repo_name stringlengths 6 130 | hexsha list | file_path list | code list | apis list |
|---|---|---|---|---|
kblancato/theia-net | [
"cdb912e1b35701f22928e084913e004352a6fe95"
] | [
"theia-net/classification/modules/model.py"
] | [
"import torch\nimport torch.nn as nn\nimport torch.nn.functional as F\nfrom torch.autograd import Variable\n\n\nclass CNN(torch.nn.Module):\n \"\"\"\n 1D CNN model architecture.\n \n Attributes\n ----------\n num_in : int\n Exposure in seconds.\n \n n_classes : int\n Nu... | [
[
"torch.nn.BatchNorm1d",
"torch.nn.Dropout",
"torch.cat",
"torch.nn.Linear",
"torch.nn.Conv1d",
"torch.nn.AvgPool1d"
]
] |
kangzhiq/sunpy | [
"fad034a2ca0bebfa041e47b18a0789d2bc4b4aa6"
] | [
"sunpy/timeseries/tests/test_timeseries_factory.py"
] | [
"# -*- coding: utf-8 -*-\n\"\"\"\nCreated on Thu Jun 23 12:08:21 2016\n\n@author: alex_\n\"\"\"\n\nimport os\nimport glob\nimport pytest\nimport datetime\nimport numpy as np\nfrom pandas import DataFrame\nfrom collections import OrderedDict\n\nimport sunpy.data.test\nimport sunpy.timeseries\nfrom sunpy.util.metadat... | [
[
"numpy.arange",
"pandas.DataFrame"
]
] |
skyduy/zfverify | [
"a49e314df7b8b3822dd941b44d68c0fde77df9c9"
] | [
"Verify-Manual-python/predict/predictOneVsAll.py"
] | [
"# coding: utf-8\nfrom numpy import dot, hstack, ones, argmax\nfrom sigmoid import sigmoid\n\n\ndef predictOneVsAll(all_theta, X):\n m = X.shape[0]\n\n X = hstack((ones((m, 1)), X))\n\n real_all_theta = all_theta.transpose()\n all_predict = sigmoid(dot(X, real_all_theta))\n\n Accuracy = all_predict.m... | [
[
"numpy.dot",
"numpy.argmax",
"numpy.ones"
]
] |
middlec000/wordler | [
"ad76dea50f0baab398d16366bfc55557ae187fce"
] | [
"src/main.py"
] | [
"import streamlit as st\nimport pandas as pd\nfrom helper_methods import *\n\n\ndef suggest(df: pd.DataFrame, original_length: int, num_words_to_display: int, sort_by: str) -> None:\n \"\"\"\n Print the suggested words nicely and ordered by the desired metric.\n\n Args:\n df (pd.DataFrame): Remainin... | [
[
"pandas.read_csv"
]
] |
Rocketknight1/pytorch-pretrained-BERT | [
"2c03c10d5e34badf17298e8f070c8c0169febe22"
] | [
"pytorch_pretrained_bert/modeling.py"
] | [
"# coding=utf-8\n# Copyright 2018 The Google AI Language Team Authors and The HuggingFace Inc. team.\n# Copyright (c) 2018, NVIDIA CORPORATION. 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... | [
[
"torch.nn.Softmax",
"torch.load",
"torch.zeros",
"torch.nn.Embedding",
"torch.nn.Dropout",
"torch.nn.CrossEntropyLoss",
"torch.ones",
"torch.sqrt",
"torch.from_numpy",
"torch.arange",
"tensorflow.train.list_variables",
"torch.ones_like",
"torch.sigmoid",
"to... |
flo-compbio/xlmhg | [
"c29d913386443396254774b8cff5cff2b5731323"
] | [
"tests/01_algorithms/test_correct_pval.py"
] | [
"# Copyright (c) 2016-2019 Florian Wagner\n#\n# This file is part of XL-mHG.\n\n\"\"\"Tests for the Cython implementations of the XL-mHG p-value..\"\"\"\n\nimport numpy as np\nfrom scipy.stats import hypergeom\n\nfrom xlmhg import mhg, mhg_cython\n\ndef test_cross():\n \"\"\"Compares p-values calculated using PV... | [
[
"scipy.stats.hypergeom.sf",
"numpy.empty",
"numpy.ones"
]
] |
guylapid/materialize | [
"8629a120a5a628b6ef06f379b48ba723797db944"
] | [
"demo/http_logs/apps/loadgen.py"
] | [
"#!/usr/bin/env python3\n\n# Copyright Materialize, Inc. and contributors. All rights reserved.\n#\n# Use of this software is governed by the Business Source License\n# included in the LICENSE file at the root of this repository.\n#\n# As of the Change Date specified in that file, in accordance with\n# the Business... | [
[
"numpy.random.poisson",
"numpy.sum",
"numpy.random.zipf"
]
] |
pints-team/markov-builder | [
"7accb6e7bc64a2a2afa35d4594c3f4dc3284923c"
] | [
"examples/simulation.py"
] | [
"#!/usr/bin/env python3\n\n# Simulate data from the Beattie model and M10 model using a Gillespie\n# algorithm output plots into examples/example_output or\n# MARKOVBUILDER_EXAMPLE_OUTPUT if it exists\n\nimport logging\nimport os\nimport sys\n\nimport matplotlib.pyplot as plt\nimport pandas as pd\n\nfrom markov_bui... | [
[
"pandas.concat",
"pandas.DataFrame",
"matplotlib.pyplot.savefig",
"matplotlib.pyplot.figure"
]
] |
hummat/if-net | [
"6eb6b3860159ba0a46167844020d8cbc7717fbb4"
] | [
"models/local_model.py"
] | [
"import torch\nimport torch.nn as nn\nimport torch.nn.functional as F\n\n\n# 1D convolution is used for the decoder. It acts as a standard FC, but allows to use a batch of point samples features,\n# additionally to the batch over the input objects.\n# The dimensions are used as follows:\n# batch_size (N) = #3D obje... | [
[
"torch.Tensor",
"torch.cat",
"torch.reshape",
"torch.nn.MaxPool3d",
"torch.nn.Conv3d",
"torch.nn.functional.grid_sample",
"torch.nn.Conv1d",
"torch.nn.ReLU",
"torch.nn.BatchNorm3d"
]
] |
lazy-turtle/SharpMask-RCNN | [
"f6a3106b029b8147cecec429ec9a3d747449274f"
] | [
"mrcnn/model.py"
] | [
"\"\"\"\nMask R-CNN\nThe main Mask R-CNN model implementation.\n\nCopyright (c) 2017 Matterport, Inc.\nLicensed under the MIT License (see LICENSE for details)\nWritten by Waleed Abdulla\n\"\"\"\n\nimport os\nimport random\nimport datetime\nimport re\nimport math\nimport logging\nfrom collections import OrderedDict... | [
[
"numpy.amax",
"numpy.expand_dims",
"tensorflow.concat",
"tensorflow.control_dependencies",
"tensorflow.stack",
"tensorflow.reduce_sum",
"tensorflow.minimum",
"tensorflow.cast",
"tensorflow.image.crop_and_resize",
"tensorflow.image.non_max_suppression",
"tensorflow.equal... |
HumaticsLAB/AttentionBasedMultiModalRNN | [
"0c060a97cdddf1348938a5f2d456e83e5f8bf887"
] | [
"config.py"
] | [
"import torch\n\nDEVICE = torch.device('cuda:0')\nDATASET_PATH = \"dataset/images\"\nTRAIN_DATASET = \"dataset/train.csv\"\nTEST_DATASET = \"dataset/test.csv\"\nCOMPOSED_GTREND = \"dataset/gtrends.csv\"\nCATEG_DICT = \"category_labels.pt\"\nCOLOR_DICT = \"color_labels.pt\"\nFAB_DICT = \"fabric_labels.pt\"\nNUM_EPOC... | [
[
"torch.device"
]
] |
PauloCirino/deep-learning-coursera | [
"69a89206bf4b0ec3148a1b69a2b31fb79e6adc7c"
] | [
"Neural-Networks-and-Deep-Learning/Logistic Regression as a Neural Network/Logistic Regression with a Neural Network mindset.py"
] | [
"\n# coding: utf-8\n\n# # Logistic Regression with a Neural Network mindset\n# \n# Welcome to your first (required) programming assignment! You will build a logistic regression classifier to recognize cats. This assignment will step you through how to do this with a Neural Network mindset, and so will also hone yo... | [
[
"matplotlib.pyplot.legend",
"matplotlib.pyplot.imshow",
"numpy.dot",
"scipy.misc.imresize",
"scipy.ndimage.imread",
"numpy.log",
"numpy.abs",
"numpy.squeeze",
"matplotlib.pyplot.plot",
"numpy.round",
"numpy.exp",
