Java* API Reference for Intel® Data Analytics Acceleration Library 2019

LowOrderMomsDenseBatch.java

/* file: LowOrderMomsDenseBatch.java */
/*******************************************************************************
* Copyright 2014-2018 Intel Corporation.
*
* This software and the related documents are Intel copyrighted materials, and
* your use of them is governed by the express license under which they were
* provided to you (License). Unless the License provides otherwise, you may not
* use, modify, copy, publish, distribute, disclose or transmit this software or
* the related documents without Intel's prior written permission.
*
* This software and the related documents are provided as is, with no express
* or implied warranties, other than those that are expressly stated in the
* License.
*******************************************************************************/
/*
// Content:
// Java example of computing low order moments in the batch 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 LowOrderMomsDenseBatch {
/* Input data set parameters */
private static final String datasetFileName = "../data/batch/covcormoments_dense.csv";
private static DaalContext context = new DaalContext();
private static Result result;
public static void main(String[] args) throws java.io.FileNotFoundException, java.io.IOException {
/* Retrieve the input data from a .csv file */
FileDataSource dataSource = new FileDataSource(context, datasetFileName,
DataSource.DictionaryCreationFlag.DoDictionaryFromContext,
DataSource.NumericTableAllocationFlag.DoAllocateNumericTable);
dataSource.loadDataBlock();
/* Create algorithm objects to compute low order moments using the default method */
Batch algorithm = new Batch(context, Float.class, Method.defaultDense);
/* Set input objects for the algorithm */
NumericTable input = dataSource.getNumericTable();
algorithm.input.set(InputId.data, input);
/* Compute low order moments */
result = algorithm.compute();
printResults();
context.dispose();
}
private static void printResults() {
Service.printNumericTable("Minimum:", result.get(ResultId.minimum));
Service.printNumericTable("Maximum:", result.get(ResultId.maximum));
Service.printNumericTable("Sum:", result.get(ResultId.sum));
Service.printNumericTable("Sum of squares:", result.get(ResultId.sumSquares));
Service.printNumericTable("Sum of squared difference from the means:", result.get(ResultId.sumSquaresCentered));
Service.printNumericTable("Mean:", result.get(ResultId.mean));
Service.printNumericTable("Second order raw moment:", result.get(ResultId.secondOrderRawMoment));
Service.printNumericTable("Variance:", result.get(ResultId.variance));
Service.printNumericTable("Standart deviation:", result.get(ResultId.standardDeviation));
Service.printNumericTable("Variation:", result.get(ResultId.variation));
}
}

For more complete information about compiler optimizations, see our Optimization Notice.