Python* API Reference for Intel® Data Analytics Acceleration Library 2020 Update 1

qr_dense_batch.py

1 # file: qr_dense_batch.py
2 #===============================================================================
3 # Copyright 2014-2020 Intel Corporation
4 #
5 # Licensed under the Apache License, Version 2.0 (the "License");
6 # you may not use this file except in compliance with the License.
7 # You may obtain a copy of the License at
8 #
9 # http://www.apache.org/licenses/LICENSE-2.0
10 #
11 # Unless required by applicable law or agreed to in writing, software
12 # distributed under the License is distributed on an "AS IS" BASIS,
13 # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
14 # See the License for the specific language governing permissions and
15 # limitations under the License.
16 #===============================================================================
17 
18 
19 
20 
21 import os
22 import sys
23 
24 from daal.algorithms import qr
25 from daal.data_management import FileDataSource, DataSourceIface
26 
27 utils_folder = os.path.realpath(os.path.abspath(os.path.dirname(os.path.dirname(__file__))))
28 if utils_folder not in sys.path:
29  sys.path.insert(0, utils_folder)
30 from utils import printNumericTable
31 
32 DAAL_PREFIX = os.path.join('..', 'data')
33 
34 # Input data set parameters
35 datasetFileName = os.path.join(DAAL_PREFIX, 'batch', 'qr.csv')
36 nRows = 16000
37 
38 if __name__ == "__main__":
39 
40  # Initialize FileDataSource<CSVFeatureManager> to retrieve input data from .csv file
41  dataSource = FileDataSource(
42  datasetFileName, DataSourceIface.doAllocateNumericTable,
43  DataSourceIface.doDictionaryFromContext
44  )
45 
46  # Retrieve the data from input file
47  dataSource.loadDataBlock(nRows)
48 
49  # Create algorithm to compute QR decomposition
50  algorithm = qr.Batch()
51 
52  algorithm.input.set(qr.data, dataSource.getNumericTable())
53 
54  res = algorithm.compute()
55 
56  # Print results
57  printNumericTable(res.get(qr.matrixQ), "Orthogonal matrix Q:", 10)
58  printNumericTable(res.get(qr.matrixR), "Triangular matrix R:")

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