"matplotlib.pyplot.xlabel",
"numpy.array",
"n... |
mtsolmn/lantz-drivers | [
"f48caf9000ddd08f2abb837d832e341410af4788"
] | [
"lantz/drivers/microsoft/usbcam.py"
] | [
"import cv2\nimport numpy as np\nfrom lantz.core import Action, Driver, Feat\n\n\nclass USBCam(Driver):\n\n def __init__(self, device_id):\n self.device_id = device_id\n self._flipud = False\n self._fliplr = False\n self._rotation = 0\n return\n\n def initialize(self):\n ... | [
[
"numpy.fliplr",
"numpy.flipud"
]
] |
uniLee1119/Final-NeuralFBProphet | [
"40caac12a1805da6a061452ea5571b48d6f2bb8f"
] | [
"src/Final-NeuralFBProphet/prop_two_optim.py"
] | [
"import argparse\n\nimport joblib\nimport numpy as np\nimport optuna\nfrom fbprophet import Prophet\nfrom optuna import Trial\nfrom optuna.samplers import TPESampler\nfrom sklearn.metrics import mean_squared_error\n\nfrom data.dataset import two_seconds_dataset\n\nparse = argparse.ArgumentParser(\"Optimize\")\npars... | [
[
"sklearn.metrics.mean_squared_error",
"numpy.max",
"numpy.min"
]
] |
millerda/seaborn | [
"5a67fa98ed4efa5b3761f2d9d184fb8addfac6de"
] | [
"seaborn/rcmod.py"
] | [
"\"\"\"Control plot style and scaling using the matplotlib rcParams interface.\"\"\"\nimport warnings\nimport functools\nimport matplotlib as mpl\nfrom cycler import cycler\nfrom . import palettes\n\n\n__all__ = [\"set_theme\", \"set\", \"reset_defaults\", \"reset_orig\",\n \"axes_style\", \"set_style\", ... | [
[
"matplotlib.rcParams.update"
]
] |
brenobeirigo/vrplot | [
"e9ec5450940bd576f43c4ed07f17ae228dbd0eb8"
] | [
"vrplot/animated.py"
] | [
"################################################################################\n## PLOT ########################################################################\n################################################################################\n\n# ANIMATIONS\n#%matplotlib widget\nimport matplotlib.pyplot as plt\... | [
[
"matplotlib.pyplot.subplots",
"matplotlib.animation.FuncAnimation",
"matplotlib.pyplot.close"
]
] |
Cryaaa/tribolium-clustering | [
"f5751ec8c007e95e8a9688d2d8e34508b04f0822"
] | [
"tribolium_clustering/data_visualisation/_plot_cvi_each_timepoint_3D.py"
] | [
"def plot_cvi_each_timepoint_3D(cvi_scores_concatenated, timepoints_list, cluster_numbers, cvi_name = '', timepoint_label = 'Timepoints'):\n '''Plots a 3D plot displaying timepoint indices, cluster numbers and their cluster validation index scores\n \n Parameters\n ----------\n cvi_scores_concatenate... | [
[
"numpy.meshgrid",
"numpy.reshape",
"numpy.array",
"matplotlib.pyplot.show",
"matplotlib.pyplot.figure"
]
] |
beconstant/urnn | [
"7c74d0eff7181756c080cd44cce732cef2089242"
] | [
"utils/theano_complex_extension.py"
] | [
"import numpy as np\n\nfrom theano import tensor\n\n\n#------------------------------------------------------------------------------\n# Complex theano funcs\n\ndef frac(A):\n return A[0, :, :], A[1, :, :]\n\n\ndef skew_frac(A):\n return tensor.tril(A, -1) - tensor.tril(A, -1).T,\\\n tensor.triu(A, ... | [
[
"numpy.tensordot"
]
] |
ryscet/pySeries | [
"3ab1e0a9dbdeaef34c6c6d1fed5b248203c84fea"
] | [
"pyseries/Pipelines/AnalyzeBinRIv.py"
] | [
"# -*- coding: utf-8 -*-\n\"\"\"\nCreated on Fri Jun 24 12:27:09 2016\n\n@author: user\n\"\"\"\n\nimport sys\nsys.path.insert(0, '/Users/user/Desktop/repo_for_pyseries/pyseries')\n\nimport pyseries.LoadingData as loading\nimport pyseries.Preprocessing as prep\nimport pyseries.Analysis as analysis\nimport matplotlib... | [
[
"matplotlib.pyplot.plot",
"scipy.signal.welch",
"matplotlib.pyplot.figure"
]
] |
yzhq97/distortion-free-wide-angle.pytorch | [
"3d8899a84e5f5c4fca62385116bfdaf4876b2ff7"
] | [
"src/data.py"
] | [
"import cv2\nimport os\nimport numpy as np\nfrom torch.utils.data import Dataset\nfrom stereographic import get_uniform_stereo_mesh\nfrom perception import get_face_masks, get_object_masks\n\n\nclass ImageDataset(Dataset):\n\n def __init__(self, args, root='data'):\n\n self.Q = args.Q\n self.mesh_d... | [
[
"numpy.log",
"numpy.pad",
"numpy.linalg.norm",
"numpy.stack",
"numpy.exp"
]
] |
pkan2/addons | [
"8fe50d7600a592b06984f1ead61fdd8adb008ad1"
] | [
"tensorflow_addons/layers/normalizations_test.py"
] | [
"# Copyright 2019 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.convert_to_tensor",
"numpy.expand_dims",
"numpy.sqrt",
"tensorflow.cast",
"numpy.mean",
"tensorflow.random.set_seed",
"numpy.random.randint",
"tensorflow.keras.layers.deserialize",
"tensorflow.keras.optimizers.RMSprop",
"tensorflow.keras.layers.Conv2D",
"num... |
sosaucily/hummingbot | [
"082883319253399b2c7a321c709c97dcd84b9b72"
] | [
"hummingbot/client/command/config_command.py"
] | [
"import asyncio\nfrom typing import (\n List,\n Any,\n)\nfrom decimal import Decimal\nimport pandas as pd\nfrom os.path import join\nfrom hummingbot.client.settings import (\n GLOBAL_CONFIG_PATH,\n CONF_FILE_PATH,\n)\nfrom hummingbot.client.config.global_config_map import global_config_map\nfrom humming... | [
[
"pandas.DataFrame"
]
] |
samkreter/kmeans-clustering-with-spatial-bias | [
"17d47c564074f8d789b7f5370ea0acc56c19f529"
] | [
"getDataSet.py"
] | [
"import scipy.io\nimport numpy as np\n\n#convert main dataset\n# mat = scipy.io.loadmat(\"Indian_pines.mat\")\n# npMat = np.array(mat['indian_pines'])\n\n# np.save(\"npIndian_pines.npy\",npMat)\n\n#convert ground truth data set\nmat = scipy.io.loadmat(\"Indian_pines_gt.mat\")\nnpMat = np.array(mat['indian_pines_gt'... | [
[
"numpy.array",
"numpy.save"
]
] |
alanbseo/deepgreen | [
"b8a19c83d75f275c5e58bc7a48beb22ce61a81d9"
] | [
"PythonScripts/Flickr_BatchTagging_EU_keal.py"
] | [
"import os\nimport json\n\nimport numpy as np\nimport pandas as pd\n\nfrom keras.applications import inception_resnet_v2\n\nfrom keras.preprocessing import image\n\nimg_width, img_height = 331, 331\n\n\nimport fnmatch\n\nfrom shutil import copyfile\n\nimport PIL\nfrom PIL import ImageFile\n\nImageFile.LOAD_TRUNCATE... | [
[
"numpy.expand_dims",
"numpy.empty",
"pandas.DataFrame",
"numpy.concatenate",
"numpy.ceil",
"numpy.argsort",
"numpy.array",
"numpy.vstack"
]
] |
brettkoonce/fairscale | [
"05ce7971d256893a7707a8a99e89ec3ef75ab7c0"
] | [
"tests/nn/model_parallel/test_layers.py"
] | [
"# coding=utf-8\n\n# Copyright (c) Facebook, Inc. and its affiliates. All rights reserved.\n#\n# This source code is licensed under the BSD license found in the\n# LICENSE file in the root directory of this source tree.\n\n# Copyright (c) 2020, NVIDIA CORPORATION. All rights reserved.\n#\n# Licensed under the Apac... | [
[
"torch.nn.Embedding",
"torch.cuda.is_available",
"torch.split",
"torch.distributed.get_rank",
"torch.allclose",
"torch.ones",
"torch.randn",
"torch.distributed.barrier",
"torch.equal",
"torch.mul",
"torch.rand",
"torch.nn.Sequential",
