LowOrderMomsDenseOnline.java

/* file: LowOrderMomsDenseOnline.java */
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/*
 //  Content:
 //     Java example of computing low order moments in the online processing mode
 */

package com.intel.daal.examples.moments;

import com.intel.daal.algorithms.low_order_moments.*;
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 LowOrderMomsDenseOnline {

    /* Input data set parameters */
    private static final String datasetFileName = "../data/online/covcormoments_dense.csv";
    private static final int    nVectorsInBlock = 50;

    private static FileDataSource dataSource;

    private static Result result;

    private static DaalContext context = new DaalContext();

    public static void main(String[] args) throws java.io.FileNotFoundException, java.io.IOException {
        /* Retrieve the input data from a .csv file */
        dataSource = new FileDataSource(context, datasetFileName,
                DataSource.DictionaryCreationFlag.DoDictionaryFromContext,
                DataSource.NumericTableAllocationFlag.DoAllocateNumericTable);

        /* Create algorithm objects to compute low order moments in the online processing mode using the default method */
        Online algorithm = new Online(context, Float.class, Method.defaultDense);

        /* Set input objects for the algorithm */
        NumericTable input = dataSource.getNumericTable();
        algorithm.input.set(InputId.data, input);

        while (dataSource.loadDataBlock(nVectorsInBlock) == nVectorsInBlock) {
            /* Compute partial low order moments estimates */
            algorithm.compute();
        }

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

        printResults();

        context.dispose();
    }

    private static void printResults() {
        NumericTable minimum = result.get(ResultId.minimum);
        NumericTable maximum = result.get(ResultId.maximum);
        NumericTable sum = result.get(ResultId.sum);
        NumericTable sumSquares = result.get(ResultId.sumSquares);
        NumericTable sumSquaresCentered = result.get(ResultId.sumSquaresCentered);
        NumericTable mean = result.get(ResultId.mean);
        NumericTable secondOrderRawMoment = result.get(ResultId.secondOrderRawMoment);
        NumericTable variance = result.get(ResultId.variance);
        NumericTable standardDeviation = result.get(ResultId.standardDeviation);
        NumericTable variation = result.get(ResultId.variation);

        Service.printNumericTable("Minimum:", minimum);
        Service.printNumericTable("Maximum:", maximum);
        Service.printNumericTable("Sum:", sum);
        Service.printNumericTable("Sum of squares:", sumSquares);
        Service.printNumericTable("Sum of squared difference from the means:", sumSquaresCentered);
        Service.printNumericTable("Mean:", mean);
        Service.printNumericTable("Second order raw moment:", secondOrderRawMoment);
        Service.printNumericTable("Variance:", variance);
        Service.printNumericTable("Standart deviation:", standardDeviation);
        Service.printNumericTable("Variation:", variation);
    }
}
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