repo_name stringlengths 6 130 | hexsha list | file_path list | code list | apis list |
|---|---|---|---|---|
harry-zuzan/Redescend-Likelihood | [
"c203f1430e0200226b3dd0ec19621a2408ee1648"
] | [
"setup.py"
] | [
"from distutils.core import setup\nfrom distutils.extension import Extension\nfrom Cython.Build import cythonize\n\nimport numpy\n\nnumpy_inc = numpy.get_include()\n\nextensions = [\n Extension(\"redescendl.redescend_likelihood\",\n\t\t\t[\"redescendl/redescend_likelihood.pyx\"],\n include_dirs = [numpy_i... | [
[
"numpy.get_include"
]
] |
anukaal/cloud | [
"2b6c9127734ea22b6c1aaa070ac06124e5960c57",
"2b6c9127734ea22b6c1aaa070ac06124e5960c57"
] | [
"src/python/tensorflow_cloud/tuner/tests/integration/distributing_cloudtuner_integration_test.py",
"src/python/tensorflow_cloud/tuner/tests/unit/utils_test.py"
] | [
"# Lint as: python3\n# Copyright 2020 Google LLC. 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# Unl... | [
[
"tensorflow.io.gfile.isdir",
"tensorflow.keras.layers.Dense",
"tensorflow.compat.v1.enable_eager_execution",
"tensorflow.test.main",
"tensorflow.keras.Sequential",
"tensorflow.keras.datasets.mnist.load_data",
"tensorflow.keras.backend.clear_session",
"tensorflow.io.gfile.rmtree",
... |
ObliviousParadigm/pandas | [
"08febd2b9f77fd8f943de92939788e8bc53ee2d2"
] | [
"pandas/tests/test_algos.py"
] | [
"from datetime import datetime\nfrom itertools import permutations\nimport struct\n\nimport numpy as np\nfrom numpy.random import RandomState\nimport pytest\n\nfrom pandas._libs import algos as libalgos, groupby as libgroupby, hashtable as ht\nfrom pandas.compat.numpy import np_array_datetime64_compat\nimport panda... | [
[
"pandas.PeriodIndex",
"pandas.core.algorithms.duplicated",
"pandas.isna",
"pandas._testing.assert_numpy_array_equal",
"numpy.unique",
"pandas._libs.hashtable.Float64HashTable",
"pandas.core.dtypes.common.is_float_dtype",
"numpy.zeros",
"pandas.unique",
"pandas.date_range",
... |
gena/paper-osm-2015 | [
"1e3a16c4449f8a7b036365d9d3f1d97aabafb76e"
] | [
"notebooks/utils/shapely_plot.py"
] | [
"import matplotlib.pyplot as plt\r\n\r\n# from numba import jit\r\n\r\n# @jit\r\ndef draw_(g, fill, outline, lw, alpha):\r\n gType = g.geom_type\r\n if gType == 'Point':\r\n plt.plot(g.x, g.y, 'k,')\r\n elif gType == 'LineString':\r\n x, y = g.xy\r\n plt.plot(x, y, 'b-', color=outline,... | [
[
"matplotlib.pyplot.axes",
"matplotlib.pyplot.plot",
"matplotlib.pyplot.fill",
"matplotlib.pyplot.figure"
]
] |
LukasMosser/stochastic_seismic_waveform_inversion | [
"4976c3b9a39b8d246d3d220056f235df6fc7dbb3"
] | [
"seisgan/fwi/pde/seismic/plotting.py"
] | [
"import numpy as np\ntry:\n import matplotlib as mpl\n import matplotlib.pyplot as plt\n from matplotlib import cm\n from mpl_toolkits.axes_grid1 import make_axes_locatable\n\n mpl.rc('font', size=16)\n mpl.rc('figure', figsize=(8, 6))\nexcept:\n plt = None\n cm = None\n\n\ndef plot_perturba... | [
[
"matplotlib.pyplot.gca",
"matplotlib.pyplot.scatter",
"numpy.min",
"matplotlib.rc",
"matplotlib.pyplot.colorbar",
"numpy.max",
"numpy.transpose",
"matplotlib.pyplot.xlabel",
"numpy.array",
"matplotlib.pyplot.show",
"matplotlib.pyplot.ylabel"
]
] |
brandon-b-miller/dask-sql | [
"8919fc0326b20a807e0d22d34e3d92372fb1bc93"
] | [
"tests/integration/fixtures.py"
] | [
"import os\nimport tempfile\n\nimport dask.dataframe as dd\nimport numpy as np\nimport pandas as pd\nimport pytest\nfrom dask.datasets import timeseries\nfrom dask.distributed import Client\nfrom pandas.testing import assert_frame_equal\n\ntry:\n import cudf\n\n # importing to check for JVM segfault\n impo... | [
[
"pandas.read_sql_query",
"numpy.random.seed",
"numpy.random.choice",
"pandas.DataFrame",
"pandas.testing.assert_frame_equal",
"numpy.random.rand",
"pandas.date_range",
"numpy.random.randint"
]
] |
ankushpanwar19/Multi-Task-Learning | [
"1808ba1821ae3c4d414e31d583d31b15782daa38",
"1808ba1821ae3c4d414e31d583d31b15782daa38"
] | [
"mtl/utils/visualization.py",
"mtl/experiments/experiment_semseg_with_depth.py"
] | [
"import matplotlib\nimport matplotlib.cm\nimport numpy as np\nimport torch\nimport torch.nn.functional as F\nfrom matplotlib.font_manager import findfont, FontProperties\nfrom PIL import Image, ImageFont, ImageDraw\nfrom torchvision.utils import make_grid\n\nfrom mtl.datasets.definitions import MOD_RGB, MOD_SEMSEG,... | [
[
"numpy.rollaxis",
"torch.max",
"torch.full",
"torch.cat",
"torch.min",
"matplotlib.font_manager.FontProperties",
"torch.from_numpy",
"torch.unsqueeze",
"torch.tensor",
"torch.unique",
"torch.nn.functional.interpolate",
"matplotlib.cm.get_cmap",
"torch.clamp",
... |
Nanosekunde/openpilot | [
"334c74172f1b8cab278fb6203d8cf0338652ad55"
] | [
"selfdrive/controls/lib/latcontrol_helpers.py"
] | [
"import numpy as np\nimport math\nfrom common.numpy_fast import interp\n\n_K_CURV_V = [1., 0.6]\n_K_CURV_BP = [0., 0.002]\n\n# lane width http://safety.fhwa.dot.gov/geometric/pubs/mitigationstrategies/chapter3/3_lanewidth.cfm\n_LANE_WIDTH_V = [3., 3.8]\n\n# break points of speed\n_LANE_WIDTH_BP = [0., 31.]\n\n\ndef... | [
[
"numpy.abs",
"numpy.arctan",
"numpy.clip",
"numpy.arange",
"numpy.linalg.pinv"
]
] |
Leonardo767/gridworld-learning | [
"4c48e276378828cc308c83a858d719c29e8dfd80"
] | [
"soft_actor_critic/sac_torch.py"
] | [
"import os\nimport torch as T\nimport torch.nn.functional as F\nimport numpy as np\nfrom buffer import ReplayBuffer\nfrom net import ActorNetwork, CriticNetwork, ValueNetwork\n\n\nclass Agent():\n def __init__(self, alpha=0.0003, beta=0.0003, input_dims=[8], env=None, gamma=0.99,\n n_actions=2, m... | [
[
"torch.mean",
"torch.Tensor",
"torch.min",
"torch.tensor",
"torch.nn.functional.mse_loss"
]
] |
royerloic/dexp | [
"1f132d21ac2093725a5a83bc20fa0a45ae09bfe6"
] | [
"dexp/processing/deconvolution/lr_deconvolution.py"
] | [
"import math\nfrom typing import Optional, Tuple, Union\n\nimport numpy\n\nfrom dexp.processing.filters.fft_convolve import fft_convolve\nfrom dexp.processing.filters.kernels.gaussian import gaussian_kernel_nd\nfrom dexp.processing.filters.kernels.wiener_butterworth import wiener_butterworth_kernel\nfrom dexp.proce... | [
[
"numpy.pad"
]
] |
redbubble/implicit | [
"fe85f79f8b547a75e42186bf5357ad2f395366a4"
] | [
"implicit/nmslib_als.py"
] | [
"import itertools\nimport logging\n\nimport numpy\nfrom implicit.als import AlternatingLeastSquares\nfrom implicit.approximate_als import augment_inner_product_matrix\n\nlog = logging.getLogger(\"implicit\")\n\nlogging.getLogger('nmslib').setLevel(logging.WARNING)\n\n\nclass NMSLibALSWrapper:\n \"\"\"A wrapper o... | [
[
"numpy.arange",
"numpy.append",
"numpy.delete",
"numpy.linalg.norm"
]
] |
Biswajit2902/pyrasta | [
"5e77a1d842be7429f81959250a937e2304a1d7f2"
] | [
"rasta/feature.py"
] | [
"from __future__ import print_function, division\n\"\"\"\n@ About :\n@ Author : Biswajit Satapathy\n@ ref. : https://labrosa.ee.columbia.edu/matlab/rastamat/\n\"\"\"\nfrom . import utils as rasta_utils\nfrom scipy import signal\nimport numpy as np\n\ndef rastaplp(x, fs = 8000, window_time = 0.025, hop_time = 0.010,... | [