"torch.LongTensor",
"to... |
neilshah13/capstone21 | [
"1be9175d70041cb3ee429f31dd51dd11c7ab39af"
] | [
"python_backend/triton_client/tao_triton/python/postprocessing/trafficcamnet_processor.py"
] | [
"# Copyright (c) 2021, NVIDIA CORPORATION. All rights reserved.\n# \n# Permission is hereby granted, free of charge, to any person obtaining\n# a copy of this software and associated documentation files (the\n# \"Software\"), to deal in the Software without restriction, including\n# without limitation the rights to... | [
[
"numpy.min",
"numpy.unique",
"sklearn.cluster.DBSCAN",
"numpy.max",
"numpy.float64",
"numpy.array",
"numpy.sum"
]
] |
rezoo/chainer_computational_cost | [
"987b0a2cd7670390ca0d69152214d6bc8f656c7b"
] | [
"tests/test_cost_calculators/test_connection.py"
] | [
"import chainer.functions as F\nimport numpy as np\n\nfrom chainer.functions.connection.convolution_2d \\\n import Convolution2DFunction\nfrom chainer.functions.connection.deconvolution_2d \\\n import Deconvolution2DFunction\nfrom chainer.functions.connection.linear import LinearFunction\n\nfrom helpers impor... | [
[
"numpy.int64",
"numpy.random.randn"
]
] |
zaman13/Optoelectronic-tweezers-interface | [
"a43440b9035a69ee54c5b34fe49e8b3dd0ac8d11"
] | [
"Codes/OET_interface_v0.5.py"
] | [
"\n\n# -*- coding: utf-8 -*-\n\"\"\"\nCreated on Mon Nov 15 20:34:23 2021\n\n@author: Mohammad Asif Zaman\n\n\nKeyboard commands:\n \nx : Quit/exit program \nArrow keys: Movement\nq : Increase object size\na : Decrease object size\nw : Increase width of the object\nd : ... | [
[
"numpy.cos",
"numpy.sin"
]
] |
hatim-ez/berkeley-cs294-deep-rl | [
"8ffd415e8140b18f9456bc8560a099e98456bf05"
] | [
"hw4/model_based_policy.py"
] | [
"import tensorflow as tf\nimport tensorflow_probability as tfp\nimport numpy as np\n\nimport utils\n\n\nclass ModelBasedPolicy(object):\n\n def __init__(self,\n env,\n init_dataset,\n horizon=15,\n num_random_action_selection=4096,\n ... | [
[
"tensorflow.losses.mean_squared_error",
"tensorflow.concat",
"tensorflow.truncated_normal",
"tensorflow.unstack",
"tensorflow.zeros",
"numpy.squeeze",
"tensorflow.placeholder",
"tensorflow.contrib.framework.argsort",
"tensorflow.subtract",
"tensorflow.global_variables_initi... |
itprorh66/SolarPV-Simulator | [
"0e689e608d4c1888dde82f506ad42c3291f33f60"
] | [
"SolarPV/NasaData.py"
] | [
"#!/usr/bin/env python3\n# -*- coding: utf-8 -*-\n\"\"\"\nCreated on Thu Apr 26 19:11:58 2018\nModified on 02/22/2019 for version 0.1.0\nModified on 02/04/2021 to simplify the logic and make better use of Pandas methods\n\n@author: Bob Hentz\n\n-----------------------------------------------------------------------... | [
[
"pandas.json_normalize",
"pandas.to_datetime"
]
] |
FredaXin/eda_and_beyond | [
"d78d25c305f1a23f1568d420ba8bb6bee12e5c38"
] | [
"eda_and_beyond/eda_tools.py"
] | [
"import numpy as np\nimport pandas as pd\nimport matplotlib.pyplot as plt\nimport seaborn as sns\n\nfrom sklearn.linear_model import LinearRegression, LassoCV, RidgeCV\nfrom sklearn.model_selection import cross_val_score, train_test_split\nfrom sklearn.preprocessing import StandardScaler, PolynomialFeatures\nfrom s... | [
[
"pandas.concat",
"matplotlib.pyplot.tight_layout",
"numpy.sum",
"sklearn.metrics.r2_score",
"sklearn.metrics.median_absolute_error",
"matplotlib.pyplot.figure",
"sklearn.metrics.mean_absolute_error",
"matplotlib.pyplot.subplots",
"sklearn.model_selection.train_test_split",
... |
alwinw/sktime | [
"a6f17bd586df6bbc8e6c783f08eda4c30d2353f9"
] | [
"sktime/transformers/series_as_features/dictionary_based/_sax.py"
] | [
"# -*- coding: utf-8 -*-\nimport sys\n\nimport numpy as np\nimport pandas as pd\nimport scipy.stats\n\nfrom sktime.transformers.series_as_features.base import BaseSeriesAsFeaturesTransformer\nfrom sktime.transformers.series_as_features.dictionary_based import PAA\n\n# TO DO: verify this returned pandas is consis... | [
[
"numpy.asarray",
"numpy.arange",
"pandas.Series",
"pandas.DataFrame"
]
] |
orestisfl/arxiv-classifier | [
"df41ad84137b48f77c3a27ee1c84471e22819967"
] | [
"train.py"
] | [
"import json\nimport logging\nimport os\nimport pickle\nimport random\n\nimport pandas as pd\nfrom scipy.special import softmax\nfrom simpletransformers.classification import ClassificationModel\n\nlogging.basicConfig(level=logging.INFO)\ntransformers_logger = logging.getLogger(\"transformers\")\ntransformers_logge... | [
[
"scipy.special.softmax",
"pandas.DataFrame"
]
] |
sun-xiaoyu/allennlp | [
"b49aff6aac4e9912564ee8235250d50c9d17e53f"
] | [
"allennlp/modules/seq2seq_encoders/pytorch_transformer_wrapper.py"
] | [
"from typing import Optional\n\nfrom overrides import overrides\nimport torch\nfrom torch import nn\n\nfrom allennlp.modules.seq2seq_encoders.seq2seq_encoder import Seq2SeqEncoder\nfrom allennlp.nn.util import add_positional_features\n\n\n@Seq2SeqEncoder.register(\"pytorch_transformer\")\nclass PytorchTransformer(S... | [
[
"torch.nn.TransformerEncoderLayer",
"torch.nn.Embedding",
"torch.nn.TransformerEncoder",
"torch.nn.init.xavier_uniform_"
]
] |
VoxelPi/compm | [
"745019d4e0d156910f19ed9168949f150356a349"
] | [
"ue/ue_05/problem_6.py"
] | [
"import numpy as np\n\ndef pseudo(A):\n # Check if matrix A is injective.\n if np.linalg.det(A.T @ A) < 1e-9:\n print(\"the given matrix is not injective.\")\n return\n\n # Return pseudo-inverse (See lecture notes page 155)\n print(\"the given matrix is injective.\")\n return np.linalg.... | [
[
"numpy.linalg.det",
"numpy.linalg.lstsq",
"numpy.array",
"numpy.linalg.inv"
]
] |
gizzmo25/pythoncode-tutorials | [
"39a413fc1da232ad6de7e5f1e8955564dc65448e",
"39a413fc1da232ad6de7e5f1e8955564dc65448e"
] | [
"machine-learning/image-transformation/cropping.py",
"machine-learning/edge-detection/edge_detector.py"
] | [
"import numpy as np\r\nimport cv2\r\nimport matplotlib.pyplot as plt\r\n\r\n# read the input image\r\nimg = cv2.imread(\"city.jpg\")\r\n# convert from BGR to RGB so we can plot using matplotlib\r\nimg = cv2.cvtColor(img, cv2.COLOR_BGR2RGB)\r\n# disable x & y axis\r\nplt.axis('off')\r\n# show the image\r\nplt.imshow... | [
[
"matplotlib.pyplot.imsave",
"matplotlib.pyplot.imshow",
"matplotlib.pyplot.show",
"matplotlib.pyplot.axis"
],
[
"matplotlib.pyplot.imshow",
"matplotlib.pyplot.show"
]
] |
scottwedge/ev3sim | [
"751c9902e7615d27d52e4b45b34e6acb47c06d24"
] | [
"ev3sim/devices/colour/base.py"
] | [
"import random\nimport numpy as np\n\n\nclass ColourSensorMixin:\n\n RGB_RAW = \"RGB-RAW\"\n\n device_type = \"lego-sensor\"\n mode = RGB_RAW\n\n SENSOR_RADIUS = 1\n SENSOR_POINTS = 100\n\n def _SenseValueAboutPosition(self, centrePosition, valueGetter):\n # Randomly sample value from SENSO... | [
[
"numpy.array",
"numpy.cos"
]
] |
