py"
] | [
"from tensorflow import keras\n\ndef classify(path):\n model = keras.models.load_model(\"Cat_Dog_Classification.h5\")\n load_image = keras.preprocessing.image.load_image(path,target_size=(200,200))\n image_array = keras.preprocessing.image.img_to_array(load_image)\n reshape_array = image_array.reshape(1... | [
[
"tensorflow.keras.models.load_model",
"tensorflow.keras.preprocessing.image.img_to_array",
"tensorflow.keras.preprocessing.image.load_image"
]
] |
ericlearning/style-transfer | [
"f387515b4ffe441c4677400a65b9e7fdb50c979f"
] | [
"FastStyleTransfer/utils.py"
] | [
"import os\nimport glob\nimport torch\nimport pandas as pd\nimport seaborn as sn\nimport torch.nn as nn\nimport torch.optim as optim\nimport matplotlib.pyplot as plt\nfrom torch.optim.lr_scheduler import _LRScheduler\nfrom sklearn.metrics import confusion_matrix\nfrom PIL import Image\n\ndef set_lr(optimizer, lrs):... | [
[
"torch.optim.Adam",
"sklearn.metrics.confusion_matrix",
"pandas.DataFrame",
"matplotlib.pyplot.subplot",
"matplotlib.pyplot.show",
"matplotlib.pyplot.hist",
"matplotlib.pyplot.figure"
]
] |
chathurawidanage/cylon | [
"ac61b7a50880138fe67de21adee208016a94979a"
] | [
"cpp/src/experiments/generate_csv.py"
] | [
"##\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 law or agreed to in writing, software\n# distri... | [
[
"numpy.random.rand"
]
] |
ZoRoronoa/Camera-Aware-Proxy | [
"352f900bbae330f18c2bfe2b3f2516fb4e31adea",
"352f900bbae330f18c2bfe2b3f2516fb4e31adea",
"352f900bbae330f18c2bfe2b3f2516fb4e31adea"
] | [
"reid/utils/evaluation_metrics/retrieval.py",
"reid/utils/evaluation_metrics/ranking.py",
"CAP-newCluster/reid/utils/clustering.py"
] | [
"import numpy as np\nfrom sklearn import metrics as sk_metrics\nimport torch\n\nclass PersonReIDMAP:\n '''\n Compute Rank@k and mean Average Precision (mAP) scores\n Used for Person ReID\n Test on MarKet and Duke\n '''\n\n def __init__(self, query_feature, query_cam, query_label, gallery_feature, ... | [
[
"numpy.square",
"numpy.in1d",
"torch.from_numpy",
"numpy.argwhere",
"sklearn.metrics.pairwise.euclidean_distances",
"numpy.append",
"sklearn.metrics.pairwise.cosine_distances",
"numpy.mean",
"numpy.argsort",
"torch.clamp",
"numpy.array",
"torch.pow"
],
[
"nu... |
miketrumpis/lfp_scroller | [
"ce4dbf85bb4d31f2eacfb5d68a5049499637722c"
] | [
"fast_scroller/h5data.py"
] | [
"import numpy as np\nfrom scipy.linalg import LinAlgError\nfrom scipy.signal import lfilter, lfilter_zi, hilbert\nfrom scipy.interpolate import interp1d\nimport h5py\nfrom tqdm import tqdm\nfrom ecogdata.util import input_as_2d\nfrom ecogdata.util import nextpow2\n\n\ndef h5mean(array, axis, rowmask=(), start=0, st... | [
[
"numpy.abs",
"numpy.linspace",
"numpy.isnan",
"numpy.arange",
"numpy.empty_like",
"scipy.signal.lfilter_zi",
"numpy.cumsum",
"scipy.interpolate.interp1d",
"numpy.iterable",
"scipy.signal.lfilter",
"numpy.array",
"numpy.zeros",
"numpy.sum",
"scipy.signal.hilb... |
fakecoinbase/TheCyberHeadslashCyberHead | [
"b1c5d8c157ff5bb976778ff5f7901d82e41d7d3e"
] | [
"cyberhead/modules/brokers/coinbase/Coinbase.py"
] | [
"import cbpro\nimport pandas as pd\nfrom base64 import b64encode\n\nclass Coinbase:\n\tdef __init__(self, API_KEY, API_SECRET, API_PASS, ENV_URL=\"https://api-public.sandbox.pro.coinbase.com\"):\n\t\tself.API_KEY = API_KEY\n\t\tself.API_SECRET = API_SECRET\n\t\tself.API_PASS = API_PASS\n\t\tself.ENV_URL = ENV_URL\n... | [
[
"pandas.DataFrame"
]
] |
jdlaubrie/shell-elem | [
"f87cb9ca9179533d3a645a494e7ef4d39666ddc6"
] | [
"3rd_check/surgery/penalty.py"
] | [
"# -*- coding: utf-8 -*-\r\nimport numpy as np\r\nimport pandas as pd\r\nimport matplotlib.pyplot as plt\r\n\r\nNbrOfNodes = 35\r\nkeygnra = ' TIME: GANDRA STEP: 80.000 FRAME: 1.000'\r\nkeystent = ' TIME: STENT STEP: 1.000 FRAME: 1.000'\r\nkeygnrb = ' TIME: GANDRB STEP: 100.000 FRAME: 1.000'\r... | [
[
"matplotlib.pyplot.legend",
"matplotlib.pyplot.gca",
"pandas.Series",
"matplotlib.pyplot.rc",
"matplotlib.pyplot.savefig",
"matplotlib.pyplot.plot",
"numpy.append",
"matplotlib.pyplot.subplot",
"matplotlib.pyplot.close",
"matplotlib.pyplot.axis",
"numpy.argsort",
"m... |
NRuf77/proset | [
"101d491e05c2423faddca31029232982f46d8831",
"101d491e05c2423faddca31029232982f46d8831",
"101d491e05c2423faddca31029232982f46d8831",
"101d491e05c2423faddca31029232982f46d8831",
"101d491e05c2423faddca31029232982f46d8831",
"101d491e05c2423faddca31029232982f46d8831",
"101d491e05c2423faddca31029232982f46d883... | [
"scripts/wine/wine_explain.py",
"scripts/checker/checker_knn_fit.py",
"proset/utility/other.py",
"scripts/cancer/cancer_prepare_data.py",
"scripts/iris_2f/iris_2f_xgb_diagnostics.py",
"scripts/xor_6_6f/xor_6_6f_xgb_diagnostics.py",
"scripts/checker_rot/checker_rot_xgb_fit.py",
"scripts/wine/wine_knn_d... | [
"\"\"\"Explain proset classifier trained on wine classification data.\r\n\r\nCopyright by Nikolaus Ruf\r\nReleased under the MIT license - see LICENSE file for details\r\n\"\"\"\r\n\r\nfrom copy import deepcopy\r\nimport gzip\r\nimport os\r\nimport pickle\r\n\r\nimport matplotlib.pyplot as plt\r\nimport numpy as np... | [
[
"matplotlib.pyplot.gca",
"numpy.abs",
"numpy.sqrt",
"numpy.arange",
"numpy.argsort",
"matplotlib.pyplot.figure"
],
[
"sklearn.preprocessing.StandardScaler",
"numpy.random.RandomState"
],
[
"sklearn.metrics.pairwise_distances",
"numpy.log",
"numpy.unique",
"n... |
joelnmdyer/SignatuRE | [
"085a9d727e504bd25bbebdebaa58867211a52c8d",
"085a9d727e504bd25bbebdebaa58867211a52c8d"
] | [
"signature/train_and_sample.py",
"signature/utils/compute_metrics.py"
] | [
"import argparse\nimport logging\nimport numpy as np\nimport os\nimport sbi.utils as utils\nfrom sbi.inference.base import infer\nfrom sbi import analysis as analysis\nfrom sbi.inference import SMCABC, SNRE_A, simulate_for_sbi, prepare_for_sbi\nfrom sklearn.linear_model import LinearRegression\nimport statsmodels.a... | [
[
"numpy.dot",
"numpy.log",
"numpy.sqrt",
"numpy.var",
"numpy.cov",
"numpy.mean",
"sklearn.linear_model.LinearRegression",
"numpy.savetxt",
"numpy.array",
"torch.as_tensor"
],
[
"numpy.mean"
]
] |
tlunet/pySDC | [
"209e0015a46f861e3658691b7f8724cb1b36c97e",
"209e0015a46f861e3658691b7f8724cb1b36c97e",
"209e0015a46f861e3658691b7f8724cb1b36c97e"
] | [
"pySDC/playgrounds/fft/AllenCahn_contracting_circle_FFT.py",
"pySDC/projects/RDC/equidistant_RDC.py",
"pySDC/playgrounds/deprecated/Dedalus/playground_datatypes.py"
] | [