[
"scipy.signal.lfilter",
"numpy.log",
"numpy.exp",
"numpy.multiply"
]
] |
theboxahaan/Oort | [
"05a3aa1677a10f8e621055b1626ef82e73d09759",
"05a3aa1677a10f8e621055b1626ef82e73d09759"
] | [
"oort/oort.py",
"training/utils/yogi.py"
] | [
"from .utils.lp import *\nimport math, numpy\n\nfrom random import Random\nfrom collections import OrderedDict\nimport logging\nimport numpy as np2\n\ndef create_training_selector(args):\n return _training_selector(args)\n\ndef create_testing_selector(data_distribution=None, client_info=None, model_size=None):\n... | [
[
"numpy.random.seed",
"numpy.random.choice"
],
[
"torch.sqrt",
"torch.sign"
]
] |
Lxkxkx/Graph-Recurrent-Neural-Network-for-Text-Classification | [
"1d113b8693d5a8775c83954a122d5e6595d72355"
] | [
"train.py"
] | [
"import time\r\nfrom sklearn import metrics\r\nfrom torch import nn\r\nimport torch\r\nfrom config import *\r\nimport config\r\nfrom data_state import get_data_loader\r\nfrom model_lstm import Model\r\n\r\n\r\ndef train_eval(cate, loader, model, optimizer, loss_func, device):\r\n model.train() if cate == \"tr... | [
[
"torch.nn.CrossEntropyLoss",
"torch.cat",
"torch.tensor",
"sklearn.metrics.precision_recall_fscore_support",
"torch.save",
"torch.cuda.is_available",
"sklearn.metrics.classification_report",
"sklearn.metrics.accuracy_score"
]
] |
ivanst0/onnxruntime | [
"d52b9aca680829715b69e2f8cd544a34d91bb526",
"d52b9aca680829715b69e2f8cd544a34d91bb526"
] | [
"onnxruntime/python/tools/transformers/benchmark_gpt2.py",
"orttraining/orttraining/python/training/orttrainer.py"
] | [
"# -------------------------------------------------------------------------\n# Copyright (c) Microsoft Corporation. All rights reserved.\n# Licensed under the MIT License. See License.txt in the project root for\n# license information.\n# --------------------------------------------------------------------------... | [
[
"torch.device",
"torch.__config__.parallel_info"
],
[
"torch.zeros",
"torch.tensor",
"torch.no_grad",
"numpy.testing.assert_allclose",
"numpy.array"
]
] |
BKDevelop/mach_learn_playground | [
"8f368058a61a722bdb8daa0627fe44839bda7dfd"
] | [
"NFL Predict/PredictPlays2.py"
] | [
"import csv\nfrom sklearn import tree, svm\nfrom sklearn.neural_network import MLPClassifier\nimport random\n\ngameSituations_train = []\nplayCalls_train = []\n\n\n# initialize different models\ntreeModel = tree.DecisionTreeClassifier()\nlinearSVC = svm.LinearSVC()\nneuralNetwork = MLPClassifier()\n\n\n# get data f... | [
[
"sklearn.neural_network.MLPClassifier",
"sklearn.tree.DecisionTreeClassifier",
"sklearn.svm.LinearSVC"
]
] |
jessicaleu24/NSF-demo | [
"ec05ee45f6934aeb06c56eab5746dd88ce09af24"
] | [
"grasp/data/data_utils.py"
] | [
"import os\nimport sys\nimport copy\nimport random\n\nimport torch\nimport torch.utils.data\nimport torch.nn as nn\nimport numpy as np\nfrom scipy.ndimage.interpolation import rotate\nfrom scipy import signal\nfrom skimage import feature\n\nfrom detectron2.structures import Boxes, ImageList, Instances, RotatedBoxes... | [
[
"numpy.sqrt",
"numpy.arctan",
"numpy.rad2deg",
"numpy.max",
"numpy.mean",
"numpy.where",
"numpy.random.randint",
"torch.ones",
"numpy.fliplr",
"numpy.arange",
"numpy.eye",
"torch.from_numpy",
"torch.tensor",
"numpy.sin",
"matplotlib.pyplot.figure",
"... |
danielvicentini/distancebot | [
"4ae2abeec6e29577d5f5c7bf3fdc974e6a187f13",
"4ae2abeec6e29577d5f5c7bf3fdc974e6a187f13"
] | [
"DB/bdFluxQueries.py",
"mask-detection/video.py"
] | [
"import sys\r\nimport os\r\n#sys.path.append(os.path.abspath('..'))\r\n\r\nPACKAGE_PARENT = '..'\r\nSCRIPT_DIR = os.path.dirname(os.path.realpath(os.path.join(os.getcwd(), os.path.expanduser(__file__))))\r\nsys.path.append(os.path.normpath(os.path.join(SCRIPT_DIR, PACKAGE_PARENT)))\r\n\r\nfrom influxdb_client impor... | [
[
"pandas.DataFrame"
],
[
"torch.max",
"torch.cuda.is_available",
"torch.load"
]
] |
CMU-IDS-2022/assignment-2-tia | [
"55259579dba5e09001c80fdbf9eb247a4b8b55f7"
] | [
"streamlit_app.py"
] | [
"import streamlit as st\nimport pandas as pd\nimport altair as alt\nfrom vega_datasets import data\n\n\n\n\nfrom re import U\nimport streamlit as st\nimport pandas as pd\nimport altair as alt\n\nimport numpy as np\n#from vega_datasets import data\n\n@st.cache\ndef load_data():\n \"\"\"\n Write 1-2 lines of co... | [
[
"pandas.merge",
"pandas.read_csv",
"numpy.log"
]
] |
radiasoft/rsdynfric | [
"0d905e1ef85063ec6fe93df64751f7b8c19da160"
] | [
"examples/eidelyur/MCOOL/classic_magnus_approaches/Gauss-Kronrod_integration.py"
] | [
"#! /usr/bin/env python\n#\ndef abwe1 ( n, m, tol, coef2, even, b, x ) :\n\n#*****************************************************************************80\n#\n## ABWE1 calculates a Kronrod abscissa and weight.\n#\n# Licensing:\n#\n# This code is distributed under the GNU LGPL license.\n#\n# Modified:\n#\n# ... | [
[
"numpy.array",
"numpy.zeros",
"numpy.sqrt",
"numpy.sin"
]
] |
georgy7/toyfloat | [
"0bbcb452353ccd7e2ca1447904e7d0cc929038c9"
] | [
"images/plot.py"
] | [
"import matplotlib.pyplot as plt\nimport csv\nimport numpy as np\n\ndef get_data(data_fn, max_value):\n values = []\n precision = []\n\n tsv_file = open(data_fn)\n read_tsv = csv.reader(tsv_file, delimiter=\"\\t\")\n\n for row in read_tsv:\n v = float(row[0])\n p = float(row[1])\n\n ... | [
[
"numpy.polyfit",
"matplotlib.pyplot.xscale",
"matplotlib.pyplot.yscale",
"matplotlib.pyplot.savefig",
"matplotlib.pyplot.axes",
"matplotlib.pyplot.plot",
"matplotlib.pyplot.ylabel",
"numpy.log10",
"matplotlib.pyplot.grid",
"matplotlib.pyplot.subplots_adjust",
"matplotli... |
hpleva/ai4materials | [
"5b5548f4fbfd4751cd1f9d57cedaa1e1d7ca04b2"
] | [
"ai4materials/dataprocessing/preprocessing.py"
] | [
"# coding=utf-8\n# Copyright 2016-2018 Angelo Ziletti\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 a... | [
[
"sklearn.model_selection.ShuffleSplit",
"tensorflow.as_dtype",
"numpy.unique",
"numpy.asarray",
"numpy.arange",
"tensorflow.set_random_seed",
"sklearn.preprocessing.StandardScaler",
"sklearn.model_selection.StratifiedShuffleSplit",
"numpy.zeros"
]
] |
tachidok/cellular_automata | [
"73e3c15b14333835c4613edd98296cf5d7b58741"
] | [
"bin/plot_time_space.py"
] | [
"#!/usr/bin/env python\n\nimport numpy as np\nimport matplotlib.pyplot as plt\nimport argparse\n\nEXTRA_SMALL_SIZE = 8\nSMALL_SIZE = 10\nMEDIUM_SIZE = 12\nBIG_SIZE = 14\nEXTRA_BIG_SIZE = 16\n\nplt.rc('font', size=SMALL_SIZE) # controls default text sizes\nplt.rc('axes', titlesize=EXTRA_BIG_SIZE) # fonts... | [
[
"numpy.arange",
"matplotlib.pyplot.rc",
"matplotlib.pyplot.subplots",
"matplotlib.pyplot.close",
"matplotlib.pyplot.show",
"numpy.loadtxt"
]
] |
liqimai/ArrayDebug | [
"a75dfedae73ffdc3e2fad866495d463dde12953c"
] | [
"tests/test_array_like.py"
] | [
"import pandas as pd\nimport numpy as np\nimport unittest\nfrom inspect import cleandoc\n\nimport arraydebug # noqa\n\n\nclass TestArrayLike(unittest.TestCase):\n def test_pd_dataframe(self):\n \"\"\"\n <DataFrame: shape=(6, 4), dtype=int64>\n A B C D\n 201... | [
