repo_name stringlengths 6 130 | hexsha list | file_path list | code list | apis list |
|---|---|---|---|---|
cbreuel/pipelines | [
"22a85b4af642b896b57293c0d15d0f20c995be99"
] | [
"components/local/confusion_matrix/src/confusion_matrix.py"
] | [
"# Copyright 2018 Google LLC\n#\n# Licensed under the Apache License, Version 2.0 (the \"License\");\n# you may not use this file except in compliance with the License.\n# You may obtain a copy of the License at\n#\n# http://www.apache.org/licenses/LICENSE-2.0\n#\n# Unless required by applicable law or agreed ... | [
[
"sklearn.metrics.confusion_matrix",
"pandas.DataFrame",
"sklearn.metrics.accuracy_score",
"tensorflow.python.lib.io.file_io.read_file_to_string",
"tensorflow.python.lib.io.file_io.get_matching_files",
"tensorflow.python.lib.io.file_io.FileIO",
"pandas.concat",
"pandas.read_csv"
]... |
neu-vig/ezflow | [
"1eb6f675e72b1de6db7b35d61ca4ef0082bae890"
] | [
"tests/test_utils.py"
] | [
"from gettext import find\n\nimport torch\n\nfrom ezflow.utils import (\n AverageMeter,\n coords_grid,\n endpointerror,\n find_free_port,\n forward_interpolate,\n is_port_available,\n upflow,\n)\n\n\ndef test_endpointerror():\n\n pred = torch.rand(4, 2, 256, 256)\n target = torch.rand(4, ... | [
[
"torch.rand"
]
] |
jerry99s/second.pytorch | [
"449c7c0d081eaad44f08159f64af26d2a59f1f4c",
"414de8936a165d7cdba4a6eb15ce9603201d2e61"
] | [
"torchplus/metrics.py",
"second/utils/eval.py"
] | [
"import numpy as np\nimport torch\nimport torch.nn.functional as F\nfrom torch import nn\n\n\nclass Scalar(nn.Module):\n def __init__(self):\n super().__init__()\n self.register_buffer('total', torch.FloatTensor([0.0]))\n self.register_buffer('count', torch.FloatTensor([0.0]))\n\n def for... | [
[
"torch.sigmoid",
"torch.max",
"torch.FloatTensor",
"torch.clamp",
"numpy.prod",
"torch.tensor",
"torch.nn.functional.softmax",
"torch.sum"
],
[
"numpy.concatenate",
"numpy.max",
"numpy.array",
"numpy.zeros",
"numpy.sum",
"numpy.stack",
"numpy.cos",
... |
rdguez-mariano/fast_imas_IPOL | [
"4c09fa3754c7ff300aa313d4e50a606c07b4b340"
] | [
"adaptiveIMAS/hesaffnet/extract_geom_and_desc_upisupTh.py"
] | [
"#!/usr/bin/python2 -utt\n# -*- coding: utf-8 -*-\nfrom __future__ import print_function\nimport torch\nimport torch.nn as nn\nimport numpy as np\nimport sys\nimport os\nimport time\n\nfrom PIL import Image\nfrom torch.autograd import Variable\nimport torch.backends.cudnn as cudnn\nimport torch.optim as optim\nfrom... | [
[
"numpy.array",
"torch.no_grad",
"numpy.savetxt",
"torch.load"
]
] |
thiagomurtinho/Iris_Classification | [
"8b04fed7f7162c3a6bd276c0dbfb2c291c02492c"
] | [
"app/utils/mathPlots.py"
] | [
"import matplotlib.pyplot as plt\n\ndef plot(X, Y, ajust=False, line=None, line_label=None, line_color=None ):\n \"\"\"\n type= dot/linear\n \"\"\"\n\n plt.scatter(X,Y,label='Y(X)')\n plt.xlabel('X')\n plt.ylabel('Y')\n plt.legend()\n\n if ajust:\n plt.plot(X,line,label=line_label,color=line_color)\n\n ... | [
[
"matplotlib.pyplot.xlabel",
"matplotlib.pyplot.plot",
"matplotlib.pyplot.legend",
"matplotlib.pyplot.show",
"matplotlib.pyplot.ylabel",
"matplotlib.pyplot.scatter"
]
] |
peterpanmj/dask | [
"26986346320ce1bfa3a7c0eb9f636375233d750b"
] | [
"dask/utils.py"
] | [
"import functools\nimport inspect\nimport os\nimport re\nimport shutil\nimport sys\nimport tempfile\nimport uuid\nimport warnings\nfrom _thread import RLock\nfrom collections.abc import Iterator\nfrom contextlib import contextmanager, nullcontext, suppress\nfrom datetime import datetime, timedelta\nfrom errno impor... | [
[
"numpy.empty",
"numpy.random.RandomState",
"numpy.allclose",
"numpy.frombuffer",
"numpy.cumsum"
]
] |
2AUK/pyrism | [
"7067fa7a261adc2faabcffbcb2d40d395e42a3c8"
] | [
"pyrism/Core/Transforms.py"
] | [
"#!/usr/bin/env python3\n\"\"\"\ntransforms.py\n\nImplementation of the forward and backward fourier-bessel\ntransforms (Hankel transform) using the discrete sine transform function via scipy.\n\n\"\"\"\n\nimport numpy as np\nfrom scipy.fftpack import dst, idst\n\n\ndef discrete_hankel_transform(\n r: np.ndarray... | [
[
"scipy.fftpack.idst",
"scipy.fftpack.dst"
]
] |
alihkousha/Golestan_Bot | [
"e0c4c364386cea3ea8e6b7b6dceef20e81923599"
] | [
"Data_Handler.py"
] | [
"import pandas as pd\nimport os\nimport numpy as np\n\npaths = {\n 'Data' : os.path.join(os.getcwd(), 'Data')\n}\n\n\ndef json_reader(file):\n df = pd.read_json(os.path.join(paths['Data'], file),encoding='utf-8', dtype=int)\n df.set_index('Lesson-Code')\n return df\n\ndef DataFrame_appender(df : pd.Data... | [
[
"numpy.where",
"pandas.concat"
]
] |
mjj1094/Attention_BERT_62 | [
"22cae03ab7bcb09cfd3f8b0b9f2239f8e3ba56ce"
] | [
"net_with_pretrained_bert.py"
] | [
"# coding=utf-8\n# Copyright 2018 The Google AI Language Team Authors and The HugginFace Inc. team.\n#\n# Licensed under the Apache License, Version 2.0 (the \"License\");\n# you may not use this file except in compliance with the License.\n# You may obtain a copy of the License at\n#\n# http://www.apache.org/l... | [
[
"torch.nn.Linear",
"torch.cat",
"torch.cuda.manual_seed",
"torch.ones",
"torch.squeeze",
"torch.cuda.is_available",
"torch.load",
"torch.transpose",
"torch.nn.CrossEntropyLoss",
"torch.sum",
"torch.sigmoid",
"torch.sqrt",
"torch.nn.Softmax",
"torch.manual_se... |
jschmid-oth-aw/sklearn-porter | [
"2216661eb54eebaecb9775fa17f945f476d052fb"
] | [
"sklearn_porter/Porter.py"
] | [
"# -*- coding: utf-8 -*-\n\nimport os\nimport sys\nimport types\n\nimport numpy as np\n\nfrom sklearn.metrics import accuracy_score\nfrom sklearn.tree import DecisionTreeClassifier\nfrom sklearn.tree import DecisionTreeRegressor\nfrom sklearn.ensemble import AdaBoostClassifier\nfrom sklearn.ensemble import RandomFo... | [
[
"numpy.array",
"numpy.empty",
"sklearn.metrics.accuracy_score"
]
] |
Shreyas-Gururaj/Point_Contrast_ME0.5.3 | [
"72bc78001b0b4529ca96f193764dcac0c5a0ce0f",
"72bc78001b0b4529ca96f193764dcac0c5a0ce0f"
] | [
"pretrain/pointcontrast/lib/transforms.py",
"pretrain/data_preprocess/scannet_pair/SensorData.py"
] | [
"# Copyright (c) Facebook, Inc. and its affiliates.\n# \n# This source code is licensed under the MIT license found in the\n# LICENSE file in the root directory of this source tree.\n\n\nimport numpy as np\nimport random\n\nclass Compose:\n\n def __init__(self, transforms):\n self.transforms = transforms\n\n d... | [
[
"numpy.random.normal"
],
[
"numpy.fromstring",
"numpy.savetxt"
]
] |
ankit27kh/Computational-Physics-PH354 | [
"d37c93e430a0f282251a814456890acb4a2961fe"
] | [
"Ankit Khandelwal_HW6/Exercise 9/exercise 9 Jacobi.py"
] | [
"\"\"\"\nHome Work 6\nAnkit Khandelwal\nExercise 9 Jacobi\n15863\n\"\"\"\n\nfrom math import exp\n\nimport matplotlib.pyplot as plt\nimport numpy as np\n\nxv = np.linspace(-1, 1, 40)\nyv = np.linspace(-1, 1, 40)\n\ndelta = 2 / 39\n\n\ndef rho(x, y):\n if x <= 0.3 and x >= -0.3:\n return exp(-abs(y) / 0.1)... | [
[
"matplotlib.pyplot.colorbar",
"matplotlib.pyplot.contourf",
"numpy.zeros",
"matplotlib.pyplot.xlabel",
"numpy.copy",
"matplotlib.pyplot.plot",
"matplotlib.pyplot.figure",
"matplotlib.pyplot.ylabel",
"matplotlib.pyplot.show",
"numpy.linspace"
]
] |
qqhann/KnowledgeTracing | [
