covariance_csr_batch.cpp

/* file: covariance_csr_batch.cpp */
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/*
!  Content:
!    C++ example of variance-covariance matrix computation in the batch
!    processing mode
!
!******************************************************************************/

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

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

typedef float   dataFPType;         /* Input data floating-point type */
typedef double  algorithmFPType;    /* Algorithm floating-point type */

/* Input data set parameters
   Input matrix is stored in the compressed sparse row format with one-based indexing
 */
const string datasetFileName = "../data/batch/covcormoments_csr.csv";

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

    /* Read datasetFileName from a file and create a numeric table to store input data */
    services::SharedPtr<CSRNumericTable> dataTable(createSparseTable<dataFPType>(datasetFileName));

    /* Create an algorithm to compute variance-covariance matrix using the default method */
    covariance::Batch<algorithmFPType, covariance::fastCSR> algorithm;
    algorithm.input.set(covariance::data, dataTable);

    /* Compute a variance-covariance matrix */
    algorithm.compute();

    /* Get the computed variance-covariance matrix */
    services::SharedPtr<covariance::Result> res = algorithm.getResult();

    printNumericTable(res->get(covariance::covariance), "Covariance matrix (upper left square 10*10) :", 10, 10);
    printNumericTable(res->get(covariance::mean),       "Mean vector:", 1, 10);

    return 0;
}