Examples with SortedKeyProperties org.dkpro.tc.ml.report.util.SortedKeyProperties used on opensource projects

Example 1 with SortedKeyProperties

use of org.dkpro.tc.ml.report.util.SortedKeyProperties in project dkpro-tc by dkpro.

the class CrfSuiteOutcomeIDReport method generateProperties.

protected Properties generateProperties(Map<String, Integer> aMapping, List<String> predictions, List<String> testFeatures) throws Exception {
    Properties p = new SortedKeyProperties();
    int maxLines = predictions.size();
    for (int idx = 1; idx < maxLines; idx++) {
        String entry = predictions.get(idx);
        String[] split = entry.split("\t");
        if (split.length != 2) {
            continue;
        }
        String featureEntry = testFeatures.get(idx - 1);
        String id = extractTCId(featureEntry);
        String[] idsplit = id.split("_");
        // make ids sortable by enforcing zero-prefixing
        String zeroPaddedId = String.format("%04d_%04d_%04d%s", Integer.valueOf(idsplit[0]), Integer.valueOf(idsplit[1]), Integer.valueOf(idsplit[2]), idsplit.length > 3 ? "_" + idsplit[3] : "");
        int numGold = aMapping.get(split[0]);
        String numPred = getPrediction(aMapping, split[1]);
        p.setProperty(zeroPaddedId, numPred + SEPARATOR_CHAR + numGold + SEPARATOR_CHAR + THRESHOLD_DUMMY_CONSTANT);
    }
    return p;
}

Example 2 with SortedKeyProperties

use of org.dkpro.tc.ml.report.util.SortedKeyProperties in project dkpro-tc by dkpro.

the class LibsvmDataFormatOutcomeIdReport method execute.

@Override
public void execute() throws Exception {
    init();
    baslinePreparation();
    Map<Integer, String> id2label = getId2LabelMapping(isRegression);
    String header = buildHeader(id2label, isRegression);
    List<String> predictions = readPredictions();
    Map<String, String> index2instanceIdMap = getMapping(isUnit || isSequence);
    Properties prop = new SortedKeyProperties();
    int lineCounter = 0;
    for (String line : predictions) {
        if (line.startsWith("#")) {
            continue;
        }
        String[] split = line.split(";");
        String key = index2instanceIdMap.get(lineCounter + "");
        String predictionString = getPrediction(split[0]);
        String goldString = split[1];
        if (isRegression) {
            prop.setProperty(key, predictionString + ";" + goldString + ";" + THRESHOLD_CONSTANT);
        } else {
            int pred = Double.valueOf(predictionString).intValue();
            int gold = Double.valueOf(goldString).intValue();
            prop.setProperty(key, pred + ";" + gold + ";" + THRESHOLD_CONSTANT);
        }
        lineCounter++;
    }
    File targetFile = getTargetOutputFile();
    FileWriterWithEncoding fw = null;
    try {
        fw = new FileWriterWithEncoding(targetFile, "utf-8");
        prop.store(fw, header);
    } finally {
        IOUtils.closeQuietly(fw);
    }
}

Example 3 with SortedKeyProperties

use of org.dkpro.tc.ml.report.util.SortedKeyProperties in project dkpro-tc by dkpro.

the class KerasMetaReport method execute.

@Override
public void execute() throws Exception {
    String python = getDiscriminator(getContext(), DIM_PYTHON_INSTALLATION);
    String kerasVersion = getKerasVersion(python);
    String numpyVersion = getNumpyVersion(python);
    String tensorFlowVersion = getTensorflowVersion(python);
    String theanoVersion = getTheanoVersion(python);
    Properties p = new SortedKeyProperties();
    p.setProperty("KerasVersion", kerasVersion);
    p.setProperty("NumpyVersion", numpyVersion);
    p.setProperty("TensorFlowVersion", tensorFlowVersion);
    p.setProperty("TheanoVersion", theanoVersion);
    File file = getContext().getFile("softwareVersions.txt", AccessMode.READWRITE);
    FileOutputStream fos = null;
    try {
        fos = new FileOutputStream(file);
        p.store(fos, "Version information");
    } finally {
        IOUtils.closeQuietly(fos);
    }
}

Example 4 with SortedKeyProperties

use of org.dkpro.tc.ml.report.util.SortedKeyProperties in project dkpro-tc by dkpro.

the class BasicResultReport method execute.

@Override
public void execute() throws Exception {
    String learningMode = getDiscriminator(getContext().getStorageService(), getContext().getId(), DIM_LEARNING_MODE);
    Properties pa = new SortedKeyProperties();
    pa = addPredictedResults(pa, learningMode);
    pa = addMajorityBaselineResults(pa, learningMode);
    pa = addRandomBaselineResult(pa, learningMode);
    writeConfusionMatrixForSingleLabel(learningMode);
    writeToDisk(pa);
}

Example 5 with SortedKeyProperties

use of org.dkpro.tc.ml.report.util.SortedKeyProperties in project dkpro-tc by dkpro.

the class DeepLearningId2OutcomeReport method execute.

@Override
public void execute() throws Exception {
    init();
    baselinePreparation();
    File file = getContext().getFile(FILENAME_PREDICTION_OUT, AccessMode.READONLY);
    List<String> predictions = getPredictions(file);
    predictions = update(predictions);
    Map<String, String> map = loadMap(isIntegerMode);
    Map<String, String> inverseMap = inverseMap(map);
    StringBuilder header = new StringBuilder();
    header.append("ID=PREDICTION;GOLDSTANDARD;THRESHOLD\nlabels ");
    List<String> k = new ArrayList<>(map.keySet());
    for (Integer i = 0; i < map.keySet().size(); i++) {
        if (!isRegression) {
            if (!isIntegerMode) {
                header.append(i + "=" + inverseMap.get(i + ""));
            } else {
                header.append(i + "=" + map.get(i + ""));
            }
            if (i + 1 < k.size()) {
                header.append(" ");
            }
        }
    }
    List<String> nameOfTargets = getNameOfTargets();
    Properties prop = new SortedKeyProperties();
    int shift = 0;
    for (int i = 0; i < predictions.size(); i++) {
        String p = predictions.get(i);
        if (p.startsWith("#Gold")) {
            // targets files
            continue;
        }
        if (p.trim().isEmpty()) {
            shift++;
            continue;
        }
        String id = determineId(nameOfTargets, i, shift);
        String[] split = p.split("\t");
        if (isMultiLabel) {
            multilabelReport(id, split, isIntegerMode, prop, map);
            continue;
        }
        String gold = null;
        String prediction = null;
        if (isRegression) {
            gold = split[0];
            prediction = split[1];
        } else {
            if (isIntegerMode) {
                gold = split[0];
                prediction = split[1];
            } else {
                gold = map.get(split[0]).toString();
                prediction = map.get(split[1]).toString();
            }
        }
        prop.setProperty("" + id, prediction + SEPARATOR_CHAR + gold + SEPARATOR_CHAR + THRESHOLD);
    }
    File id2o = getTargetFile();
    OutputStreamWriter osw = null;
    try {
        osw = new OutputStreamWriter(new FileOutputStream(id2o), "utf-8");
        prop.store(osw, header.toString());
    } finally {
        IOUtils.closeQuietly(osw);
    }
}