"cecdb9af0c44efffd1ce3359f331d7d7782f551b"
] | [
"model/seq2seq.py"
] | [
"import logging\nimport math\nimport os\nimport pickle\nimport random\nimport sys\nimport time\nfrom math import ceil, log\nfrom pathlib import Path\nfrom typing import Dict, List, Set, Tuple\n\nimport matplotlib.pyplot as plt\nimport numpy as np\nimport pandas as pd\nimport seaborn as sns\nimport torch\nimport tor... | [
[
"torch.nn.Linear",
"torch.sigmoid",
"torch.nn.Dropout",
"torch.nn.LSTM",
"torch.max",
"torch.nn.Embedding"
]
] |
lvyufeng/Elmo_mindspore | [
"2002b477738a8a805f3fa1f02af8163724795489"
] | [
"elmo/modules/embedding.py"
] | [
"import json\nimport mindspore\nimport mindspore.nn as nn\nimport numpy as np\nimport mindspore.ops as P\nfrom mindspore.common.initializer import Uniform, Normal\nfrom elmo.modules.highway import HighWay\nfrom elmo.nn.layers import Conv1d, Dense, Embedding\n\n\"\"\"\nNotice: We don't use `bidirectional` flag to en... | [
[
"numpy.sqrt"
]
] |
gokceneraslan/tracer | [
"cd59435a237a87854cbc3e6e466349e48ca2cfe9"
] | [
"tracerlib/tasks.py"
] | [
"from __future__ import print_function\n\nimport csv\n\nimport six\nimport matplotlib as mpl\nimport pandas as pd\nimport numpy as np\nfrom pprint import pprint\n\nfrom tracerlib import io, core\nfrom tracerlib.io import check_binary\n\nmpl.use('pdf')\nimport re\nimport seaborn as sns\nfrom matplotlib import pyplot... | [
[
"matplotlib.use",
"pandas.merge",
"matplotlib.colors.hex2color",
"pandas.DataFrame",
"matplotlib.pyplot.xlabel",
"numpy.percentile",
"matplotlib.pyplot.gca",
"matplotlib.pyplot.figure",
"matplotlib.pyplot.ylabel",
"matplotlib.pyplot.axvline",
"matplotlib.colors.rgb2hex"... |
Tawkir-Ahmed/towards_data_science | [
"d3247c8ee2bdaaa50642324795cb631b5322a780"
] | [
"apps/vb_learning_rate/app.py"
] | [
"\nimport os\n\nimport dash\nimport dash_core_components as dcc\nimport dash_html_components as html\nfrom dash.dependencies import Input, Output\n\nimport numpy as np\n\nexternal_stylesheets = ['https://codepen.io/chriddyp/pen/bWLwgP.css']\n\n# Create layout\napp = dash.Dash(__name__, external_stylesheets=external... | [
[
"numpy.arange"
]
] |
LiLee1/High_Capacity_Complex_Networks | [
"bd365261c303ef6cb704852814be862bc63230e7"
] | [
"models_ieee_icc.py"
] | [
"\"\"\"\n# Author\nJakob Krzyston (jakobk@gatech.edu)\n\n# Purpose\nBuild architecture for I/Q modulation classification as seen in Krzyston et al. 2020\n\"\"\"\n\nimport torch\nfrom torch import nn\nfrom torch import optim\nimport torch.nn.functional as F\n\n\n##### LINEAR COMBINATION FOR COMPLEX CONVOLUTION #####... | [
[
"torch.nn.Linear",
"torch.cat",
"torch.nn.Dropout",
"torch.nn.init.kaiming_normal_",
"torch.nn.init.xavier_uniform_",
"torch.nn.Conv2d",
"torch.nn.functional.relu"
]
] |
chensheng19/Tensorflow-Base | [
"73f7f22c8214a123abe5d625a7459feadd33e318"
] | [
"chapter-5/example-1.py"
] | [
"#! usr/bin/env python\n# coding:utf-8\n#=====================================================\n# Copyright (C) 2020 * Ltd. All rights reserved.\n#\n# Author : Chen_Sheng19\n# Editor : VIM\n# Create time : 2020-07-05\n# File name : \n# Description : \n#\n#================================================... | [
[
"tensorflow.zeros",
"tensorflow.argmax",
"tensorflow.reset_default_graph",
"tensorflow.train.Saver",
"tensorflow.Session",
"tensorflow.matmul",
"tensorflow.log",
"tensorflow.placeholder",
"tensorflow.global_variables_initializer",
"tensorflow.random_normal",
"tensorflow... |
yc015/KALMUS | [
"b0510e4cba8463a0a514ed18d572bd62c892ad21"
] | [
"kalmus/tkinter_windows/plot_barcodes_windows/PlotBarcodeWindow.py"
] | [
"\"\"\"\nPlotBarcodeWindow Class\nColorHistogramWindow Class\nRGBColorCubeWindow Class\nOutputCSVWindow Class\n\"\"\"\n\nimport tkinter\nimport tkinter.filedialog\nfrom tkinter.messagebox import showinfo, showerror\n\nimport matplotlib.pyplot as plt\nfrom matplotlib.backends.backend_tkagg import (FigureCanvasTkAgg,... | [
[
"matplotlib.pyplot.subplots",
"matplotlib.pyplot.figure",
"matplotlib.backends.backend_tkagg.FigureCanvasTkAgg",
"numpy.arange",
"matplotlib.pyplot.tight_layout",
"matplotlib.pyplot.axis",
"matplotlib.backends.backend_tkagg.NavigationToolbar2Tk"
]
] |
jass3941/MCF | [
"86f379d04063c0bb994fd8ddf067fa0e32c91123"
] | [
"run.py"
] | [
"# -*- coding: utf-8 -*-\n\"\"\"\nCreated on Mon Jan 18 00:23:52 2021\n\n@author: daham.kim\n\"\"\"\n\nimport pandas as pd\nimport numpy as np\nimport graph as gp\nimport data_loading as load\nimport similarity_measure as sim\n\n\nimport os\nfrom multiprocessing import Pool\n\ndef filepath_change(filepath):\n pr... | [
[
"pandas.DataFrame",
"numpy.arange",
"numpy.empty"
]
] |
sunsmarterjie/GOLD_NAS | [
"3b40c2a0700b1d07b96c2f9351057623efd0488f"
] | [
"cifar_search/operations.py"
] | [
"import torch\nimport torch.nn as nn\nimport torch.nn.functional as F\n\nOPS = {\n 'avg_pool_3x3': lambda C, stride, affine: nn.Sequential(\n nn.AvgPool2d(3, stride=stride, padding=1, count_include_pad=False), nn.BatchNorm2d(C, affine=affine)),\n 'max_pool_3x3': lambda C, stride, affine: nn.Sequential(... | [
[
"torch.nn.MaxPool2d",
"torch.nn.AvgPool2d",
"torch.nn.BatchNorm2d",
"torch.nn.ReLU",
"torch.nn.Conv2d"
]
] |
yutong-xie/CS498-DL-Assignment | [
"a0c93422c31a19ece7abbd2a7bb19f7feb8ea5ef"
] | [
"assignment3/assignment3_p1/classifier.py"
] | [
"import torch\nimport torch.nn as nn\nfrom torch.autograd import Variable\nimport torch.nn.functional as F\nfrom torch import optim\nimport numpy as np\n\nNUM_CLASSES = 21\n\nclass SimpleClassifier(nn.Module):\n def __init__(self):\n super(SimpleClassifier, self).__init__()\n self.conv1 = nn.Conv2d... | [
[
"torch.nn.Linear",
"torch.nn.Dropout",
"torch.cat",
"torch.nn.MaxPool2d",
"torch.nn.BatchNorm2d",
"torch.nn.ReLU",
"torch.nn.Conv2d"
]
] |
PawelGlomski-Intel/incubator-mxnet | [
"13e9d572b3059ebe0d1d4f6d452db4f971375588"
] | [
"tests/python/unittest/test_gluon.py"
] | [
"# Licensed to the Apache Software Foundation (ASF) under one\n# or more contributor license agreements. See the NOTICE file\n# distributed with this work for additional information\n# regarding copyright ownership. The ASF licenses this file\n# to you under the Apache License, Version 2.0 (the\n# \"License\"); y... | [
[
"numpy.array",
"numpy.random.rand",
"numpy.asarray",
"numpy.ones",
"numpy.prod",
"numpy.random.randint",
"numpy.dtype"
]
] |
aragilar/scipy | [
"cc3bfa91f662999996cd1cfdec4465bb9943ab1c",
"cc3bfa91f662999996cd1cfdec4465bb9943ab1c"
] | [
"scipy/sparse/construct.py",
"scipy/cluster/setup.py"
] | [
"\"\"\"Functions to construct sparse matrices\n\"\"\"\nfrom __future__ import division, print_function, absolute_import\n\n__docformat__ = \"restructuredtext en\"\n\n__all__ = ['spdiags', 'eye', 'identity', 'kron', 'kronsum',\n 'hstack', 'vstack', 'bmat', 'rand', 'random', 'diags', 'block_diag']\n\n\nimpo... | [
[
"numpy.concatenate",
"numpy.empty",
"numpy.asarray",
"numpy.zeros",
"numpy.common_type",
"numpy.random.RandomState",
"numpy.ones",
"numpy.nonzero",
"numpy.atleast_1d",
"numpy.arange",
"numpy.cumsum",
"scipy._lib.six.xrange",
"numpy.iinfo",
"numpy.dtype",
... |
anonymous-ai-for-earth/satellite-to-satellite-translation | [
