Example usage for java.lang Math log10

Introduction

In this page you can find the example usage for java.lang Math log10.

Prototype

@HotSpotIntrinsicCandidate
public static double log10(double a) 

Source Link

Document

Returns the base 10 logarithm of a double value.

Usage

From source file:io.github.msdk.features.ransacaligner.RANSAC.java

/**
 * Calculate k (number of trials)//  ww w . ja va  2s.  c om
 *
 * @return number of trials "k" required to select a subset of n good data
 * points.
 */
private double getK() {
    double w = 0.1;
    double b = Math.pow(w, n);
    return Math.log10(1 - 0.99) / Math.log10(1 - b) + (Math.sqrt(1 - b) / b);
}

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From source file:org.dkpro.similarity.experiments.sts2013.util.WordIdfValuesGenerator.java

public static void computeIdfScores(Mode mode, Dataset dataset) throws Exception {
    URL inputUrl = ResourceUtils.resolveLocation(
            DATASET_DIR + "/" + mode.toString().toLowerCase() + "/STS.input." + dataset.toString() + ".txt");
    List<String> lines = IOUtils.readLines(inputUrl.openStream(), "utf-8");

    Map<String, Double> idfValues = new HashMap<String, Double>();

    File outputFile = new File(
            UTILS_DIR + "/word-idf/" + mode.toString().toLowerCase() + "/" + dataset.toString() + ".txt");

    System.out.println("Computing word idf values");

    if (outputFile.exists()) {
        System.out.println(" - skipping, already exists");
    } else {/*from  w w  w  .jav a 2s .  c om*/
        System.out.println(" - this may take a while...");

        // Build up token representations of texts
        Set<List<String>> docs = new HashSet<List<String>>();

        for (String line : lines) {
            List<String> doc = new ArrayList<String>();

            Collection<Lemma> lemmas = getLemmas(line);

            for (Lemma lemma : lemmas) {
                try {
                    String token = lemma.getValue().toLowerCase();
                    doc.add(token);
                } catch (NullPointerException e) {
                    System.err.println(" - unparsable token: " + lemma.getCoveredText());
                }
            }

            docs.add(doc);
        }

        // Get the shared token list
        Set<String> tokens = new HashSet<String>();
        for (List<String> doc : docs) {
            tokens.addAll(doc);
        }

        // Get the idf numbers
        for (String token : tokens) {
            double count = 0;
            for (List<String> doc : docs) {
                if (doc.contains(token)) {
                    count++;
                }
            }
            idfValues.put(token, count);
        }

        // Compute the idf
        for (String lemma : idfValues.keySet()) {
            double idf = Math.log10(lines.size() / idfValues.get(lemma));
            idfValues.put(lemma, idf);
        }

        // Store persistently
        StringBuilder sb = new StringBuilder();
        for (String key : idfValues.keySet()) {
            sb.append(key + "\t" + idfValues.get(key) + LF);
        }
        FileUtils.writeStringToFile(outputFile, sb.toString());

        System.out.println(" - done");
    }
}

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From source file:org.apache.gossip.accrual.FailureDetector.java

public synchronized Double computePhiMeasure(long now) {
    if (latestHeartbeatMs == -1 || descriptiveStatistics.getN() < minimumSamples) {
        return null;
    }/*  w ww .  j ava2  s.co m*/
    long delta = now - latestHeartbeatMs;
    try {
        double probability;
        if (distribution.equals("normal")) {
            double standardDeviation = descriptiveStatistics.getStandardDeviation();
            standardDeviation = standardDeviation < 0.1 ? 0.1 : standardDeviation;
            probability = new NormalDistributionImpl(descriptiveStatistics.getMean(), standardDeviation)
                    .cumulativeProbability(delta);
        } else {
            probability = new ExponentialDistributionImpl(descriptiveStatistics.getMean())
                    .cumulativeProbability(delta);
        }
        final double eps = 1e-12;
        if (1 - probability < eps) {
            probability = 1.0;
        }
        return -1.0d * Math.log10(1.0d - probability);
    } catch (MathException | IllegalArgumentException e) {
        LOGGER.debug(e);
        return null;
    }
}

---

From source file:com.slownet5.pgprootexplorer.utils.FileUtils.java

public static String getReadableSize(long size) {
    if (size <= 0)
        return "0B";
    final String[] units = new String[] { "B", "KB", "MB", "GB", "TB" };
    int digitGroups = (int) (Math.log10(size) / Math.log10(1024));

    return new DecimalFormat("#,##0.#").format(size / Math.pow(1024, digitGroups)) + " " + units[digitGroups];
}

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From source file:org.um.feri.ears.problems.Task.java

/**
 * @param stop the stopping criteria/*  w  w w  .j a v a2 s .c o m*/
 * @param eval the maximum number of evaluations allowed
 * @param allowedTime the maximum CPU time allowed in milliseconds
 * @param epsilon the epsilon value for global optimum
 * @param p the problem
 */

public Task(EnumStopCriteria stop, int eval, long allowedTime, int maxIterations, double epsilon, Problem p) {
    this(stop, eval, allowedTime, maxIterations, epsilon, p, (int) Math.log10((1. / epsilon) + 1));
}

