Example usage for org.apache.commons.math3.linear ArrayRealVector map

Introduction

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

Prototype

@Override
public ArrayRealVector map(UnivariateFunction function) 

Source Link

Usage

From source file:edu.utexas.cs.tactex.subscriptionspredictors.LWRCustOldAppache.java

/**
  * LWR prediction//from   www  . j  a va  2 s  .c o  m
  * 
  * @param X
  * @param Y
  * @param x0
  * @param tau
  * @return
  */
public Double LWRPredict(ArrayRealVector X, ArrayRealVector Y, double x0, final double tau) {
    ArrayRealVector X0 = new ArrayRealVector(X.getDimension(), x0);
    ArrayRealVector delta = X.subtract(X0);
    ArrayRealVector sqDists = delta.ebeMultiply(delta);
    UnivariateFunction expTau = new UnivariateFunction() {
        @Override
        public double value(double arg0) {
            //log.info(" cp univariate tau " + tau);
            return Math.pow(Math.E, -arg0 / (2 * tau));
        }
    };
    ArrayRealVector W = sqDists.map(expTau);
    double Xt_W_X = X.dotProduct(W.ebeMultiply(X));
    if (Xt_W_X == 0.0) {
        log.error(" cp LWR cannot predict - 0 denominator returning NULL");
        log.error("Xcv is " + X.toString());
        log.error("Ycv is " + Y.toString());
        log.error("x0 is " + x0);
        return null; // <==== NOTE: a caller must be prepared for it
    }
    double theta = (1.0 / Xt_W_X) * X.ebeMultiply(W).dotProduct(Y);

    return theta * x0;
}

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