"e69036b2f9efd757329b2dfc51620fb466973a7a"
] | [
"models/segmentation.py"
] | [
"import os, sys\nsys.path.append(os.path.dirname(os.path.dirname(os.path.abspath(__file__))))\nimport glob\n\nimport torch\nimport torchvision\nfrom torch import nn\nfrom torch.utils.data import Dataset, ConcatDataset, DataLoader\nfrom torch.utils.tensorboard import SummaryWriter\n\nfrom utils import get_sensor_sta... | [
[
"torch.nn.MSELoss",
"torch.nn.Sigmoid",
"torch.save",
"torch.nn.ReLU",
"torch.nn.Conv2d",
"torch.nn.BCELoss",
"torch.load"
]
] |
bellettif/DMP | [
"47c8be1a4d99cc13045efa76356f224ebf0d4718"
] | [
"pyDOSCP/utils.py"
] | [
"'''\nCreated on Dec 15, 2014\n\n@author: Francois Belletti\n'''\n\nimport numpy as np\n\ndef compute_regularized_obj(A, solution, o_vect, sigma):\n return np.sum((np.dot(A, solution) - o_vect) ** 2) + sigma * np.sum(solution ** 2)\n\ndef compute_original_obj(A, solution, o_vect, sigma):\n return np.sum((np.d... | [
[
"numpy.sum",
"numpy.dot"
]
] |
L0laapk3/RLBot-ReorientML | [
"df9d773f58481a6829b25f0dc88506b9a6707210"
] | [
"policy.py"
] | [
"import torch\nfrom torch import Tensor\nfrom torch.nn import Module, Linear, ReLU\nimport sys\n\nclass Actor(Module):\n def __init__(self, hidden_size, hidden_size_2):\n super().__init__()\n self.linear1 = Linear(16, hidden_size)\n self.linear2 = Linear(hidden_size, hidden_size_2)\n ... | [
[
"torch.nn.Linear",
"torch.clamp",
"torch.nn.ReLU"
]
] |
hsukyle/acai | [
"83b6f2aba82f8f13ac53ff1e28ab18bf1ba4e55d"
] | [
"lib/layers.py"
] | [
"# Copyright 2018 Google LLC\n#\n# Licensed under the Apache License, Version 2.0 (the \"License\");\n# you may not use this file except in compliance with the License.\n# You may obtain a copy of the License at\n#\n# https://www.apache.org/licenses/LICENSE-2.0\n#\n# Unless required by applicable law or agreed ... | [
[
"tensorflow.reduce_prod",
"tensorflow.variable_scope",
"tensorflow.nn.avg_pool",
"tensorflow.tile",
"tensorflow.random_normal"
]
] |
Ninei/GANs | [
"31ced71f7cb9d650c5c099895489fbdf99a67903"
] | [
"Exercise/Sound/WaveLet_DWT.py"
] | [
"import os\nimport pywt\nimport matplotlib.pyplot as plt\nimport numpy as np\nimport librosa\nimport scipy.io as sio\nimport scipy.io.wavfile\n\ndef checkPath(target) :\n if not os.path.exists(target): os.makedirs(target)\n\n#### Check Dataset & Output Directory\nROOT_INPUT_PATH = os.path.join(os.path.abspath(__... | [
[
"scipy.io.wavfile.read",
"matplotlib.pyplot.grid",
"matplotlib.pyplot.savefig",
"matplotlib.pyplot.title",
"scipy.io.wavfile.write",
"matplotlib.pyplot.figure",
"matplotlib.pyplot.tight_layout",
"matplotlib.pyplot.show",
"matplotlib.pyplot.subplot"
]
] |
xDUDSSx/BattleCity-Python | [
"490348af708d2552a500ff5464de308436bb45c0"
] | [
"src/core/entities/movable.py"
] | [
"import numpy as np\n\nfrom pyglet.shapes import Rectangle\n\nfrom core import entities\nfrom core import constants\nfrom core import collision\nfrom core import utils\n\n\nclass Movable(entities.entity.Entity):\n \"\"\"\n An entity that can move around in the game world.\n Handles collision with other ent... | [
[
"numpy.copy",
"numpy.zeros"
]
] |
kerwinreyes/logisticgrowthmodel | [
"3d06f65182fc66008fe99606921458412532f8dc"
] | [
"logistic.py"
] | [
"#Reyes, Kerwiwn & Navarro, Jeric\n#CS - 302\n\nimport math\nimport numpy as np\nimport pandas as pd\nimport scipy.optimize as optim\nimport matplotlib.pyplot as plt\n\n#import the data\ndata = pd.read_csv('Philippine_data_logistic.csv', sep=';')\ndata = data['total_cases']\ndata = data.reset_index(drop=False)\ndat... | [
[
"numpy.array",
"scipy.optimize.curve_fit",
"numpy.random.exponential",
"matplotlib.pyplot.xlabel",
"matplotlib.pyplot.title",
"matplotlib.pyplot.legend",
"numpy.exp",
"matplotlib.pyplot.show",
"matplotlib.pyplot.ylabel",
"matplotlib.pyplot.scatter",
"pandas.read_csv"
... |
neonkitchen/disentangling-vae | [
"e33148469fd1da50aef35686f337f2452f08ff6e"
] | [
"disvae/training.py"
] | [
"import imageio\nimport logging\nimport os\nfrom timeit import default_timer\nfrom collections import defaultdict\n\nfrom tqdm import trange\nimport torch\nfrom torch.nn import functional as F\n\nfrom disvae.utils.modelIO import save_model\nimport wandb\n\n\nTRAIN_LOSSES_LOGFILE = \"train_losses.log\"\n\n\nclass Tr... | [
[
"torch.device"
]
] |
13070151771/cat-eye-detection | [
"1d9ca38c8339a714b342170f76a63964d1933db2"
] | [
"train.py"
] | [
"\"\"\"\nRetrain the YOLO model for your own dataset.\n\"\"\"\nimport numpy as np\nimport keras.backend as K\nfrom keras.layers import Input, Lambda\nfrom keras.models import Model\nfrom keras.callbacks import TensorBoard, ModelCheckpoint, EarlyStopping\n\nfrom yolo3.model import preprocess_true_boxes, yolo_body, t... | [
[
"numpy.array",
"numpy.zeros",
"numpy.random.shuffle"
]
] |
willwhitney/quantile-baselines | [
"41cb52fd0fc2651bdab69b17df4d48c86b909eab"
] | [
"logger.py"
] | [
"from torch.utils.tensorboard import SummaryWriter\nfrom collections import defaultdict\nimport json\nimport os\nimport csv\nimport shutil\nimport torch\nimport numpy as np\nfrom termcolor import colored\n\nCOMMON_TRAIN_FORMAT = [\n ('episode', 'E', 'int'),\n ('step', 'S', 'int'),\n ('episode_reward', 'R',... | [
[
"numpy.array",
"torch.utils.tensorboard.SummaryWriter"
]
] |
neilsambhu/carla-simulator3 | [
"9838cd12c865950088d33a931f75424da0077fc7"
] | [
"scenario_runner/srunner/scenarios/control_loss.py"
] | [
"#!/usr/bin/env python\n\n#\n# This work is licensed under the terms of the MIT license.\n# For a copy, see <https://opensource.org/licenses/MIT>.\n\n\"\"\"\nControl Loss Vehicle scenario:\n\nThe scenario realizes that the vehicle looses control due to\nbad road conditions, etc. and checks to see if the vehicle\nre... | [
[
"numpy.random.randint"
]
] |
supervisely-ecosystem/Open3D-ML | [
"1c26dce2126f5b38f3801d3f9b9599fe978ad559",
"1c26dce2126f5b38f3801d3f9b9599fe978ad559"
] | [
"ml3d/tf/models/point_pillars.py",
"supervisely/train/src/sly_dashbord_logger.py"
] | [
"import tensorflow as tf\nimport numpy as np\nimport pickle\nimport random\n\nfrom tqdm import tqdm\nimport os\n\nfrom open3d.ml.tf.ops import voxelize\n\nfrom .base_model_objdet import BaseModel\nfrom ...utils import MODEL\n\nfrom ..utils.objdet_helper import Anchor3DRangeGenerator, BBoxCoder, multiclass_nms, limi... | [
[
"tensorflow.RaggedTensor.from_row_splits",
"tensorflow.ones_like",
"tensorflow.reshape",
"tensorflow.keras.layers.Dense",
"tensorflow.keras.Sequential",
"tensorflow.scatter_nd",
"tensorflow.zeros_like",
"tensorflow.math.top_k",
"tensorflow.stack",
"tensorflow.keras.layers.B... |
hi64n/burger_war_5th | [
"4e81e678b0f54bf32316e5cd0b26aa298e6d98bf"
] | [
"burger_war_dev/scripts/nn_run.py"
] | [
"#!/usr/bin/env python\n# -*- coding: utf-8 -*-\n\n#\nimport rospy\nimport random\n\nfrom geometry_msgs.msg import Twist\n\nimport tf\n\nimport numpy as np\nimport actionlib\nimport requests\nimport math\nfrom move_base_msgs.msg import MoveBaseAction, MoveBaseGoal\nimport actionlib_msgs\nfrom nav_msgs.msg import Od... | [
[
"numpy.ones"
]
] |
Zhou1993napolun/Pose_enabler | [
"669fffd6cea57fec5fa9bd95868cc48347700f42",
"669fffd6cea57fec5fa9bd95868cc48347700f42"
] | [
"lib/core/inference.py",
