package edu.hawaii.jmotif.performance.ford;
import java.io.IOException;
import java.util.HashMap;
import java.util.List;
import java.util.Map;
import edu.hawaii.jmotif.performance.UCRUtils;
import edu.hawaii.jmotif.text.SAXCollectionStrategy;
import edu.hawaii.jmotif.text.TextUtils;
import edu.hawaii.jmotif.text.WordBag;
import edu.hawaii.jmotif.timeseries.TSException;
/**
* Helper-runner for CBF test.
*
* @author psenin
*
*/
public class FordBWebProper {
private static int CLASSIC = 0;
private static int EXACT = 1;
private static int NOREDUCTION = 2;
// data locations
private static final String TRAINING_DATA = "data/ford/Ford_B_TRAIN";
private static final String TEST_DATA = "data/ford/Ford_B_TEST";
// SAX parameters to try
//
private static final int[][] params = { { 430, 10, 15, NOREDUCTION },
{ 430, 10, 17, NOREDUCTION } };
/**
* @param args
* @throws TSException
* @throws IndexOutOfBoundsException
* @throws IOException
*/
public static void main(String[] args) throws IndexOutOfBoundsException, TSException, IOException {
// making training and test collections
Map<String, List<double[]>> trainData = UCRUtils.readUCRData(TRAINING_DATA);
Map<String, List<double[]>> testData = UCRUtils.readUCRData(TEST_DATA);
for (int[] p : params) {
// extract parameters
int WINDOW_SIZE = p[0];
int PAA_SIZE = p[1];
int ALPHABET_SIZE = p[2];
SAXCollectionStrategy strategy = SAXCollectionStrategy.CLASSIC;
if (EXACT == p[3]) {
strategy = SAXCollectionStrategy.EXACT;
}
else if (NOREDUCTION == p[3]) {
strategy = SAXCollectionStrategy.NOREDUCTION;
}
// making training bags collection
List<WordBag> bags = TextUtils.labeledSeries2WordBags(trainData, PAA_SIZE, ALPHABET_SIZE,
WINDOW_SIZE, strategy);
HashMap<String, HashMap<String, Double>> tfidf = TextUtils.computeTFIDF(bags);
tfidf = TextUtils.normalizeToUnitVectors(tfidf);
// classifying
int testSampleSize = 0;
int positiveTestCounter = 0;
for (String label : tfidf.keySet()) {
List<double[]> testD = testData.get(label);
for (double[] series : testD) {
positiveTestCounter = positiveTestCounter
+ TextUtils.classify(label, series, tfidf, PAA_SIZE, ALPHABET_SIZE, WINDOW_SIZE,
strategy);
testSampleSize++;
}
}
double accuracy = (double) positiveTestCounter / (double) testSampleSize;
double error = 1.0d - accuracy;
System.out.println(WINDOW_SIZE + "," + PAA_SIZE + "," + ALPHABET_SIZE + "," + accuracy + ","
+ error);
// System.out.println(new CosineDistanceMatrix(tfidf).toString());
}
}
}