zbzhzhy/Hyperspectral-Image-Super-resolution-via-Deep-Progressive-Zero-centric-Residual-Learning | [
"39f103a19fd54cc765487389f14f90a23e5e96bf"
] | [
"demo_cave/Hyper_loader_2.py"
] | [
"import numpy as np\r\nimport torch\r\nimport cv2\r\nfrom torch.utils.data import Dataset, DataLoader, TensorDataset\r\nfrom torch.autograd import Variable\r\nimport scipy.ndimage as scin\r\nfrom scipy import ndimage\r\nfrom get_name import get_name\r\nimport scipy.io as scio\r\nimport h5py\r\n# import lmdb\r\nimpo... | [
[
"numpy.rot90",
"scipy.io.loadmat",
"numpy.tensordot",
"numpy.transpose",
"numpy.load",
"numpy.flip"
]
] |
marcusfilipesr/ross | [
"e00bc10e694ecaf82ee24af82f649da7458fc91d"
] | [
"ross/results.py"
] | [
"\"\"\"ROSS plotting module.\n\nThis module returns graphs for each type of analyses in rotor_assembly.py.\n\"\"\"\nimport copy\nimport inspect\nfrom abc import ABC\nfrom collections.abc import Iterable\nfrom pathlib import Path\n\nimport numpy as np\nimport pandas as pd\nimport toml\nfrom plotly import graph_objec... | [
[
"numpy.imag",
"numpy.sqrt",
"numpy.linspace",
"numpy.arctan",
"pandas.DataFrame",
"numpy.dtype",
"numpy.max",
"numpy.zeros_like",
"numpy.exp",
"numpy.hstack",
"numpy.ones_like",
"numpy.arange",
"numpy.sin",
"numpy.real",
"numpy.repeat",
"numpy.isclos... |
EdwardYGLi/snake_RL | [
"210f552faca380c054fb5310b6c61ea2b1dfadcc"
] | [
"snake.py"
] | [
"\"\"\"\nCreated by Edward Li at 10/6/20\nfollowed game code from https://github.com/maurock/snake-ga\n\"\"\"\n\nimport argparse\nimport random\nimport sys\nfrom collections import deque\nimport itertools\n\nimport numpy as np\nimport pygame\n\n\ndef update_screen():\n pygame.display.update()\n\n\ndef display(pl... | [
[
"numpy.array",
"numpy.sqrt",
"numpy.array_equal",
"numpy.ones"
]
] |
mjw99/Musketeer | [
"0299a7974ad90c09d8d9206fcf862e45f9fddf30"
] | [
"musketeer/equilibriumConstants.py"
] | [
"import tkinter as tk\n\nimport numpy as np\n\nfrom . import moduleFrame\n\n\nclass GetKsCustom():\n def __init__(self, titration):\n self.titration = titration\n popup = tk.Toplevel()\n popup.title(\"Edit equilibrium constant values\")\n popup.grab_set()\n # TODO: implement\n\... | [
[
"numpy.identity",
"numpy.insert"
]
] |
eposs/solution_scattering | [
"c9e1570cdc7ad0b5b9303770e798bd0bb71650c3"
] | [
"quickplots.py"
] | [
"import glob\nimport matplotlib.pyplot as plt\nimport pandas as pd\nfrom saxs_plots import real_space_plotter\n\ndats = glob.glob('./*dat')\ndiffs = [item for item in dats if \"diff\" in item]\nsums = [item for item in dats if \"sum\" in item]\navgs = [item for item in dats if \"diff\" not in item]\nspfs = [item fo... | [
[
"pandas.read_table"
]
] |
qin-yu/elf | [
"bb8e0a41c1c2539ac6f866271751139271fbeeb1"
] | [
"elf/parallel/operations.py"
] | [
"import multiprocessing\n# would be nice to use dask for all of this instead of concurrent.futures\n# so that this could be used on a cluster as well\nfrom concurrent import futures\nfrom numbers import Number\nfrom functools import partial\nfrom tqdm import tqdm\n\nfrom .common import get_blocking\nfrom ..util imp... | [
[
"numpy.isin"
]
] |
igorperic17/object_detection_tf_example | [
"4d79eb45f5cf05af51e1055f72e4226dfa0f3538"
] | [
"benchmark.py"
] | [
"import tensorflow.compat.v2 as tf\nimport tensorflow_datasets as tfds\n\ntf.enable_v2_behavior()\n\nfrom tensorflow.python.framework.ops import disable_eager_execution\ndisable_eager_execution()\n\nfrom tensorflow.python.compiler.mlcompute import mlcompute\nmlcompute.set_mlc_device(device_name='gpu')\n\n\n(ds_trai... | [
[
"tensorflow.compat.v2.keras.layers.Flatten",
"tensorflow.compat.v2.enable_v2_behavior",
"tensorflow.compat.v2.keras.layers.MaxPooling2D",
"tensorflow.python.compiler.mlcompute.mlcompute.set_mlc_device",
"tensorflow.compat.v2.keras.layers.Dense",
"tensorflow.compat.v2.keras.optimizers.Adam"... |
kasimte/RLs | [
"0eba84bd7cc571269f874b65923bec2188828ef6"
] | [
"gym_wrapper.py"
] | [
"import gym\r\nimport numpy as np\r\nimport threading\r\n\r\n\r\nclass MyThread(threading.Thread):\r\n\r\n def __init__(self, func, args=()):\r\n super().__init__()\r\n self.func = func\r\n self.args = args\r\n\r\n def run(self):\r\n self.result = self.func(*self.args)\r\n\r\n d... | [
[
"numpy.array",
"numpy.where"
]
] |
asmaalrawi/geopm | [
"e93548dfdd693a17c81163787ba467891937356d"
] | [
"integration/experiment/power_sweep/gen_plot_node_efficiency.py"
] | [
"#!/usr/bin/env python\n#\n# Copyright (c) 2015, 2016, 2017, 2018, 2019, 2020, Intel Corporation\n#\n# Redistribution and use in source and binary forms, with or without\n# modification, are permitted provided that the following conditions\n# are met:\n#\n# * Redistributions of source code must retain the ... | [
[
"matplotlib.pyplot.tight_layout",
"matplotlib.pyplot.figure",
"matplotlib.pyplot.margins",
"matplotlib.pyplot.savefig",
"pandas.DataFrame",
"matplotlib.pyplot.setp",
"matplotlib.pyplot.close",
"matplotlib.pyplot.axis",
"matplotlib.pyplot.yticks",
"matplotlib.pyplot.hist",
... |
googleinterns/smart-content-summary | [
"595c8e2cb0e160a87cacb954a2a030953fdce6c5"
] | [
"classifier/run_classifier_utils.py"
] | [
"# Copyright 2020 Google LLC\n#\n# Licensed under the Apache License, Version 2.0 (the \"License\");\n# you may not use this file except in compliance with the License.\n# You may obtain a copy of the License at\n#\n# https://www.apache.org/licenses/LICENSE-2.0\n#\n# Unless required by applicable law or agreed ... | [
[
"tensorflow.metrics.mean",
"tensorflow.train.Scaffold",
"tensorflow.concat",
"tensorflow.reduce_mean",
"tensorflow.reshape",
"tensorflow.train.init_from_checkpoint",
"tensorflow.truncated_normal_initializer",
"tensorflow.trainable_variables",
"tensorflow.equal",
"tensorflow... |
wyli/cpp-py-example | [
"a5a09f1a5d93565dadb082aefa2807e1d157187f"
] | [
"ex/gauss.py"
] | [
"#!/usr/bin/env python3\n\nfrom pymycpp import Bitmap\nimport scipy.ndimage as ndi\n\n\nif __name__ == '__main__':\n img = Bitmap('baboon.bmp')\n\n data_np = img.data()\n\n ndi.gaussian_filter(input=data_np,\n sigma=(5, 15, 0),\n order=0,\n ... | [
[
"scipy.ndimage.gaussian_filter"
]
] |
simpsus/fmp_python | [
"858e3ff276aa24da77d242c0d72c7ec2a91ac875"
] | [
"fmp_python/common/fmpdecorator.py"
] | [
"import os\nimport functools\nimport pandas as pd\nimport inspect\nfrom datetime import datetime\nfrom pathlib import Path\n\nfrom fmp_python.common.fmpexception import FMPException\n\n\nclass FMPDecorator():\n\n @classmethod\n def inject_api_key(cls,func):\n @functools.wraps(func)\n def deco_fu... | [
[
"pandas.DataFrame"
]
] |
Fariborzzz/fiftyone | [
"06975961f5ee649dd36429feb21c959dfc0744ed"
] | [
"fiftyone/utils/eval/regression.py"
] | [