[
"numpy.arange",
"pandas.date_range"
]
] |
DefTruth/AnchorDETR | [
"7b1f11c6b8946dd9821d1c080657a488e8fdd9ae"
] | [
"models/transformer.py"
] | [
"# ------------------------------------------------------------------------\n# Copyright (c) 2021 megvii-model. All Rights Reserved.\n# ------------------------------------------------------------------------\n# Modified from Deformable DETR (https://github.com/fundamentalvision/Deformable-DETR)\n# Copyright (c) 20... | [
[
"torch.nn.Dropout",
"torch.nn.init.uniform_",
"torch.ones",
"torch.nn.MultiheadAttention",
"torch.cat",
"torch.nn.init.constant_",
"torch.nn.Embedding",
"torch.nn.LayerNorm",
"torch.nn.Linear",
"torch.arange",
"torch.nn.ReLU",
"torch.meshgrid"
]
] |
Nephiloso/MouseSegmentation | [
"4e9d0f7331d7f99663a0dcdd4af1e2af599f88cf",
"4e9d0f7331d7f99663a0dcdd4af1e2af599f88cf"
] | [
"utils/transformer.py",
"utils/TrainNetwork.py"
] | [
"# Copyright 2016 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.clip_by_value",
"tensorflow.matmul",
"tensorflow.concat",
"tensorflow.range",
"tensorflow.zeros",
"tensorflow.slice",
"tensorflow.shape",
"tensorflow.stack",
"tensorflow.reshape",
"tensorflow.cast",
"tensorflow.expand_dims",
"tensorflow.ones_like",
"... |
marka17/vqvae | [
"1e0249d1504a6cf616f8edd7da24ecc717129806"
] | [
"train_vae.py"
] | [
"import pathlib\nimport argparse\nimport json\nfrom pprint import pprint\nfrom tqdm import tqdm\n\nimport torch\nfrom torch import optim\nfrom torch.utils.data import DataLoader\n\ntry:\n from torch.utils.tensorboard import SummaryWriter\nexcept ImportError:\n from tensorboardX import SummaryWriter\n\nfrom to... | [
[
"torch.no_grad",
"torch.utils.data.DataLoader",
"torch.cuda.is_available"
]
] |
lamps-lab/Citation-Parser | [
"76b452ff7ad981b89dc64d9fe0a0849140e48bae"
] | [
"Trainer/citation-parser-trainer.py"
] | [
"'''\n This is used for training deep learning model\n'''\n\n#!/usr/bin/env python\n# coding: utf-8\n\n\nimport os\nimport time\nimport gensim\nfrom collections import Counter\nimport torch\nfrom torch import nn\nfrom torch.optim import Adam\nfrom torch.optim import AdamW\nfrom spacy.lang.id import Indonesian\ni... | [
[
"torch.manual_seed",
"torch.cuda.empty_cache",
"torch.nn.DataParallel",
"torch.as_tensor",
"torch.no_grad",
"torch.cuda.is_available",
"torch.cuda.get_device_name",
"torch.device",
"torch.cuda.device_count",
"torch.save"
]
] |
Einavg7/PIG_FinalProject | [
"bcf7077703b44325f978d37c8bf1ec3aac34e0f8"
] | [
"Codes/Processing/processing.py"
] | [
"import math\nimport pandas as pd\nimport os\nfrom datetime import datetime, timedelta\nimport csv\n\ndef OpenFile(filePath):\n \"\"\"\n Opens a shapefile in QGIS\n\n Parameters\n ----------\n filePath :STRING\n Path to the shapefile to open\n\n Returns\n -------\n layer : QgsVectorLa... | [
[
"pandas.DataFrame"
]
] |
tensorflow-pool/FaceBoxes-tensorflow | [
"74e0cbe6a29843f93e062a4ac8e1b131f76fc6d3"
] | [
"face_detector.py"
] | [
"import tensorflow as tf\nimport numpy as np\n\n\nclass FaceDetector:\n def __init__(self, model_path, gpu_memory_fraction=0.25, visible_device_list='0'):\n \"\"\"\n Arguments:\n model_path: a string, path to a pb file.\n gpu_memory_fraction: a float number.\n visib... | [
[
"tensorflow.Graph",
"numpy.expand_dims",
"tensorflow.import_graph_def",
"tensorflow.gfile.GFile",
"tensorflow.ConfigProto",
"tensorflow.GPUOptions",
"tensorflow.Session",
"tensorflow.GraphDef",
"numpy.array"
]
] |
bhanuchandrika/pylearn | [
"a48ac733faa72821700491c09caa9b0f0b6f559c"
] | [
"bubble-sort.py"
] | [
"#-----importing the dataset and creation of list\nimport pandas as pd\ndf = pd.read_csv(\"https://raw.githubusercontent.com/ineelhere/pylearn/master/RGTE11_dataset/2010_RGTE11.csv\", encoding=\"unicode_escape\") #import the data\ndata=list(df[\"Popn_2010\"])\n#-----bubble sort\nfor i in range(0,len(data)):\n fo... | [
[
"pandas.read_csv"
]
] |
bva99/PINN-KS | [
"da2de335c3d8740341e1caf9af21b904528fb3a9"
] | [
"lib/network.py"
] | [
"import tensorflow as tf\nfrom .fflayer import ffLayer\n\nclass Network:\n \"\"\"\n Build a physics informed neural network (PINN) model for the\n Kuramoto-Sivashinsky equation.\n \"\"\"\n\n @classmethod\n def build(cls, num_inputs=2, layers=None, activation=tf.nn.tanh,\n sig_t=[1], s... | [
[
"tensorflow.multiply",
"tensorflow.keras.models.Model",
"tensorflow.keras.layers.Dense",
"tensorflow.keras.models.Sequential",
"tensorflow.keras.layers.Input"
]
] |
ajouellette/advent-of-code21 | [
"910d790ca6ac8c844e277c71d458726ff92a187d"
] | [
"11/main.py"
] | [
"import numpy as np\n\n\ndef load_input(file):\n array = []\n for line in file:\n row = []\n for c in line.strip():\n row.append(int(c))\n array.append(row)\n return np.asarray(array)\n\n\ndef step(octopi):\n # step 1: all octopi increment\n octopi += 1\n # step 2: ... | [
[
"numpy.logical_xor",
"numpy.asarray",
"numpy.zeros_like",
"numpy.prod",
"numpy.sum"
]
] |
MLeib/Cirq | [
"2f8326c5f71006ff17c9353e30d35cd9e11aca2a"
] | [
"cirq-core/cirq/sim/sparse_simulator.py"
] | [
"# Copyright 2018 The Cirq Developers\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 o... | [
[
"numpy.reshape",
"numpy.empty",
"numpy.copyto",
"numpy.dtype"
]
] |
xchani/simpledet | [
"3e7587f0a4403003bc4eda8a8403ec385bb980f8"
] | [
"utils/create_crowdhuman_roidb.py"
] | [
"import argparse\nimport os\nimport pickle as pkl\nimport numpy as np\nimport random\nfrom PIL import Image\nimport concurrent.futures\nimport json\n\ndef parse_args():\n parser = argparse.ArgumentParser(description='Generate SimpleDet GroundTruth Database for Crowdhuman-like dataset')\n parser.add_argument('... | [
[
"numpy.arange",
"numpy.array",
"numpy.random.shuffle"
]
] |
vandal-dev/vandal | [
"1981c86f4de6632776a4132ecbc206fac5188f32"
] | [
"vandal/objects/dijkstra.py"
] | [
"# type hints and annotations.\r\nfrom vandal.plugins.metaclass import Meta\r\nfrom vandal.plugins.types import (\r\n VandalType,\r\n IntegerType,\r\n FloatType,\r\n NumberType,\r\n ReturnType,\r\n PrintType,\r\n GraphType,\r\n StringType,\r\n ListType,\r\n TupleType,\r\n Dictionary... | [
[
"pandas.DataFrame"
]
] |
chronoverse/zipline-reloaded | [
"c07be2e2b48fded0295d074ea1e7b11047946090"
] | [
"setup.py"
] | [
"#!/usr/bin/env python\n#\n# Copyright 2014 Quantopian, 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 requir... | [
[
"numpy.get_include"
]
] |
CookieBox26/trellisnet | [
"356b1d9828012cc4929728a492b771c44161e089"
] | [
"trellisnet.py"
] | [
"import torch\nfrom torch import nn\nimport torch.nn.functional as F\nfrom trellisnet.optimizations import weight_norm, VariationalDropout, VariationalHidDropout\n\n__author__ = 'shaojieb'\n\n\nclass WeightShareConv1d(nn.Module):\n def __init__(self, input_dim, hidden_dim, n_out, kernel_size, dropouth=0.0):\n ... | [
[
"torch.sigmoid",
"torch.zeros",
"torch.cat",
"torch.nn.functional.conv1d",
"torch.tanh",
"torch.nn.Conv1d",
"torch.nn.functional.pad"
]
] |
anish-lu-yihe/MINERVA | [
