CovarianceDenseBatch.java

/* file: CovarianceDenseBatch.java */
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/*
 //  Content:
 //     Java example of dense variance-covariance matrix computation in the batch
 //     processing mode
 */

package com.intel.daal.examples.covariance;

import com.intel.daal.algorithms.covariance.*;
import com.intel.daal.data_management.data.HomogenNumericTable;
import com.intel.daal.data_management.data.NumericTable;
import com.intel.daal.data_management.data_source.DataSource;
import com.intel.daal.data_management.data_source.FileDataSource;
import com.intel.daal.examples.utils.Service;
import com.intel.daal.services.DaalContext;

class CovarianceDenseBatch {
    /* Input data set parameters */
    private static final String datasetFileName = "../data/batch/covcormoments_dense.csv";

    private static DaalContext context = new DaalContext();

    public static void main(String[] args) throws java.io.FileNotFoundException, java.io.IOException {

        /* Retrieve the input data */
        FileDataSource dataSource = new FileDataSource(context, datasetFileName,
                DataSource.DictionaryCreationFlag.DoDictionaryFromContext,
                DataSource.NumericTableAllocationFlag.DoAllocateNumericTable);
        dataSource.loadDataBlock();

        /* Create an algorithm to compute a variance-covariance matrix using the single-pass method */
        Batch alg = new Batch(context, Double.class, Method.defaultDense);
        NumericTable input = dataSource.getNumericTable();
        alg.input.set(InputId.data, input);

        /* Compute the variance-covariance matrix */
        Result res = alg.compute();

        HomogenNumericTable covariance = (HomogenNumericTable) res.get(ResultId.covariance);
        HomogenNumericTable mean = (HomogenNumericTable) res.get(ResultId.mean);

        Service.printNumericTable("Covariance matrix:", covariance);
        Service.printNumericTable("Mean vector:", mean);

        context.dispose();
    }
}