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

PCATransformDenseBatch.java

/* file: PCATransformDenseBatch.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 PCA transformation algorithm
*/
package com.intel.daal.examples.pca_transform;
import com.intel.daal.algorithms.pca.Batch;
import com.intel.daal.algorithms.pca.InputId;
import com.intel.daal.algorithms.pca.Method;
import com.intel.daal.algorithms.pca.Result;
import com.intel.daal.algorithms.pca.ResultId;
import com.intel.daal.algorithms.pca.ResultsToComputeId;
import com.intel.daal.data_management.data.NumericTable;
import com.intel.daal.data_management.data.CSRNumericTable;
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;
import com.intel.daal.algorithms.pca.*;
import com.intel.daal.algorithms.pca.transform.*;
import com.intel.daal.data_management.data.NumericTable;
import com.intel.daal.data_management.data.KeyValueDataCollection;
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;
import com.intel.daal.algorithms.pca.ResultId;
class PCATransformDenseBatch {
private static final String dataset = "../data/batch/pca_transform.csv";
private static DaalContext context = new DaalContext();
public static void main(String[] args) throws java.io.FileNotFoundException, java.io.IOException {
/* Retrieve the input data */
FileDataSource dataSource = new FileDataSource(context, dataset,
DataSource.DictionaryCreationFlag.DoDictionaryFromContext,
DataSource.NumericTableAllocationFlag.DoAllocateNumericTable);
dataSource.loadDataBlock();
NumericTable input = dataSource.getNumericTable();
/* Create a PCA algorithm */
Batch algorithm =
new Batch(context, Float.class, Method.correlationDense);
/* Set an input object for the algorithm */
algorithm.input.set(InputId.data, input);
algorithm.parameter.setResultsToCompute(ResultsToComputeId.mean | ResultsToComputeId.variance | ResultsToComputeId.eigenvalue);
/* Compute PCA */
Result result = algorithm.compute();
Service.printNumericTable("Eigenvalues:",result.get(ResultId.eigenValues));
Service.printNumericTable("Eigenvectors:",result.get(ResultId.eigenVectors));
//KeyValueDataCollection resultCollection = result.get(TransformDataInputId.dataForTransform);
Service.printNumericTable("Eigenvalues kv:",result.get(ResultId.eigenValues));
Service.printNumericTable("Means kv:",result.get(ResultId.means));
Service.printNumericTable("Variances kv:",result.get(ResultId.variances));
long a=2;
TransformInput inputDataAlg = new TransformInput(context,a);
//inputDataAlg.set(TransformInputId.eigenvectors, result.get(ResultId.eigenVectors));
long b=3;
KeyValueDataCollection dataCollection = new KeyValueDataCollection(context);
/* Create a PCA transform algorithm */
TransformBatch transformAlgorithm = new TransformBatch(context, Float.class, TransformMethod.defaultDense, 2);
/* Set an input object for the algorithm */
transformAlgorithm.input.set(TransformInputId.data, input);
ResultId transformResultId = new ResultId(TransformDataInputId.dataForTransform.getValue());
int id = transformResultId.getValue();
//System.out.println(id);
/* Set eigenvectors for the algorithm */
transformAlgorithm.input.set(TransformInputId.eigenvectors, result.get(ResultId.eigenVectors));
NumericTable trNumTable = result.get(ResultId.means);
transformAlgorithm.input.set(TransformDataInputId.dataForTransform,dataCollection);
/* Compute PCA transfromation */
TransformResult transformResult = transformAlgorithm.compute();
/* Print the results of stage */
//Service.printNumericTable("First 4 rows of the input data:", input, 4);
//Service.printNumericTable("First 4 rows of the PCA transformation result:",
// transformResult.get(TransformResultId.transformedData), 4);
Service.printNumericTable("Transformed data:", transformResult.get(TransformResultId.transformedData));
context.dispose();
}
}

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