"demo/demo_0.py"
] | [
"# ------------------------------------------------------------------------------\n# Copyright (c) Microsoft\n# Licensed under the MIT License.\n# Written by Bin Xiao (Bin.Xiao@microsoft.com)\n# ------------------------------------------------------------------------------\n\nfrom __future__ import absolute_import\... | [
[
"numpy.array",
"numpy.tile",
"numpy.sign",
"numpy.argmax",
"numpy.amax",
"numpy.greater",
"numpy.floor"
],
[
"torch.device",
"numpy.array",
"numpy.asarray",
"numpy.zeros",
"torch.no_grad",
"torch.from_numpy",
"torch.cuda.is_available",
"torch.load",
... |
vlad17/run-lmc | [
"bddb7df2aa3dcec17380d858325bf50502fffb4e",
"bddb7df2aa3dcec17380d858325bf50502fffb4e"
] | [
"runlmc/linalg/identity.py",
"runlmc/mean/test_zero.py"
] | [
"# Copyright (c) 2016, Vladimir Feinberg\n# Licensed under the BSD 3-clause license (see LICENSE)\n\nimport numpy as np\n\nfrom .matrix import Matrix\nfrom ..util.docs import inherit_doc\n\n# TODO(test)\n@inherit_doc\nclass Identity(Matrix):\n def __init__(self, n):\n super().__init__(n, n)\n\n def mat... | [
[
"numpy.identity"
],
[
"numpy.arange",
"numpy.zeros"
]
] |
tab1tha/pandas | [
"f51f0987f0d7ed20ef8cd0ce2c02697a9f2426c8"
] | [
"pandas/conftest.py"
] | [
"from datetime import date, time, timedelta, timezone\nfrom decimal import Decimal\nimport operator\nimport os\n\nfrom dateutil.tz import tzlocal, tzutc\nimport hypothesis\nfrom hypothesis import strategies as st\nimport numpy as np\nimport pytest\nfrom pytz import FixedOffset, utc\n\nimport pandas.util._test_decor... | [
[
"numpy.array",
"numpy.float",
"pandas.set_option",
"pandas.Period",
"pandas.Interval",
"pandas.Timestamp",
"pandas.util.testing.getSeriesData",
"pandas.core.base.SelectionMixin._cython_table.items",
"numpy.datetime64"
]
] |
arufus/pytorch-slimming | [
"3e9cccc9a826d72ce63ad3cb7a1a3a8175d10b70"
] | [
"main.py"
] | [
"import os\nimport argparse\nimport 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\nfrom vgg import vgg\nimport shutil\n\n# Training settings\nparser = argparse.ArgumentParser(description... | [
[
"torch.cuda.manual_seed",
"torch.autograd.Variable",
"torch.save",
"torch.sign",
"torch.manual_seed",
"torch.nn.functional.cross_entropy",
"torch.cuda.is_available",
"torch.load"
]
] |
alibalapour/HATNet | [
"c4e50746f68140068bae75a6b07525046255d0b5",
"c4e50746f68140068bae75a6b07525046255d0b5"
] | [
"criterions/cross_entropy.py",
"train_and_eval/trainer.py"
] | [
"from torch import nn\nfrom torch.nn import functional as F\n\n# adapted from Fairseq\n\nclass CrossEntropyWithLabelSmoothing(nn.Module):\n def __init__(self, ls_eps=0.1, ignore_idx=None, reduce=True, reduction='mean', *args, **kwargs):\n super(CrossEntropyWithLabelSmoothing, self).__init__()\n sel... | [
[
"torch.nn.functional.log_softmax"
],
[
"torch.device",
"torch.no_grad",
"torch.from_numpy",
"torch.cuda.device_count",
"numpy.linspace",
"torch.backends.cudnn.is_available",
"torch.nn.DataParallel"
]
] |
aashokvardhan/fastestimator | [
"d0d3a032448e8cb7cd2cd16cf5e68e056d946f3a"
] | [
"fastestimator/backend/_get_gradient.py"
] | [
"# Copyright 2019 The FastEstimator 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 r... | [
[
"tensorflow.is_tensor",
"torch.ones_like"
]
] |
microgold/Becca35 | [
"85ee5f530717518b1b43ba9a310e4f0d70b290a4"
] | [
"becca/affect.py"
] | [
"\"\"\"\nThe Affect class.\n\"\"\"\n\nimport os\nimport numpy as np\nimport matplotlib.pyplot as plt\n\nimport becca.tools as tools\n\n\nclass Affect(object):\n \"\"\"\n Track reward over time.\n\n Affect, or mood, is the level of arousal of the brain.\n It is influenced by the recent history of reward ... | [
[
"numpy.random.normal",
"numpy.array",
"numpy.minimum",
"matplotlib.pyplot.xlabel",
"matplotlib.pyplot.savefig",
"matplotlib.pyplot.plot",
"numpy.mean",
"matplotlib.pyplot.figure",
"matplotlib.pyplot.ylabel",
"matplotlib.pyplot.gca",
"numpy.maximum"
]
] |
realiti4/tianshou | [
"29a39d4801e8449e32ceccc03f20522293444acc"
] | [
"tianshou/data/buffer/base.py"
] | [
"import h5py\nimport numpy as np\nfrom typing import Any, Dict, List, Tuple, Union, Optional\n\nfrom tianshou.data import Batch\nfrom tianshou.data.utils.converter import to_hdf5, from_hdf5\nfrom tianshou.data.batch import _create_value, _alloc_by_keys_diff\n\n\nclass ReplayBuffer:\n \"\"\":class:`~tianshou.data... | [
[
"numpy.array",
"numpy.stack",
"numpy.arange",
"numpy.random.choice"
]
] |
janjagusch/pyquickhelper | [
"d42e1579ea20f5add9a9cd2b6d2d0a3533aee40b"
] | [
"_unittests/ut_helpgen/test_changes_graph.py"
] | [
"\"\"\"\n@brief test log(time=1s)\n@author Xavier Dupre\n\"\"\"\n\nimport sys\nimport os\nimport unittest\nimport warnings\nimport pandas\n\nfrom pyquickhelper.loghelper.flog import fLOG\nfrom pyquickhelper.helpgen.sphinx_main_helper import produce_code_graph_changes\nfrom pyquickhelper.pycode import fix_t... | [
[
"pandas.read_csv",
"matplotlib.pyplot.subplots",
"matplotlib.pyplot.close",
"matplotlib.pyplot.style.use"
]
] |
shanaka-desoysa/kaggle-amazon | [
"9634a356753db7982cc81aaabc04a30140408c7b"
] | [
"report/conv_filter_visualization.py"
] | [
"'''Visualization of the filters of VGG16, via gradient ascent in input space.\nThis script can run on CPU in a few minutes (with the TensorFlow backend).\nResults example: http://i.imgur.com/4nj4KjN.jpg\n'''\nfrom __future__ import print_function\n\nfrom scipy.misc import imsave\nimport numpy as np\nimport time\nf... | [
[
"numpy.random.random",
"numpy.clip",
"numpy.zeros",
"scipy.misc.imsave"
]
] |
KNJohnson/landlab | [
"e53e46cb5e4eacaa05b4aca21ac0c99d1b2de4df",
"e53e46cb5e4eacaa05b4aca21ac0c99d1b2de4df",
"e53e46cb5e4eacaa05b4aca21ac0c99d1b2de4df"
] | [
"examples/stream_power/simple_sp_driver.py",
"landlab/plot/tests/test_imshow_grid.py",
"landlab/components/lithology/tests/test_litholayers.py"
] | [
"\"\"\"\nsimple_sp_driver.py\n\nA simple driver implementing Braun-Willett flow routing and then a\n(non-fastscape) stream power component.\nDEJH, 09/15/14\n\"\"\"\nfrom __future__ import print_function\n\nimport time\n\nimport numpy\nimport pylab\n\nfrom landlab import ModelParameterDictionary, RasterModelGrid\nfr... | [
[
"numpy.arange",
"numpy.random.rand"
],
[
"matplotlib.pyplot.clf",
"matplotlib.backends.backend_pdf.PdfPages",
"numpy.arange"
],
[
"numpy.array"
]
] |
wx-b/gradio | [
"0e0e6f82ecf7af83cf1f4006c2afdc06492f68e9"
] | [
"gradio/interface.py"
] | [
"\"\"\"\nThis is the core file in the `gradio` package, and defines the Interface class, including methods for constructing the\ninterface using the input and output types.\n\"\"\"\n\nimport gradio\nfrom gradio.inputs import InputComponent, get_input_instance\nfrom gradio.outputs import OutputComponent, get_output_... | [
[
"tensorflow.keras.backend.get_session",
"tensorflow.get_default_graph"
]
] |
Franckyi/Simulation-Telecom | [
"e856b78bd1da487d52676fc97750be73858f3f30"
] | [
"src/modulation.py"
] | [
"#!/usr/bin/env python\n# coding: utf-8\n\nimport numpy as np\n\nfrom codage import coder_nrz\n\n\ndef binaire_vers_decimal(bits):\n \"\"\"\n Transforme un tableau de bits en entier\n :param bits: Le tableau de bits\n :return: L'entier représentant la valeur binaire\n \"\"\"\n s = \"\"\n for bi... | [