"\"\"\"\nRegression evaluation.\n\n| Copyright 2017-2021, Voxel51, Inc.\n| `voxel51.com <https://voxel51.com/>`_\n|\n\"\"\"\nimport logging\nimport itertools\nimport numbers\n\nimport numpy as np\nimport sklearn.metrics as skm\nfrom tabulate import tabulate\n\nimport eta.core.utils as etau\n\nimport fiftyone.core.e... | [
[
"sklearn.metrics.explained_variance_score",
"sklearn.metrics.r2_score",
"numpy.sqrt",
"sklearn.metrics.median_absolute_error",
"numpy.asarray",
"sklearn.metrics.mean_absolute_error",
"sklearn.metrics.mean_squared_error",
"sklearn.metrics.max_error",
"numpy.mean",
"numpy.arr... |
Laubeee/caffe-tensorflow | [
"1a5c027b19c6e9d4bc5f2cb4d5906efe46c60466"
] | [
"convert.py"
] | [
"#!/usr/bin/env python\n\nimport os\nimport sys\nimport numpy as np\nimport argparse\nfrom kaffe import KaffeError, print_stderr\nfrom kaffe.tensorflow import TensorFlowTransformer\n\nimport shutil\nimport tensorflow as tf\nfrom tensorflow.python.tools.freeze_graph import freeze_graph\n\n\ndef fatal_error(msg):\n ... | [
[
"tensorflow.InteractiveSession",
"tensorflow.python.tools.freeze_graph.freeze_graph",
"tensorflow.placeholder",
"numpy.save",
"tensorflow.train.Saver"
]
] |
kuna-systems/detr | [
"ae18dec551b4810eb44d58d612c5181812305a1b"
] | [
"d2/detr/detr.py"
] | [
"# Copyright (c) Facebook, Inc. and its affiliates. All Rights Reserved\nimport logging\nimport math\nfrom typing import List\n\nimport numpy as np\nimport torch\nimport torch.distributed as dist\nimport torch.nn.functional as F\nfrom scipy.optimize import linear_sum_assignment\nfrom torch import nn\n\nfrom detectr... | [
[
"torch.nn.functional.softmax",
"torch.ones",
"torch.Tensor",
"torch.load",
"torch.device",
"torch.as_tensor"
]
] |
AndyYuan96/MVF-End-to-End-Multi-View-Fusion-for-3D-Object-Detection-in-LiDAR-Point-Clouds- | [
"cf34897f25353a3f348d0a39c8db5ba15cadb2d7"
] | [
"pcdet/models/bbox_heads/anchor_target_assigner.py"
] | [
"# This file is modified from https://github.com/traveller59/second.pytorch\n\nimport numpy as np\nimport numpy.random as npr\nimport numba\nfrom ...utils import common_utils\n\n\ndef unmap(data, count, inds, fill=0):\n '''Unmap a subset of item (data) back to the original set of items (of\n size count)'''\n ... | [
[
"numpy.linspace",
"numpy.einsum",
"numpy.concatenate",
"numpy.where",
"numpy.reshape",
"numpy.arange",
"numpy.stack",
"numpy.sin",
"numpy.full",
"numpy.zeros",
"numpy.transpose",
"numpy.meshgrid",
"numpy.array",
"numpy.sum",
"numpy.maximum",
"numpy.t... |
islamazhar/trees | [
"502565c5bf02503c7bece09cddd93f9368da02c3"
] | [
"trees/mcmc.py"
] | [
"import random\nimport logging\nimport numpy as np\n\nclass MetropolisHastingsSampler(object):\n\n def __init__(self, tree, X):\n self.tree = tree\n self.X = X\n self.last_move = None\n self.likelihoods = []\n\n def initialize_assignments(self):\n self.tree.initialize_from_d... | [
[
"numpy.arange",
"numpy.exp",
"numpy.random.random"
]
] |
flying-Yan/BCNN | [
"31ebb985cb1556b6f98aa71459ee74c3490bbe1d"
] | [
"models/cb_ResNet18.py"
] | [
"import torch\nimport torch.nn as nn\nfrom models.binarized_fun import * \n\nclass ResBlock_1(nn.Module):\n\n def __init__(self, inchannel):\n super(ResBlock_1, self).__init__()\n \n self.tanh = nn.Hardtanh(-1.3,1.3)\n \n self.conv1 = nn.Sequential(\n self.tanh,... | [
[
"torch.nn.Conv2d",
"torch.nn.Linear",
"torch.nn.AvgPool2d",
"torch.nn.BatchNorm2d",
"torch.nn.ReLU",
"torch.nn.Hardtanh"
]
] |
TauferLab/SOMOSPIE | [
"512bfc1a287d014f3c3d885a22b23825ce536c92"
] | [
"deprecated/hyppo_testing/hypppo2.py"
] | [
"#!/usr/bin/env python3\n\n# Code by Travis Johnston, 2017.\n# Modified and parallelized by Danny Rorabaugh, 2018/9.\n# HYbrid Parallel Piecewise POlynomial.\n\n\nimport argparse, csv, random\nimport numpy as np\n### https://docs.python.org/3.1/library/itertools.html#itertools.combinations_with_replacement\nfrom it... | [
[
"numpy.product",
"numpy.linalg.lstsq",
"numpy.std",
"numpy.savetxt",
"numpy.argsort",
"numpy.array",
"numpy.loadtxt"
]
] |
Stargrazer82301/CAAPR | [
"4adead7dd85072cf14e2afb0f6b99b4f92d34201"
] | [
"CAAPR/CAAPR_Main.py"
] | [
"# Import smorgasbord\r\nimport sys\r\nimport os\r\nimport gc\r\nimport time\r\nimport random\r\n#import warnings\r\n#warnings.filterwarnings('ignore')\r\nimport matplotlib\r\nmatplotlib.use('Agg')\r\nimport multiprocessing as mp\r\nimport CAAPR\r\nimport CAAPR.CAAPR_IO\r\nimport CAAPR.CAAPR_Pipeline\r\nimport pdb\... | [
[
"matplotlib.use"
]
] |
HXPRedBlue/mmocr | [
"914613d53484712be67c38d50bb902a218884b24"
] | [
"mmocr/apis/inference.py"
] | [
"import numpy as np\nimport torch\nfrom mmcv.ops import RoIPool\nfrom mmcv.parallel import collate, scatter\nfrom mmdet.datasets import replace_ImageToTensor\nfrom mmdet.datasets.pipelines import Compose\n\n\ndef disable_text_recog_aug_test(cfg, set_types=None):\n \"\"\"Remove aug_test from test pipeline of text... | [
[
"torch.no_grad"
]
] |
rileydr/SSFC-Data | [
"b9169dfe47c939f4c7a49d9e53e05ba90d066301"
] | [
"code/utilities/densmore_v3.py"
] | [
"import pandas as pd\nimport numpy as np\nimport matplotlib.pyplot as plt\nimport seaborn as sns\n\nfrom sklearn.linear_model import LinearRegression, LogisticRegression\nfrom sklearn.model_selection import train_test_split, cross_val_score\nfrom sklearn.preprocessing import PolynomialFeatures, StandardScaler\nfrom... | [
[
"matplotlib.pyplot.yticks",
"sklearn.linear_model.LogisticRegression",
"matplotlib.pyplot.title",
"sklearn.model_selection.train_test_split",
"sklearn.neighbors.KNeighborsClassifier",
"sklearn.preprocessing.StandardScaler",
"numpy.exp",
"matplotlib.pyplot.xticks",
"matplotlib.p... |
yemen2016/FakeNewsDetection | [
"1caad62b068fb125f18c2f35299c36981a86ba55"
] | [
"ML Code/NB.py"
] | [
"from sklearn import model_selection, preprocessing, linear_model, naive_bayes, metrics, svm\nfrom sklearn.feature_extraction.text import TfidfVectorizer, CountVectorizer\nfrom sklearn import decomposition, ensemble\nfrom sklearn.model_selection import cross_validate\nimport pandas, xgboost, numpy, textblob, string... | [
[
"sklearn.naive_bayes.MultinomialNB",
"sklearn.metrics.precision_score",
"sklearn.model_selection.train_test_split",
"pandas.DataFrame",
"sklearn.feature_extraction.text.CountVectorizer",
"sklearn.metrics.f1_score",
"sklearn.metrics.recall_score",
"sklearn.feature_extraction.text.Tf... |
otanet/RLAS2021_chatbot_DeepRL_20220111 | [
"96c6c15ebd0f0c30f6532c64212eca48d134ba6a"
] | [
"dqn_agent.py"
] | [
"from keras.models import Sequential\nfrom keras.layers import Dense\n# from keras.optimizers import Adam\nfrom tensorflow.keras.optimizers import Adam\nimport random, copy\nimport numpy as np\nfrom dialogue_config import rule_requests, agent_actions\nimport re\n\n\n# Some of the code based off of https://jaromiru.... | [
[
