Example usage for org.apache.commons.math3.linear RealVector getDimension

List of usage examples for org.apache.commons.math3.linear RealVector getDimension

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Introduction

In this page you can find the example usage for org.apache.commons.math3.linear RealVector getDimension.

Prototype

public abstract int getDimension();

Source Link

Document

Returns the size of the vector.

Usage

From source file:org.knime.knip.core.util.ApacheMathTools.java

/**
 * Creates a numDims dimensions image where all dimensions d<numDims are of size 1 and the last dimensions contains
 * the vector./*from   ww w .  j a v a2 s  . c om*/
 * 
 * @param <R>
 * @param ar
 * @param type
 * @param numDims number of dimensions
 * @return
 */
public static <R extends RealType<R>> Img<R> vectorToImage(final RealVector ar, final R type, final int numDims,
        final ImgFactory<R> fac) {
    final long[] dims = new long[numDims];

    for (int i = 0; i < (dims.length - 1); i++) {
        dims[i] = 1;
    }
    dims[dims.length - 1] = ar.getDimension();
    final Img<R> res = fac.create(dims, type);
    final Cursor<R> c = res.cursor();
    while (c.hasNext()) {
        c.fwd();
        c.get().setReal(ar.getEntry(c.getIntPosition(numDims - 1)));
    }

    return res;
}

From source file:org.lambda3.indra.core.function.AlphaSkewRelatednessFunction.java

@Override
public double sim(RealVector r1, RealVector r2, boolean sparse) {
    if (r1.getDimension() != r2.getDimension()) {
        return 0;
    }//from w ww .ja v a2  s .  c  om

    double alpha = 0.99;
    double divergence = 0.0;

    for (int i = 0; i < r1.getDimension(); ++i) {
        if (r1.getEntry(i) > 0.0 && r2.getEntry(i) > 0.0) {
            divergence += r1.getEntry(i)
                    * Math.log(r1.getEntry(i) / ((1 - alpha) * r1.getEntry(i) + alpha * r2.getEntry(i)));
        }
    }

    double result = (1 - (divergence / Math.sqrt(2 * Math.log(2))));
    return Math.abs(result);
}

From source file:org.lambda3.indra.core.function.ChebyshevRelatednessFunction.java

@Override
public double sim(RealVector r1, RealVector r2, boolean sparse) {
    if (r1.getDimension() != r2.getDimension()) {
        return 0;
    }//from w  w  w.  j  a v a2s .  c o  m

    double max = 0;
    double tmp;

    for (int i = 0; i < r1.getDimension(); ++i) {
        tmp = Math.abs((r1.getEntry(i) - r2.getEntry(i)));
        max = (tmp > max ? tmp : max);
    }

    double result = 1 / (1 + (max == Double.NaN ? 0 : max));
    return Math.abs(result);
}

From source file:org.lambda3.indra.core.function.CityBlockRelatednessFunction.java

@Override
public double sim(RealVector r1, RealVector r2, boolean sparse) {
    if (r1.getDimension() != r2.getDimension()) {
        return 0;
    }/*from  w ww . j av  a 2 s .c  o m*/

    double sum = 0.0;

    for (int i = 0; i < r1.getDimension(); ++i) {
        sum += Math.abs((r1.getEntry(i) - r2.getEntry(i)));
    }

    double result = 1 / (1 + (sum == Double.NaN ? 0 : sum));
    return Math.abs(result);
}

From source file:org.lambda3.indra.core.function.DiceRelatednessFunction.java

@Override
public double sim(RealVector r1, RealVector r2, boolean sparse) {
    if (r1.getDimension() != r2.getDimension()) {
        return 0;
    }/*from   w w w .ja va 2 s  .c om*/

    double min = 0.0;
    double sum = 0.0;

    for (int i = 0; i < r1.getDimension(); ++i) {
        if (r1.getEntry(i) > r2.getEntry(i)) {
            min += r2.getEntry(i);
        } else {
            min += r1.getEntry(i);
        }
        sum += r1.getEntry(i) + r2.getEntry(i);
    }

    if (sum == 0) {
        return 0;
    }

    double result = 2 * min / sum;
    return Math.abs(result);
}

From source file:org.lambda3.indra.core.function.Jaccard2RelatednessFunction.java