[
"numpy.sin",
"numpy.log2"
]
] |
JonasFrey96/FlowPose6D | [
"2297ab5fa0afd0c247d59c2f1c7f899f078e2893"
] | [
"src/helper/bounding_box.py"
] | [
"import numpy as np\nimport matplotlib.pyplot as plt\nimport copy\nimport torch\n\nfrom .camera import backproject_points_batch, backproject_points, backproject_point\n\n\nclass BoundingBox():\n def __init__(self, p1, p2):\n \"p1 = u,v u=height v=widht starting top_left 0,0\"\n if p1[0] < p2[0] an... | [
[
"torch.nonzero",
"numpy.array",
"torch.stack",
"torch.min",
"torch.max",
"matplotlib.pyplot.savefig",
"torch.nn.functional.interpolate",
"matplotlib.pyplot.figure",
"torch.isinf",
"matplotlib.pyplot.show",
"matplotlib.pyplot.axis",
"matplotlib.pyplot.imshow"
]
] |
vimarkova/dggru | [
"019106a491f28f15aa33a3ae1b575794f1a6e1af"
] | [
"cnn_hcp.py"
] | [
"import torch\nimport torch.nn as nn\nfrom torchvision import models, transforms\nfrom dataset import HCPDataset\n# from torch.utils.data import DataLoader\nfrom torch_geometric.data import DataLoader\nfrom torch.utils.tensorboard import SummaryWriter\nimport torch.nn.functional as F\n\nEPOCHS = 120\nIS_SEX = True ... | [
[
"torch.nn.Linear",
"torch.nn.MaxPool2d",
"torch.nn.functional.dropout",
"torch.unsqueeze",
"torch.nn.Conv2d",
"torch.cuda.is_available",
"torch.nn.CrossEntropyLoss",
"torch.reshape"
]
] |
TremaMiguel/LightGBM | [
"da9072fde2b5cd7160866e7e9e49a14e7fba8bf3"
] | [
"python-package/lightgbm/plotting.py"
] | [
"# coding: utf-8\n\"\"\"Plotting library.\"\"\"\nfrom copy import deepcopy\nfrom io import BytesIO\nfrom typing import Any, Dict, List, Optional, Tuple, Union\n\nimport numpy as np\n\nfrom .basic import Booster, _log_warning\nfrom .compat import GRAPHVIZ_INSTALLED, MATPLOTLIB_INSTALLED\nfrom .sklearn import LGBMMod... | [
[
"numpy.count_nonzero",
"matplotlib.image.imread",
"matplotlib.ticker.MaxNLocator",
"matplotlib.pyplot.subplots"
]
] |
wiederm/protex | [
"7fb945dcee138705e28465f4657678185ed97cb8"
] | [
"protex/update.py"
] | [
"from collections import defaultdict\n\nfrom scipy.spatial import distance_matrix\nfrom protex.system import IonicLiquidSystem\nimport logging\nimport numpy as np\nfrom simtk import unit\n\nlogger = logging.getLogger(__name__)\n\n\nclass Update:\n def __init__(self, ionic_liquid: IonicLiquidSystem) -> None:\n ... | [
[
"scipy.spatial.distance_matrix",
"numpy.linspace",
"scipy.spatial.distance.cdist",
"numpy.sqrt"
]
] |
mcallistertyler95/melgan-neurips | [
"58ab3cd753b57f1416182e6d9c317c7e5b9131a5"
] | [
"spec2wav/interface.py"
] | [
"from spec2wav.modules import Generator, Audio2Mel, Audio2Cqt\n\nfrom pathlib import Path\nimport yaml\nimport torch\nimport os\n\n\ndef get_default_device():\n if torch.cuda.is_available():\n return \"cuda\"\n else:\n return \"cpu\"\n\n\ndef load_model(spec2wav_path, device=get_default_device()... | [
[
"torch.no_grad",
"torch.cuda.is_available",
"torch.load"
]
] |
claydodo/grid_utils | [
"1a08cb8ca226bb22ddac01be2a0863919d736767"
] | [
"grid_utils/tiler/xy_tiler.py"
] | [
"# -*- coding:utf-8 -*-\n\nimport six\nimport numpy as np\n\n__all__ = ['XYTiler']\n\n\nclass XYTiler(object):\n _offset_dict = {\n \"center\": (0.5, 0.5),\n \"lowerleft\": (0.0, 0.0),\n \"lowerright\": (1.0, 0.0),\n \"upperleft\": (0.0, 1.0),\n \"upperright\": (1.0, 1.0)\n ... | [
[
"numpy.full",
"numpy.linspace",
"numpy.arange",
"numpy.floor"
]
] |
mandli/scipy | [
"ce90df2874c39595ef69a586a3e7fdd9cb9b6f48",
"ce90df2874c39595ef69a586a3e7fdd9cb9b6f48"
] | [
"scipy/io/matlab/mio4.py",
"scipy/linalg/decomp.py"
] | [
"''' Classes for read / write of matlab (TM) 4 files\n'''\nimport sys\nimport warnings\n\nimport numpy as np\nfrom numpy.compat import asbytes, asstr\n\nimport scipy.sparse\n\nfrom miobase import MatFileReader, docfiller, matdims, \\\n read_dtype, convert_dtypes, arr_to_chars, arr_dtype_number, \\\n MatWrit... | [
[
"numpy.product",
"numpy.array",
"numpy.empty",
"numpy.asarray",
"numpy.zeros",
"numpy.ascontiguousarray",
"numpy.ndarray",
"numpy.compat.asstr",
"numpy.dtype",
"numpy.compat.asbytes"
],
[
"numpy.equal",
"numpy.array",
"numpy.asarray",
"numpy.zeros",
... |
ControlNet/tensorneko | [
"70dfb2f6395e1703dbdf5d5adcfed7b1334efb8f",
"70dfb2f6395e1703dbdf5d5adcfed7b1334efb8f"
] | [
"src/tensorneko/layer/log.py",
"src/tensorneko/evaluation/iou.py"
] | [
"import torch\nfrom torch import Tensor, log\n\nfrom ..neko_module import NekoModule\n\n\nclass Log(NekoModule):\n \"\"\"\n The module version of :func:`torch.log` operation.\n\n Args:\n eps (``float``, optional): A bias applied to the input to avoid ``-inf``. Default ``0``.\n\n Examples::\n\n ... | [
[
"torch.log"
],
[
"torch.clamp",
"torch.tensor",
"torch.minimum",
"torch.maximum"
]
] |
davidcaron/raven | [
"c8dd818e42b81120acf57cef0a340f42785074cf"
] | [
"raven/processes/wps_graph_objective_function_fit.py"
] | [
"#!/usr/bin/env python2\n# -*- coding: utf-8 -*-\n\"\"\"\nCreated on Wed Jun 12 13:23:00 2019\n\n@author: ets\n\"\"\"\n\nfrom pathlib import Path\n\nfrom matplotlib import pyplot as plt\nfrom pywps import ComplexInput, ComplexOutput\nfrom pywps import FORMATS\nfrom pywps import Format\nfrom pywps import Process\n\n... | [
[
"matplotlib.pyplot.close"
]
] |
marco-willi/HiDDeN-tensorflow | [
"f657b41ee145452f6b187b99f8c26fa4af2fba79",
"f657b41ee145452f6b187b99f8c26fa4af2fba79"
] | [
"tests/test_noise_gaussian_blur.py",
"tests/test_noise_dropout.py"
] | [
"import tensorflow as tf\nimport numpy as np\n\nfrom noise import gaussian\n\n\nclass GaussianKernelTests(tf.test.TestCase):\n\n def setUp(self):\n \"\"\" Compare with Values from\n https://en.wikipedia.org/wiki/Gaussian_blur\n \"\"\"\n\n self.wiki_example = np.array([\n ... | [
[
"numpy.array",
"tensorflow.ones",
"tensorflow.reduce_sum",
"numpy.expand_dims"
],
[
"tensorflow.zeros",
"tensorflow.ones",
"numpy.prod",
"tensorflow.reduce_sum",
"tensorflow.test.main",
"tensorflow.split"
]
] |
ngaggion/Chest-x-ray-Baselines | [
"c1969b334e1df700da2bdbe57862c09b7647888b"
] | [
"models/PCA.py"
] | [
"import torch\nimport torch.nn as nn\nimport torch.nn.functional as F\nimport numpy as np\nfrom models.modelUtils import residualBlock\n\nclass EncoderConv(nn.Module):\n def __init__(self, latents = 64, hw = 16):\n super(EncoderConv, self).__init__()\n \n self.latents = latents\n self... | [
[
"torch.nn.Linear",
"numpy.array",
"torch.nn.MaxPool2d",
"numpy.load",
"torch.from_numpy",
"torch.matmul"
]
] |
daxiongpro/Pytorch-CapsuleNet | [
"05d67384620c87c67b81894d3a8868bc3bb5f93e"
] | [
"data_loader.py"
] | [
"import torch\r\nfrom torchvision import datasets, transforms\r\n\r\n\r\nclass Dataset:\r\n def __init__(self, dataset, _batch_size):\r\n super(Dataset, self).__init__()\r\n if dataset == 'mnist':\r\n dataset_transform = transforms.Compose([\r\n transforms.ToTensor(),\r\n ... | [
[
"torch.utils.data.DataLoader"
]
] |
facebookresearch/opacus | [
"5cc574ff877b0be5634dde8fdd5130b7090491a6"
] | [
"benchmarks/utils.py"
] | [
"# Copyright (c) Meta Platforms, Inc. and affiliates.\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... | [
[
"torch.cuda.reset_peak_memory_stats",
"torch.cuda.max_memory_allocated",
"torch.cuda.memory_allocated"
]
] |