"931d79170855cb187992ee1fb8520ae61f3cf875"
] | [
"minerva.py"
] | [
"# -*- coding: utf-8 -*-\n\"\"\"\nCreated on Sat Jan 30 18:05:17 2021\n\n@author: Lu, Yihe\n\nOriginal Minverva2 from Hintzman (1984)\n\"\"\"\n\nimport numpy as np\n\ndef proba0(x):\n _x = np.asarray(x)\n _x[_x > 1], _x[_x < -1] = 1, -1\n p = 1 - np.abs(_x)\n return p\n\nclass Minerva2: # Hintzman (1984... | [
[
"numpy.dot",
"numpy.abs",
"numpy.asarray",
"numpy.reshape",
"numpy.concatenate",
"numpy.sum",
"numpy.empty"
]
] |
AustinT/ai4sci-2021-denovo-benchmarks | [
"32ecd258394156581c2435769a3ab4aa3823b72b",
"32ecd258394156581c2435769a3ab4aa3823b72b"
] | [
"src/regression/gp_exact.py",
"src/selfies_ga/ga_funcs.py"
] | [
"import argparse\nimport functools\nimport json\nfrom pathlib import Path\n\nimport numpy as np\nimport pandas as pd\nimport torch\n\nimport dockstring_data\nfrom regression.regression_utils import (\n get_regression_parser,\n split_dataframe_train_test,\n eval_regression,\n)\nfrom gp import (\n Tanimot... | [
[
"pandas.read_csv",
"numpy.stack",
"torch.as_tensor"
],
[
"numpy.allclose",
"numpy.random.choice",
"numpy.min",
"numpy.asarray",
"numpy.median",
"numpy.max",
"numpy.std",
"numpy.mean"
]
] |
thdb-theo/Polynomial | [
"9943ee5eb175ef01720954c6a95c685bd7fd5f6c"
] | [
"poly/rational.py"
] | [
"from numbers import Number\nimport math\nfrom functools import reduce\nimport random\nimport re\n\nfrom polynomial import Polynomial\nimport misc\n\n\nclass Rational:\n __slots__ = 'numerator', 'denominator', 'name'\n\n def __init__(self, numerator, denominator, name='f'):\n if isinstance(numerator, (... | [
[
"matplotlib.pyplot.legend",
"numpy.linspace",
"matplotlib.pyplot.subplots",
"matplotlib.pyplot.setp",
"matplotlib.pyplot.grid",
"matplotlib.pyplot.show"
]
] |
abrahamneben/orbcomm_beam_mapping | [
"71b3e7d6e4214db0a6f4e68ebeeb7d7f846f5004"
] | [
"power_data_to_sat_passes/refModel/plot_model_abraham.py"
] | [
"import healpy as hp\nimport numpy as n\nimport sys\nimport matplotlib.pyplot as plt\n\nc=3.e8\nf=137.5e6\nlamb = c/f\nh=0.3\nvmin=-10\n\n# Hertzian Dipole model\nnsides = 8\nnpixels = hp.nside2npix(nsides)\nthetas,phis = hp.pix2ang(nsides,n.arange(npixels))\nhpower = (1-n.sin(thetas)**2*n.cos(phis)**2)*n.sin(2*n.p... | [
[
"numpy.arange",
"numpy.cos",
"numpy.genfromtxt",
"numpy.sin",
"numpy.log10",
"matplotlib.pyplot.show",
"numpy.zeros"
]
] |
liruilong940607/A-NeRF | [
"19cb6c4fd389266214ac0d7215a44011cb1bebf5",
"19cb6c4fd389266214ac0d7215a44011cb1bebf5"
] | [
"core/load_perfcap.py",
"core/pose_opt.py"
] | [
"import os\nimport cv2\nimport h5py\nimport imageio\nimport numpy as np\n\nfrom .dataset import PoseRefinedDataset\nfrom .load_surreal import dilate_masks\nfrom .process_spin import process_spin_data, write_to_h5py, read_spin_data\nfrom .utils.skeleton_utils import *\n\ndef process_perfcap_data(data_path, subject='... | [
[
"numpy.array"
],
[
"torch.cat",
"torch.zeros",
"torch.load",
"numpy.concatenate",
"torch.no_grad",
"torch.ones",
"numpy.unique",
"numpy.arange",
"torch.tensor",
"torch.inverse",
"torch.arange",
"torch.ones_like",
"torch.optim.Adam",
"torch.LongTensor... |
ekorudiawan/Hurocup-KidSize-ROS | [
"6fed47662ca427f77504982c4ab9d880827bcf84"
] | [
"catkin_ws/src/image_streamer/src/image_streamer.py"
] | [
"import cv2 as cv\nimport numpy as np\nimport rospy\nimport roslib\nfrom sensor_msgs.msg import Image\nfrom cv_bridge import CvBridge, CvBridgeError\n\nbridge = CvBridge()\n\ndef main():\n rospy.loginfo(\"Image Streamer - Running\")\n rospy.init_node(\"image_streamer\")\n img_pub = rospy.Publisher(\"/usb_c... | [
[
"numpy.array"
]
] |
sylvchev/timeflux_example | [
"b957bc8bc96dd5bb8eb3000b2c2abb158300d3b1"
] | [
"test/test_arithmetic.py"
] | [
"\"\"\"Tests for arithmetic.py\"\"\"\n\nimport pytest\nimport pandas as pd\nfrom pandas.testing import assert_frame_equal\nfrom timeflux.core.io import Port\nfrom timeflux_example.nodes.arithmetic import Add, MatrixAdd\n\ndef test_add():\n node = Add(1)\n node.i = Port()\n node.i.data = pd.DataFrame([[1, 1... | [
[
"pandas.testing.assert_frame_equal",
"pandas.DataFrame"
]
] |
Emrys-Lee/Traffic4D-Release | [
"17cdc84a3a8108f28b4a35e6aa8af1cad19ff6f3"
] | [
"src/modules/activity_clustering.py"
] | [
"import numpy as np\nimport cv2\nfrom sklearn import mixture\nfrom utils.utils_geom import r_to_unit_grad, generate_spline_points_given_frames, generate_spline_tangent_world\nfrom utils.utils_save import *\n\ndef merge_similar_clusters_first(means, index_global):\n \"\"\"merge clusters with similiar trajectory d... | [
[
"sklearn.mixture.GaussianMixture",
"numpy.random.seed",
"numpy.arange",
"numpy.linalg.norm",
"numpy.arctan2",
"numpy.average",
"sklearn.mixture.BayesianGaussianMixture",
"numpy.repeat",
"numpy.array",
"numpy.where"
]
] |
markrofail/multi-modal-deep-learning-for-vehicle-sensor-data-abstraction-and-attack-detection | [
"2f252c072f3091bb27506978dd90311f7f82f386"
] | [
"src/multimodal/data/kitti/make_records.py"
] | [
"import multiprocessing\n\nimport numpy as np\nfrom joblib import Parallel, delayed\nfrom tqdm import tqdm\n\nfrom src.helpers import paths, tfrecord\nfrom src.helpers.flags import AttackModes, Verbose\n\n\ndef _get_input_path(drive_date, drive_number, frame, attack):\n if attack:\n return paths.attack.processe... | [
[
"numpy.load",
"numpy.array"
]
] |
paul-shannon/dockerizedMicroservices | [
"6de08e40cea63117969215a2550934ac7ef79e2f"
] | [
"trenaGelinas/nbserver/hub/Trena.py"
] | [
"import zmq, json\nimport pandas as pd\nfrom ipyTrenaViz import *\nimport time, os\n\nclass Trena:\n\n def __init__(self, genomeName):\n socketContext = zmq.Context();\n self.trenaServer = socketContext.socket(zmq.REQ)\n self.trenaServer.connect(\"tcp://trena:%s\" % \"5547\")\n self.tv = ... | [
[
"pandas.DataFrame"
]
] |
hengyicai/AdaND | [
"5e3fefb1cf40c42215a37246efc64958ae6db005",
"5e3fefb1cf40c42215a37246efc64958ae6db005"
] | [
"projects/controllable_dialogue/controllable_seq2seq/modules.py",
"parlai/agents/dialog_evaluator/auto_evaluator.py"
] | [
"#!/usr/bin/env python3\n\n# Copyright (c) Facebook, Inc. and its affiliates.\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\n\"\"\"Seq2seq module adapted to handle CT controlled models.\"\"\"\n\nimport math\nimport torch\nimport torch... | [
[
"torch.nn.Softmax",
"torch.LongTensor",
"torch.nn.Dropout",
"torch.nn.parameter.Parameter",
"torch.nn.functional.softmax",
"torch.Tensor",
"torch.cat",
"torch.nn.functional.log_softmax",
"torch.nn.Embedding",
"torch.nn.utils.rnn.pack_padded_sequence",
"torch.nn.Tanh",
... |
UoMfzp/transformer-xl-Chinese-Pytorch | [
"435641ed138e81f949c5b557b5a13c0a09fb6018"
] | [
"proj_adaptive_softmax.py"
] | [
"from collections import defaultdict\n\nimport numpy as np\n\nimport torch\nimport torch.nn as nn\nimport torch.nn.functional as F\n\nCUDA_MAJOR = int(torch.version.cuda.split('.')[0])\nCUDA_MINOR = int(torch.version.cuda.split('.')[1])\n\nclass ProjectedAdaptiveLogSoftmax(nn.Module):\n def __init__(self, n_toke... | [
[
"torch.nn.functional.log_softmax",
