cor_dense_online.cpp

/* file: cor_dense_online.cpp */
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/*
!  Content:
!    C++ example of dense correlation matrix computation in the online
!    processing mode
!******************************************************************************/

#include "daal.h"
#include "service.h"

using namespace std;
using namespace daal;
using namespace daal::algorithms;

/* Input data set parameters */
const string datasetFileName = "../data/batch/covcormoments_dense.csv";
const size_t nObservations   = 50;

int main(int argc, char *argv[])
{
    checkArguments(argc, argv, 1, &datasetFileName);

    /* Initialize FileDataSource<CSVFeatureManager> to retrieve the input data from a .csv file */
    FileDataSource<CSVFeatureManager> dataSource(datasetFileName, DataSource::doAllocateNumericTable,
                                                 DataSource::doDictionaryFromContext);

    /* Create an algorithm to compute a dense correlation matrix in the online processing mode using the default method */
    covariance::Online<> algorithm;

    /* Set the parameter to choose the type of the output matrix */
    algorithm.parameter.outputMatrixType = covariance::correlationMatrix;

    while (dataSource.loadDataBlock(nObservations) == nObservations)
    {
        /* Set input objects for the algorithm */
        algorithm.input.set(covariance::data, dataSource.getNumericTable());

        /* Compute partial estimates */
        algorithm.compute();
    }

    /* Finalize the result in the online processing mode */
    algorithm.finalizeCompute();

    /* Get the computed dense correlation matrix */
    covariance::ResultPtr res = algorithm.getResult();

    printNumericTable(res->get(covariance::correlation), "Correlation matrix:");
    printNumericTable(res->get(covariance::mean),        "Mean vector:");

    return 0;
}
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