dzelge/xcube | [
"1e5049a227df4a50435d9aac6aacf2bcbaa3e2dd"
] | [
"test/sampledata.py"
] | [
"import numpy as np\nimport pandas as pd\nimport xarray as xr\n\n\ndef new_test_dataset(time, height=180, **indexers):\n \"\"\"\n Create a test dataset with dimensions (\"time\", \"lat\", \"lon\") and data variables given by *indexers*.\n\n :param time: Single date/time string or sequence of date-time stri... | [
[
"pandas.to_datetime",
"numpy.full",
"numpy.array",
"numpy.linspace"
]
] |
yuxuzi/alpha_factory | [
"b99ce165d3edbac50765bfa877f6ea2a982faca9"
] | [
"alpha_factory/data/datasource/hdf_reader.py"
] | [
"\"\"\"\nHDF5 Pricing File Format\n------------------------\nAt the top level, the file is keyed by country (to support regional\nfiles containing multiple countries).\n\nWithin each country, there are 4 subgroups:\n\n``/data``\n^^^^^^^^^\nEach field (OHLCV) is stored in a dataset as a 2D array, with a row per\nsid... | [
[
"pandas.to_datetime",
"numpy.array",
"numpy.isnan",
"numpy.setdiff1d",
"numpy.zeros",
"pandas.Timestamp",
"numpy.where",
"numpy.asscalar",
"numpy.sort",
"pandas.Series",
"numpy.in1d"
]
] |
mmcenta/jax-baselines | [
"98a19b23abca1f3f5933c1b7178ed34f392de8dd"
] | [
"jax_baselines/vpg/vpg.py"
] | [
"import functools\nimport os\nimport time\nfrom collections import namedtuple\n\nimport gym\nfrom gym.spaces import Box, Discrete\nimport haiku as hk\nimport jax\nimport jax.experimental.optix as optix\nimport jax.numpy as jnp\nfrom jax.experimental.optimizers import adam\nfrom jax import random\nimport numpy as np... | [
[
"numpy.array"
]
] |
bobaseb/neural_link_SV_iDE | [
"ff45ec4850dd40e2bdfc153efa45575871cedbd9"
] | [
"behavioral/validate_ide.py"
] | [
"import numpy as np\nimport pandas as pd\nimport statsmodels.api as sm\nfrom scipy.stats import entropy\nfrom scipy.stats import pearsonr,spearmanr\nfrom matplotlib import cm\nfrom scipy import stats, optimize\nfrom matplotlib import pyplot as plt\nimport os\nimport inspect\nimport dv_funcs\nimport time\nimport se... | [
[
"numpy.mean",
"scipy.stats.pearsonr",
"scipy.stats.ttest_1samp",
"numpy.nanmean",
"pandas.concat",
"pandas.read_csv",
"matplotlib.pyplot.xticks",
"numpy.random.normal",
"matplotlib.pyplot.colorbar",
"pandas.DataFrame",
"scipy.stats.ttest_rel",
"scipy.optimize.minimi... |
gamerDecathlete/prob_mbrl | [
"efba089bb066f32ad9133ac2504099e05aac5846"
] | [
"examples/deep_pilco_mm.py"
] | [
"import argparse\nimport atexit\nimport copy\nimport datetime\nimport numpy as np\nimport os\nimport torch\nimport tensorboardX\n\nfrom functools import partial\nfrom prob_mbrl import utils, models, algorithms, envs\n\nif __name__ == '__main__':\n parser = argparse.ArgumentParser(\"Deep-PILCO with moment matchin... | [
[
"numpy.random.seed",
"numpy.ones",
"torch.manual_seed",
"torch.cuda.is_available",
"torch.tensor",
"torch.set_flush_denormal",
"torch.set_num_threads"
]
] |
tknrsgym/quara | [
"8f3337af83cdd02bb85632bb1e297902b1fff8fb"
] | [
"quara/protocol/qtomography/standard/standard_qpt.py"
] | [
"import itertools\r\nfrom itertools import product\r\nfrom typing import List, Tuple, Union, Dict\r\n\r\nimport numpy as np\r\n\r\nfrom quara.objects.state import State\r\nfrom quara.objects.povm import Povm\r\nfrom quara.objects.gate import Gate\r\nfrom quara.objects.qoperation import QOperation\r\nfrom quara.obje... | [
[
"numpy.outer",
"numpy.array",
"numpy.sqrt",
"numpy.zeros"
]
] |
Raalsky/neptune-client | [
"24ac58581774e61056d49cd1a22727799c14ad54"
] | [
"tests/neptune/test_project.py"
] | [
"#\n# Copyright (c) 2019, Neptune Labs Sp. z o.o.\n#\n# Licensed under the Apache License, Version 2.0 (the \"License\");\n# you may not use this file except in compliance with the License.\n# You may obtain a copy of the License at\n#\n# http://www.apache.org/licenses/LICENSE-2.0\n#\n# Unless required by appli... | [
[
"pandas.DataFrame.from_dict"
]
] |
DiarKarim/Visual-Proprioceptive | [
"dfdb0cbfbbcdea1f487cde992cc04e6a55b1b037"
] | [
"VisualProprioceptive_Analysis/Perception.py"
] | [
"import numpy as np\nimport matplotlib.pyplot as plt\nimport pandas as pd\nimport os\nimport random\nfrom scipy.optimize import curve_fit\nfrom scipy.stats import norm\n\n# Function Definitions\n# Curve fitting part\n# define the true objective function ----------------------------------------------\ndef psyFunctio... | [
[
"scipy.optimize.curve_fit",
"numpy.asarray",
"numpy.round",
"pandas.DataFrame",
"matplotlib.pyplot.plot",
"numpy.exp",
"numpy.shape",
"numpy.nanmin",
"numpy.nanmean",
"numpy.arange",
"numpy.abs",
"matplotlib.pyplot.scatter",
"numpy.nanmax",
"scipy.stats.norm... |
vinnamkim/captum | [
"b7429d1561b6018e0d53d68eaafc6632e97ac164"
] | [
"captum/_utils/common.py"
] | [
"#!/usr/bin/env python3\nimport typing\nfrom enum import Enum\nfrom inspect import signature\nfrom typing import Any, Callable, List, Tuple, Union, cast, overload\n\nimport torch\nfrom torch import Tensor, device\nfrom torch.nn import Module\n\nfrom .._utils.typing import Literal, TargetType\n\n\nclass ExpansionTyp... | [
[
"torch.cat",
"torch.tensor",
"torch.numel"
]
] |
smarie/python-m5p | [
"d10f1d454301df64375ce641a442952bb05a4e43"
] | [
"src/m5py/export.py"
] | [
"from numbers import Integral\n\nimport numpy as np\nfrom io import StringIO\n\nfrom sklearn.tree import _tree\nfrom sklearn.tree._criterion import FriedmanMSE\n\nfrom m5py.main import is_leaf, ConstantLeafModel, M5Base, check_is_fitted\n\n\ndef export_text_m5(decision_tree, out_file=None, max_depth=None,\n ... | [
[
"numpy.around",
"numpy.argmax",
"numpy.mod"
]
] |
pnorton-usgs/notebooks | [
"17a38ecd3f3c052b9bd785c2e53e16a9082d1e71"
] | [
"06_CBH/dynamic_parameters_to_netcdf.py"
] | [
"# ---\n# jupyter:\n# jupytext:\n# formats: ipynb,py:percent\n# text_representation:\n# extension: .py\n# format_name: percent\n# format_version: '1.3'\n# jupytext_version: 1.13.7\n# kernelspec:\n# display_name: Python [conda env:bandit_py3]\n# language: python\n# nam... | [
[
"pandas.read_csv"
]
] |
kailiang-zhong/DESCN | [
"2aab9da518f1426d8bc753e82e2be6d8d54ce537"
] | [
"model/dataset.py"
] | [
"import torch\nimport pandas as pd\n\n\nclass ESXDataset(torch.utils.data.Dataset):\n def __init__(self, train_X, train_Y, train_T, train_E):\n self.train_X = torch.from_numpy(train_X).float()\n self.train_T = torch.from_numpy(train_T).float() # label of treatment status\n self.train_Y = to... | [
[
"torch.from_numpy"
]
] |
Pi-Pi-project/PiPi-Kermit | [
"90161eced0ac527e6aeeeb26a380cc7e77194239"
] | [
"train.py"
] | [
"import os\nos.environ['TF_CPP_MIN_LOG_LEVEL'] = \"3\"\nfrom tensorflow.keras.layers import *\nfrom tensorflow.keras.models import Sequential\nfrom tensorflow.keras.callbacks import EarlyStopping, ModelCheckpoint, ReduceLROnPlateau\nfrom train_preprocessing import processed_data\n\ndef model_train(email):\n inpu... | [
[
"tensorflow.keras.models.Sequential"
]
] |
mimakaev/cooler | [
"84b0d510dc3baf0b9ef3592f9d27ba795e1802ee"
] | [
"cooler/balance.py"
] | [
"# -*- coding: utf-8 -*-\nfrom __future__ import absolute_import, division, print_function\nfrom functools import partial\nfrom operator import add\nimport warnings\n\nimport numpy as np\n\nfrom ._logging import get_logger\nfrom .tools import split, partition\nfrom .util import mad\n\n__all__ = [\"balance_cooler\"]... | [