"import os\n\nimport dill\nimport matplotlib.ticker as ticker\nimport numpy as np\n\nimport pySDC.helpers.plot_helper as plt_helper\nfrom pySDC.helpers.stats_helper import filter_stats, sort_stats\nfrom pySDC.implementations.collocation_classes.gauss_radau_right import CollGaussRadau_Right\nfrom pySDC.implementatio... | [
[
"numpy.ptp",
"numpy.std",
"numpy.argmax",
"numpy.mean",
"numpy.argmin",
"numpy.var",
"matplotlib.ticker.FormatStrFormatter",
"numpy.array"
],
[
"scipy.special.orthogonal.roots_legendre",
"numpy.prod",
"numpy.roll",
"numpy.array",
"numpy.zeros",
"numpy.su... |
Shuai-Xie/LP-DeepSSL | [
"9389c6cb0b83c7ca509ce284c4d86b600ca44a9b"
] | [
"mean_teacher/losses.py"
] | [
"# Copyright (c) 2018, Curious AI Ltd. All rights reserved.\n#\n# This work is licensed under the Creative Commons Attribution-NonCommercial\n# 4.0 International License. To view a copy of this license, visit\n# http://creativecommons.org/licenses/by-nc/4.0/ or send a letter to\n# Creative Commons, PO Box 1866, Mou... | [
[
"torch.nn.functional.kl_div",
"torch.nn.functional.softmax",
"torch.nn.functional.log_softmax",
"torch.sum",
"torch.nn.functional.mse_loss"
]
] |
balrajmarimuthu/CarND-Capstone | [
"bc3e52c5e940e3da51efad219ab89fb3580fb717"
] | [
"ros/src/tl_detector/tl_detector.py"
] | [
"#!/usr/bin/env python\nimport rospy\nfrom std_msgs.msg import Int32\nfrom geometry_msgs.msg import PoseStamped, Pose\nfrom styx_msgs.msg import TrafficLightArray, TrafficLight\nfrom styx_msgs.msg import Lane\nfrom sensor_msgs.msg import Image\nfrom cv_bridge import CvBridge\nfrom light_classification.tl_classifier... | [
[
"scipy.spatial.KDTree"
]
] |
uunal/adapter-transformers | [
"73a95a75f803e8fd243fc3d55ff3a9d557891377"
] | [
"src/transformers/adapters/models/distilbert.py"
] | [
"from typing import Union\n\nimport torch\nfrom torch import nn\n\nfrom ..composition import AdapterCompositionBlock, parse_composition\nfrom ..model_mixin import InvertibleAdaptersMixin, ModelAdaptersMixin\nfrom .bert import BertEncoderAdaptersMixin, BertModelHeadsMixin, BertOutputAdaptersMixin, BertSelfOutputAdap... | [
[
"torch.zeros"
]
] |
gsyqax/pandas | [
"cb35d8a938c9222d903482d2f66c62fece5a7aae",
"cb35d8a938c9222d903482d2f66c62fece5a7aae",
"148f9fd74fc71cb7509c0898883036316efc6f89",
"cb35d8a938c9222d903482d2f66c62fece5a7aae",
"cb35d8a938c9222d903482d2f66c62fece5a7aae"
] | [
"pandas/tests/arrays/boolean/test_construction.py",
"pandas/core/missing.py",
"pandas/tests/frame/test_subclass.py",
"asv_bench/benchmarks/arithmetic.py",
"pandas/tests/tseries/frequencies/test_freq_code.py"
] | [
"import numpy as np\nimport pytest\n\nimport pandas as pd\nimport pandas._testing as tm\nfrom pandas.arrays import BooleanArray\nfrom pandas.core.arrays.boolean import coerce_to_array\n\n\n@pytest.fixture\ndef data():\n return pd.array(\n [True, False] * 4 + [np.nan] + [True, False] * 44 + [np.nan] + [Tru... | [
[
"pandas._testing.assert_numpy_array_equal",
"pandas.core.arrays.boolean.coerce_to_array",
"pandas.arrays.BooleanArray._from_sequence_of_strings",
"pandas.array",
"pandas.arrays.BooleanArray",
"pandas._testing.assert_extension_array_equal",
"pandas.date_range",
"numpy.array"
],
... |
VitoRazor/Lidar_RGB_detector | [
"5308ba24a90d6e8d73940be4b40d31eccb4df94b"
] | [
"second/pytorch/train.py"
] | [
"import copy\nimport json\nimport os\nfrom pathlib import Path\nimport pickle\nimport shutil\nimport time\nimport re \nimport fire\nimport numpy as np\nimport torch\nfrom google.protobuf import text_format\n\nimport second.data.kitti_common as kitti\nimport torchplus\nfrom second.builder import target_assigner_buil... | [
[
"numpy.random.get_state",
"torch.cuda.synchronize",
"numpy.random.seed",
"torch.load",
"torch.cuda.device_count",
"torch.utils.data.DataLoader",
"torch.tensor",
"torch.no_grad",
"numpy.mean",
"torch.cuda.is_available",
"torch.device",
"torch.nn.DataParallel",
"n... |
KyunghoWon-GIST/PyRiemann-with-OpenViBE | [
"2a070fdadb040ce6edad81aef497d054ddd70130"
] | [
"python-Riemann-online.py"
] | [
"import pickle\r\nimport numpy as np\r\nimport pyriemann\r\nimport sklearn\r\nimport scipy\r\nimport matplotlib as mpl\r\nmpl.use('Qt5Agg') # for using pyplot (pip install pyqt5)\r\nimport matplotlib.pyplot as plt\r\nfrom scipy import signal\r\nfrom scipy.signal import butter, filtfilt, sosfiltfilt\r\n\r\n# Pyriema... | [
[
"matplotlib.pyplot.gca",
"numpy.expand_dims",
"matplotlib.use",
"matplotlib.pyplot.ylim",
"matplotlib.pyplot.plot",
"matplotlib.pyplot.ioff",
"scipy.signal.butter",
"matplotlib.pyplot.clf",
"numpy.mean",
"matplotlib.pyplot.xlim",
"scipy.signal.sosfiltfilt",
"matplot... |
yage99/tensorflow | [
"c7fa71b32a3635eb25596ae80d007b41007769c4",
"be084bd7a4dd241eb781fc704f57bcacc5c9b6dd",
"be084bd7a4dd241eb781fc704f57bcacc5c9b6dd",
"be084bd7a4dd241eb781fc704f57bcacc5c9b6dd",
"be084bd7a4dd241eb781fc704f57bcacc5c9b6dd",
"be084bd7a4dd241eb781fc704f57bcacc5c9b6dd",
"be084bd7a4dd241eb781fc704f57bcacc5c9b6d... | [
"tensorflow/python/data/experimental/service/server_lib_test.py",
"tensorflow/compiler/mlir/tensorflow/tests/tf_saved_model/exported_python_args.py",
"tensorflow/python/kernel_tests/signal/spectral_ops_test.py",
"tensorflow/python/kernel_tests/confusion_matrix_test.py",
"tensorflow/python/keras/layers/einsu... | [
"# Copyright 2020 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.data.experimental.service.server_lib.DispatchServer",
"tensorflow.python.data.experimental.service.server_lib.WorkerServer",
"tensorflow.python.platform.test.main"
],
[
"tensorflow.compiler.mlir.tensorflow.tests.tf_saved_model.common.do_test",
"tensorflow.compat.v2.Tenso... |
evanloshin/CarND-Behavioral-Cloning-P3 | [
"22ec89cdea5257a10512f07b07fc4c074bc7c649"
] | [
"drive.py"
] | [
"import argparse\nimport base64\nfrom datetime import datetime\nimport os\nimport shutil\n\nimport numpy as np\nimport socketio\nimport eventlet\nimport eventlet.wsgi\nfrom PIL import Image\nfrom flask import Flask\nfrom io import BytesIO\n\nfrom keras.models import load_model\nimport h5py\nfrom keras import __vers... | [
[
"numpy.asarray"
]
] |
frederikschubert/rltime | [
"d1722ffd4cf7b4599655b8d9c64abc243919afc9"
] | [
"rltime/eval.py"
] | [
"\"\"\" Entry point for evaluating/rendering a trained policy. \"\"\"\n\nimport argparse\nimport json\nimport os\nimport numpy as np\nimport time\nimport datetime\n\nfrom rltime.general.config import load_config\nfrom rltime.general.utils import deep_dictionary_update\nfrom rltime.general.type_registry import get_r... | [
[
"numpy.min",
"numpy.median",
"numpy.max",
"numpy.std",
"numpy.mean",
"numpy.random.rand",
"numpy.array"
]
] |
apexrl/EBIL-torch | [