"numpy.amax",
"tensorflow.keras.optimizers.Adam",
"numpy.argmax",
"numpy.array",
"numpy.zeros"
]
] |
ishine/AFILM | [
"be8b13ed3f45f4f58cbd37a9fe079d786be398e8"
] | [
"codes/utils.py"
] | [
"import os\nimport numpy as np\nimport h5py\nimport librosa\nimport soundfile as sf\nfrom scipy import interpolate\n\nfrom scipy.signal import decimate\nfrom matplotlib import pyplot as plt\n\n\ndef load_h5(h5_path):\n with h5py.File(h5_path, 'r') as hf:\n print('List of arrays in input file:', list(hf.ke... | [
[
"scipy.interpolate.splrep",
"matplotlib.pyplot.imshow",
"matplotlib.pyplot.tight_layout",
"numpy.pad",
"numpy.abs",
"scipy.signal.decimate",
"numpy.arange",
"matplotlib.pyplot.savefig",
"scipy.interpolate.splev",
"numpy.angle",
"numpy.zeros"
]
] |
Jodainc/Method-Numerics-24.9-Point | [
"f99ebc3eae6ee5b2ef35219c3fc3aaf333a4572d"
] | [
"methodnumeric.py"
] | [
"import numpy as npp\nfrom matplotlib import pyplot as plt\nfrom numpy import array\n\n\nx_data = npp.array([87.8, 96.6, 176, 263, 351, 571,834,1129,1624,2107,2678,3380,4258])\ny_data = npp.array([153,204,255,306,357,408,459,510,561,612,663,714,765])\n\ns=[87.8, 96.6, 176, 263, 351, 571,834,1129,1624,2107,2678,338... | [
[
"numpy.polyfit",
"matplotlib.pyplot.plot",
"numpy.exp",
"numpy.array",
"numpy.polyval"
]
] |
Niram7777/tensorflow | [
"0e40b3e0c30caff9427c1da54c40b6236608ec15"
] | [
"tensorflow/python/ops/array_ops.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.gen_math_ops.select_v2",
"tensorflow.python.util.tf_decorator.make_decorator",
"tensorflow.python.ops.gen_array_ops.list_diff",
"tensorflow.python.framework.ops.RegisterGradient",
"tensorflow.python.ops.gen_array_ops.strided_slice",
"tensorflow.python.ops.gen_array_o... |
shaominghe/stargan_adience | [
"7b59cae38acd0f32bf63695280b833ba7366e804"
] | [
"solver_classification.py"
] | [
"from model import Generator\nfrom model import Discriminator\nfrom torch.autograd import Variable\nfrom torchvision.utils import save_image\nimport torch\nimport torch.nn.functional as F\nimport numpy as np\nfrom model_agecomparison import Classificationmodel, getCossloss, getKLloss\nimport os\nimport time\nimport... | [
[
"torch.mean",
"torch.abs",
"torch.load",
"torch.zeros",
"numpy.arange",
"torch.nn.functional.cross_entropy",
"torch.sum",
"torch.cuda.is_available",
"torch.autograd.grad",
"torch.argmax"
]
] |
prerakgarg07/cloudyfsps | [
"4a6a185343ed1e09b9f201a465c37e377ef42101"
] | [
"demos/test_hden.py"
] | [
"#!/usr/bin/env python\n# -*- coding: utf-8 -*-\n\nfrom __future__ import (division, print_function, absolute_import,\n unicode_literals)\nimport os\nimport sys\nimport numpy as np\nimport fsps\nfrom past.utils import old_div\nfrom cloudyfsps.ASCIItools import (writeASCII, compileASCII, check... | [
[
"numpy.array"
]
] |
mengwa41/Ax | [
"fe20381214fd287a2088b0ccdd8c67337aaccf22"
] | [
"ax/service/tests/test_ax_client.py"
] | [
"#!/usr/bin/env python3\n# Copyright (c) Facebook, Inc. and its affiliates.\n#\n# This source code is licensed under the MIT license found in the\n# LICENSE file in the root directory of this source tree.\n\nimport math\nimport sys\nimport time\nfrom math import ceil\nfrom typing import List, Tuple\nfrom unittest.m... | [
[
"numpy.int32"
]
] |
bolecodex/amazon-sagemaker-immersion-day | [
"2894145bb0abd4961cb0e0b7c6d1e89264b76716"
] | [
"lab3/mnist-2.py"
] | [
"import tensorflow as tf\nimport argparse\nimport os\nimport numpy as np\nimport json\n\n\ndef model(x_train, y_train, x_test, y_test):\n \"\"\"Generate a simple model\"\"\"\n # Sequential： 创建顺序模型, 此模型为最简单的线性、从头到尾的结构顺序，不分叉，是多个网络层的线性堆叠。 参数：数组中的内容为模型中的层次结构\n model = tf.keras.models.Sequential([\n tf.k... | [
[
"tensorflow.keras.layers.Dense",
"tensorflow.keras.layers.Flatten",
"tensorflow.keras.layers.Dropout"
]
] |
onboarding92/AutonomousDrive | [
"80045ffd15ba9ee5b7c39ac7ffa9325616588cff"
] | [
"utils/utils.py"
] | [
"from __future__ import division\nimport math\nimport torch\nimport torch.nn as nn\nimport numpy as np\n\ndef load_classes(path):\n \"\"\"\n Loads class labels at 'path'\n \"\"\"\n fp = open(path, \"r\")\n names = fp.read().split(\"\\n\")[:-1]\n return names\n\n\ndef weights_init_normal(m):\n c... | [
[
"numpy.expand_dims",
"torch.max",
"torch.zeros",
"torch.cat",
"numpy.concatenate",
"numpy.where",
"torch.ones",
"numpy.eye",
"numpy.finfo",
"numpy.argmax",
"torch.sort",
"numpy.zeros",
"torch.nn.init.constant_",
"torch.min",
"torch.nn.init.normal_",
... |
disease-data-intelligence/3G_weight_loss_prediction | [
"476ced900f5a4595877257e38eccbe5e53cb64c2"
] | [
"ML_scripts/ensemble_scoring.py"
] | [
"#!/usr/bin/python3\n\n# Import packages\nseed = 42\nimport numpy as np\nnp.random.seed(seed) # Set numpy random seed\nimport os\nimport pandas as pd\nimport matplotlib.pyplot as plt\nfrom sklearn.metrics import roc_curve\nimport utils as u\n\n###############################\n# Ensemble predictions\n#############... | [
[
"pandas.concat",
"matplotlib.pyplot.tight_layout",
"pandas.Series",
"numpy.random.seed",
"matplotlib.pyplot.title",
"numpy.arange",
"matplotlib.pyplot.rc",
"matplotlib.pyplot.subplots",
"sklearn.metrics.roc_curve",
"matplotlib.pyplot.get_cmap",
"matplotlib.pyplot.savefi... |
cw-tan/deft | [
"abb4d23fa0bb53031c13daef9942bceba4afd655"
] | [
"test/tools_for_tests.py"
] | [
"import numpy as np\nfrom scipy.special import sph_harm\n\ndef get_box_geometry(vectors):\n \"\"\"expects box vectors in rows of 'vectors'\"\"\"\n\n # get box lengths, angles, and volume\n lengths = np.linalg.norm(vectors, axis=1)\n angles = np.empty(3)\n angles[0] = np.arccos(\n vectors[1... | [
[
"numpy.sqrt",
"numpy.abs",
"numpy.linalg.inv",
"numpy.arange",
"numpy.divide",
"numpy.rint",
"numpy.linalg.norm",
"numpy.arccos",
"scipy.special.sph_harm",
"numpy.linalg.det",
"numpy.arctan2",
"numpy.array",
"numpy.meshgrid",
"numpy.zeros",
"numpy.empty"... |
npirvin/Radiative-Transport-PV | [
"d5236bfae5789fd2be5bb0190e962a83c24b3ae7"
] | [
"single_cell_power.py"
] | [
"\"\"\" Created on Thu Jun 21 14:31:46 2018\r\nAuthor: Nicholas Irvin \r\n\r\nThis module determines the output power of a cell.\r\nIf using the diffusion model, then spectral.py calculates the total current,\r\n and this module calcualtes the power.\r\nIf not using the diffusion model, then spectral.py calculate... | [
[
"numpy.log",
"scipy.optimize.brentq",
"scipy.optimize.minimize_scalar"
]
] |
astaff/audio | [
"27a0f7653bc2918e314b4225782d2b29ef31ae4a"
] | [
"torchaudio/_backend.py"
] | [
"from functools import wraps\nfrom typing import Any, List, Union\n\nimport platform\nimport torch\nfrom torch import Tensor\n\nfrom . import _soundfile_backend, _sox_backend\n\n\n_audio_backend = \"soundfile\" if platform.system() == \"Windows\" else \"sox\"\n_audio_backends = {\"sox\": _sox_backend, \"soundfile\"... | [