[
"numpy.bincount",
"numpy.isnan",
"numpy.zeros",
"numpy.log",
"numpy.median",
"numpy.copy",
"numpy.ones",
"numpy.exp",
"numpy.arange",
"numpy.sqrt",
"numpy.abs"
]
] |
CNES/swot_simulator | [
"92d0bb4a274ec9923265567968beea3be4283e61"
] | [
"tests/test_random_signal.py"
] | [
"import os\nimport pickle\nimport numpy as np\nimport xarray as xr\n\nimport swot_simulator\nimport swot_simulator.random_signal as random_signal\n\nROOT = os.path.dirname(os.path.abspath(__file__))\n\n\ndef test_gen_signal_1d():\n with open(os.path.join(ROOT, \"data\", \"gen_signal_1d.bin\"), \"rb\") as stream:... | [
[
"numpy.random.default_rng"
]
] |
PhoenixMark0/ChestX-ray14-pytorch | [
"a8cc9bef45de7f40273e84c46c8d3c3d02bfe413"
] | [
"pytorch_code/densenet.py"
] | [
"import re\nimport torch\nimport torch.nn as nn\nimport torch.nn.functional as F\nimport torch.utils.checkpoint as cp\nfrom collections import OrderedDict\nfrom torch import Tensor\nfrom torch.jit.annotations import List\n\n\n__all__ = ['DenseNet', 'densenet121', 'densenet169', 'densenet201', 'densenet161']\n\nmode... | [
[
"torch.nn.Linear",
"torch.cat",
"torch.flatten",
"torch.nn.AdaptiveAvgPool2d",
"torch.nn.init.constant_",
"torch.nn.MaxPool2d",
"torch.nn.AvgPool2d",
"torch.nn.functional.dropout",
"torch.nn.BatchNorm2d",
"torch.nn.init.kaiming_normal_",
"torch.nn.functional.adaptive_av... |
wladimir-crypto/TensowFlow-Food | [
"c5e115f96d3fca04fe256e9b2f3075f77e083a75",
"c5e115f96d3fca04fe256e9b2f3075f77e083a75"
] | [
"tensorflow_examples/lite/model_maker/core/task/model_spec/object_detector_spec.py",
"tensorflow_examples/lite/model_maker/third_party/recommendation/ml/model/keras_losses_test.py"
] | [
"# Copyright 2020 The TensorFlow Authors. All Rights Reserved.\n#\n# Licensed under the Apache License, Version 2.0 (the \"License\");\n# you may not use this file except in compliance with the License.\n# You may obtain a copy of the License at\n#\n# http://www.apache.org/licenses/LICENSE-2.0\n#\n# Unless requ... | [
[
"tensorflow.config.set_soft_device_placement",
"tensorflow.io.gfile.GFile",
"tensorflow.lite.TFLiteConverter.from_saved_model",
"tensorflow.config.experimental_run_functions_eagerly",
"tensorflow.keras.mixed_precision.experimental.set_policy",
"tensorflow.compat.v1.logging.warn",
"tens... |
sf-fl/federatedML | [
"6cb48525d662ba1bad12702622f2b43f67da67cf"
] | [
"test/other/eda.py"
] | [
"import seaborn as sns\nimport numpy as np\nimport matplotlib.pyplot as plt\nimport pandas as pd\nimport os\nimport sys\n\n\nos.chdir(os.path.dirname(sys.path[0]))\n\ntrain = pd.read_csv('./client/data_storage/data_7.csv')\ntrain.drop('phone_num', axis=1, inplace=True)\ncols = [c for c in train.columns] #返回数据的列名到... | [
[
"matplotlib.pyplot.xlabel",
"matplotlib.pyplot.subplots",
"matplotlib.pyplot.ylabel",
"matplotlib.pyplot.show",
"pandas.read_csv",
"numpy.unique"
]
] |
Asap7772/railrl_evalsawyer | [
"baba8ce634d32a48c7dfe4dc03b123e18e96e0a3",
"baba8ce634d32a48c7dfe4dc03b123e18e96e0a3",
"baba8ce634d32a48c7dfe4dc03b123e18e96e0a3",
"baba8ce634d32a48c7dfe4dc03b123e18e96e0a3",
"baba8ce634d32a48c7dfe4dc03b123e18e96e0a3",
"baba8ce634d32a48c7dfe4dc03b123e18e96e0a3"
] | [
"rlkit/launchers/experiments/ashvin/bear_launcher.py",
"experiments/steven-images/discrete_classic_envs.py",
"rlkit/envs/mujoco/ant.py",
"rlkit/torch/vae/vae_trainer.py",
"rlkit/envs/goal_generation/pickup_goal_dataset.py",
"experiments/ashvin/rss/pusher1/original/rig_demos.py"
] | [
"\"\"\"\nExample usage from command line\npython railrl/launchers/experiments/ashvin/bear_launcher.py --demo_data=/home/ashvin/data/s3doodad/demos/icml2020/hand/pen2_sparse.npy --eval_freq=1000 --algo_name=BEAR --env_name=pen-v0 --log_dir=data_walker_BEAR/ --lagrange_thresh=10.0 --distance_type=MMD --mode=auto --nu... | [
[
"numpy.array",
"numpy.median",
"numpy.random.seed",
"torch.manual_seed",
"numpy.std",
"numpy.random.randint"
],
[
"numpy.prod"
],
[
"numpy.concatenate",
"numpy.clip",
"numpy.isfinite",
"numpy.square"
],
[
"torch.cat",
"torch.stack",
"numpy.mean",... |
d1ngn1gefe1/lmdis-rep | [
"b334d7e5eb281948107ac6781807945ff7a4dfc2"
] | [
"net_modules/auto_struct/keypoint_encoder.py"
] | [
"from net_modules import keypoints_2d\nimport tensorflow as tf\nimport zutils.tf_math_funcs as tmf\nimport numpy as np\nimport zutils.pt_utils as ptu\nimport net_modules.auto_struct.utils as asu\nimport prettytensor as pt\nimport math\nfrom zutils.py_utils import *\nimport zutils.tf_graph_utils as tgu\n\n\nfrom net... | [
[
"tensorflow.exp",
"tensorflow.ones",
"tensorflow.ones_like",
"tensorflow.reshape",
"tensorflow.zeros_like",
"tensorflow.to_float",
"tensorflow.random_normal",
"tensorflow.add_to_collection",
"tensorflow.square",
"tensorflow.concat",
"numpy.log",
"tensorflow.random_u... |
esmou2/Kylearn-pytorch | [
"2e07f7b40b3cbbabf8be6b1abc8a350ddc66eef0"
] | [
"Training/control.py"
] | [
"import numpy as np\n\n\nclass TrainingControl():\n def __init__(self, max_step, evaluate_every_nstep, print_every_nstep):\n self.state_dict = {\n 'epoch': 0,\n 'batch': 0,\n 'step': 0,\n 'step_to_evaluate': False,\n 'step_to_print': False,\n ... | [
[
"numpy.equal",
"numpy.mod"
]
] |
nihirv/blt-vqg | [
"73ce8510fb2a696b44b686e38418cc0a11982162"
] | [
"train_iq.py"
] | [
"import argparse\nimport os\nimport pickle\nfrom types import SimpleNamespace\nfrom typing import OrderedDict\nfrom pytorch_lightning import callbacks\n\nfrom torch._C import device\nfrom utils.vocab import build_vocab, load_vocab\nfrom utils.data_loader import get_loader\nfrom utils import NLGEval\nfrom torchvisio... | [
[
"torch.nn.MSELoss",
"numpy.mean",
"torch.cuda.is_available",
"torch.tensor",
"torch.nn.CrossEntropyLoss",
"torch.multiprocessing.set_sharing_strategy"
]
] |
plocandido/docinfrati | [
"ad563c93efed1d6909a7650d299cac9adf8a1348",
"ad563c93efed1d6909a7650d299cac9adf8a1348"
] | [
".venv/lib/python3.10/site-packages/nltk/cluster/em.py",
".venv/lib/python3.10/site-packages/nltk/cluster/gaac.py"
] | [
"# Natural Language Toolkit: Expectation Maximization Clusterer\r\n#\r\n# Copyright (C) 2001-2022 NLTK Project\r\n# Author: Trevor Cohn <tacohn@cs.mu.oz.au>\r\n# URL: <https://www.nltk.org/>\r\n# For license information, see LICENSE.TXT\r\n\r\ntry:\r\n import numpy\r\nexcept ImportError:\r\n pass\r\n\r\nfrom ... | [
[
"numpy.array",
"numpy.dot",
"numpy.log",
"numpy.zeros",
"numpy.ones",
"numpy.linalg.det",
"numpy.exp",
"numpy.identity",
"numpy.multiply.outer",
"numpy.linalg.inv"
],
[
"numpy.array",
"numpy.ones",
"numpy.arange"
]
] |
ricklentz/2dimageto3dmodel | [
"52647408c419f9626133c79c7ce884bb01ac5f72"
] | [
"code/camera/coordinate_system_transformation.py"
] | [
"\"\"\"\nTraditional pipeline in computer graphics renders images from the viewpoint of a virtual pin-hole\ncamera by using the very frequent perspective projection.\n\nView direction is initially set along the negative z-axis in camera coordinate system.\nSo, 3D content which we define needs a transformation from ... | [
[
"torch.unbind",
"torch.stack"
]
] |
ami-iit/liecasadi | [
"92a4b94adec7561ff57cf83b6e0505428771f8d7"