"8d257d5efa36f7c608085e34a7cdd3e996962d3f"
] | [
"rlkit/core/base_algorithm.py"
] | [
"import abc\nimport pickle\nimport time\nfrom collections import OrderedDict\nfrom copy import deepcopy\n\nimport gtimer as gt\nimport numpy as np\n\nfrom rlkit.core import logger, eval_util\nfrom rlkit.data_management.env_replay_buffer import EnvReplayBuffer\nfrom rlkit.data_management.path_builder import PathBuil... | [
[
"numpy.array",
"numpy.random.randint"
]
] |
VolkerH/gputools | [
"b8732c3cf82b96c6960497e6d82ce6b2bac463aa"
] | [
"gputools/convolve/minmax_filter.py"
] | [
"from __future__ import print_function, unicode_literals, absolute_import, division\nimport logging\n\nlogger = logging.getLogger(__name__)\n\nimport os\nimport numpy as np\nfrom gputools import OCLArray, OCLProgram, get_device\n\nfrom gputools.core.ocltypes import assert_bufs_type\nfrom gputools.utils.tile_iterato... | [
[
"numpy.ascontiguousarray",
"numpy.int32",
"numpy.ceil",
"numpy.isscalar",
"numpy.empty"
]
] |
domingoesteban/robolearn | [
"0d20125425c352b80ef2eeed1c0b11ab6497b11a",
"0d20125425c352b80ef2eeed1c0b11ab6497b11a"
] | [
"robolearn/torch/policies/tanh_gaussian_promp_multi_policy.py",
"robolearn/torch/policies/tanh_gaussian_composed_multi_policy.py"
] | [
"import math\nimport torch\nfrom torch import nn as nn\nfrom torch.distributions import Normal\nfrom robolearn.torch.core import PyTorchModule\nfrom robolearn.torch.utils.pytorch_util import np_ify\nfrom torch.nn.modules.normalization import LayerNorm\nimport robolearn.torch.utils.pytorch_util as ptu\nfrom robolear... | [
[
"torch.nn.BatchNorm1d",
"torch.sqrt",
"torch.sum",
"torch.nn.Sigmoid",
"torch.tanh",
"torch.nn.Linear",
"torch.exp",
"torch.log",
"torch.nn.modules.normalization.LayerNorm",
"torch.index_select",
"torch.batch_norm"
],
[
"torch.nn.BatchNorm1d",
"torch.isnan",... |
kcexn/singular-value-decomposition | [
"63e2a23f9f0db9aa361e338b8065d59b80f7649e"
] | [
"coded_distributed_computing.py"
] | [
"''' coded_distributed_computing\nThis module contains functions related to a study of the coded distributed computing model.\n\n'''\nimport numpy as np\n\ndef encode_matrix(A: np.matrix, G: np.matrix) -> np.matrix:\n ''' encode_matrix\n Parameters:\n ---\n A: np.matrix, input matrix to code.\n G: np... | [
[
"numpy.matmul"
]
] |
sanzgiri/MaatPy | [
"381a0d31f1afdd2c53b9ccbb410eb0df6b4b9965"
] | [
"maatpy/dataset.py"
] | [
"import warnings\nimport numpy as np\nimport pandas as pd\n\nfrom collections import Counter\n\nfrom sklearn.datasets import make_classification\nfrom sklearn.utils import check_X_y\nfrom sklearn.utils import Bunch\nfrom sklearn.preprocessing import LabelEncoder\nfrom imblearn.under_sampling.prototype_selection imp... | [
[
"pandas.read_csv",
"sklearn.datasets.make_classification",
"sklearn.utils.check_X_y",
"numpy.unique",
"sklearn.preprocessing.LabelEncoder"
]
] |
beesk135/ReID-Survey | [
"d1467c0ce5d3ca78640196360a05df9ff9f9f42a"
] | [
"evaluate/__init__.py"
] | [
"import torch \n\nfrom .eval_reid import eval_func\n\ndef euclidean_dist(x, y):\n m, n = x.size(0), y.size(0)\n xx = torch.pow(x, 2).sum(1, keepdim=True).expand(m, n)\n yy = torch.pow(y, 2).sum(1, keepdim=True).expand(n, m).t()\n dist = xx + yy\n dist.addmm_(1, -2, x, y.t())\n dist = dist.clamp(mi... | [
[
"torch.pow"
]
] |
xujin1184104394/coco-analyze | [
"fefe16025554dbf831e71d32d6601dd8f00286a8"
] | [
"analysisAPI/scoringErrors.py"
] | [
"## imports\nimport os, time\nimport numpy as np\nimport matplotlib.pyplot as plt\n\n# package imports \nfrom . import utilities\n\ndef scoringErrors( coco_analyze, oks, imgs_info, saveDir ):\n loc_dir = saveDir + '/scoring_errors'\n if not os.path.exists(loc_dir):\n os.makedirs(loc_dir)\n f = open(... | [
[
"matplotlib.pyplot.legend",
"numpy.sqrt",
"matplotlib.pyplot.title",
"numpy.linspace",
"matplotlib.pyplot.subplots",
"matplotlib.pyplot.savefig",
"matplotlib.pyplot.xlim",
"numpy.argmax",
"matplotlib.pyplot.grid",
"matplotlib.pyplot.close",
"numpy.argsort",
"matplot... |
sirjamesmeddel-gitty/intuition | [
"cd517e6b3b315a743eb4d0d0dc294e264ab913ce",
"cd517e6b3b315a743eb4d0d0dc294e264ab913ce",
"cd517e6b3b315a743eb4d0d0dc294e264ab913ce",
"cd517e6b3b315a743eb4d0d0dc294e264ab913ce"
] | [
"tests/core/test_configuration.py",
"intuition/api/datafeed.py",
"intuition/core/analyzes.py",
"tests/api/test_datafeed.py"
] | [
"'''\nTests for intuition.core.configuration\n'''\n\nimport unittest\nfrom nose.tools import raises\nimport dna.test_utils as test_utils\nimport pandas as pd\nimport intuition.core.configuration as configuration\nfrom dna.errors import DynamicImportFailed\nfrom intuition.errors import InvalidConfiguration\n\n\nclas... | [
[
"pandas.date_range"
],
[
"pandas.DataFrame"
],
[
"pandas.Series",
"pandas.datetime.date",
"pandas.DatetimeIndex",
"pandas.DataFrame",
"numpy.mean",
"pandas.datetime.strptime",
"pandas.datetools.BDay",
"pandas.datetools.MonthBegin",
"numpy.array"
],
[
"pa... |
rkripa/PS-FCN | [
"eb8ddbd60964830c06432a734a2cf6dce34f70f0"
] | [
"models/PS_FCN_run.py"
] | [
"import torch\nimport torch.nn as nn\nfrom torch.nn.init import kaiming_normal_\nfrom models import model_utils\n\nclass FeatExtractor(nn.Module):\n def __init__(self, batchNorm=False, c_in=3, other={}):\n super(FeatExtractor, self).__init__()\n self.other = other\n self.conv1 = model_utils.... | [
[
"torch.nn.functional.normalize",
"torch.Tensor",
"torch.cat",
"torch.nn.Conv2d",
"torch.split",
"torch.stack",
"torch.nn.init.kaiming_normal_"
]
] |
ComputationalMechanics/SurfaceTopography | [
"6751be427c89d526ef4857300409596c79119029",
"6751be427c89d526ef4857300409596c79119029",
"7dc7346cb9545326a3323fda0d402f254eae8c0e",
"6751be427c89d526ef4857300409596c79119029",
"7dc7346cb9545326a3323fda0d402f254eae8c0e"
] | [
"SurfaceTopography/Uniform/Filtering.py",
"test/test_reliability_cutoff.py",
"examples/bicubic_interpolation.py",
"test/IO/test_io.py",
"SurfaceTopography/Nonuniform/common.py"
] | [
"#\n# Copyright 2020-2021 Lars Pastewka\n# 2020-2021 Antoine Sanner\n#\n# ### MIT license\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 ... | [
[
"numpy.abs",
"numpy.fft.rfft",
"scipy.signal.get_window",
"numpy.fft.rfftfreq",
"numpy.arange",
"numpy.sqrt",
"numpy.real",
"numpy.where"
],
[
"numpy.isfinite",
"numpy.testing.assert_almost_equal",
"numpy.mean",
"numpy.testing.assert_allclose",
"numpy.array"... |
georgetown-analytics/DC-Bikeshare | [
"42676654d103cdaddfb76db76d1eece533251261",
"42676654d103cdaddfb76db76d1eece533251261"
] | [
"final_plots/read_aws.py",
"report_queries/dockless_trips_by_operator.py"
