Java* API Reference for Intel® Data Analytics Acceleration Library 2016 Update 4

LowOrderMomentsCSROnline.java

/* file: LowOrderMomentsCSROnline.java */
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/*
// Content:
// Java example of computing low order moments in the online 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.NumericTable;
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 LowOrderMomentsCSROnline {
/* Input data set parameters */
private static final String datasetFileNames[] = new String[] { "../data/online/covcormoments_csr_1.csv",
"../data/online/covcormoments_csr_2.csv", "../data/online/covcormoments_csr_3.csv",
"../data/online/covcormoments_csr_4.csv" };
private static final int nBlocks = 4;
private static Result result;
private static DaalContext context = new DaalContext();
public static void main(String[] args) throws java.io.FileNotFoundException, java.io.IOException {
/* Create algorithm objects to compute low order moments in the online processing mode using the default method */
Online algorithm = new Online(context, Double.class, Method.fastCSR);
for (int i = 0; i < nBlocks; i++) {
/* Read the input data from a file */
CSRNumericTable dataTable = Service.createSparseTable(context, datasetFileNames[i]);
/* Set input objects for the algorithm */
algorithm.input.set(InputId.data, dataTable);
/* Compute partial low order moments estimates */
PartialResult pres = algorithm.compute();
dataTable.dispose();
pres.dispose();
}
/* 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);
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);
}
}