"torch.zeros",
"torch.cat",
"torch.Tensor",
"torch.nn.ModuleList",
"torch.zeros_like",
"torch.nn.Linear",
"torch.nn.ParameterList",
"torch.version.cuda.split",
"torch.nn.functional.linear"
]
] |
AskdataInc/askdata-api-python-client | [
"82d63e5aad68e109cafe54aab29cf98cb5587588"
] | [
"askdata/integration.py"
] | [
"import pandas as pd\n\nimport requests\n\nfrom oauth2client.service_account import ServiceAccountCredentials\n\nfrom googleapiclient.discovery import build\nfrom requests.adapters import HTTPAdapter\nfrom urllib3 import Retry\n\nimport json\n\n\n\"\"\" \nRead google sheet as dataframe\n\n\nIf you read with API, yo... | [
[
"pandas.read_excel",
"pandas.read_csv",
"pandas.to_datetime",
"pandas.DataFrame",
"pandas.read_parquet"
]
] |
sdss/Totoro | [
"74befd99bda47ebb8c03a276b57371b5788e154a"
] | [
"Totoro/tests/testSets.py"
] | [
"#!/usr/bin/env python\n# encoding: utf-8\n\"\"\"\ntestSets.py\n\nCreated by José Sánchez-Gallego on 27 Aug 2014.\nLicensed under a 3-clause BSD license.\n\nRevision history:\n 27 Aug 2014 J. Sánchez-Gallego\n Initial version\n\n\"\"\"\n\nfrom __future__ import division, print_function\n\nimport unittest\n\... | [
[
"numpy.array"
]
] |
YuRui8879/CPSC2021_python | [
"bfa4c565ec3113528e73b064041082863cd228b4"
] | [
"code/entry_2021.py"
] | [
"#!/usr/bin/env python3\n\nimport numpy as np\nimport os\nimport sys\n\nimport wfdb\nfrom utils import qrs_detect, comp_cosEn, save_dict\nfrom DataAdapter import DataAdapter2\nimport torch.utils.data as Data\nfrom model import CNN,RNN\nimport torch\nfrom read_code import load_data,norm\nfrom scipy.signal import but... | [
[
"matplotlib.pyplot.legend",
"torch.load",
"numpy.squeeze",
"torch.utils.data.DataLoader",
"matplotlib.pyplot.plot",
"torch.no_grad",
"torch.cuda.is_available",
"numpy.where",
"numpy.stack",
"numpy.save",
"scipy.signal.butter",
"scipy.interpolate.interp1d",
"nump... |
drwxyh/Simulator-1 | [
"d3d5911ae7bf3ed9b98f979a78816b4c2516bac1"
] | [
"simulator/simulator.py"
] | [
"import os\nimport sys\nimport random\nimport re\nimport copy\nimport matplotlib\nimport matplotlib.pyplot as plt\nimport pandas as pd\nimport numpy as np\nimport logging\nimport datetime as dt\nfrom math import radians, cos, sin, asin, sqrt\nfrom datetime import datetime,timedelta\nfrom objects.objects import Clus... | [
[
"pandas.concat",
"pandas.read_csv",
"matplotlib.pyplot.title",
"matplotlib.pyplot.scatter",
"matplotlib.pyplot.ylim",
"pandas.DataFrame",
"numpy.sin",
"matplotlib.pyplot.plot",
"numpy.timedelta64",
"matplotlib.pyplot.xlim",
"matplotlib.pyplot.xlabel",
"numpy.array",... |
ChampDBG/PlayGround | [
"b5c685c5fd6bcbbd19fb1bc918614fbdea41f7f0"
] | [
"cython/cliffwalk_v3/py_cliffwalk.py"
] | [
"import numpy as np\n\nclass cliffwalk():\n def __init__(self, Steps, Method):\n # environment parameters\n self.Gamma = 0.99\n self.Epsilon = 0.1\n self.Alpha = 0.05\n self.steps = Steps\n self.method = Method\n # learning setting\n self.state = 36\n ... | [
[
"numpy.full",
"numpy.max",
"numpy.argmax",
"numpy.random.rand",
"numpy.zeros",
"numpy.sum",
"numpy.random.randint"
]
] |
marcostx/meutcc | [
"ac51c81879f56124b70813b72a54532bc8c37d3e"
] | [
"scripts/drivers_distributions.py"
] | [
"\nimport matplotlib\nmatplotlib.use('Agg')\nimport matplotlib.pyplot as plt\n\nf = open('driver_imgs_list.csv')\nlines = f.readlines()[1:] # header\ndrivers = {}\nfor line in lines:\n\tdriver, c, img = line[:-1].split(',')\n\tif driver not in drivers:\n\t\tdrivers[driver] = [0 for x in range(10)]\n\tclassindex = i... | [
[
"matplotlib.use",
"matplotlib.pyplot.savefig",
"matplotlib.pyplot.figure"
]
] |
ratvec/ratvec | [
"ba1442de57fbb8004f5a0295b1d4768f72db6acf"
] | [
"src/ratvec/metrics.py"
] | [
"# -*- coding: utf-8 -*-\n\nimport distance\nimport numpy as np\n\nfrom ratvec.utils import ngrams\n\n\n# TODO replace with numpy implementation of sorensen dice?\n\ndef sorensen_plus(a: str, b: str) -> float:\n length = min(len(a), len(b))\n ng = [\n distance.sorensen(ngrams(a, n), ngrams(b, n))\n ... | [
[
"numpy.sum"
]
] |
Tubbz-alt/iGibson | [
"66263f48b16d328c3c8cc60558c7fea63eb47b7e"
] | [
"gibson2/utils/data_utils/ext_scene/scripts/step_4_convert_to_ig.py"
] | [
"#!/usr/bin/env python\n\nimport os\nimport json\nimport math\nimport shutil\nimport gibson2\nimport argparse\nimport numpy as np\nimport xml.etree.ElementTree as ET\nfrom gibson2.utils.utils import parse_config\n\nfrom gibson2.scenes.igibson_indoor_scene import SCENE_SOURCE\nfrom gibson2.utils.assets_utils import ... | [
[
"numpy.asarray",
"numpy.cos",
"numpy.linalg.norm",
"numpy.sin",
"numpy.std",
"numpy.mean",
"numpy.random.rand",
"numpy.array"
]
] |
HarmanDotpy/Visual-Sudoku-Solver-Deep-Learning | [
"f620c1e79c9031f9eaa881190ba3b775be53272b"
] | [
"useful_scripts/numpy2images.py"
] | [
"import numpy as np\nimport matplotlib.pyplot as plt\nimport os\nimport PIL.Image as Image\nimport torch.optim as optim\nimport argparse\n\nif __name__ == \"__main__\":\n parser = argparse.ArgumentParser()\n parser.add_argument('--savedir', type=str, default = None)\n parser.add_argument('--numpy_images_fi... | [
[
"numpy.load",
"numpy.max",
"numpy.random.permutation"
]
] |
nathan-diodan/js50 | [
"6bc356fb4b2f9af6bc81a37d822469fe58c5aee5"
] | [
"js50py/lamp_player.py"
] | [
"import colorsys\nimport math\nimport time\nfrom multiprocessing import Process, Queue\nfrom pathlib import Path\nfrom queue import Empty as qu_Empty\nfrom threading import Thread\nimport random\nimport moderngl\nimport numpy as np\nimport sounddevice as sd\nimport zmq\nfrom matplotlib import cm\nfrom pyhap import ... | [
[
"numpy.random.random",
"numpy.fft.rfft",
"numpy.cos",
"numpy.sin",
"numpy.frombuffer",
"matplotlib.cm.get_cmap",
"numpy.random.uniform",
"numpy.flip",
"numpy.roll",
"numpy.zeros",
"numpy.random.randint"
]
] |
yuval-olshaker/OpenNMT-py | [
"46e2c138e4edb3942dfa1a5c05f35a484fb78c20"
] | [
"onmt/models/model.py"
] | [
"\"\"\" Onmt NMT Model base class definition \"\"\"\nimport torch\nimport torch.nn as nn\n\n\nclass NMTModel(nn.Module):\n \"\"\"\n Core trainable object in OpenNMT. Implements a trainable interface\n for a simple, generic encoder + decoder model.\n\n Args:\n encoder (onmt.encoders.EncoderBase): an... | [
[
"torch.argmax"
]
] |
zhigangjiang/DLAndML-Experiment | [
"162fb9c2a0865b6adf16f9a9e9a3f6a9b3e7f9b6"
] | [
"Hw/H8_Seq2Seq/data.py"
] | [
"import re\nimport json\nimport torch.utils.data as data\nimport numpy as np\nimport os\nimport torch\n\n\nclass LabelTransform(object):\n def __init__(self, size, pad):\n self.size = size\n self.pad = pad\n\n def __call__(self, label):\n label = np.pad(label, (0, (self.size - label.shape... | [
[
"numpy.asarray",
"torch.LongTensor",
"numpy.pad"
]
] |
brianpinto91/atfm-delay-prediction | [
"ab2db44b4c6319769cda1255553cc4e665cf9fa1"
] | [
"training/utils.py"
] | [
"import pandas as pd\nimport numpy as np\nimport datetime as dt\nfrom sklearn.metrics import r2_score, mean_absolute_error, mean_squared_error\nimport matplotlib.pyplot as plt\nimport os\nimport logging\nimport json\n\n# data directory containing the raw NMIR files\nNMIR_DATA_DIR = \"data/NMIR\"\n\n# savepath for t... | [
