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

cov_dense_batch.py

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40 
41 
42 
43 
44 import os
45 import sys
46 
47 from daal.algorithms import covariance
48 from daal.data_management import FileDataSource, DataSourceIface
49 
50 utils_folder = os.path.realpath(os.path.abspath(os.path.dirname(os.path.dirname(__file__))))
51 if utils_folder not in sys.path:
52  sys.path.insert(0, utils_folder)
53 from utils import printNumericTable
54 
55 DAAL_PREFIX = os.path.join('..', 'data')
56 
57 # Input data set parameters
58 dataFileName = os.path.join(DAAL_PREFIX, 'batch', 'covcormoments_dense.csv')
59 
60 if __name__ == "__main__":
61 
62  # Initialize FileDataSource to retrieve input data from .csv file
63  dataSource = FileDataSource(
64  dataFileName,
65  DataSourceIface.doAllocateNumericTable,
66  DataSourceIface.doDictionaryFromContext
67  )
68 
69  # Retrieve the data from input file
70  dataSource.loadDataBlock()
71 
72  # Create algorithm to compute dense variance-covariance matrix in batch mode
73  algorithm = covariance.Batch()
74 
75  # Set input arguments of the algorithm
76  algorithm.input.set(covariance.data, dataSource.getNumericTable())
77 
78  # Get computed variance-covariance matrix
79  res = algorithm.compute()
80 
81  # Print values
82  printNumericTable(res.get(covariance.covariance), "Covariance matrix:")
83  printNumericTable(res.get(covariance.mean), "Mean vector:")

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