Example usage for org.apache.commons.math3.util FastMath exp

Introduction

In this page you can find the example usage for org.apache.commons.math3.util FastMath exp.

Prototype

public static double exp(double x)

Source Link

Document

Exponential function.

Usage

From source file:com.vsthost.rnd.commons.math.ext.linear.ExtMath.java

/**
 * Returns a fast, nearly accurate implementation of exponential function.
 *
 * <p>Note that the implementation is not yet settled. There are faster or more accurate ways to do it.</p>
 *
 * @param x A double value to be provided
 * @return The e^x as a double value.//from  w  w w .j a  v  a2  s . c  o  m
 */
public static double fastExp(double x) {
    return FastMath.exp(x);

    // Below, we have other ways of achieving this:
    //
    // Method 1:
    // =========
    // x = 1d + x / 256d;
    // x *= x; x *= x; x *= x; x *= x;
    // x *= x; x *= x; x *= x; x *= x;
    // return x;
    //
    // Method 2:
    // =========
    //
    // return Math.exp(x);
    //
    // Method 3:
    // =========
    //
    // return Double.longBitsToDouble(((long) (1512775 * val + 1072632447)) << 32);
    //
    // Method 4:
    // =========
    //
    // return Double.longBitsToDouble(((long) (1512775 * val + (1072693248 - 60801))) << 32);
}

From source file:edu.emory.mathcs.nlp.learning.util.MLUtils.java

/** Transform the scores into softmax regression. */
static public void softmax(float[] scores) {
    float sum = 0;

    for (int i = 0; i < scores.length; i++) {
        scores[i] = (float) FastMath.exp(scores[i]);
        sum += scores[i];//from   w  w  w.  j  a  v a 2s  . com
    }

    for (int i = 0; i < scores.length; i++)
        scores[i] /= sum;
}

From source file:jmb.jcortex.mapfunctions.SigmoidActivationFunction.java

@Override
public DoubleUnaryOperator getFunction() {
    return x -> 1 / (1 + FastMath.exp(-x));
}

From source file:gdsc.smlm.model.AiryPattern.java

/**
 * Calculate the intensity of the AiryPattern at distance x from the centre using a Gaussian approximation
 * /*ww w .j  av  a  2s  .  c o  m*/
 * @param x
 * @return The intensity
 */
public static double intensityGaussian(double x) {
    if (x == 0)
        return 1;
    x /= FACTOR;
    return FastMath.exp(-0.5 * (x * x));
}

From source file:com.gedaeusp.domain.Exponential.java

public static double value(double t, double v0, double a, double tau) {
    return v0 + a * FastMath.exp(-t / tau);
}

From source file:edu.emory.mathcs.nlp.deeplearning.activation.SoftmaxFunction.java

@Override
public void transform(double[] scores) {
    double sum = 0;

    for (int i = 0; i < scores.length; i++) {
        scores[i] = FastMath.exp(scores[i]);
        sum += scores[i];// w  ww  .java  2s .c  om
    }

    for (int i = 0; i < scores.length; i++)
        scores[i] /= sum;
}

From source file:com.gedaeusp.domain.Biexponential.java

public static double value(double t, double v0, double a1, double a2, double tau1, double tau2) {
    return v0 + a1 * FastMath.exp(-t / tau1) + a2 * FastMath.exp(-t / tau2);
}

From source file:edu.emory.mathcs.nlp.learning.activation.SoftmaxFunction.java

@Override
public void apply(float[] scores) {
    float sum = 0, max = DSUtils.max(scores);
    max = 0;//from www.  j a  va2s .com

    for (int i = 0; i < scores.length; i++) {
        scores[i] = (float) FastMath.exp(scores[i] - max);
        sum += scores[i];
    }

    sum = 1f / (1 + sum);

    for (int i = 0; i < scores.length; i++)
        scores[i] *= sum;
}

From source file:com.davidbracewell.math.functions.LogLoss.java

@Override
public double calculate(double n1, double n2) {
    return FastMath.log(1 + FastMath.exp(-(n1 * n2)));
}

From source file:edu.emory.mathcs.nlp.learning.normalization.SoftmaxFunction.java

@Override
public void apply(float[] scores) {
    float sum = 0, max = DSUtils.max(scores);
    max = 0;//from ww w.j  ava  2  s.co  m

    for (int i = 0; i < scores.length; i++) {
        scores[i] = (float) FastMath.exp(scores[i] - max);
        sum += scores[i];
    }

    if (sum != 0) {
        sum = 1f / sum;
    }

    for (int i = 0; i < scores.length; i++)
        scores[i] *= sum;
}