[
"pandas.read_csv",
"sklearn.metrics.r2_score",
"pandas.to_datetime",
"numpy.abs",
"numpy.isnan",
"sklearn.metrics.mean_absolute_error",
"matplotlib.pyplot.subplots",
"pandas.DataFrame",
"sklearn.metrics.mean_squared_error",
"numpy.concatenate",
"numpy.array"
]
] |
ylfzr/maml-reptile-HB | [
"41d864633ac864683e2ad8145bfdd52357c79b69"
] | [
"maml.py"
] | [
"\"\"\" Code for the MAML algorithm and network definitions. \"\"\"\nfrom __future__ import print_function\nimport numpy as np\nimport sys\nimport pdb\nimport tensorflow as tf\nimport time\nfrom tensorflow.python import debug as tfdbg\ntry:\n import special_grads\nexcept KeyError as e:\n print('WARN: Cannot d... | [
[
"tensorflow.get_variable",
"numpy.sqrt",
"tensorflow.zeros",
"tensorflow.reduce_sum",
"tensorflow.nn.l2_loss",
"tensorflow.map_fn",
"tensorflow.summary.scalar",
"tensorflow.placeholder_with_default",
"tensorflow.stop_gradient",
"tensorflow.contrib.layers.xavier_initializer"... |
tonymisic/Localizing-Visual-Sounds-the-Hard-Way | [
"d3652d2314ac8a5cfadf4f569fbf05baffffdd35"
] | [
"losses.py"
] | [
"from turtle import pos\nimport numpy as np, torch, torch.nn as nn\nimport torch.nn.functional as F\n\nclass HardWayLoss(torch.nn.Module):\n \"\"\"My implementation of HardWay Loss\n \"\"\"\n def __init__(self):\n super(HardWayLoss, self).__init__()\n\n def forward(self, positives, negatives, dev... | [
[
"torch.exp",
"torch.tensor"
]
] |
KyleAnthonyShepherd/SISRRA_tensor_contraction | [
"df631076b88fb12c562950790e96b359b0962d46"
] | [
"ICOSSAR_2021/ATRnumbaTrie.py"
] | [
"'''\nThis module calculates the all terminal reliability of undirected graphs\n\nFunctions\n---------\n**ATR(EdgeList,EP,verbose=False,TrieHashThreshold=10) :** \n Calculates the All Terminal Reliability of a undirected graph defined by EdgeList.\n\nNotes\n-----\nWhen these functions are first executed, numba ... | [
[
"numpy.ones",
"numpy.all",
"numpy.int64",
"numpy.max",
"numpy.copy",
"numpy.uint64",
"numpy.argsort",
"numpy.array",
"numpy.zeros"
]
] |
BellaNasirudin/py21cmmc_fg | [
"928822d07760c481c7673c83c1b7bf4421310b31"
] | [
"tests/instrumental_tests.py"
] | [
"\"\"\"\nSome tests of the instrumental core/likelihood.\n\"\"\"\n\nfrom py21cmmc_fg.core import CoreInstrumental, ForegroundsBase\nfrom py21cmmc_fg.likelihood import LikelihoodInstrumental2D\nfrom py21cmmc_fg.diagnostics import imaging\nimport numpy as np\n\nfrom powerbox.dft import fft, ifft\nimport matplotlib\nm... | [
[
"numpy.logical_and",
"numpy.add.outer",
"numpy.arange",
"matplotlib.use",
"matplotlib.pyplot.savefig",
"numpy.sin",
"matplotlib.pyplot.clf",
"numpy.meshgrid",
"numpy.zeros"
]
] |
killax-d/Counter-Coins-API | [
"97acede70e26b23f96883bb14e2bf6ace3759174",
"97acede70e26b23f96883bb14e2bf6ace3759174"
] | [
"routes/classify.py",
"modules/AI/research/findContour.py"
] | [
"from datetime import datetime\nfrom os import makedirs, path\nfrom os.path import join, dirname, realpath\nfrom flask import Blueprint, Response, request, jsonify\nimport json\nimport uuid\nfrom modules.AI.utils import prepare\nimport numpy as np\nimport cv2\n\nfrom services.classifier import ClassifierService\nfr... | [
[
"numpy.fromstring"
],
[
"numpy.ones"
]
] |
ingredio/Phase3 | [
"1b70313a1fd483e71b30a59dd0eb78ed80623fb6"
] | [
"entity_extraction/src/train_task1.py"
] | [
"import config_task1 as config\nimport statistics\nfrom tqdm import tqdm, trange\nimport torch\nfrom transformers import BertForTokenClassification, AdamW, get_linear_schedule_with_warmup\nimport numpy as np\nfrom sklearn.metrics import classification_report, precision_score, f1_score\nimport sys\nimport dataset_ta... | [
[
"torch.load",
"sklearn.metrics.precision_score",
"pandas.DataFrame",
"numpy.argmax",
"torch.no_grad",
"sklearn.metrics.f1_score",
"sklearn.metrics.classification_report"
]
] |
dsbrown1331/bcprefs | [
"37a499a2ae7f93731a8a91b888823df252115b08"
] | [
"spinup/experiments/bc_prefs/good_bad_demo_degradation.py"
] | [
"import torch\nfrom torch.optim import Adam\nimport torch.nn as nn\nimport numpy as np\nimport gym\nimport os\nimport copy\nimport matplotlib.pyplot as plt\nimport matplotlib.patches as patches\nfrom spinup.algos.pytorch.bc.bc import train_good_bad_bc_policy, evaluate_policy\n\ntorchify = lambda x: torch.FloatTenso... | [
[
"numpy.random.seed",
"torch.manual_seed",
"torch.FloatTensor",
"numpy.mean",
"torch.device"
]
] |
Yorkbenno/SEAM | [
"6213fea7de5ac8bfbc8e1d15dd322fcd28a35917"
] | [
"network/resnet38d.py"
] | [
"import torch\nfrom torch import nn\nimport numpy as np\n\nimport torch.nn.functional as F\nclass ResBlock(nn.Module):\n def __init__(self, in_channels, mid_channels, out_channels, stride=1, first_dilation=None, dilation=1):\n super(ResBlock, self).__init__()\n\n self.same_shape = (in_channels == o... | [
[
"torch.nn.Dropout2d",
"numpy.asarray",
"numpy.empty_like",
"torch.nn.Conv2d",
"torch.nn.functional.relu",
"torch.nn.BatchNorm2d"
]
] |
fgrsnau/combilp | [
"915b2a82f683996d3a015039a93474c81cec77d1"
] | [
"combilp/model.py"
] | [
"# Copyright (c) 2017 Stefan Haller\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 rights\n# to use, copy, modify, merge, pu... | [
[
"numpy.asarray",
"numpy.zeros"
]
] |
mniyas/gramex | [
"b1d21067cb3939e8be63542336bc716038f37815"
] | [
"tests/test_auth.py"
] | [
"import os\nimport json\nimport time\nimport email\nimport shutil\nimport requests\nimport lxml.html\nimport pandas as pd\nimport sqlalchemy as sa\nfrom nose.tools import eq_, ok_\nfrom nose.plugins.skip import SkipTest\nfrom tornado.web import create_signed_value\nfrom urllib.parse import urlencode, urljoin\nimpor... | [
[
"pandas.read_sql",
"pandas.DataFrame",
"pandas.ExcelWriter"
]
] |
keyofdeath/AugmentedReality | [
"dfd30e17c9af5a4c392ae618d9f1f0fbf8a4e5b6"
] | [
"ImgOperator/Tool.py"
] | [
"#!/usr/bin/env python\n# -*- coding: utf-8 -*-\n\nimport cv2\nimport numpy as np\nimport glob\nfrom ImgOperator.Filtration.Canny import ImgCanny\nfrom copy import deepcopy\n\n\ndef take_pic(cam):\n \"\"\"\n\n :param cam:\n :return:\n \"\"\"\n while True:\n ret, frame = cam.read()\n cv2... | [
[
"numpy.argmax",
"numpy.zeros",
"numpy.argmin",
"numpy.diff"
]
] |
Theigrams/deeplearning-models | [
"1259c75284bf66316470c3b74ac59d74a66760ff"
] | [
"pytorch_ipynb/helper_utils.py"
] | [
"import os\nimport random\nimport numpy as np\nimport torch\n\n\ndef set_all_seeds(seed):\n os.environ[\"PL_GLOBAL_SEED\"] = str(seed)\n random.seed(seed)\n np.random.seed(seed)\n torch.manual_seed(seed)\n torch.cuda.manual_seed_all(seed)\n \n\ndef set_deterministic():\n if torch.cuda.is_availa... | [
[
"numpy.random.seed",
"torch.manual_seed",
"torch.set_deterministic",
"torch.cuda.is_available",
"torch.cuda.manual_seed_all"
]
] |
fraunhofer-iais/IAIS-Python-Snippets | [
"a3ee610d6270cda2c891688851696c34831ffa2b"
] | [
"Modelling/Regression/SVR.py"
] | [
