Python* API Reference for Intel® Data Analytics Acceleration Library 2019 Update 5

svd_dense_batch.py

1 # file: svd_dense_batch.py
2 #===============================================================================
3 # Copyright 2014-2019 Intel Corporation.
4 #
5 # This software and the related documents are Intel copyrighted materials, and
6 # your use of them is governed by the express license under which they were
7 # provided to you (License). Unless the License provides otherwise, you may not
8 # use, modify, copy, publish, distribute, disclose or transmit this software or
9 # the related documents without Intel's prior written permission.
10 #
11 # This software and the related documents are provided as is, with no express
12 # or implied warranties, other than those that are expressly stated in the
13 # License.
14 #===============================================================================
15 
16 
17 
18 
19 import os
20 import sys
21 
22 from daal.algorithms import svd
23 from daal.data_management import FileDataSource, DataSourceIface
24 
25 utils_folder = os.path.realpath(os.path.abspath(os.path.dirname(os.path.dirname(__file__))))
26 if utils_folder not in sys.path:
27  sys.path.insert(0, utils_folder)
28 from utils import printNumericTable
29 
30 DAAL_PREFIX = os.path.join('..', 'data')
31 
32 # Input data set parameters
33 datasetFileName = os.path.join(DAAL_PREFIX, 'batch', 'svd.csv')
34 nRows = 16000
35 
36 if __name__ == "__main__":
37 
38  # Initialize FileDataSource<CSVFeatureManager> to retrieve input data from .csv file
39  dataSource = FileDataSource(
40  datasetFileName,
41  DataSourceIface.doAllocateNumericTable,
42  DataSourceIface.doDictionaryFromContext
43  )
44 
45  # Retrieve the data from input file
46  dataSource.loadDataBlock(nRows)
47 
48  # Create algorithm to compute SVD decomposition
49  algorithm = svd.Batch()
50 
51  algorithm.input.set(svd.data, dataSource.getNumericTable())
52 
53  # Compute SVD decomposition
54  res = algorithm.compute()
55 
56  # Print results
57  printNumericTable(res.get(svd.singularValues), "Singular values:")
58  printNumericTable(res.get(svd.rightSingularMatrix), "Right orthogonal matrix V:")
59  printNumericTable(res.get(svd.leftSingularMatrix), "Left orthogonal matrix U:", 10)

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