] | [
"import psycopg2\nimport psycopg2.extras\nimport pandas as pd\nimport os\nimport time\nfrom pathlib import Path\nfrom dotenv import load_dotenv\n\n\ndef read_only_connect_aws():\n env_path = 'env_readonly.env'\n load_dotenv(dotenv_path=env_path)\n host = \"bikeshare-restored.cs9te7lm3pt2.us-east-1.rds.amaz... | [
[
"pandas.read_sql"
],
[
"pandas.read_sql"
]
] |
daroari/pygmt | [
"e022851d62814a9255ed2bb63ae092b666b832b9"
] | [
"pygmt/tests/test_datasets_earth_relief.py"
] | [
"\"\"\"\nTest basic functionality for loading Earth relief datasets.\n\"\"\"\nimport numpy as np\nimport numpy.testing as npt\nimport pytest\nfrom pygmt.datasets import load_earth_relief\nfrom pygmt.exceptions import GMTInvalidInput\n\n\ndef test_earth_relief_fails():\n \"\"\"\n Make sure earth relief fails f... | [
[
"numpy.arange"
]
] |
minhmanho/rrdncnn | [
"f09ef7d92e31bfd43a548bb476970cfe38d32508"
] | [
"pytorch_ssim.py"
] | [
"import torch\r\nimport torch.nn.functional as F\r\nfrom torch.autograd import Variable\r\nimport numpy as np\r\nfrom math import exp\r\n\r\ndef gaussian(window_size, sigma):\r\n gauss = torch.Tensor([exp(-(x - window_size//2)**2/float(2*sigma**2)) for x in range(window_size)])\r\n return gauss/gauss.sum()\r\... | [
[
"torch.nn.functional.conv2d"
]
] |
kay-wong/DiscoBERT | [
"814c741e2a049de3afc489835e0df3ccf9fb4fe9"
] | [
"model/archival_gnns.py"
] | [
"# Graph Conv and Relational Graph Conv\nimport itertools\nimport torch\nfrom typing import List, Union\n\nimport dgl\nimport torch.nn as nn\nimport torch.nn.functional as F\nfrom allennlp.common import FromParams\nfrom allennlp.common import Registrable\nfrom allennlp.modules.encoder_base import _EncoderBase\nfrom... | [
[
"torch.nn.Dropout",
"torch.nn.ModuleList",
"torch.sum",
"torch.nn.Linear",
"torch.bmm",
"torch.stack"
]
] |
paigeco/VirtualGoniometer | [
"536e7e77fbb036ad8d777b42e751a0f3e80b8242"
] | [
"src/AngleMeasurement/RP1DClustering.py"
] | [
"import numpy as np\nfrom .PCASmallestEig import pca_smallest_eig, pca_smallest_eig_powermethod\nfrom .Withness import withness\nfrom .CalculateAngle import get_angle\n\n#RP1D clustering from\n#Han, Sangchun, and Mireille Boutin. \"The hidden structure of image datasets.\" 2015 IEEE International Conference on Imag... | [
[
"numpy.dot",
"numpy.reshape",
"numpy.linalg.norm",
"numpy.max",
"numpy.mean",
"numpy.argmin",
"numpy.random.rand",
"numpy.cross",
"numpy.zeros",
"numpy.sum"
]
] |
nipreps/mriqc | [
"e021008da0a2ef1c48e882baf932139a673349f9"
] | [
"mriqc/interfaces/anatomical.py"
] | [
"# emacs: -*- mode: python; py-indent-offset: 4; indent-tabs-mode: nil -*-\n# vi: set ft=python sts=4 ts=4 sw=4 et:\n#\n# Copyright 2021 The NiPreps Developers <nipreps@gmail.com>\n#\n# Licensed under the Apache License, Version 2.0 (the \"License\");\n# you may not use this file except in compliance with the Licen... | [
[
"scipy.ndimage.binary_erosion",
"numpy.issubdtype",
"numpy.all",
"numpy.max",
"numpy.zeros_like",
"numpy.mean",
"scipy.ndimage.binary_opening",
"numpy.ones_like",
"numpy.pad",
"scipy.ndimage.generate_binary_structure",
"numpy.asanyarray",
"numpy.min",
"numpy.med... |
GrumpyMeow/ownphotos-backend | [
"98d8e9136e9188009afe08657f943dba3df80ccb"
] | [
"api/util.py"
] | [
"import base64\nimport pickle\nimport itertools\n\nfrom scipy import linalg\nfrom sklearn.decomposition import PCA\nimport numpy as np\nfrom sklearn import cluster\nfrom sklearn import mixture\nfrom scipy.spatial import distance\nfrom sklearn.preprocessing import StandardScaler\n\n\nimport requests\n\nfrom config i... | [
[
"numpy.log",
"numpy.where",
"numpy.bincount"
]
] |
matham/Ceed | [
"b81a14a6b8211e5f4582418ddea34c951ab2667e"
] | [
"ceed/tests/test_app/test_stage.py"
] | [
"import os\nimport sys\nimport math\nfrom contextlib import contextmanager\nfrom math import isclose\nimport numpy as np\nimport pytest\n\nimport ceed\nfrom .examples.stages import create_test_stages, make_stage, StageWrapper, \\\n stage_classes, assert_stages_same\nfrom typing import Type, List, Union\nfrom cee... | [
[
"numpy.asarray",
"numpy.arange",
"numpy.all",
"numpy.array",
"numpy.sum",
"numpy.isin"
]
] |
igorlucci/koalas | [
"8803344d620261981003175bd1edc3c4120b84e2"
] | [
"databricks/koalas/base.py"
] | [
"#\n# Copyright (C) 2019 Databricks, 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/licenses/LICENSE-2.0\n#\n# Unless required by applicable la... | [
[
"numpy.timedelta64",
"pandas.api.types.is_list_like"
]
] |
abhi526691/Covid-Guard | [
"9c050ef44201c01f512169ffb146ad0da5278ec1",
"9c050ef44201c01f512169ffb146ad0da5278ec1"
] | [
"main.py",
"video_recorder.py"
] | [
"# import the necessary packages\r\nfrom tensorflow.keras.preprocessing.image import img_to_array\r\nfrom tensorflow.keras.applications.mobilenet_v2 import preprocess_input\r\nfrom tensorflow.keras.models import load_model\r\nfrom imutils.video import VideoStream,FileVideoStream\r\nimport imutils\r\nimport numpy as... | [
[
"tensorflow.keras.models.load_model",
"numpy.random.seed",
"tensorflow.keras.applications.mobilenet_v2.preprocess_input",
"numpy.ones",
"numpy.argmax",
"numpy.array",
"tensorflow.keras.preprocessing.image.img_to_array"
],
[
"numpy.array"
]
] |
fmamitrotta/pyNastran | [
"90f957887a4f68f8e58b07c15e1ac69c66b9c6f4"
] | [
"pyNastran/op2/tables/geom/ept.py"
] | [
"\"\"\"\ndefines readers for BDF objects in the OP2 EPT/EPTS table\n\"\"\"\n#pylint: disable=C0103,R0914\nfrom __future__ import annotations\nfrom struct import unpack, Struct\nfrom functools import partial\nfrom typing import Tuple, List, TYPE_CHECKING\n\nimport numpy as np\n\n#from pyNastran import is_release\nfr... | [
[
"numpy.frombuffer",
"numpy.where"
]
] |
FelipeH92/Task-Space-Control-Vision | [
"77d9f709d7cb0afb50ef9baf6ba39304aca445e5",
"77d9f709d7cb0afb50ef9baf6ba39304aca445e5"
] | [
"Experiments/src/Task Control - Python/UR5Class.py",
"Experiments/src/Task Control - Python/trajectoryCheck.py"
] | [
"#!/usr/bin/python\r\n# -*- coding: utf-8 -*-\r\n## @package UR5\r\n# Documentação para o pacote de classes UR5.\r\n#\r\n# Documentação do código produzido para controle do manipulador UR5 e geração e controle de suas posições.\r\n# Cada código aqui documentado possui uma breve descrição de sua função, suas entr... | [
[
"numpy.dot",
"numpy.radians",
"numpy.sqrt",
"numpy.asarray",
"numpy.nan_to_num",
"numpy.arctan2",
"numpy.all",
"numpy.concatenate",
"numpy.mean",
"numpy.any",
"numpy.hstack",
"numpy.eye",
"numpy.sin",
"scipy.signal.butter",
"numpy.real",
"scipy.signa... |
