halfdan/eva2
1
0
Fork 0
Code Issues Pull Requests Projects Releases Wiki Activity

Fix broken Jama references and move some methods to Mathematics class.

Browse Source
This commit is contained in:
Fabian Becker 2015-12-10 22:34:17 +01:00
parent 49e1d53bd1
commit c0bcb6fc95
4 changed files with 67 additions and 15 deletions
Show Stats Download Patch File Download Diff File Expand all files Collapse all files

12
src/main/java/eva2/optimization/operator/mutation/MutateESCovarianceMatrixAdaptionPlus.java
View File

@ -4,7 +4,7 @@ import eva2.optimization.individuals.AbstractEAIndividual;
import eva2.optimization.individuals.InterfaceESIndividual;
import eva2.optimization.population.Population;
import eva2.problems.InterfaceOptimizationProblem;
import Jama.Matrix;
import eva2.tools.math.Mathematics;
import eva2.util.annotation.Description;
@Description("This is the CMA mutation according to Igel,Hansen,Roth 2007")
@ -113,12 +113,12 @@ public class MutateESCovarianceMatrixAdaptionPlus extends
}
if (psuccess < pthresh) {
C = C.multi((1.0 - cov));
C.plusEquals(Matrix.outer(pathS, pathS).multi(cov));
C = C.times((1.0 - cov));
C.plusEquals(Mathematics.outer(pathS, pathS).times(cov));
} else {
C = C.multi((1.0 - cov)).plus(
(Matrix.outer(pathS, pathS).plus(
C.multi(c * (2.0 - c))).multi(cov)));
C = C.times((1.0 - cov)).plus(
(Mathematics.outer(pathS, pathS).plus(
C.times(c * (2.0 - c))).times(cov)));
}
}

7
src/main/java/eva2/optimization/operator/mutation/MutateESRankMuCMA.java
View File

@ -727,13 +727,10 @@ public class MutateESRankMuCMA implements InterfaceAdaptOperatorGenerational, In
* @return
*/
public boolean testNoChangeAddingDevAxis(Population pop, double d, int gen) {
// if all(xmean == xmean + 0.1*sigma*BD(:,1+floor(mod(countiter,N))))
// i = 1+floor(mod(countiter,N));
// stopflag(end+1) = {'warnnoeffectaxis'};
CMAParamSet params = (CMAParamSet) pop.getData(cmaParamsKey);
int dim = params.meanX.length;
int k = gen % dim;
double[] ev_k = params.mB.getColumn(k);
double[] ev_k = Mathematics.getColumn(params.mB, k);
Mathematics.svMult(Math.sqrt(params.eigenvalues[k]), ev_k, ev_k); // this is now e_k*v_k = BD(:,...)
int i = 0;
@ -771,7 +768,7 @@ public class MutateESRankMuCMA implements InterfaceAdaptOperatorGenerational, In
*/
public boolean testCCondition(Population pop, double d) {
CMAParamSet params = (CMAParamSet) pop.getData(cmaParamsKey);
Pair<Double, Double> minMax = params.mC.getMinMaxDiag();
Pair<Double, Double> minMax = Mathematics.getMinMaxDiag(params.mC);
return (minMax.head <= 0) || (minMax.tail >= d);
}

5
src/main/java/eva2/optimization/population/Population.java
View File

@ -1,5 +1,6 @@
package eva2.optimization.population;
import Jama.Matrix;
import eva2.gui.editor.GenericObjectEditor;
import eva2.optimization.individuals.*;
import eva2.optimization.operator.distancemetric.EuclideanMetric;
@ -10,7 +11,6 @@ import eva2.optimization.operator.selection.probability.AbstractSelProb;
import eva2.tools.EVAERROR;
import eva2.tools.Pair;
import eva2.tools.Serializer;
import Jama.Matrix;
import eva2.tools.math.Mathematics;
import eva2.tools.math.RNG;
import eva2.tools.math.StatisticUtils;
@ -501,9 +501,10 @@ public class Population extends ArrayList<AbstractEAIndividual> implements Popul
if (template instanceof InterfaceDataTypeDouble) {
double[][] range = ((InterfaceDataTypeDouble) template).getDoubleRange();
Matrix rlhM = StatisticUtils.rlh(pop.size(), range, true);
for (int i = 0; i < pop.size(); i++) {
AbstractEAIndividual tmpIndy = pop.getEAIndividual(i);
((InterfaceDataTypeDouble) tmpIndy).setDoubleGenotype(rlhM.getRowShallow(i));
((InterfaceDataTypeDouble) tmpIndy).setDoubleGenotype(rlhM.getArray()[i]);
}
} else {
System.err.println("Error: data type double required for Population.createUniformSampling");

58
src/main/java/eva2/tools/math/Mathematics.java
View File

@ -1,8 +1,9 @@
package eva2.tools.math;
import Jama.Matrix;
import eva2.optimization.tools.DoubleArrayComparator;
import eva2.tools.EVAERROR;
import Jama.Matrix;
import eva2.tools.Pair;
import eva2.tools.math.interpolation.BasicDataSet;
import eva2.tools.math.interpolation.InterpolationException;
import eva2.tools.math.interpolation.SplineInterpolation;
@ -262,6 +263,59 @@ public final class Mathematics {
return A;
}
/**
* Given two vectors, ``[a0, a1, ..., aM]`` and ``[b0, b1, ..., bN]``,
* the outer product becomes::
* <p>
* [[a0*b0 a0*b1 ... a0*bN ]
* [a1*b0 .
* [ ... .
* [aM*b0 aM*bN ]]
*/
public static Matrix outer(double[] a, double[] b) {
double[][] M = new double[a.length][b.length];
for (int i = 0; i < a.length; i++) {
for (int j = 0; j < b.length; j++) {
M[i][j] = a[i] * b[j];
}
}
return new Matrix(M);
}
/**
* Return the minimum and maximum value on the diagonal
* as a pair.
*
* @return
*/
public static Pair<Double, Double> getMinMaxDiag(Matrix m) {
if (m.getRowDimension() < 1 || m.getColumnDimension() < 1) {
return null;
}
double v = m.get(0, 0);
Pair<Double, Double> ret = new Pair<>(v, v);
for (int i = 1; i < Math.min(m.getRowDimension(), m.getColumnDimension()); i++) {
v = m.get(i, i);
ret.head = Math.min(ret.head, v);
ret.tail = Math.max(ret.tail, v);
}
return ret;
}
/**
* Copy a column from the matrix.
*
* @return Matrix elements packed in a one-dimensional array by columns.
*/
public static double[] getColumn(Matrix m, int k) {
double[] vals = new double[m.getRowDimension()];
for (int i = 0; i < m.getRowDimension(); i++) {
vals[i] = m.get(i, k);
}
return vals;
}
/**
* Return a matrix A which performs the rotation of vec to (1,0,0,...0) if
* forward is true, else return a matrix B which performs the reverted
@ -277,7 +331,7 @@ public final class Mathematics {
.getRowDimension());
Matrix z = (Matrix) vec.clone();
z.multi(1. / z.norm2()); // normalize
z.times(1. / z.norm2()); // normalize
for (int i = 1; i < vec.getRowDimension(); i++) {
double w = Math.atan2(z.get(i, 0), z.get(0, 0));// calc angle