Java* API Reference for Intel® Data Analytics Acceleration Library 2018 Update 3

LowOrderMomsCSRDistr.java

/* file: LowOrderMomsCSRDistr.java */
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* Copyright 2014-2018 Intel Corporation.
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/*
// Content:
// Java example of computing low order moments in the distributed processing
// mode.
//
// Input matrix is stored in the compressed sparse row (CSR) format with
// one-based indexing.
*/
package com.intel.daal.examples.moments;
import com.intel.daal.algorithms.low_order_moments.*;
import com.intel.daal.data_management.data.CSRNumericTable;
import com.intel.daal.data_management.data.HomogenNumericTable;
import com.intel.daal.examples.utils.Service;
import com.intel.daal.services.DaalContext;
/*
// Input data set is stored in the compressed sparse row format
*/
class LowOrderMomsCSRDistr {
/* Input data set parameters */
private static final String datasetFileNames[] = new String[] { "../data/distributed/covcormoments_csr_1.csv",
"../data/distributed/covcormoments_csr_2.csv", "../data/distributed/covcormoments_csr_3.csv",
"../data/distributed/covcormoments_csr_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) throws java.io.IOException {
/* Read the input data from a file */
CSRNumericTable dataTable = Service.createSparseTable(context, datasetFileNames[block]);
/* Create algorithm objects to compute low order moments in the distributed processing mode using the default method */
DistributedStep1Local algorithm = new DistributedStep1Local(context, Float.class, Method.fastCSR);
/* Set input objects for the algorithm */
algorithm.input.set(InputId.data, dataTable);
/* 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, Float.class, Method.fastCSR);
/* 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() {
HomogenNumericTable minimum = (HomogenNumericTable) result.get(ResultId.minimum);
HomogenNumericTable maximum = (HomogenNumericTable) result.get(ResultId.maximum);
HomogenNumericTable sum = (HomogenNumericTable) result.get(ResultId.sum);
HomogenNumericTable sumSquares = (HomogenNumericTable) result.get(ResultId.sumSquares);
HomogenNumericTable sumSquaresCentered = (HomogenNumericTable) result.get(ResultId.sumSquaresCentered);
HomogenNumericTable mean = (HomogenNumericTable) result.get(ResultId.mean);
HomogenNumericTable secondOrderRawMoment = (HomogenNumericTable) result.get(ResultId.secondOrderRawMoment);
HomogenNumericTable variance = (HomogenNumericTable) result.get(ResultId.variance);
HomogenNumericTable standardDeviation = (HomogenNumericTable) result.get(ResultId.standardDeviation);
HomogenNumericTable variation = (HomogenNumericTable) 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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