[
"torch.is_tensor"
]
] |
OmerRe/Zero_DCE_TF | [
"457c28751ccedd343a5bcdc750306d6f7501a3bc"
] | [
"test.py"
] | [
"import keras\nimport tensorflow as tf\nimport keras.backend as K\nimport os\nimport sys\nimport argparse\nimport time\nimport src.model\nimport numpy as np\nimport glob\n\nfrom PIL import Image\nfrom src.loss import *\nfrom src.model import DCE_x\nfrom keras import Model, Input\nfrom keras.layers import Concatenat... | [
[
"numpy.expand_dims",
"numpy.asarray",
"tensorflow.cast",
"tensorflow.compat.v1.enable_eager_execution",
"numpy.array"
]
] |
sboominathan/DeepRL | [
"a415f23b9fff2f7179b1bd3c42ee46df64a605d4"
] | [
"agent/DDPG_agent.py"
] | [
"#######################################################################\n# Copyright (C) 2017 Shangtong Zhang(zhangshangtong.cpp@gmail.com) #\n# Permission given to modify the code as long as you keep this #\n# declaration at the top #\n#######################... | [
[
"numpy.stack",
"numpy.save"
]
] |
hzhwcmhf/pytorch-pretrained-BERT | [
"485adde74244f9b614263420d1f823660e0f96fe"
] | [
"tests/optimization_test.py"
] | [
"# coding=utf-8\n# Copyright 2018 The Google AI Language Team 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# Unl... | [
[
"torch.nn.MSELoss",
"torch.tensor"
]
] |
activatedgeek/uncertainty-da-bayesian-classification | [
"a270fb095f4790dea15327145897d09d0ba9c80b",
"a270fb095f4790dea15327145897d09d0ba9c80b"
] | [
"src/bnn_priors/bnn_priors/models/dense_nets.py",
"src/bnn_priors/bnn_priors/data/UCI/uci.py"
] | [
"from torch import nn, Tensor\n\nfrom .layers import Linear\nfrom .base import RegressionModel, RaoBRegressionModel, ClassificationModel\nfrom .. import prior\n\n__all__ = ('LinearNealNormal', 'LinearPrior', 'DenseNet', 'RaoBDenseNet',\n 'ClassificationDenseNet', 'LinearRegression', 'LogisticRegression',\... | [
[
"torch.nn.Sequential",
"torch.nn.ReLU",
"torch.nn.Identity"
],
[
"torch.mean",
"torch.std",
"numpy.loadtxt"
]
] |
snad-space/ad_examples | [
"7c62a81f52e79874d6215b262f5a849d56eeae4f"
] | [
"ad_examples/ad/kde_outlier.py"
] | [
"import numpy.random as rnd\n\nfrom ..common.gen_samples import *\nfrom ..common.gen_samples import *\n\n\"\"\"\npythonw -m ad_examples.ad.kde_outlier\n\"\"\"\n\n\nif __name__ == \"__main__\":\n\n logger = logging.getLogger(__name__)\n\n args = get_command_args(debug=True, debug_args=[\"--debug\",\n ... | [
[
"numpy.random.seed"
]
] |
wjy199708/my_point_painting | [
"32dd845b08a94e222e913471e42e9d9e128ba213"
] | [
"train.py"
] | [
"import torch\nimport copy\nfrom model import SSD, MultiBoxLoss\nfrom dataset import KittiDataset\nfrom torch.utils.data import DataLoader\nimport time\n\n\ndef train_model(model, dataloaders, criterion, optimizer, num_epochs=1):\n device = torch.device(\"cuda:0\" if torch.cuda.is_available() else \"cpu\")\n ... | [
[
"torch.set_grad_enabled",
"torch.utils.data.DataLoader",
"torch.cuda.is_available"
]
] |
DewMaple/head_box | [
"27ac90511344bfa75b340d1db960365e9eb148c7"
] | [
"utils/__init__.py"
] | [
"from distutils.version import LooseVersion\n\nimport tensorflow as tf\n\nTENSORFLOW_VERSION = LooseVersion(tf.__version__)\n\n\ndef tf_concat(axis, values, **kwargs):\n if TENSORFLOW_VERSION >= LooseVersion('1.0'):\n return tf.concat(values, axis, **kwargs)\n else:\n return tf.concat(axis, valu... | [
[
"tensorflow.concat"
]
] |
todo-group/exact | [
"ee76421fab9b2b1eaf77d6b01830a18e66f7180a"
] | [
"gallery/ising-square-tc/plot.py"
] | [
"import math\nimport matplotlib.pyplot as plt\n\nfilename = \"result-p15.dat\"\n\nwith open(filename, 'r') as f:\n for line in f:\n data = line.split()\n if (data[0] == \"inf\"):\n free_energy_inf = float(data[6])\n energy_inf = float(data[7])\n\nL = []\nfree_energy = []\nener... | [
[
"matplotlib.pyplot.legend",
"matplotlib.pyplot.xscale",
"matplotlib.pyplot.yscale",
"matplotlib.pyplot.savefig",
"matplotlib.pyplot.plot",
"matplotlib.pyplot.grid",
"matplotlib.pyplot.xlabel",
"matplotlib.pyplot.show"
]
] |
dornik/sporeagent | [
"a95139c47534670f7a47f86adf62d3e488981409"
] | [
"dataset/dataset.py"
] | [
"import numpy as np\nimport torch\nfrom torch.utils.data import Dataset\nimport torchvision\nimport os\nimport pickle\nimport trimesh\nimport sys\nimport skimage.io as skio\nfrom tqdm import tqdm\nimport open3d as o3d\nimport cv2 as cv\nfrom scipy.spatial.transform.rotation import Rotation\nimport glob\n\nimport co... | [
[
"numpy.hstack",
"numpy.sqrt",
"torch.cat",
"numpy.linalg.inv",
"numpy.uint8",
"numpy.eye",
"numpy.vstack",
"numpy.arange",
"numpy.linalg.norm",
"numpy.dstack",
"numpy.stack",
"numpy.asarray",
"numpy.ones",
"scipy.spatial.transform.rotation.Rotation.from_eule... |
sharmasaravanan/openface-Verification | [
"e2471e827eee2c86e92861f5fd59affa04c725ba"
] | [
"openface/torch_neural_net.py"
] | [
"# Copyright 2015-2016 Carnegie Mellon University\r\n#\r\n# Licensed under the Apache License, Version 2.0 (the \"License\");\r\n# you may not use this file except in compliance with the License.\r\n# You may obtain a copy of the License at\r\n#\r\n# http://www.apache.org/licenses/LICENSE-2.0\r\n#\r\n# Unless r... | [
[
"numpy.array"
]
] |
kerrywang/Advanced-Lane-Finding | [
"146fd169b9c9a0c58d2bd6103e147fdc4a26684d"
] | [
"lane_finding_pipeline/GradientFilter.py"
] | [
"from lane_finding_pipeline.piplineinterface import PipeLineInterface\nimport cv2\nimport numpy as np\nimport constant\nimport os\nclass GradientFilter(PipeLineInterface):\n def __init__(self, filter=[]):\n self.filters = filter\n\n def addFilter(self, filterClass):\n assert isinstance(filterCla... | [
[
"numpy.absolute",
"numpy.sqrt",
"numpy.ones",
"numpy.max",
"numpy.zeros_like",
"numpy.zeros"
]
] |
liuweiping2020/advForNLP | [
"cb4d21ead7a05826999edec2e6745e5301c4a19c"
] | [
"src/run.py"
] | [
"# coding: UTF-8\nimport time\nimport torch\nimport numpy as np\nfrom trains.train_eval import train, init_network\nfrom importlib import import_module\nimport argparse\n\nparser = argparse.ArgumentParser(description='Chinese Text Classification')\nparser.add_argument('--model', type=str, required=True,\n ... | [
[
"torch.manual_seed",
"numpy.random.seed",
"torch.cuda.manual_seed_all"
]
] |
gpaw789/weather_sim | [
"2b0137cc87c05d811771b5ffa413a477e685681d"
] | [
"master/GenerateWeather.py"
] | [
"import random\nimport datetime\nfrom time import sleep\nimport pickle\nimport helpers\nimport pandas as pd\n\n# structure\n# main() is text interface\n# build_position() is the function that builds the lat/long coodinates\n# running() is the function that runs while loop indefinitely and print the datastream\n# ge... | [
[
"pandas.DataFrame"
]
] |
danielkelshaw/ConcreteDropout | [
"65be53d3ecf558992f1c473c90e206717946897b"
