LowOrderMomentsDenseDistributed.java

/* file: LowOrderMomentsDenseDistributed.java */
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/*
 //  Content:
 //     Java example of computing low order moments in the distributed 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 LowOrderMomentsDenseDistributed {

    /* Input data set parameters */
    private static final String datasetFileNames[] = new String[] { "../data/distributed/covcormoments_dense_1.csv",
            "../data/distributed/covcormoments_dense_2.csv", "../data/distributed/covcormoments_dense_3.csv",
            "../data/distributed/covcormoments_dense_4.csv" };

    private static final int nBlocks         = 4;

    private static PartialResult[] partialResult = new PartialResult[nBlocks];
    private static Result          result;

    private static DaalContext context = new DaalContext();

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

        for (int i = 0; i < nBlocks; i++) {
            computeOnLocalNode(i);
        }

        computeOnMasterNode();

        printResults();

        context.dispose();
    }

    private static void computeOnLocalNode(int block) {
        /* Retrieve the input data from a .csv file */
        FileDataSource dataSource = new FileDataSource(context, datasetFileNames[block],
                DataSource.DictionaryCreationFlag.DoDictionaryFromContext,
                DataSource.NumericTableAllocationFlag.DoAllocateNumericTable);
        /* Retrieve the data from an input file */
        dataSource.loadDataBlock();

        /* Create algorithm objects to compute low order moments in the distributed processing mode using the default method */
        DistributedStep1Local algorithm = new DistributedStep1Local(context, Double.class, Method.defaultDense);

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

        /* Compute partial low order moments estimates on local nodes */
        partialResult[block] = algorithm.compute();
    }

    private static void computeOnMasterNode() {
        /* Create algorithm objects to compute low order moments in the distributed processing mode using the default method */
        DistributedStep2Master algorithm = new DistributedStep2Master(context, Double.class, Method.defaultDense);

        /* Set input objects for the algorithm */
        for (int i = 0; i < nBlocks; i++) {
            algorithm.input.add(DistributedStep2MasterInputId.partialResults, partialResult[i]);
        }

        /* Compute a partial low order moments estimate on the master node from the partial estimates on local nodes */
        algorithm.compute();

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

    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);

        System.out.println("Low order moments:");
        Service.printNumericTable("Min:", minimum);
        Service.printNumericTable("Max:", maximum);
        Service.printNumericTable("Sum:", sum);
        Service.printNumericTable("SumSquares:", sumSquares);
        Service.printNumericTable("SumSquaredDiffFromMean:", sumSquaresCentered);
        Service.printNumericTable("Mean:", mean);
        Service.printNumericTable("SecondOrderRawMoment:", secondOrderRawMoment);
        Service.printNumericTable("Variance:", variance);
        Service.printNumericTable("StandartDeviation:", standardDeviation);
        Service.printNumericTable("Variation:", variation);
    }
}