package edu.hawaii.jmotif.performance.ftwords; import java.io.BufferedWriter; import java.io.FileWriter; import java.util.List; import java.util.Map; import java.util.Map.Entry; import edu.hawaii.jmotif.performance.UCRGenericClassifier; import edu.hawaii.jmotif.performance.UCRUtils; import edu.hawaii.jmotif.text.SAXCollectionStrategy; /** * Helper-runner for CBF test. * * @author psenin * */ public class UCR50wordsKNNThreaded extends UCRGenericClassifier { // num of threads to use // private static final int THREADS_NUM = 1; // data // private static final String TRAINING_DATA = "data/50words/50words_TRAIN"; private static final String TEST_DATA = "data/50words/50words_TEST"; // output prefix // private static final String outputPrefix = "ftwords1_loocv"; // SAX parameters to use // private static final int WINDOW_MIN = 190; private static final int WINDOW_MAX = 190; private static final int WINDOW_INCREMENT = 5; private static final int PAA_MIN = 9; private static final int PAA_MAX = 9; private static final int PAA_INCREMENT = 1; private static final int ALPHABET_MIN = 3; private static final int ALPHABET_MAX = 3; private static final int ALPHABET_INCREMENT = 1; // leave out parameters // private static final int LEAVE_OUT_NUM = 1; private UCR50wordsKNNThreaded() { super(); } /** * @param args * @throws Exception */ public static void main(String[] args) throws Exception { // configuring strategy // SAXCollectionStrategy strategy = SAXCollectionStrategy.NOREDUCTION; String strategyPrefix = "noreduction"; if (args.length > 0) { String strategyP = args[0]; if ("EXACT".equalsIgnoreCase(strategyP)) { strategy = SAXCollectionStrategy.EXACT; strategyPrefix = "exact"; } if ("CLASSIC".equalsIgnoreCase(strategyP)) { strategy = SAXCollectionStrategy.CLASSIC; strategyPrefix = "classic"; } } consoleLogger.fine("strategy: " + strategyPrefix + ", leaving out: " + LEAVE_OUT_NUM); // make up window sizes int[] window_sizes = makeArray(WINDOW_MIN, WINDOW_MAX, WINDOW_INCREMENT); // make up paa sizes int[] paa_sizes = makeArray(PAA_MIN, PAA_MAX, PAA_INCREMENT); // make up alphabet sizes int[] alphabet_sizes = makeArray(ALPHABET_MIN, ALPHABET_MAX, ALPHABET_INCREMENT); // reading training and test collections // Map<String, List<double[]>> trainData = UCRUtils.readUCRData(TRAINING_DATA); consoleLogger.fine("trainData classes: " + trainData.size() + ", series length: " + trainData.entrySet().iterator().next().getValue().get(0).length); for (Entry<String, List<double[]>> e : trainData.entrySet()) { consoleLogger.fine(" training class: " + e.getKey() + " series: " + e.getValue().size()); } int totalTestSample = 0; Map<String, List<double[]>> testData = UCRUtils.readUCRData(TEST_DATA); consoleLogger.fine("testData classes: " + testData.size()); for (Entry<String, List<double[]>> e : testData.entrySet()) { consoleLogger.fine(" test class: " + e.getKey() + " series: " + e.getValue().size()); totalTestSample = totalTestSample + e.getValue().size(); } List<String> result = trainKNNFoldJMotifThreaded(THREADS_NUM, window_sizes, paa_sizes, alphabet_sizes, strategy, trainData, LEAVE_OUT_NUM); BufferedWriter bw = new BufferedWriter(new FileWriter(outputPrefix + "_" + strategyPrefix + "_" + LEAVE_OUT_NUM + ".csv")); for (String line : result) { bw.write(line + CR); } bw.close(); } }