piojanu/tf_utils | [
"169bd3334dd11954cf8f411f2c918f76cd609fab"
] | [
"samples/mnist_vae.py"
] | [
"import argparse\nimport io\nimport os.path\n\nimport matplotlib.pyplot as plt\nimport numpy as np\nimport tensorflow as tf\nimport tensorflow_probability as tfp\nfrom tqdm import tqdm\n\nfrom tf_utils import AttrDict, attrdict_from_yaml, lazy_property_with_scope, share_variables\n\ntfd = tfp.distributions\ntfl = t... | [
[
"tensorflow.convert_to_tensor",
"tensorflow.norm",
"numpy.product",
"tensorflow.reduce_mean",
"tensorflow.zeros",
"tensorflow.summary.image",
"tensorflow.train.MonitoredSession",
"tensorflow.reshape",
"matplotlib.pyplot.subplots",
"tensorflow.keras.datasets.mnist.load_data"... |
pkyIntelligence/FasterRCNN | [
"230953938efdba8f8c127fcc0bb746fcce8d9463",
"230953938efdba8f8c127fcc0bb746fcce8d9463"
] | [
"FasterRCNN/layers/roi_align.py",
"FasterRCNN/data/samplers/grouped_batch_sampler.py"
] | [
"import torch\nimport math\n\nfrom torch import nn\nfrom ..utils.utils import point_interpolate\n\n\nclass ROIAlign(nn.Module):\n def __init__(self, output_size, spatial_scale, sampling_ratio):\n \"\"\"\n Args:\n output_size (tuple): h, w\n spatial_scale (float): scale the inp... | [
[
"torch.Tensor",
"torch.split"
],
[
"numpy.asarray",
"numpy.unique"
]
] |
dhingratul/RNN | [
"9e1ac582dbf8251769817b34fc9d791fa8c20376"
] | [
"Memory_RNN.py"
] | [
"#!/usr/bin/env python3\n# -*- coding: utf-8 -*-\n\"\"\"\nCreated on Wed May 24 11:28:50 2017\n\n@author: dhingratul\n\"\"\"\nfrom __future__ import print_function, division\nimport numpy as np\nimport tensorflow as tf\nimport helpers\n# hyperparams\nnum_epochs = 10000\ntotal_series_length = 100\ntruncated_backprop... | [
[
"tensorflow.matmul",
"tensorflow.nn.softmax",
"tensorflow.concat",
"tensorflow.train.AdagradOptimizer",
"tensorflow.unstack",
"tensorflow.reduce_mean",
"tensorflow.reshape",
"tensorflow.placeholder",
"tensorflow.global_variables_initializer",
"tensorflow.nn.sparse_softmax_c... |
ashok-arjun/few-shot-ssl-public | [
"3cf522031aa40b4ffb61e4693d0b48fdd5669276"
] | [
"fewshot/data/compress_tiered_imagenet.py"
] | [
"# Copyright (c) 2018 Mengye Ren, Eleni Triantafillou, Sachin Ravi, Jake Snell,\n# Kevin Swersky, Joshua B. Tenenbaum, Hugo Larochelle, Richars S. Zemel.\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 d... | [
[
"numpy.load",
"numpy.savez"
]
] |
selimfirat/pysad | [
"dff2ff38258eb8a85c9d34cf5f0b876fc1dc9ede",
"dff2ff38258eb8a85c9d34cf5f0b876fc1dc9ede"
] | [
"tests/transform/preprocessing/test_instance_unit_norm_scaler.py",
"pysad/models/loda.py"
] | [
"\n\ndef test_instance_unit_norm_scaler():\n import numpy as np\n from pysad.transform.preprocessing import InstanceUnitNormScaler\n\n X = np.random.rand(100, 25)\n scaler = InstanceUnitNormScaler()\n\n scaled_X = scaler.fit_transform(X)\n assert np.all(np.isclose(np.linalg.norm(scaled_X, axis=1),... | [
[
"numpy.linalg.norm",
"numpy.random.rand"
],
[
"numpy.log",
"numpy.sqrt",
"numpy.ones",
"numpy.int",
"numpy.random.permutation",
"numpy.random.randn",
"numpy.searchsorted",
"numpy.histogram",
"numpy.sum",
"numpy.zeros"
]
] |
corganhejijun/frontal-trans | [
"1509babf2447a53a772703b09cb6a2daec6968a7"
] | [
"test_sample.py"
] | [
"# -*- coding: utf-8 -*- \nimport os\nimport cv2\nfrom scipy import misc\nfrom PIL import Image\n\nsample_path = 'datasets/celeb_train/lfw_trans'\ndest_path = sample_path + \"/../dest\"\nmiddleSize = 64\nimgSize = 256\nkernel_size = (5, 5)\nsigma = 5\n\nif not os.path.exists(dest_path):\n os.mkdir(dest_path)\n\n... | [
[
"scipy.misc.imresize"
]
] |
YusrilHasanuddin/bangkit-capstone-CAP0166 | [
"51742f7af47fa285154793a6ea74de1d78d945b3"
] | [
"ml-project/extract_face_yusril.py"
] | [
"import sys\nimport os\nimport traceback\nfrom PIL import Image\nfrom facenet_pytorch import MTCNN\nimport matplotlib.image as mpimg\nimport numpy as np\n\n\ndef detect_faces(image_path):\n mtcnn = MTCNN(margin=20, keep_all=True,\n post_process=False, device='cuda:0')\n image = image_path\n ... | [
[
"matplotlib.image.imread"
]
] |
sailab-code/SAILenv | [
"e202be04de468a58e58ae858693245f5556c3597"
] | [
"example_unity_socket.py"
] | [
"#\n# Copyright (C) 2020 Enrico Meloni, Luca Pasqualini, Matteo Tiezzi\n# University of Siena - Artificial Intelligence Laboratory - SAILab\n#\n#\n# SAILenv is licensed under a MIT license.\n#\n# You should have received a copy of the license along with this\n# work. If not, see <https://en.wikipedia.org/wiki/MIT_L... | [
[
"numpy.reshape",
"numpy.max",
"numpy.zeros"
]
] |
georgeAccnt-GH/Azure2019 | [
"5c9774b644d3ea15590d72d3de9363df72abf7ab"
] | [
"src/AzureFunctions/ComputeGradient/AzureUtilities.py"
] | [
"import numpy as np\nimport segyio\nimport subprocess\nimport os, h5py\nfrom scipy import interpolate\nfrom devito import Eq, Operator\nfrom azure.storage.blob import BlockBlobService, PublicAccess\n\nblob_service = BlockBlobService(account_name='', account_key='')\n\n###############################################... | [
[
"scipy.interpolate.splrep",
"numpy.abs",
"numpy.linspace",
"numpy.min",
"numpy.arange",
"scipy.interpolate.splev",
"numpy.concatenate",
"numpy.max",
"numpy.ones",
"numpy.fromstring",
"numpy.zeros"
]
] |
TwinIsland/img2java | [
"6b6788daa0a97acb1e455ead9d7bd09d7d881ab2"
] | [
"treat.py"
] | [
"from matplotlib import pyplot as plt\nimport numpy as np\nimport cv2\nfrom scipy import stats\nimport translate\nfrom skimage import transform\n\n#####################################\nimgData = cv2.imread('van.jpg',0)\ncompressRate = 0.4\n#####################################\n\nimgData = np.array(imgData)\nshape... | [
[
"matplotlib.pyplot.imshow",
"numpy.array",
"scipy.stats.zscore",
"matplotlib.pyplot.show"
]
] |
MinhTuDo/MD-MOENAS | [
"edd6ec8c3f89cfbe9674873425c5056e72899edb"
] | [
"procedure/problem/efficiency_performance/mo_nats.py"
] | [
"from procedure.problem.base import nats as base\n\nimport numpy as np\n\nclass EfficiencyAccuracyNATS(base.NATS):\n def __init__(self, efficiency, **kwargs):\n super().__init__(n_obj=2, **kwargs)\n self.msg += efficiency + '={:.3f}, ' + 'valid-error' + '={:.3f}'\n self.efficiency = efficien... | [
[
"numpy.row_stack",
"numpy.mean",
"numpy.column_stack"
]
] |
Gaskell-1206/MSI_vs_MSS_Classification | [
"be6fd8a6961624367b2bb0e1299219e940f6f418"
] | [
"Step2_Training_MIL/train_MIL_classification_trained_cnn_models.py"
] | [
"# Run MIL classification use pretrained CNN models\n# Reference: 1.Campanella, G. et al. Clinical-grade computational pathology using weakly supervised\n# deep learning on whole slide images. Nat Med 25, 1301–1309 (2019).\n# doi:10.1038/s41591-019-0508-1. Available from http://www.nature.com/... | [