"# Model via support vector machine\nfrom sklearn.svm import SVR\nfrom sklearn.model_selection import GridSearchCV\n\nparameters = {'kernel':['rbf'], 'C':10.0**np.arange(-4, 4), 'epsilon':[0.1, 0.2]}\n\nmodel = SVR()\nregs = GridSearchCV(model, parameters, cv=10)\nregs.fit(X_train, y_train)\nreg = regs.best_estimat... | [
[
"sklearn.svm.SVR",
"sklearn.model_selection.GridSearchCV"
]
] |
MaxLell/Chrome_Dino_AI | [
"6a586b6894a2c07f0e247fb28d96372250530346"
] | [
"library/Dino_Game.py"
] | [
"import pygame as pg\r\nimport random\r\nimport os\r\nimport numpy as np\r\nfrom sys import exit\r\n\r\nfrom Dino import *\r\nfrom Obstacles import *\r\nfrom Background import *\r\n\r\nclass DinoGame():\r\n\r\n def __init__(self):\r\n\r\n # Set screen parameters\r\n pg.init()\r\n self.disp_x... | [
[
"numpy.random.randint"
]
] |
rikyborg/presto-measure | [
"b04379f2c010c0c15a5b9b935ca9293694c89327",
"b04379f2c010c0c15a5b9b935ca9293694c89327",
"b04379f2c010c0c15a5b9b935ca9293694c89327"
] | [
"load_two_tone_single.py",
"sweep_power.py",
"jumps.py"
] | [
"# -*- coding: utf-8 -*-\n\"\"\"\nLoader for files saved by two_tone_single.py\n\"\"\"\nimport h5py\nfrom matplotlib import rcParams\nimport matplotlib.pyplot as plt\nimport numpy as np\n\nrcParams['figure.dpi'] = 331.3\n\nload_filename = \"\"\n\n\ndef load(load_filename):\n with h5py.File(load_filename, \"r\") ... | [
[
"numpy.abs",
"numpy.angle",
"matplotlib.pyplot.subplots"
],
[
"numpy.logspace",
"numpy.arange",
"numpy.zeros",
"numpy.mean"
],
[
"numpy.arange",
"numpy.zeros",
"numpy.mean"
]
] |
tarepan/state-spaces | [
"3427a1f12a29ad8ccebaa8ee105f62f7f8a3d891"
] | [
"src/models/sequence/ss/standalone/s4.py"
] | [
"\"\"\" Standalone version of Structured (Sequence) State Space (S4) model. \"\"\"\n\n\nimport logging\nfrom functools import partial\nimport math\nimport numpy as np\nfrom scipy import special as ss\nimport torch\nimport torch.nn as nn\nimport torch.nn.functional as F\nimport torch.nn.utils as U\nfrom pytorch_ligh... | [
[
"numpy.diag",
"torch.nn.init.uniform_",
"torch.nn.GLU",
"torch.cat",
"torch.zeros",
"torch.sum",
"torch.no_grad",
"numpy.exp",
"numpy.where",
"torch.ones",
"torch.einsum",
"torch.randn",
"numpy.eye",
"torch.eye",
"numpy.arange",
"torch.nn.Sigmoid",
... |
csuter/probability | [
"c12366f1878c8583c462261b502e27cefc62263c"
] | [
"tensorflow_probability/python/experimental/nn/util/__init__.py"
] | [
"# Copyright 2019 The TensorFlow Probability Authors.\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 a... | [
[
"tensorflow.python.util.all_util.remove_undocumented"
]
] |
YunyaoCheng/Books | [
"8196417fdc86128f9a8e1f012ca801a07d2984d2"
] | [
"Computer Science/eat_tensorflow2_in_30_days/practice/1_procession of tf modeling/1_example of structured data modeling/main.py"
] | [
"#一，准备数据\nimport numpy as np\nimport pandas as pd\nimport tensorflow as tf\nimport matplotlib.pyplot as plt\nfrom tensorflow.keras import layers, models\n\ndftrain_raw = pd.read_csv('./data/titanic/train.csv')\ndftest_raw = pd.read_csv('./data/titanic/test.csv')\ndftrain_raw.head(10)\n\nax = dftrain_raw['Survived']... | [
[
"tensorflow.keras.models.load_model",
"pandas.concat",
"pandas.read_csv",
"matplotlib.pyplot.legend",
"matplotlib.pyplot.title",
"tensorflow.keras.layers.Dense",
"pandas.DataFrame",
"matplotlib.pyplot.plot",
"matplotlib.pyplot.ylabel",
"tensorflow.keras.backend.clear_sessio... |
jryzkns/U-iDE_BLACKE | [
"75179ef8102b9751a7fac4ef9cbb0516a73cbab4"
] | [
"model/angle_models/angL2.py"
] | [
"import torch\nimport torch.nn as nn\nimport torch.nn.functional as F\nimport torch.optim as optim\nfrom torchvision import datasets, transforms\nfrom torch.autograd import Variable\n\nimport pandas\nimport numpy as np\n\nfrom sklearn.preprocessing import LabelEncoder\nfrom sklearn.model_selection import train_test... | [
[
"torch.LongTensor",
"pandas.read_csv",
"torch.nn.CrossEntropyLoss",
"torch.norm",
"torch.utils.data.TensorDataset",
"torch.nn.functional.cross_entropy",
"torch.utils.data.DataLoader",
"sklearn.model_selection.train_test_split",
"torch.FloatTensor",
"torch.cuda.is_available"... |
pprp/SimpleDetection | [
"d4bb85afc07a73141deda04ca6bc024a1fa94e71"
] | [
"utils/utils.py"
] | [
"import os\nimport random\nimport sys\nfrom xml.etree import ElementTree as ET\nfrom tqdm import tqdm\n\nimport cv2\nimport matplotlib.pyplot as plt\nimport numpy as np\nimport torch\nfrom torch.utils.data import DataLoader, Dataset\nfrom sklearn.model_selection import train_test_split\n\nmain_path = os.path.dirnam... | [
[
"torch.cuda.manual_seed",
"numpy.random.seed",
"torch.Tensor",
"torch.manual_seed",
"torch.from_numpy",
"torch.tensor",
"torch.cuda.is_available",
"torch.device",
"numpy.array",
"numpy.zeros",
"torch.stack"
]
] |
antonpaquin/mlflow | [
"bb6e5e9e50554a157bd7adacce1c1c9a78438386"
] | [
"mlflow/pyfunc/__init__.py"
] | [
"# -*- coding: utf-8 -*-\n\n\"\"\"Export and import of generic Python models.\n\nThis module defines generic filesystem format for Python models and provides utilities\nfor saving and loading to and from this format. The format is self contained in the sense\nthat it includes all necessary information for anyone to... | [
[
"pandas.Series",
"pandas.DataFrame"
]
] |
mcx/quad | [
"67b0e1771e62c5371bac75bf82eb6ca1d882045b"
] | [
"utils/video_aligner.py"
] | [
"#!/usr/bin/env python3\n\n# Copyright 2020 Josh Pieper, jjp@pobox.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 License.\n# You may obtain a copy of the License at\n#\n# http://www.apache.org/licenses/LICENSE-2.0\n#\n# Un... | [
[
"scipy.signal.correlate",
"numpy.arange",
"scipy.interpolate.interp1d",
"numpy.argmax",
"numpy.array",
"scipy.io.wavfile.read"
]
] |
lenhattan86/tf_bench | [
"8b2b363fb6a819d84b3b11552c2ea97886188a18"
] | [
"scripts/tf_cnn_benchmarks/tf_cnn_benchmarks.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.device",
"tensorflow.concat",
"numpy.sqrt",
"tensorflow.control_dependencies",
"tensorflow.reduce_sum",
"tensorflow.RunMetadata",
"tensorflow.global_variables",
"tensorflow.cast",
"tensorflow.python.layers.convolutional.conv2d",
"tensorflow.python.ops.data_flow_... |
rahul263-stack/PROJECT-Dump | [
"d8b1cfe0da8cad9fe2f3bbd427334b979c7d2c09"
] | [
"covid19.py"
] | [
"import pandas as pd\n\ndf = pd.read_csv('https://opendata.ecdc.europa.eu/covid19/casedistribution/csv')\n# Remove unuseful columns\ndf = df[['dateRep', 'cases', 'deaths', 'countriesAndTerritories', 'countryterritoryCode', 'continentExp']]\n# Rename columns\ndf = df.rename(columns={\n 'dateRep': 'date',\n 'co... | [
[
"pandas.read_csv",
"pandas.to_datetime"
]
] |
oceanbupt/GBDT_Simple_Tutorial | [
"a337fbabc50fadf84bf87f222a71f58586eb261b"
] | [
"example.py"
] | [
"import os\nimport shutil\nimport logging\nimport argparse\nimport pandas as pd\nfrom GBDT.gbdt import GradientBoostingRegressor\nfrom GBDT.gbdt import GradientBoostingBinaryClassifier\nfrom GBDT.gbdt import GradientBoostingMultiClassifier\n# author: not me\n\nlogging.basicConfig(level=logging.INFO)\nlogger = loggi... | [
[
"pandas.set_option",
"pandas.DataFrame"
]
] |