] | [
"tests/test_concrete_dropout.py"
] | [
"import torch\nimport torch.nn as nn\nfrom torch import Tensor\n\nfrom condrop.concrete_dropout import ConcreteDropout\n\n\nclass TestConcreteDropout:\n\n def test_forward(self):\n\n to_pass = torch.ones(5)\n\n cd = ConcreteDropout(\n weight_regulariser=1e-6,\n dropout_regular... | [
[
"torch.nn.Linear",
"torch.ones"
]
] |
bblais/pyndamics | [
"fc1552af4bd07ed36412c0455981bae050179ad7"
] | [
"examples/Reproduce ODE API.py"
] | [
"#!/usr/bin/env python\n# coding: utf-8\n\n# In[1]:\n\n\nget_ipython().run_line_magic('pylab', 'inline')\n\n\n# ## Reproducing PyMC3 ODE_API_introduction\n# \n# https://github.com/pymc-devs/pymc3/blob/master/docs/source/notebooks/ODE_API_introduction.ipynb\n# \n# text for the equations taken from this original. Al... | [
[
"scipy.integrate.odeint"
]
] |
RamanLab/iCOMIC | [
"1310bd51641ce28d4193fa21a002767ca434fc23"
] | [
"icomic/deseq_tsv.py"
] | [
"#!/usr/bin/env python3\nimport numpy as np\nimport pandas as pd\nimport os\n\ntest_dir = './results/em_results'\n\nsample = []\nunit = []\ncondition = []\n\nfor file in os.listdir(test_dir):\n if file.endswith(\".counts\"):\n sample.append(file)\n else:\n pass\n \n\n\nfor i in range(len(samp... | [
[
"pandas.DataFrame"
]
] |
poposca/digit_classifier | [
"63d1515b576b6f984fcf1eea5c6a4d6bc040be16"
] | [
"tensorflow_examples/lite/model_maker/core/task/configs.py"
] | [
"# Copyright 2019 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.v1.Session"
]
] |
highlight0112/pyscf | [
"4afbd42bad3e72db5bb94d8cacf1d5de76537bdd",
"4afbd42bad3e72db5bb94d8cacf1d5de76537bdd"
] | [
"pyscf/tdscf/rks.py",
"pyscf/grad/casscf.py"
] | [
"#!/usr/bin/env python\n# Copyright 2014-2018 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.where",
"numpy.sqrt",
"numpy.empty"
],
[
"numpy.arange",
"numpy.dot",
"numpy.einsum"
]
] |
Unifall/DEKR | [
"3f410bcab420166b030508efd6c71a027c66d5b5"
] | [
"lib/dataset/CrowdPoseDataset.py"
] | [
"# ------------------------------------------------------------------------------\n# Copyright (c) Microsoft\n# Licensed under the MIT License.\n# The code is based on HigherHRNet-Human-Pose-Estimation.\n# (https://github.com/HRNet/HigherHRNet-Human-Pose-Estimation)\n# Modified by Zigang Geng (zigang@mail.ustc.edu.... | [
[
"numpy.amax",
"numpy.min",
"numpy.amin",
"numpy.max",
"numpy.zeros"
]
] |
jairideout/onecodex | [
"905d533376b808a0b2ea74c2e9c5ea1e87754a81"
] | [
"onecodex/viz/_distance.py"
] | [
"# -*- coding: utf-8 -*-\nfrom itertools import chain\nimport warnings\n\nfrom onecodex.exceptions import OneCodexException\nfrom onecodex.distance import DistanceMixin\n\n\nclass VizDistanceMixin(DistanceMixin):\n def _compute_distance(self, rank, metric):\n if rank is None:\n raise OneCodexEx... | [
[
"pandas.concat",
"pandas.DataFrame",
"sklearn.manifold.MDS",
"sklearn.metrics.pairwise.euclidean_distances",
"scipy.cluster.hierarchy.dendrogram",
"scipy.spatial.distance.squareform",
"numpy.random.RandomState"
]
] |
vilmar-hillow/kaggle_tgs_salt | [
"8e4db82b08abbf44ed803a0800402ae48dc7ff86"
] | [
"build_submit.py"
] | [
"from pathlib import Path\nimport cv2\nimport numpy as np\nimport pandas as pd\n\n\npred_folder = Path('./predictions/')\n\n\ndef RLenc(img, order='F', format=True):\n \"\"\"\n img is binary mask image, shape (r,c)\n order is down-then-right, i.e. Fortran\n format determines if the order needs to be pre... | [
[
"numpy.where",
"pandas.DataFrame.from_dict"
]
] |
PacktPublishing/-Introduction-to-Bayesian-Analysis-in-Python | [
"e0ab762a6cd4423b59d0dbf22e8224028b88c29d"
] | [
"Section 3/3.2.py"
] | [
"#!/usr/bin/env python\n# coding: utf-8\n\n# In[7]:\n\n\nget_ipython().run_line_magic('matplotlib', 'inline')\nimport scipy.stats as stats\nfrom IPython.core.pylabtools import figsize\nimport numpy as np\nimport matplotlib.pyplot as plt\n\nfigsize(12.5, 9)\n\nnorm_pdf = stats.norm.pdf\n\nplt.subplot(311)\nx = np.li... | [
[
"matplotlib.pyplot.legend",
"numpy.linspace",
"matplotlib.pyplot.title",
"matplotlib.pyplot.autoscale",
"scipy.stats.norm.pdf",
"numpy.max",
"matplotlib.pyplot.subplot",
"matplotlib.pyplot.hist"
]
] |
ajaybhat/DLND | [
"014e4973835817c6e727ff164e5253371f28fe07"
] | [
"Project 5/helper.py"
] | [
"import math\nimport os\nimport hashlib\nfrom urllib.request import urlretrieve\nimport zipfile\nimport gzip\nimport shutil\n\nimport numpy as np\nfrom PIL import Image\nfrom tqdm import tqdm\n\n\ndef _read32(bytestream):\n \"\"\"\n Read 32-bit integer from bytesteam\n :param bytestream: A bytestream\n ... | [
[
"numpy.sqrt",
"numpy.reshape",
"numpy.squeeze",
"numpy.dtype",
"numpy.frombuffer"
]
] |
Tripartito/AugmentedReality | [
"b0a4455bc15ab5a5647b221bd1efa715fe9114cc"
] | [
"CV/5_LinearFilters.py"
] | [
"# Modules normally used\nimport numpy as np\nimport cv2\n\ndef CreateFrame(img, krad, color): # Frame (trick to avoid out-of-bounds access)\n height, width, depth = img.shape\n\n if color == \"white\":\n frm = np.ones((height + krad * 2, width + krad * 2, depth))\n else:\n frm = np.... | [
[
"numpy.sqrt",
"numpy.linspace",
"numpy.ones",
"numpy.exp",
"numpy.zeros"
]
] |
YhHoo/Python-ANN | [
"6d3629f54100c9dee721108352f562cd28a2e5fc"
] | [
"activity_2.py"
] | [
"import numpy as np\nimport matplotlib.pyplot as plt\nfrom activity_1 import Neural_Object\nfrom mpl_toolkits.mplot3d import Axes3D\nfrom matplotlib import cm\n\ntemp = [] # to store the weights\n\n# ------------------------------------------\n# Load the saved optimized weights from .txt\n# -----------------------... | [
[
"numpy.linspace",
"numpy.asarray",
"numpy.ones",
"numpy.meshgrid",
"numpy.zeros",
"matplotlib.pyplot.show",
"matplotlib.pyplot.figure"
]
] |
pipete40/warehousing-tools | [
"58cd057af8d0ccd3af32001b8b0dfdb0ab6b9620"
] | [
"slotting/plots.py"
] | [
"\nimport numpy as np\nfrom . import aux_funcs as af\nfrom bokeh.resources import CDN\nfrom bokeh.embed import components\nfrom bokeh.palettes import Spectral11\nfrom bokeh.plotting import figure\nfrom bokeh.models import Label\nfrom bokeh.models.tickers import FixedTicker\n\ndef graph_groups_inventory(x, N, hs, in... | [
[
"numpy.asarray",
"numpy.arange",
"numpy.cumsum",
"numpy.max",
"numpy.diff"
]
] |
arulvelkumar/jira-agile-metrics | [
"55c4a25cbaf487cf0a5faf57879c0a34473b59c9"
] | [
"jira_agile_metrics/calculators/defects_test.py"
] | [
"import pytest\nfrom pandas import Timestamp, NaT\n\nfrom ..conftest import (\n FauxJIRA as JIRA,\n FauxIssue as Issue,\n FauxFieldValue as Value,\n)\n\nfrom ..utils import extend_dict\n\nfrom ..querymanager import QueryManager\nfrom .defects import DefectsCalculator\n\n\n@pytest.fixture\ndef fields(minima... | [
[
"pandas.Timestamp"
]
] |
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