---

From source file:de.tudarmstadt.ukp.similarity.experiments.coling2012.util.CharacterNGramIdfValuesGenerator.java

@SuppressWarnings("unchecked")
public static void computeIdfScores(Dataset dataset, int n) throws Exception {
    File outputFile = new File(UTILS_DIR + "/character-ngrams-idf/" + n + "/" + dataset.toString() + ".txt");

    System.out.println("Computing character " + n + "-grams");

    if (outputFile.exists()) {
        System.out.println(" - skipping, already exists");
    } else {/*from w ww. jav  a2s  .  c om*/
        System.out.println(" - this may take a while...");

        CollectionReader reader = ColingUtils.getCollectionReader(dataset);

        // Tokenization
        AnalysisEngineDescription seg = createPrimitiveDescription(BreakIteratorSegmenter.class);
        AggregateBuilder builder = new AggregateBuilder();
        builder.add(seg, CombinationReader.INITIAL_VIEW, CombinationReader.VIEW_1);
        builder.add(seg, CombinationReader.INITIAL_VIEW, CombinationReader.VIEW_2);
        AnalysisEngine aggr_seg = builder.createAggregate();

        // Output Writer
        AnalysisEngine writer = createPrimitive(CharacterNGramIdfValuesGeneratorWriter.class,
                CharacterNGramIdfValuesGeneratorWriter.PARAM_OUTPUT_FILE, outputFile.getAbsolutePath());

        SimplePipeline.runPipeline(reader, aggr_seg, writer);

        // We now have plain text format
        List<String> lines = FileUtils.readLines(outputFile);

        Map<String, Double> idfValues = new HashMap<String, Double>();

        CharacterNGramMeasure measure = new CharacterNGramMeasure(n, new HashMap<String, Double>());

        // Get n-gram representations of texts
        List<Set<String>> docs = new ArrayList<Set<String>>();

        for (String line : lines) {
            Set<String> ngrams = measure.getNGrams(line);

            docs.add(ngrams);
        }

        // Get all ngrams
        Set<String> allNGrams = new HashSet<String>();
        for (Set<String> doc : docs)
            allNGrams.addAll(doc);

        // Compute idf values         
        for (String ngram : allNGrams) {
            double count = 0;
            for (Set<String> doc : docs) {
                if (doc.contains(ngram))
                    count++;
            }
            idfValues.put(ngram, count);
        }

        // Compute the idf
        for (String lemma : idfValues.keySet()) {
            double idf = Math.log10(lines.size() / idfValues.get(lemma));
            idfValues.put(lemma, idf);
        }

        // Store persistently
        StringBuilder sb = new StringBuilder();
        for (String key : idfValues.keySet()) {
            sb.append(key + "\t" + idfValues.get(key) + LF);
        }
        FileUtils.writeStringToFile(outputFile, sb.toString());

        System.out.println(" - done");
    }
}

---

From source file:org.lanes.text.mining.UnithoodAnalyser.java

public boolean isUnit(String left, String connector, String right) {
    long timestart = System.currentTimeMillis();

    double N = simobj.getTotalDocCount();

    //double ns = simobj.getTitleCount(left + " " + connector + " " + right);
    //double ps = ns/N;

    boolean isunitornot = false;
    //if(ps > 0){
    double nx = simobj.getDocCount(left);
    double ny = simobj.getDocCount(right);

    double px = nx / N;
    double py = ny / N;

    double nxy = simobj.getDocCount(left, right);

    double pxy = nxy / N;

    double pmi = Math.log10(pxy / (px * py));
    double normalisedpmi = pmi / -Math.log10(pxy);

    double idrleft = (nx - nxy) / nx;
    double idrrght = (ny - nxy) / ny;
    double idr = idrleft * idrrght;

    if ((pmi >= 1.1) || ((0.5 <= pmi && pmi < 0.7) && (idr < 0.6))
            || ((0.7 <= pmi && pmi < 0.9) && (0.6 <= idr && idr < 0.75))
            || ((0.9 <= pmi && pmi < 1.1) && (0.75 <= idr && idr < 0.95))) {
        isunitornot = true;//from   w ww  .  jav a 2  s .  c om
    }

