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

DataStructuresHomogen.java

/* file: DataStructuresHomogen.java */
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/*
// Content:
// Java example of using homogeneous data structures
*/
package com.intel.daal.examples.datasource;
import java.nio.DoubleBuffer;
import java.nio.FloatBuffer;
import com.intel.daal.data_management.data.HomogenNumericTable;
import com.intel.daal.data_management.data.NumericTable;
import com.intel.daal.examples.utils.Service;
import com.intel.daal.services.DaalContext;
class DataStructuresHomogen {
private static final int nVectorsHomogen = 10;
private static final int nFeaturesHomogen = 11;
private static final int firstReadRow = 0;
private static final int nRead = 3;
private static DaalContext context = new DaalContext();
public static void main(String[] args) {
System.out.println("Homogeneous numeric table example\n");
int readFeatureIdx;
double[] data = {
0.0, 0.1, 0.2, 0.3, 0.4, 0.5, 0.6, 0.7, 0.8, 0.9, 1,
1.0, 1.1, 1.2, 1.3, 1.4, 1.5, 1.6, 1.7, 1.8, 1.9, 2,
2.0, 2.1, 2.2, 2.3, 2.4, 2.5, 2.6, 2.7, 2.8, 2.9, 3,
3.0, 3.1, 3.2, 3.3, 3.4, 3.5, 3.6, 3.7, 3.8, 3.9, 4,
4.0, 4.1, 4.2, 4.3, 4.4, 4.5, 4.6, 4.7, 4.8, 4.9, 5,
5.0, 5.1, 5.2, 5.3, 5.4, 5.5, 5.6, 5.7, 5.8, 5.9, 1,
6.0, 6.1, 6.2, 6.3, 6.4, 6.5, 6.6, 6.7, 6.8, 6.9, 2,
7.0, 7.1, 7.2, 7.3, 7.4, 7.5, 7.6, 7.7, 7.8, 7.9, 3,
8.0, 8.1, 8.2, 8.3, 8.4, 8.5, 8.6, 8.7, 8.8, 8.9, 4,
9.0, 9.1, 9.2, 9.3, 9.4, 9.5, 9.6, 9.7, 9.8, 9.9, 5
};
HomogenNumericTable dataTable = new HomogenNumericTable(context, data, nFeaturesHomogen, nVectorsHomogen);
/* Read a block of rows */
DoubleBuffer dataDouble = DoubleBuffer.allocate(nRead * nFeaturesHomogen);
dataDouble = dataTable.getBlockOfRows(firstReadRow, nRead, dataDouble);
System.out.printf("%d rows are read\n",nRead);
printDoubleBuffer(dataDouble, nFeaturesHomogen, nRead, "Print 3 rows from homogeneous data array as float:");
dataTable.releaseBlockOfRows(firstReadRow, nRead, dataDouble);
/* Read a feature (column) */
DoubleBuffer dataDoubleFeatures = DoubleBuffer.allocate((int) nVectorsHomogen);
readFeatureIdx = 2;
dataDoubleFeatures = dataTable.getBlockOfColumnValues(readFeatureIdx, firstReadRow, nVectorsHomogen, dataDoubleFeatures);
printDoubleBuffer(dataDoubleFeatures, 1, nVectorsHomogen, "Print the third feature of homogeneous data:");
dataTable.releaseBlockOfColumnValues(readFeatureIdx, firstReadRow, nVectorsHomogen, dataDoubleFeatures);
/* Get a pointer to the inner array for HomogenNumericTable. This pointer is a pointer to the array data */
data[0] = 999;
double[] dataFromNumericTable = dataTable.getDoubleArray();
Service.printMatrix(dataFromNumericTable, nFeaturesHomogen, nVectorsHomogen, "Data from getArray:");
int nNewVectors = 3;
float[] newData =
{
1.0f, 2.0f, 1.0f, 2.0f, 1.0f, 2.0f, 1.0f, 2.0f, 1.0f, 2.0f, 1.0f,
3.0f, 4.0f, 3.0f, 4.0f, 3.0f, 4.0f, 3.0f, 4.0f, 3.0f, 4.0f, 3.0f,
5.0f, 6.0f, 5.0f, 6.0f, 5.0f, 6.0f, 5.0f, 6.0f, 5.0f, 6.0f, 5.0f,
};
/* Set new data to HomogenNumericTable. It mush have the same type as the numeric table. */
HomogenNumericTable newDataTable = new HomogenNumericTable(context, newData, nFeaturesHomogen, nNewVectors);
/* Ensure the data has changed */
readFeatureIdx = 1;
FloatBuffer dataFloat = FloatBuffer.allocate((int) nNewVectors);;
dataFloat = newDataTable.getBlockOfColumnValues((long)readFeatureIdx, (long)firstReadRow, (long)nNewVectors, dataFloat);
printFloatBuffer(dataFloat, 1, nNewVectors, "\nPrint the second feature of new data:");
newDataTable.releaseBlockOfColumnValues(readFeatureIdx, firstReadRow, nNewVectors, dataFloat);
context.dispose();
}
private static void printDoubleBuffer(DoubleBuffer buf, long nColumns, long nRows, String message) {
int step = (int) nColumns;
System.out.println(message);
for (int i = 0; i < nRows; i++) {
for (int j = 0; j < nColumns; j++) {
System.out.format("%6.3f ", buf.get(i * step + j));
}
System.out.println("");
}
System.out.println("");
}
private static void printFloatBuffer(FloatBuffer buf, long nColumns, long nRows, String message) {
int step = (int) nColumns;
System.out.println(message);
for (int i = 0; i < nRows; i++) {
for (int j = 0; j < nColumns; j++) {
System.out.format("%6.3f ", buf.get(i * step + j));
}
System.out.println("");
}
System.out.println("");
}
}

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