Python* API Reference for Intel® Data Analytics Acceleration Library 2018 Update 1

cov_csr_online.py

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40 
41 ## <a name="DAAL-EXAMPLE-PY-COVARIANCE_CSR_ONLINE"></a>
42 ## \example cov_csr_online.py
43 
44 import os
45 import sys
46 
47 from daal.algorithms import covariance
48 
49 utils_folder = os.path.realpath(os.path.abspath(os.path.dirname(os.path.dirname(__file__))))
50 if utils_folder not in sys.path:
51  sys.path.insert(0, utils_folder)
52 from utils import printNumericTable, createSparseTable
53 
54 DAAL_PREFIX = os.path.join('..', 'data')
55 
56 # Input data set parameters
57 nBlocks = 4
58 datasetFileNames = [
59  os.path.join(DAAL_PREFIX, 'online', 'covcormoments_csr_1.csv'),
60  os.path.join(DAAL_PREFIX, 'online', 'covcormoments_csr_2.csv'),
61  os.path.join(DAAL_PREFIX, 'online', 'covcormoments_csr_3.csv'),
62  os.path.join(DAAL_PREFIX, 'online', 'covcormoments_csr_4.csv'),
63 ]
64 
65 if __name__ == "__main__":
66 
67  # Create algorithm objects for covariance matrix computing in online mode using default method
68  algorithm = covariance.Online()
69 
70  for i in range(nBlocks):
71  dataTable = createSparseTable(datasetFileNames[i])
72 
73  # Set input arguments of the algorithm
74  algorithm.input.set(covariance.data, dataTable)
75 
76  # Compute partial covariance estimates
77  algorithm.compute()
78 
79  # Finalize online result and get computed covariance
80  res = algorithm.finalizeCompute()
81 
82  printNumericTable(res.get(covariance.covariance), "Covariance matrix (upper left square 10*10) :", 10, 10)
83  printNumericTable(res.get(covariance.mean), "Mean vector:", 1, 10)

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