[
"sklearn.metrics.roc_auc_score",
"torch.nn.CrossEntropyLoss",
"pandas.read_csv",
"torch.Tensor",
"numpy.logical_and",
"torch.utils.data.DataLoader",
"numpy.lexsort",
"torch.no_grad",
"numpy.equal",
"torch.utils.tensorboard.SummaryWriter",
"numpy.not_equal",
"sklearn... |
siddhantwahal/scipy | [
"411fbbda0f942fcce3e4b314efb11c4553baaa7c"
] | [
"scipy/stats/_distn_infrastructure.py"
] | [
"#\n# Author: Travis Oliphant 2002-2011 with contributions from\n# SciPy Developers 2004-2011\n#\nfrom scipy._lib._util import getfullargspec_no_self as _getfullargspec\n\nimport sys\nimport keyword\nimport re\nimport types\nimport warnings\nimport inspect\nfrom itertools import zip_longest\n\nfrom scipy... | [
[
"scipy.special.rel_entr",
"numpy.sqrt",
"scipy.special.ive",
"numpy.asarray",
"numpy.cumsum",
"numpy.all",
"numpy.max",
"scipy._lib.doccer.docformat",
"numpy.any",
"numpy.place",
"scipy.misc.derivative",
"scipy.special.entr",
"scipy.special.chndtr",
"numpy.a... |
saikrishna-pallerla/efficientdet-pytorch | [
"dc7b790f537d28476a26af6f793acc4757becd0d"
] | [
"effdet/data/transforms.py"
] | [
"\"\"\" COCO transforms (quick and dirty)\n\nHacked together by Ross Wightman\n\"\"\"\nimport torch\nfrom PIL import Image\nimport numpy as np\nimport random\nimport math\n\nIMAGENET_DEFAULT_MEAN = (0.485, 0.456, 0.406)\nIMAGENET_DEFAULT_STD = (0.229, 0.224, 0.225)\nIMAGENET_INCEPTION_MEAN = (0.5, 0.5, 0.5)\nIMAGEN... | [
[
"numpy.expand_dims",
"numpy.clip",
"torch.from_numpy",
"numpy.stack",
"numpy.moveaxis",
"numpy.array"
]
] |
jtwhite79/MetPy | [
"8f1880be1ee98c17cd00ae556324386d2a6301ac"
] | [
"metpy/calc/tests/test_basic.py"
] | [
"# Copyright (c) 2008-2015 MetPy Developers.\n# Distributed under the terms of the BSD 3-Clause License.\n# SPDX-License-Identifier: BSD-3-Clause\n\nimport numpy as np\nfrom numpy.testing import assert_array_equal\n\nfrom metpy.units import units\nfrom metpy.testing import assert_almost_equal, assert_array_almost_e... | [
[
"numpy.testing.assert_array_equal",
"numpy.array",
"numpy.sqrt",
"numpy.ma.array"
]
] |
LBJ-Wade/GALLUMI_public | [
"4529ab32ccfc281e5976f482fe556b672b8f464f"
] | [
"Scripts/Plotting/Posteriors_cosmo_model1/Posteriors_cosmo_model1_alternative_dust.py"
] | [
"import numpy as np\nfrom matplotlib import pyplot as plt\nimport glob\nfrom matplotlib import patches as mpatches\nimport scipy.ndimage\nfrom scipy.interpolate import PchipInterpolator\nplt.style.use(\"../template.mplstyle\")\n\n# purple - green - darkgoldenrod - blue - red\ncolors = ['purple', '#306B37', 'darkgol... | [
[
"matplotlib.patches.Patch",
"numpy.log",
"matplotlib.colors.to_rgb",
"numpy.linspace",
"numpy.cumsum",
"matplotlib.pyplot.savefig",
"numpy.transpose",
"matplotlib.pyplot.subplot",
"scipy.interpolate.PchipInterpolator",
"numpy.histogram2d",
"numpy.searchsorted",
"num... |
Yugeeth/chat-bot | [
"3198fb160f743c7be1f377d2febb889423da8c06"
] | [
"train.py"
] | [
"import numpy as np\r\nimport random\r\nimport json\r\n\r\nimport torch\r\nimport torch.nn as nn\r\nfrom torch.utils.data import Dataset, DataLoader\r\n\r\nfrom nltk_utils import bag_of_words, tokenize, stem\r\nfrom model import NeuralNet\r\n\r\nwith open('intents.json', 'r') as f:\r\n intents = json.load(f)\r\n... | [
[
"torch.nn.CrossEntropyLoss",
"torch.utils.data.DataLoader",
"torch.cuda.is_available",
"numpy.array",
"torch.save"
]
] |
TurkuNLP/paraphrase-classification | [
"625f0cf5223ecff9d25c2a4f558ca39fa5ecc794"
] | [
"para_averaging.py"
] | [
"import torch.nn.functional as F\nimport torch\nimport para_model\n\nclass ParaAvgModel(para_model.PARAModel):\n\n def __init__(self, **args):\n super().__init__(**args)\n # self.drop_layer=torch.nn.Dropout(p=0.2)\n self.cls_layer=torch.nn.Linear(self.bert.config.hidden_size*5, args['num_cla... | [
[
"torch.nn.Linear",
"torch.cat"
]
] |
joewalter/mne-python | [
"b0629bea7f5e8e94d9e2e889f45a35f9657e6dbc",
"b0629bea7f5e8e94d9e2e889f45a35f9657e6dbc",
"b0629bea7f5e8e94d9e2e889f45a35f9657e6dbc",
"b0629bea7f5e8e94d9e2e889f45a35f9657e6dbc",
"b0629bea7f5e8e94d9e2e889f45a35f9657e6dbc"
] | [
"mne/viz/circle.py",
"mne/io/meas_info.py",
"mne/gui/tests/test_file_traits.py",
"mne/beamformer/tests/test_lcmv.py",
"mne/io/tests/test_reference.py"
] | [
"\"\"\"Functions to plot on circle as for connectivity\n\"\"\"\nfrom __future__ import print_function\n\n# Authors: Alexandre Gramfort <alexandre.gramfort@telecom-paristech.fr>\n# Denis Engemann <denis.engemann@gmail.com>\n# Martin Luessi <mluessi@nmr.mgh.harvard.edu>\n#\n# License: Simplified BSD... | [
[
"numpy.linspace",
"numpy.cumsum",
"matplotlib.pyplot.get_cmap",
"numpy.max",
"numpy.zeros_like",
"numpy.any",
"numpy.where",
"matplotlib.patches.PathPatch",
"numpy.unique",
"numpy.tril_indices",
"numpy.size",
"matplotlib.pyplot.subplot",
"numpy.diff",
"numpy... |
jsaez8/qtt | [
"fa6497ace86a255f33a2192ba01d063d07d6895e"
] | [
"src/qtt/instrument_drivers/virtual_awg.py"
] | [
"# -*- coding: utf-8 -*-\n\"\"\"\nCreated on Wed Aug 31 13:04:09 2016\n\n@author: diepencjv\n\"\"\"\n\n# %%\nimport numpy as np\nimport scipy.signal\nimport logging\nimport warnings\n\nimport qcodes\nfrom qcodes import Instrument\nfrom qcodes.plots.pyqtgraph import QtPlot\nfrom qcodes.data.data_array import DataArr... | [
[
"numpy.arange",
"numpy.tile",
"numpy.ones",
"numpy.ceil",
"numpy.floor",
"numpy.array",
"numpy.zeros",
"numpy.roll"
]
] |
MarkusHaak/fieldbioinformatics | [
"3d291477a3d84968816c8e57e6078fc80135f422"
] | [
"artic/deprecated/plot_amplicon_depth.py"
] | [
"#!/usr/bin/env python3\n\n\"\"\"\nPlot the mean read depth per amplicon.\n\nThis has been written for use in the ARTIC pipeline so there are no file checks - it assumes the following:\n * the primer scheme is in ARTIC format\n * the input depth files are in the format: `chrom\\treadgroup\\tposition\\tdepth\n * rea... | [
[
"matplotlib.pyplot.legend",
"pandas.concat",
"pandas.read_csv",
"matplotlib.use",
"matplotlib.pyplot.savefig",
"pandas.cut",
"matplotlib.pyplot.close",
"matplotlib.pyplot.xticks"
]
] |
cperales/pygsom | [
"ac4d4818f441d862cb5183e1d2ea814e3f805759"
] | [
"gsom.py"
] | [
"# -*- coding: utf-8 -*-\n\"\"\"\nThe MIT License (MIT)\n\nCopyright (c) 2015 Philipp Ludwig <git@philippludwig.net>\n\nPermission is hereby granted, free of charge, to any person obtaining a copy\nof this software and associated documentation files (the \"Software\"), to deal\nin the Software without restriction, ... | [