@Override
public double sim(RealVector r1, RealVector r2, boolean sparse) {
    if (r1.getDimension() != r2.getDimension()) {
        return 0;
    }/*from   ww  w . j av a 2  s  .  com*/

    double min = 0.0;
    double max = 0.0;

    for (int i = 0; i < r1.getDimension(); ++i) {
        if (r1.getEntry(i) > r2.getEntry(i)) {
            min += r2.getEntry(i);
            max += r1.getEntry(i);
        } else {
            min += r1.getEntry(i);
            max += r2.getEntry(i);
        }
    }

    if (max == 0) {
        return 0;
    }

    return Math.abs(min / max);
}

From source file:org.lambda3.indra.core.function.JensenShannonRelatednessFunction.java

@Override
public double sim(RealVector r1, RealVector r2, boolean sparse) {
    if (r1.getDimension() != r2.getDimension()) {
        return 0;
    }//from  w ww  .j av  a 2 s.c  o m

    double divergence = 0.0;
    double avr = 0.0;

    for (int i = 0; i < r1.getDimension(); ++i) {
        avr = (r1.getEntry(i) + r2.getEntry(i)) / 2;

        if (r1.getEntry(i) > 0.0 && avr > 0.0) {
            divergence += r1.getEntry(i) * Math.log(r1.getEntry(i) / avr);
        }
    }
    for (int i = 0; i < r2.getDimension(); ++i) {
        avr = (r1.getEntry(i) + r2.getEntry(i)) / 2;

        if (r2.getEntry(i) > 0.0 && avr > 0.0) {
            divergence += r1.getEntry(i) * Math.log(r2.getEntry(i) / avr);
        }
    }

    double result = 1 - (divergence / (2 * Math.sqrt(2 * Math.log(2))));
    return Math.abs(result);
}

From source file:org.lambda3.indra.core.impl.AlphaSkewClient.java

@Override
protected double sim(RealVector r1, RealVector r2, boolean sparse) {
    if (r1.getDimension() != r2.getDimension()) {
        return 0;
    }/*from  w ww.ja  v a2  s. com*/

    double alpha = 0.99;
    double divergence = 0.0;

    for (int i = 0; i < r1.getDimension(); ++i) {
        if (r1.getEntry(i) > 0.0 && r2.getEntry(i) > 0.0) {
            divergence += r1.getEntry(i)
                    * Math.log(r1.getEntry(i) / ((1 - alpha) * r1.getEntry(i) + alpha * r2.getEntry(i)));
        }
    }

    double result = (1 - (divergence / Math.sqrt(2 * Math.log(2))));
    return Math.abs(result);
}

From source file:org.lambda3.indra.core.impl.ChebyshevClient.java

@Override
protected double sim(RealVector r1, RealVector r2, boolean sparse) {
    if (r1.getDimension() != r2.getDimension()) {
        return 0;
    }//from   w  w w .j  a va 2  s.com

    double max = 0;
    double tmp;

    for (int i = 0; i < r1.getDimension(); ++i) {
        tmp = Math.abs((r1.getEntry(i) - r2.getEntry(i)));
        max = (tmp > max ? tmp : max);
    }

    double result = 1 / (1 + (max == Double.NaN ? 0 : max));
    return Math.abs(result);
}

From source file:org.lambda3.indra.core.impl.CityBlockClient.java

@Override
protected double sim(RealVector r1, RealVector r2, boolean sparse) {
    if (r1.getDimension() != r2.getDimension()) {
        return 0;
    }/*from  w w w .j a v  a2  s .c  o m*/

    double sum = 0.0;

    for (int i = 0; i < r1.getDimension(); ++i) {
        sum += Math.abs((r1.getEntry(i) - r2.getEntry(i)));
    }

    double result = 1 / (1 + (sum == Double.NaN ? 0 : sum));
    return Math.abs(result);
}