] | [
"src/liecasadi/dualquaternion.py"
] | [
"# Copyright (C) 2021 Istituto Italiano di Tecnologia (IIT). All rights reserved.\n# This software may be modified and distributed under the terms of the\n# GNU Lesser General Public License v2.1 or any later version.\n\nimport dataclasses\nimport warnings\nfrom dataclasses import field\n\nimport casadi as cs\n\nfr... | [
[
"numpy.linalg.norm",
"numpy.random.randn",
"numpy.eye"
]
] |
David-Sebesta/Pattern-Recognition-ICP | [
"3645cfe6610f1c3bd30b4703e9ea5fd77c932abd"
] | [
"venv/Lib/site-packages/idx2numpy/test/converters_test.py"
] | [
"# -*- coding: utf-8 -*-\n\nimport sys\nimport unittest\nimport idx2numpy\nimport contextlib\nimport numpy as np\nimport os\nimport struct\n\ntry:\n from StringIO import StringIO as BytesIO # for python 2.5\nexcept ImportError:\n from io import BytesIO\n\n# unittest in Python 2.6 and lower doesn't have asser... | [
[
"numpy.array",
"numpy.shape",
"numpy.ndim",
"numpy.zeros"
]
] |
liuyangzzu/nano-compare | [
"b8d7cc74f99a00b3faeb5717ef3797cd7941d3ec"
] | [
"src/nanocompare/utils/meth_stats_tool.py"
] | [
"#!/usr/bin/env python3\n# @Author : Yang Liu\n# @FileName : meth_stats_tool.py\n# @Software : NANOME project\n# @Organization : JAX Li Lab\n# @Website : https://github.com/TheJacksonLaboratory/nanome\n\n\"\"\"\nTool for pre-processing results\n\"\"\"\nimport argparse\nimport glob\nimport gzip\nimport sys\nfrom ... | [
[
"numpy.array",
"pandas.DataFrame",
"numpy.sort",
"pandas.concat",
"pandas.read_csv"
]
] |
mauvais2/AMPL | [
"fa6279e592781a9ebdb1d3b01feeb4fbd4ad3d99"
] | [
"atomsci/ddm/pipeline/model_pipeline.py"
] | [
"#!/usr/bin/env python\n\n\"\"\"\nContains class ModelPipeline, which loads in a dataset, splits it, trains a model, and generates predictions and output\nmetrics for that model. Works for a variety of featurizers, splitters and other parameters on a generic dataset\n\"\"\"\n\nimport json\nimport logging\nimport os... | [
[
"numpy.concatenate",
"numpy.zeros",
"pandas.DataFrame",
"numpy.nansum",
"numpy.mean",
"numpy.nanmin",
"sklearn.metrics.pairwise_distances",
"numpy.any",
"numpy.nanmean",
"scipy.stats.norm.fit",
"numpy.argmax",
"numpy.sort",
"numpy.argpartition",
"numpy.nanma... |
Idate96/Mimetic-Fem | [
"75ad3b982ef7ed7c6198f526d19dc460dec28f4d",
"75ad3b982ef7ed7c6198f526d19dc460dec28f4d"
] | [
"src/tests/Yi/tests/inner_product_between_lobatto_and_gauss.py",
"src/function_space.py"
] | [
"# -*- coding: utf-8 -*-\n\"\"\"\n(SHORT NAME EXPLANATION)\n \n>>>DOCTEST COMMANDS \n(THE TEST ANSWER)\n\n@author: Yi Zhang. Created on Mon Jul 10 20:12:27 2017\n Department of Aerodynamics\n Faculty of Aerospace Engineering\n TU Delft\n \n#SUMMARY----------------\n\n#INPUTS------... | [
[
"numpy.sin",
"numpy.cos"
],
[
"numpy.max",
"numpy.size"
]
] |
StuartIanNaylor/kws_scripts | [
"285a6bb44888099a3e15c5d2bb0a212e210ad449"
] | [
"tfl-stream.py"
] | [
"import sounddevice as sd\nimport numpy as np\nimport timeit\nimport tensorflow.compat.v1 as tf\n\n\n# Parameters\ndebug_time = 0\ndebug_acc = 0\nword_threshold = 10.0\nrec_duration = 0.020\nsample_rate = 16000\nnum_channels = 1\n\n# Load the TFLite model and allocate tensors.\ninterpreter = tf.lite.Interpreter(mod... | [
[
"tensorflow.compat.v1.lite.Interpreter",
"numpy.argmax",
"numpy.reshape",
"numpy.zeros"
]
] |
DiogoM1/MBINF_SIB | [
"19e77896a8b5788747e51b20613c2f3b2888cca1",
"19e77896a8b5788747e51b20613c2f3b2888cca1"
] | [
"src/si/util/im2col.py",
"tests/util/test_metrics.py"
] | [
"import numpy as np\n\n\ndef calc_pad_dims_2D(X_shape, out_dim, kernel_shape, stride):\n if not isinstance(X_shape, tuple):\n raise ValueError(\"`X_shape` must be of type tuple\")\n\n if not isinstance(out_dim, tuple):\n raise ValueError(\"`out_dim` must be of type tuple\")\n\n if not isinsta... | [
[
"numpy.array",
"numpy.pad",
"numpy.zeros",
"numpy.tile",
"numpy.arange"
],
[
"numpy.asarray"
]
] |
giorgosVardakas/pt-dec | [
"c29b9634eb74c828efd9d2b87c613cdb0ddd1dd5"
] | [
"ptdec/model.py"
] | [
"import numpy as np\nfrom sklearn.cluster import KMeans\nimport torch\nimport torch.nn as nn\nfrom torch.utils.data.dataloader import DataLoader, default_collate\nfrom typing import Tuple, Callable, Optional, Union\nfrom tqdm import tqdm\n\nfrom ptdec.utils import target_distribution, cluster_accuracy\n\n\ndef trai... | [
[
"torch.cat",
"torch.utils.data.dataloader.DataLoader",
"sklearn.cluster.KMeans",
"numpy.copy",
"torch.no_grad",
"torch.tensor",
"torch.nn.KLDivLoss"
]
] |
scls19fr/windrose | [
"70485f90c1c88eca7af6cd67fd4644cb42332fe3"
] | [
"windrose/windrose.py"
] | [
"#!/usr/bin/env python\n# -*- coding: utf-8 -*-\n\n# from __future__ import absolute_import, division, print_function\n\nimport locale\nimport matplotlib as mpl\nimport numpy as np\nimport random\nfrom matplotlib.projections.polar import PolarAxes\nfrom numpy.lib.twodim_base import histogram2d\nimport matplotlib.py... | [
[
"matplotlib.projections.polar.PolarAxes.cla",
"numpy.histogram",
"numpy.max",
"matplotlib.legend.Legend",
"numpy.asarray",
"numpy.reshape",
"matplotlib.patches.Rectangle",
"numpy.lib.twodim_base.histogram2d",
"numpy.sum",
"numpy.copy",
"numpy.min",
"matplotlib.pyplo... |
stbaercom/europython2018_boring | [
"93c5fecbccd6f3e5d89d33cbbf3e0f5b02ae3b00"
] | [
"boring_demo_code.py"
] | [
"import os\nimport subprocess\n\n\nimport pptx\nfrom pptx.chart.data import ChartData\nfrom pptx.enum.chart import XL_CHART_TYPE\nfrom pptx.util import Inches\n\nimport pdfrw\n\nfrom pd2ppt import df_to_table\n\nimport pandas as pd\n\n\ndef load_excel_files():\n df_times = pd.read_excel(\"input_data/project_hour... | [
[
"pandas.read_excel",
"pandas.ExcelWriter",
"pandas.concat"
]
] |
console-beaver/dedo | [
"675c008291292ef3dae22d48e8c64de7ace3dc63"
] | [
"dedo/run_svae.py"
] | [
"\"\"\"\nA demo for training Sequential Variational Autoencoders.\n\npython -m dedo.run_svae --logdir=~/local/dedo --num_envs 12 --unsup_algo VAE\n\ntensorboard --logdir=/tmp/dedo --bind_all --port 6006\n\n--unsup_algo choices are: VAE, SVAE, PRED\n\nNote: this code is for research i.e. quick experimentation; it ha... | [
[
"numpy.array",
"numpy.random.randint",
"numpy.random.rand",
"numpy.stack"
]
] |
sudorudu/decision_tree | [
"b50ffcb87a60471b0e31b6c80b0964eeb53ad365"
] | [
"decision_trees/datasets/digits_raw.py"
] | [
"from typing import Tuple\nimport matplotlib.pyplot as plt\nimport numpy as np\nfrom sklearn import datasets\nfrom sklearn import svm, metrics\n\nfrom decision_trees.datasets.dataset_base import DatasetBase\n\n\ndef sample_from_scikit():\n # The digits dataset\n digits = datasets.load_digits()\n\n # The da... | [
[
"sklearn.metrics.confusion_matrix",
"sklearn.datasets.load_digits",
"matplotlib.pyplot.title",
"sklearn.svm.SVC",
"sklearn.metrics.classification_report",
"matplotlib.pyplot.show",
"matplotlib.pyplot.imshow",
"matplotlib.pyplot.axis",
"matplotlib.pyplot.subplot"
]
] |
atf1206/qPython | [
"7e64a28b1e8814a8d6b9217ce79bb8de546e62f3"
] | [
"samples/tick_subscriber.py"
] | [
"# \n# Copyright (c) 2011-2014 Exxeleron GmbH\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 ap... | [
[
"numpy.string_"
]
] |
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