Example usage for org.apache.commons.math.util FastMath log10

Introduction

In this page you can find the example usage for org.apache.commons.math.util FastMath log10.

Prototype

public static double log10(final double x) 

Source Link

Document

Compute the base 10 logarithm.

Usage

From source file:com.compomics.util.experiment.identification.psm_scoring.psm_scores.HyperScore.java

/**
 * Returns the interpolation values for the given score histogram in the
 * form {a, b}.//from w ww . ja  v  a2 s .  co  m
 *
 * @param scoreHistogram the score histogram
 * @param useCache if true the interpolation values will be stored in the
 * histograms in cache
 *
 * @return the interpolation values for the given score histogram
 */
public double[] getInterpolationValues(HashMap<Integer, Integer> scoreHistogram, boolean useCache) {

    ArrayList<Integer> bins = new ArrayList<Integer>(scoreHistogram.keySet());
    Collections.sort(bins, Collections.reverseOrder());
    ArrayList<Double> evalueFunctionX = new ArrayList<Double>(scoreHistogram.size());
    ArrayList<Double> evalueFunctionY = new ArrayList<Double>(scoreHistogram.size());
    Integer currentSum = 0;
    for (Integer bin : bins) {
        Integer nInBin = scoreHistogram.get(bin);
        if (nInBin != null) {
            currentSum += nInBin;
        }
        if (currentSum > 0) {
            Double xValue = new Double(bin);
            xValue = FastMath.log10(xValue);
            evalueFunctionX.add(xValue);
            Double yValue = new Double(currentSum);
            yValue = FastMath.log10(yValue);
            evalueFunctionY.add(yValue);
        }
    }
    if (evalueFunctionX.size() <= 1) {
        return null;
    }
    RegressionStatistics regressionStatistics = LinearRegression.getSimpleLinearRegression(evalueFunctionX,
            evalueFunctionY);
    if (useCache) {
        Double roundedA = Util.roundDouble(regressionStatistics.a, 2);
        Double roundedB = Util.roundDouble(regressionStatistics.b, 2);
        Integer nA = as.get(roundedA);
        if (nA == null) {
            as.put(roundedA, 1);
        } else {
            as.put(roundedA, nA + 1);
        }
        Integer nB = bs.get(roundedB);
        if (nB == null) {
            bs.put(roundedB, 1);
        } else {
            bs.put(roundedB, nB + 1);
        }
    }
    return new double[] { regressionStatistics.a, regressionStatistics.b };
}

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From source file:com.compomics.util.experiment.identification.psm_scoring.psm_scores.HyperScore.java

/**
 * Returns the interpolation of a list of hyperscores using a linear
 * interpolation of the form result = a * log(score) + b. If the score is
 * null, returns the number of hyperscores. The value at every score is
 * returned in a map./*from w  w w  .  j  av a 2s .  c o  m*/
 *
 * @param hyperScores a list of hyperscores
 * @param a the slope of the interpolation
 * @param b the offset of the interpolation
 *
 * @return the interpolation for every score in a map.
 */
public HashMap<Double, Double> getInterpolation(ArrayList<Double> hyperScores, Double a, Double b) {
    HashMap<Double, Double> result = new HashMap<Double, Double>();
    for (Double hyperScore : hyperScores) {
        if (!result.containsKey(hyperScore)) {
            if (hyperScore > 0) {
                double logScore = FastMath.log10(hyperScore);
                double eValue = getInterpolation(logScore, a, b);
                result.put(hyperScore, eValue);
            } else {
                Double eValue = new Double(hyperScores.size());
                result.put(hyperScore, eValue);
            }
        }
    }
    return result;
}

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