tuggeluk/auto-sklearn | [
"1c6af59ff61f1d0a3b54b16a35ffbc5d2d3828cd"
] | [
"test/test_pipeline/components/feature_preprocessing/test_NoPreprocessing.py"
] | [
"import numpy as np\nimport unittest\n\nfrom autosklearn.pipeline.components.feature_preprocessing.no_preprocessing import NoPreprocessing\nfrom autosklearn.pipeline.util import _test_preprocessing, PreprocessingTestCase\n\n\nclass NoneComponentTest(PreprocessingTestCase):\n def test_default_configuration(self):... | [
[
"numpy.min",
"numpy.max",
"numpy.std",
"numpy.mean",
"numpy.sum"
]
] |
ashishkumar1550/reidfiles | [
"6a4258e42a9c5be94d8000c319164b6aa43ac5c7"
] | [
"engine/inference.py"
] | [
"# encoding: utf-8\n\"\"\"\n@author: sherlock\n@contact: sherlockliao01@gmail.com\n\"\"\"\nimport logging\n\nimport torch\nfrom ignite.engine import Engine\n\nfrom utils.reid_metric import R1_mAP, R1_mAP_reranking\n\n\ndef create_supervised_evaluator(model, metrics,\n device=None):\n... | [
[
"torch.no_grad"
]
] |
hellovertex/PokerRL | [
"061ca745ec43ca6509111dafa4bb4b25796c8096"
] | [
"PokerRL/cfr/VanillaCFR.py"
] | [
"# Copyright (c) 2019 Eric Steinberger\n\n\nimport numpy as np\n\nfrom prl.environment.steinberger.PokerRL.cfr._CFRBase import CFRBase as _CFRBase\n\n\nclass VanillaCFR(_CFRBase):\n\n def __init__(self,\n name,\n chief_handle,\n game_cls,\n agent_be... | [
[
"numpy.expand_dims",
"numpy.maximum",
"numpy.full",
"numpy.errstate",
"numpy.sum"
]
] |
eladsar/spinningup | [
"e967f53415a493171f96324c802062f3cad4dada"
] | [
"spinup/algos/pytorch/mbfq/core.py"
] | [
"import numpy as np\nimport scipy.signal\n\nimport torch\nimport torch.nn as nn\nimport torch.nn.functional as F\nfrom torch.distributions.normal import Normal\nfrom torch.distributions.utils import _standard_normal, broadcast_all\nfrom torch.distributions.exp_family import ExponentialFamily\nfrom numbers import Nu... | [
[
"torch.cat",
"torch.distributions.utils._standard_normal",
"torch.tanh",
"torch.no_grad",
"torch.nn.functional.smooth_l1_loss",
"torch.Size",
"torch.erfinv",
"torch.tensor",
"torch.square",
"torch.nn.functional.softplus",
"torch.nn.Sequential",
"numpy.log",
"tor... |
kroonhorstdino/dota2_death_prediction | [
"9b8a3cd831abbc6ec14d94adabeab0fd34470c0b"
] | [
"train.py"
] | [
"import os\nimport random\nimport glob\nimport itertools\nimport sys\nimport time\nfrom pathlib import Path\n\nimport numpy as np\nimport pandas as pd\nfrom matplotlib import pyplot as plt\n\nimport torch\nimport torch.nn as nn\nfrom torch.autograd import Variable\nimport torch.nn.functional as F\nfrom torch.utils.... | [
[
"matplotlib.pyplot.legend",
"sklearn.metrics.roc_auc_score",
"numpy.expand_dims",
"torch.load",
"numpy.squeeze",
"torch.utils.data.DataLoader",
"matplotlib.pyplot.plot",
"numpy.mean",
"torch.no_grad",
"torch.cuda.is_available",
"torch.device",
"numpy.random.randint"... |
GRAP-UdL-AT/RGBD_fruit_detection_faster-rcnn.pytorch- | [
"d9608486a8317bc825b110cc34a6d1d496be8452"
] | [
"lib/model/roi_crop/functions/gridgen.py"
] | [
"# functions/add.py\nimport torch\nfrom torch.autograd import Function\nimport numpy as np\n\n\nclass AffineGridGenFunction(Function):\n def __init__(self, height, width,lr=1):\n super(AffineGridGenFunction, self).__init__()\n self.lr = lr\n self.height, self.width = height, width\n s... | [
[
"numpy.arange",
"torch.transpose",
"numpy.zeros",
"numpy.ones"
]
] |
muon-spectroscopy-computational-project/muspinsim | [
"d9e971edd840ab0c33b143f9b5694bc1b09011d2"
] | [
"muspinsim/experiment.py"
] | [
"\"\"\"experiment.py\n\nClasses and functions to perform actual experiments\"\"\"\n\nimport logging\nimport numpy as np\nimport scipy.constants as cnst\n\nfrom muspinsim.constants import MU_TAU\nfrom muspinsim.utils import get_xy\nfrom muspinsim.mpi import mpi_controller as mpi\nfrom muspinsim.simconfig import MuSp... | [
[
"numpy.amin",
"numpy.linalg.norm",
"numpy.real",
"numpy.linalg.eigh",
"numpy.exp",
"numpy.array",
"numpy.zeros",
"numpy.sum",
"numpy.isclose"
]
] |
pllim/photutils | [
"ff78b6dd97a9fa890b6c77b51f207d4c2ff28889"
] | [
"photutils/detection/tests/test_core.py"
] | [
"# Licensed under a 3-clause BSD style license - see LICENSE.rst\n\"\"\"\nTests for the core module.\n\"\"\"\n\nimport warnings\n\nfrom astropy.tests.helper import assert_quantity_allclose\n# from astropy.tests.helper import catch_warnings\nimport numpy as np\nfrom numpy.testing import assert_allclose, assert_array... | [
[
"numpy.ones",
"numpy.testing.assert_array_equal",
"numpy.copy",
"numpy.testing.assert_allclose",
"numpy.array",
"numpy.zeros"
]
] |
swc2124/skysurvey | [
"d856506dab7531197f483bbac581d4ddf4f8a6f0"
] | [
"skysurvey/table_bin.py"
] | [
"# -*- coding: utf-8 -*-\n# @Author: sol courtney\n# @Date: 2017-06-11 19:23:59\n# @Last Modified by: swc21\n# @Last Modified time: 2017-08-29 23:30:02\n\n'''[summary]\n\n[description]\n\nAttributes\n----------\nsys_config_fh : {[type]}\n [description]\nSysConfig : {[type]}\n [description]\nSysConfig.read... | [
[
"numpy.square",
"numpy.nonzero",
"numpy.ones",
"numpy.arctan2",
"numpy.log10",
"numpy.float64",
"numpy.load",
"numpy.logical_and"
]
] |
ppalaupuigdevall/moments-vae | [
"02089da4549a58e4a8e9620010b578e5dd2feea0",
"02089da4549a58e4a8e9620010b578e5dd2feea0"
] | [
"SOS/moments.py",
"train_hinge.py"
] | [
"\"\"\" \nAuthor: Marina Alonso\n\nThe notation from \"SoS-RSC: A Sum-of-Squares Polynomial Approach to Robustifying Subspace Clustering Algorithms\", section 2.\n\nx = [x1, x2, ... xd]\n\n n+d \ns_nd = ( )\n d\n\nMn: Moment matrix (s_nd, s_nd)\n\nv_n(x): veronese map of x: all possible mo... | [
[
"numpy.log",
"numpy.sum",
"matplotlib.pyplot.title",
"numpy.random.seed",
"numpy.linalg.inv",
"numpy.matmul",
"numpy.ones",
"scipy.special.comb",
"matplotlib.pyplot.plot",
"numpy.random.normal",
"matplotlib.pyplot.subplot",
"scipy.stats.norm.rvs",
"numpy.array",... |
joshmoore/slicedimage | [
"bdadda151337640e950cb040617ad7d969a04729"
] | [
"tests/io/v0_0_0/test_write.py"
] | [
"import codecs\nimport json\nimport numpy\nimport os\nimport tempfile\nimport unittest\n\nimport slicedimage\nfrom tests.utils import TemporaryDirectory\n\n\nbaseurl = \"file://{}\".format(os.path.abspath(os.path.dirname(__file__)))\n\n\nclass TestWrite(unittest.TestCase):\n def test_write_tileset(self):\n ... | [
[
"numpy.zeros"
]
] |
tamarervin/sdo_hmi_rvs | [
"6b3b5a5622a0b3e9a3477a5c596f009e6463cd1f"
] | [
"SolAster/tools/calculation_funcs.py"
] | [
"\"\"\"\nTamar Ervin\nDate: June 16, 2021\n\nfunctions for calculating Solar velocity corrections\nand components for derivation of SDO/HMI RVs\n\"\"\"\n\nimport datetime\nimport numpy as np\n\nimport astropy.units as u\nfrom astropy.coordinates import SkyCoord\n\nimport sunpy.map\nfrom sunpy.net import Fido\nfrom ... | [
[
"numpy.isin",
"numpy.sqrt",
"numpy.abs",
"numpy.full",
"numpy.logical_or",
"numpy.sin",
"numpy.deg2rad",
"numpy.nansum",
"numpy.real",
"numpy.array",
"numpy.logical_and",
"numpy.where",
"numpy.sum",
"numpy.zeros"
]
] |
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