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

cov_csr_batch.py

1 # file: cov_csr_batch.py
2 #===============================================================================
3 # Copyright 2014-2018 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 covariance
23 
24 utils_folder = os.path.realpath(os.path.abspath(os.path.dirname(os.path.dirname(__file__))))
25 if utils_folder not in sys.path:
26  sys.path.insert(0, utils_folder)
27 from utils import printNumericTable, createSparseTable
28 
29 DAAL_PREFIX = os.path.join('..', 'data')
30 
31 # Input matrix is stored in one-based sparse row storage format
32 datasetFileName = os.path.join(DAAL_PREFIX, 'batch', 'covcormoments_csr.csv')
33 
34 if __name__ == "__main__":
35 
36  # Read datasetFileName from file and create numeric table for storing input data
37  dataTable = createSparseTable(datasetFileName)
38 
39  # Create algorithm to compute covariance matrix using default method
40  algorithm = covariance.Batch()
41  algorithm.input.set(covariance.data, dataTable)
42 
43  # Get computed covariance
44  res = algorithm.compute()
45 
46  printNumericTable(res.get(covariance.covariance), "Covariance matrix (upper left square 10*10) :", 10, 10)
47  printNumericTable(res.get(covariance.mean), "Mean vector:", 1, 10)

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