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/*
* SonarQube
* Copyright (C) 2009-2024 SonarSource SA
* mailto:info AT sonarsource DOT com
*
* This program is free software; you can redistribute it and/or
* modify it under the terms of the GNU Lesser General Public
* License as published by the Free Software Foundation; either
* version 3 of the License, or (at your option) any later version.
*
* This program is distributed in the hope that it will be useful,
* but WITHOUT ANY WARRANTY; without even the implied warranty of
* MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU
* Lesser General Public License for more details.
*
* You should have received a copy of the GNU Lesser General Public License
* along with this program; if not, write to the Free Software Foundation,
* Inc., 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301, USA.
*/
export const mockIpynbFile = JSON.stringify({
cells: [
{
cell_type: 'markdown',
metadata: {},
source: ['# Learning a cosine with keras'],
},
{
cell_type: 'code',
execution_count: 2,
metadata: {
collapsed: false,
jupyter: {
outputs_hidden: false,
},
},
outputs: [
{
name: 'stdout',
output_type: 'stream',
text: ['(7500,)\n', '(2500,)\n'],
},
],
source: [
'import numpy as np\n',
'import sklearn.cross_validation as skcv\n',
'#x = np.linspace(0, 5*np.pi, num=10000, dtype=np.float32)\n',
'x = np.linspace(0, 4*np.pi, num=10000, dtype=np.float32)\n',
'y = np.cos(x)\n',
'\n',
'train, test = skcv.train_test_split(np.arange(x.shape[0]))\n',
'print train.shape\n',
'print test.shape',
],
},
{
cell_type: 'code',
execution_count: 3,
metadata: {
collapsed: false,
jupyter: {
outputs_hidden: false,
},
},
outputs: [
{
data: {
'text/plain': ['[<matplotlib.lines.Line2D at 0x7fb588176b90>]'],
},
execution_count: 3,
metadata: {},
output_type: 'execute_result',
},
{
data: {
'image/png':
'iVBORw0KGgoAAAANSUhEUgAAAAIAAAACCAIAAAD91JpzAAAAG0lEQVR4nGIJn1mo28/GzPDiV+yTNYAAAAD//yPBBfrGshAGAAAAAElFTkSuQmCC',
'text/plain': ['<matplotlib.figure.Figure at 0x7fb58e57c850>'],
},
metadata: {},
output_type: 'display_data',
},
],
source: ['import pylab as pl\n', '%matplotlib inline\n', 'pl.plot(x, y)'],
},
],
});
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