[
"scipy.array"
]
] |
eEcoLiDAR/lcMacroPipeline | [
"91709f93ef53a3e453f0ce967e1094688688f684"
] | [
"tests/test_grid.py"
] | [
"from pathlib import Path\nimport unittest\nimport numpy as np\nimport pylas\n\nfrom laserfarm.grid import Grid\n\ntry:\n import matplotlib\n matplotlib_available = True\nexcept ModuleNotFoundError:\n matplotlib_available = False\n\nif matplotlib_available:\n matplotlib.use('Agg')\n import matplotlib... | [
[
"matplotlib.pyplot.scatter",
"matplotlib.use",
"numpy.rint",
"matplotlib.pyplot.show",
"matplotlib.pyplot.savefig",
"matplotlib.pyplot.plot",
"numpy.all",
"numpy.column_stack",
"numpy.array",
"numpy.testing.assert_allclose",
"matplotlib.pyplot.figure"
]
] |
madhawav/plan2scene | [
"cc3481f503fc096d1a50ea4fbcc668b2a3b75fb5",
"cc3481f503fc096d1a50ea4fbcc668b2a3b75fb5"
] | [
"code/src/plan2scene/texture_gen/custom_ops/noise.py",
"code/src/plan2scene/texture_prop/graph_util.py"
] | [
"# Code adapted from https://github.com/henzler/neuraltexture/blob/master/code/custom_ops/noise/noise.py\n\nfrom torch import nn\nfrom torch.autograd import Function\nimport plan2scene.texture_gen.utils.neural_texture_helper as utils_nt\nimport noise_cuda\nimport torch\nimport numpy as np\nfrom torch.autograd impor... | [
[
"torch.zeros_like"
],
[
"torch.tensor",
"torch.zeros",
"torch.cat"
]
] |
liloganle/Reinforcement-Learning | [
"29ffb74a1c8e506c544245c9aff37e958e503f26",
"29ffb74a1c8e506c544245c9aff37e958e503f26",
"29ffb74a1c8e506c544245c9aff37e958e503f26"
] | [
"Chapter9/Figure9-1.py",
"Chapter8/Figure8-8.py",
"Chapter5/Figure5-1.py"
] | [
"# -*- coding:utf-8 -*-\n\nimport numpy as np\nfrom tqdm import tqdm\nimport matplotlib.pyplot as plt\n\n\nclass RandomWalk(object):\n def __init__(self, num_states=1000, groups=10, alpha=2e-5):\n self.num_states = num_states # the number of states\n self.groups = groups ... | [
[
"matplotlib.pyplot.legend",
"matplotlib.pyplot.figure",
"numpy.arange",
"numpy.linalg.norm",
"matplotlib.pyplot.savefig",
"matplotlib.pyplot.plot",
"numpy.random.randint",
"matplotlib.pyplot.close",
"numpy.random.binomial",
"matplotlib.pyplot.xlabel",
"matplotlib.pyplot... |
timelyportfolio/bokeh | [
"6cecb7211277b9d838039d0eb15e50a10f9ac3d1",
"6cecb7211277b9d838039d0eb15e50a10f9ac3d1",
"a976a85535cf137c6238ce9e90b41ab14ae8ce22",
"a976a85535cf137c6238ce9e90b41ab14ae8ce22",
"a976a85535cf137c6238ce9e90b41ab14ae8ce22",
"a976a85535cf137c6238ce9e90b41ab14ae8ce22"
] | [
"sphinx/source/tutorial/solutions/les_mis.py",
"examples/glyphs/prim_server.py",
"bokeh/charts/builder/tests/test_area_builder.py",
"bokeh/properties.py",
"examples/plotting/file/ajax_source.py",
"tests/glyphs/Text.py"
] | [
"import numpy as np\n\nfrom bokeh.plotting import figure, output_file, show\nfrom bokeh.models import HoverTool, ColumnDataSource\nfrom bokeh.sampledata.les_mis import data\n\n# EXERCISE: try out different sort orders for the names\nnodes = data['nodes']\nnames = [node['name'] for node in sorted(data['nodes'], key=... | [
[
"numpy.empty"
],
[
"numpy.arange"
],
[
"pandas.DataFrame",
"numpy.testing.assert_array_equal",
"numpy.array",
"numpy.zeros",
"numpy.testing.assert_array_almost_equal"
],
[
"numpy.array"
],
[
"numpy.random.random"
],
[
"numpy.linspace"
]
] |
aristoteleo/scribe-py | [
"ea28d2b588f8648b9ce1679fe18c3142aee2aa58"
] | [
"Scribe/other_estimators.py"
] | [
"import pandas\nimport numpy as np\nfrom multiprocessing import Pool\n\n\ndef __individual_corr(id1, id2, x, y):\n return (id1, id2, corr(x, y)[0])\n\n\ndef __individual_mi(id1, id2, x, y):\n return (id1, id2, mi(x, y))\n\n\ndef corr(self, number_of_processes=1):\n \"\"\"Calculate pairwise correlation over... | [
[
"pandas.DataFrame"
]
] |
frankilepro/LiTeFlow | [
"d07105ea00ad29b701e1b100d9cda2297eef19de"
] | [
"liteflow/input.py"
] | [
"\"\"\"Utilities for input pipelines.\"\"\"\n\nimport tensorflow as tf\n\n\ndef shuffle(tensors,\n capacity=32,\n min_after_dequeue=16,\n num_threads=1,\n dtypes=None,\n shapes=None,\n seed=None,\n shared_name=None,\n name='shuf... | [
[
"tensorflow.train.QueueRunner",
"tensorflow.train.add_queue_runner",
"tensorflow.RandomShuffleQueue",
"tensorflow.name_scope",
"tensorflow.train.batch"
]
] |
Nickwangpeng/tsfresh | [
"48118627d9d4644906613e25b077ce2ec82ca2f9"
] | [
"tsfresh/feature_selection/relevance.py"
] | [
"# -*- coding: utf-8 -*-\n# This file as well as the whole tsfresh package are licenced under the MIT licence (see the LICENCE.txt)\n# Maximilian Christ (maximilianchrist.com), Blue Yonder Gmbh, 2016\n\"\"\"\nContains a feature selection method that evaluates the importance of the different extracted features. To d... | [
[
"pandas.concat",
"pandas.Series"
]
] |
moonieann/welib | [
"0e430ad3ca034d0d2d60bdb7bbe06c947ce08f52",
"0e430ad3ca034d0d2d60bdb7bbe06c947ce08f52",
"0e430ad3ca034d0d2d60bdb7bbe06c947ce08f52",
"0e430ad3ca034d0d2d60bdb7bbe06c947ce08f52",
"0e430ad3ca034d0d2d60bdb7bbe06c947ce08f52",
"0e430ad3ca034d0d2d60bdb7bbe06c947ce08f52",
"0e430ad3ca034d0d2d60bdb7bbe06c947ce08f5... | [
"welib/FEM/reduction.py",
"welib/FEM/utils.py",
"welib/tools/external/setup.py",
"welib/fast/olaf.py",
"welib/tools/spectral.py",
"welib/FEM/fem_beam.py",
"welib/weio/tecplot_file.py"
] | [
"import numpy as np\n\nfrom welib.system.eva import eig\n\n\ndef CraigBampton(MM, KK, Ileader, nModesCB=None, Ifollow=None, F=None, DD=None, fullModesOut=False): \n \"\"\"\n Performs the CraigBampton (CB) reduction of a system given some input master dofs index\n and a number of modes. Reduced matrices, an... | [
[
"numpy.diag",
"numpy.ix_",
"numpy.sqrt",
"numpy.asarray",
"numpy.arange",
"numpy.eye",
"numpy.set_printoptions",
"numpy.setdiff1d",
"numpy.linalg.lstsq",
"numpy.block",
"numpy.transpose",
"numpy.array",
"numpy.zeros"
],
[
"numpy.asarray",
"numpy.arra... |
c4dt/mlbench-core | [
"8a5cf6e00ff4535b2aea23b213241858a5ee5f00"
] | [
"mlbench_core/optim/pytorch/fp_optimizers.py"
] | [
"# import ctypes\nimport logging\nimport math\n\nimport torch\nimport torch.distributed as dist\nfrom torch.nn.utils import clip_grad_norm_\n\nfrom mlbench_core.utils.pytorch.distributed import (\n AllReduceAggregation,\n AllReduceAggregationHVD,\n)\n\ntry:\n from apex.optimizers import FusedAdam\n from... | [
[
"torch.nn.utils.clip_grad_norm_",
"torch.device",
"torch.distributed.get_world_size",
"torch.nn.Parameter"
]
] |
yj1990/sec_mmf | [
"72a8c0d5a6aadb4362c07a5606c70e51b08a53cd"
] | [
"secmmf/mmf_data_loader/form_parsers.py"
] | [