    //}

    return isunitornot;
}

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From source file:edu.scripps.fl.curves.plot.GCurvePlot.java

public void addCurve(Curve curve, FitFunction function) {
    double[] yValues = (double[]) ConvertUtils.convert(curve.getResponses(), double[].class);
    double curveMinY = NumberUtils.min(yValues);
    double curveMaxY = NumberUtils.max(yValues);
    this.minY = Math.min(minY, curveMinY);
    this.maxY = Math.min(maxY, curveMaxY);
    Data yData = DataUtil.scaleWithinRange(curveMinY, curveMaxY, yValues);

    double[] xValues = (double[]) ConvertUtils.convert(curve.getConcentrations(), double[].class);
    for (int ii = 0; ii < xValues.length; ii++) {
        double x = Math.log10(xValues[ii]);
        xValues[ii] = x;//from w  w  w  . j ava  2  s .c  om
    }
    double curveMinX = NumberUtils.min(xValues);
    double curveMaxX = NumberUtils.max(xValues);
    this.minX = Math.min(minX, curveMinX);
    this.maxX = Math.min(maxX, curveMaxX);
    Data xData = DataUtil.scaleWithinRange(NumberUtils.min(xValues), NumberUtils.max(xValues), xValues);

    String hexColor = Integer
            .toHexString(((java.awt.Color) drawingSupplier.getNextPaint()).getRGB() & 0x00ffffff);
    StringBuffer sb = new StringBuffer();
    sb.append(hexColor);
    while (sb.length() < 6)
        sb.insert(0, "0");
    Color color = Color.newColor(sb.toString());

    XYLine line1 = Plots.newXYLine(xData, yData, getBackgroundColor(), "");
    //        line1.setLineStyle(LineStyle.newLineStyle(3, 1, 0));
    line1.addShapeMarkers(Shape.CIRCLE, color, 5);

    XYLine fittedLine = sampleFunctionToLine(curve, function, curveMinX, curveMaxX, 100);
    //      fittedLine.setLineStyle(LineStyle.newLineStyle(3, 1, 0));
    fittedLine.setColor(color);

    lines.add(line1);
    lines.add(fittedLine);
}

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From source file:com.hviper.codec.uodecode.PeakSignalNoiseRatioTest.java

private double computePsnrPcm16(String uoResource, String referenceResource) throws Exception {
    // Read the UO file and the reference encoder's decode output into byte arrays
    byte uoFile[] = IOUtils.toByteArray(this.getClass().getResourceAsStream(uoResource));
    byte referenceWavFile[] = IOUtils.toByteArray(this.getClass().getResourceAsStream(referenceResource));

    // Decode the UO file ourselves into a byte array
    ByteArrayOutputStream decodedWavOutputStream = new ByteArrayOutputStream(referenceWavFile.length);
    UODecode.uoToPcm16Wav(uoFile, decodedWavOutputStream);
    byte decodedWavFile[] = decodedWavOutputStream.toByteArray();

    // Find the start of the sample data; this will be after a 'data' header and four bytes of
    // content length.
    int dataStart = -1;
    for (int i = 0; i < decodedWavFile.length - 4; ++i) {
        if ((decodedWavFile[i] == 'd') && (decodedWavFile[i + 1] == 'a') && (decodedWavFile[i + 2] == 't')
                && (decodedWavFile[i + 3] == 'a')) {
            dataStart = i + 8; // 8 = length of header + chunk length
            break;
        }/*from www .ja va 2 s.co m*/
    }
    assertFalse("No 'data' header in decoded output", dataStart < 0);

    // Headers must be equal. Compare as hex strings for better assert failures here.
    String refHeaders = DatatypeConverter.printHexBinary(Arrays.copyOfRange(referenceWavFile, 0, dataStart));
    String ourHeaders = DatatypeConverter.printHexBinary(Arrays.copyOfRange(decodedWavFile, 0, dataStart));
    assertEquals("WAV headers do not match", refHeaders, ourHeaders);
    assertEquals("File lengths do not match", referenceWavFile.length, decodedWavFile.length);

    // Compute total squared error
    int cursor = dataStart;
    long totalSqError = 0;
    int sampleCount = 0;
    int worstSoFar = 0;
    for (; (cursor + 1) < referenceWavFile.length; cursor += 2) {
        short refSample = (short) ((referenceWavFile[cursor] & 0xff)
                | ((referenceWavFile[cursor + 1] & 0xff) << 8));
        short ourSample = (short) ((decodedWavFile[cursor] & 0xff)
                | ((decodedWavFile[cursor + 1] & 0xff) << 8));
        int absDiff = Math.abs(ourSample - refSample);

        long sqError = ((long) absDiff) * ((long) absDiff);
        totalSqError += sqError;
        ++sampleCount;
    }
    assertNotEquals("No samples read!", 0, sampleCount);

    // Compute the PSNR in decibels; higher the better
    double psnr;
    if (totalSqError > 0) {
        double sqrtMeanSquaredError = Math.sqrt((double) (totalSqError) / (double) (sampleCount));
        double maxValue = 65535.0;
        psnr = 20.0 * Math.log10(maxValue / sqrtMeanSquaredError);
    } else {
        // Identical! Pick a large PSNR result
        psnr = 1000.0;
    }

    return psnr;
}

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From source file:de.uniba.wiai.lspi.chord.data.ID.java

private static double log2(double x) {
    return Math.log10(x) / Math.log10(2);
}

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