"import pandas as pd\nimport bs4 as bs\nimport untangle as ut\nimport requests\nimport urllib.request as rq\nfrom collections import OrderedDict\n\nfrom secmmf.mmf_data_loader.utils import get_edgar_url\n\nclass N_MFP2:\n\n def __init__(self):\n self.select_cols()\n\n def born(self, tag):\n # if... | [
[
"pandas.wide_to_long",
"pandas.DataFrame"
]
] |
wjwainwright/Capstone | [
"a2ea661079ece6ff5008f4399b3f0f6d32c598d3"
] | [
"IsoFit.py"
] | [
"try:\n runCount += 1\nexcept:\n isoIn = False\n clIn = False\n cataIn = False\n closePlots = False\n resultsIn = False\n clusterList = []\n clusters=[]\n isochrones = []\n isoList = []\n catalogue = []\n runCount = 1\n\nclass resultClusterObj:\n def __init__(self,cl):\n ... | [
[
"matplotlib.pyplot.legend",
"numpy.polyfit",
"numpy.amax",
"numpy.sqrt",
"numpy.linspace",
"numpy.arctan",
"matplotlib.colors.to_rgba",
"numpy.asarray",
"numpy.vstack",
"matplotlib.pyplot.get_cmap",
"matplotlib.pyplot.axes",
"matplotlib.pyplot.plot",
"numpy.max"... |
aripekka/tbcalc | [
"a0337db245f5391bfa9a42123994832c299b1fbe"
] | [
"tests/test_tensor_transform.py"
] | [
"# -*- coding: utf-8 -*-\n\"\"\"\nTests for the tensor transform functions. Run with pytest.\n\nCreated on Sat May 9 00:09:00 2020\n\n@author: aripekka\n\"\"\"\n\nimport sys\nimport os.path\nimport numpy as np\n\nsys.path.insert(1, os.path.join(os.path.dirname(__file__),'..'))\n\nfrom tbcalc.transverse_deformation ... | [
[
"numpy.sqrt",
"numpy.linspace",
"numpy.isnan",
"numpy.finfo",
"numpy.arctan2",
"numpy.meshgrid"
]
] |
liyunze-coding/Trigger-Me-Elmo-2 | [
"6950ffa4bfd264e213626f1ab3cff249fbab36da"
] | [
"app.py"
] | [
"from flask import Flask, render_template, request, jsonify\nimport base64\nimport logging\nimport numpy as np\nfrom deepface import DeepFace\nfrom PIL import Image\nfrom io import BytesIO\nimport subprocess\nimport os\nimport cv2\nimport random\nimport webbrowser\n\napp = Flask(__name__)\nlog = logging.getLogger('... | [
[
"numpy.array"
]
] |
pyrito/SpeechSplit | [
"ee70ee77e54d5b7cd1b39e7bef1cb96ae78f8beb"
] | [
"solver.py"
] | [
"from torch.utils.tensorboard.summary import hparams\nfrom model import Generator_3 as Generator\nfrom model import InterpLnr\nimport matplotlib.pyplot as plt\nimport torch\nimport torch.nn.functional as F\nimport numpy as np\nimport os\nimport time\nimport datetime\nimport pickle\n\nfrom utils import pad_seq_to_2,... | [
[
"numpy.hstack",
"numpy.pad",
"torch.cat",
"torch.load",
"numpy.squeeze",
"torch.zeros_like",
"torch.from_numpy",
"torch.tensor",
"torch.nn.functional.mse_loss",
"numpy.mean",
"torch.utils.tensorboard.SummaryWriter",
"torch.cuda.is_available",
"torch.no_grad"
]... |
snsnlou/mars | [
"6b8eec162eccc8bb980a98ca2cf1e6a4b866d302",
"6b8eec162eccc8bb980a98ca2cf1e6a4b866d302",
"6b8eec162eccc8bb980a98ca2cf1e6a4b866d302",
"6b8eec162eccc8bb980a98ca2cf1e6a4b866d302",
"6b8eec162eccc8bb980a98ca2cf1e6a4b866d302"
] | [
"mars/dataframe/datastore/tests/test_datastore_execute.py",
"mars/tensor/datasource/diag.py",
"mars/dataframe/indexing/setitem.py",
"mars/tensor/datasource/eye.py",
"mars/tensor/base/isin.py"
] | [
"# 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/licenses/LICENSE-2.0\n#\n# Unless required by appl... | [
[
"pandas.concat",
"numpy.random.choice",
"pandas.RangeIndex",
"numpy.arange",
"pandas.testing.assert_frame_equal",
"numpy.random.rand",
"pandas.read_sql"
],
[
"numpy.cumsum"
],
[
"numpy.isnan",
"pandas.api.types.is_scalar",
"pandas.api.types.is_list_like",
"n... |
candleinwindsteve/Stratipy | [
"ea505df1e4830141c590922d654edfbde498b924",
"ea505df1e4830141c590922d654edfbde498b924"
] | [
"stratipy/filtering_diffusion.py",
"stratipy/nbs_cluster.py"
] | [
"#!/usr/bin/env python\n# coding: utf-8\nimport sys\nimport numpy as np\nimport scipy.sparse as sp\nfrom scipy.sparse.linalg import norm\nfrom scipy.io import loadmat, savemat\nfrom nbs_class import Ppi, Patient\nfrom subprocess import call\n# import h5py\nimport os\nimport glob\nimport time\nimport datetime\n\n# N... | [
[
"scipy.sparse.csc_matrix",
"scipy.sparse.eye",
"numpy.asarray",
"numpy.arange",
"numpy.isnan",
"scipy.io.loadmat",
"numpy.dstack",
"scipy.sparse.linalg.norm",
"numpy.zeros_like",
"numpy.argpartition",
"scipy.sparse.vstack",
"scipy.sparse.lil_matrix.transpose",
"... |
MohammadWasil/Self-Driving-Car | [
"9ef5b77e1268623c11e4c39d5c8e1e990caee273",
"9ef5b77e1268623c11e4c39d5c8e1e990caee273"
] | [
"Self Driving Car/Python with Tensorflow/driveSDC.py",
"Self Driving Car/Python with Tensorflow/CNN_Model.py"
] | [
"import socket\r\n\r\nfrom tensorflow.keras.models import load_model\r\n\r\n\r\nfrom PIL import ImageGrab\r\nimport numpy as np\r\nimport cv2\r\nimport os\r\n\r\n#Load the model.\r\nmodel = load_model(r\"D:\\Unity Game\\Self Driving Car\\SDCProgram\\Best Models\\data-003.h5\") \t# Directory to load the model\r\n\r\... | [
[
"numpy.asarray",
"tensorflow.keras.models.load_model",
"numpy.array"
],
[
"tensorflow.keras.callbacks.ModelCheckpoint",
"pandas.read_csv",
"numpy.expand_dims",
"tensorflow.keras.models.Sequential",
"tensorflow.keras.layers.Lambda",
"tensorflow.keras.layers.Dense",
"tens... |
fluxtransport/fiasco | [
"9d70d8bdb03197be1ddfd433e1392e214a1468e8",
"9d70d8bdb03197be1ddfd433e1392e214a1468e8"
] | [
"fiasco/element.py",
"fiasco/fiasco.py"
] | [
"\"\"\"\nClasses and functions for element-level operations\n\"\"\"\nimport numpy as np\nimport astropy.units as u\nimport plasmapy\n\nimport fiasco\n\n__all__ = ['Element']\n\n\nclass Element(fiasco.IonCollection):\n \"\"\"\n Collection of all ions for a particular element.\n\n The `Element` object provid... | [
[
"numpy.linalg.svd",
"numpy.zeros",
"numpy.fabs"
],
[
"scipy.interpolate.interp1d",
"numpy.zeros"
]
] |
yigitozgumus/Polimi_Thesis | [
"711c1edcf1fdb92fc6c15bf5ab1be141c13995c3",
"711c1edcf1fdb92fc6c15bf5ab1be141c13995c3",
"711c1edcf1fdb92fc6c15bf5ab1be141c13995c3"
] | [
"models/new/sencebgan.py",
"trainers/bigan_trainer.py",
"trainers/sencebgan_denoiser_trainer.py"
] | [
"import tensorflow as tf\n\nfrom base.base_model import BaseModel\nfrom utils.alad_utils import get_getter\nimport utils.alad_utils as sn\n\n\nclass SENCEBGAN(BaseModel):\n def __init__(self, config):\n super(SENCEBGAN, self).__init__(config)\n self.build_model()\n self.init_saver()\n\n d... | [
[
"tensorflow.get_variable",
"tensorflow.concat",
"tensorflow.control_dependencies",
"tensorflow.layers.dropout",
"tensorflow.reduce_sum",
"tensorflow.train.ExponentialMovingAverage",
"tensorflow.tanh",
"tensorflow.train.AdamOptimizer",
"tensorflow.group",
"tensorflow.summary... |
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