@Override
protected MatrixStore<Double> extractSolution() {
final ExpressionsBasedModel tmpModel = this.getModel();
if (tmpModel != null) {
final List<Variable> tmpFreeVariables = tmpModel.getFreeVariables();
final Set<Index> tmpFixedVariables = tmpModel.getFixedVariables();
final PrimitiveDenseStore retVal =
PrimitiveDenseStore.FACTORY.makeZero(
tmpFixedVariables.size() + tmpFreeVariables.size(), 1);
for (final Index tmpVariable : tmpFixedVariables) {
retVal.set(
tmpVariable.index, 0, tmpModel.getVariable(tmpVariable.index).getValue().doubleValue());
}
final MatrixStore<Double> tmpSolutionX = this.getSolutionX();
for (int i = 0; i < tmpFreeVariables.size(); i++) {
final Variable tmpVariable = tmpFreeVariables.get(i);
final int tmpIndexOf = tmpModel.indexOf(tmpVariable);
retVal.set(tmpIndexOf, 0, tmpSolutionX.doubleValue(i));
}
return retVal;
} else {
return this.getSolutionX().copy();
}
}
@Override
protected boolean validate() {
boolean retVal = true;
this.setState(State.VALID);
try {
final MatrixStore<Double> tmpQ = this.getQ();
final Cholesky<Double> tmpCholesky = CholeskyDecomposition.makePrimitive();
tmpCholesky.compute(tmpQ, true);
if (!tmpCholesky.isSPD()) {
// Not positive definite. Check if at least positive semidefinite.
final Eigenvalue<Double> tmpEigenvalue = EigenvalueDecomposition.makePrimitive(true);
tmpEigenvalue.compute(tmpQ, true);
final MatrixStore<Double> tmpD = tmpEigenvalue.getD();
for (int ij = 0; retVal && (ij < tmpD.getMinDim()); ij++) {
if (tmpD.doubleValue(ij, ij) < ZERO) {
retVal = false;
this.setState(State.INVALID);
}
}
}
if (retVal) {
// Q ok, check AE
// final MatrixStore<Double> tmpAE = this.getAE();
//
// final LU<Double> tmpLU = LUDecomposition.makePrimitive();
// tmpLU.compute(tmpAE);
//
// if (tmpLU.getRank() != tmpAE.getRowDim()) {
// retVal = false;
// this.setState(State.INVALID);
// }
}
} catch (final Exception ex) {
retVal = false;
this.setState(State.FAILED);
}
return retVal;
}
private QuadraticSolver buildIterationSolver(final boolean addSmallDiagonal) {
MatrixStore<Double> tmpQ = this.getQ();
final MatrixStore<Double> tmpC = this.getC();
if (addSmallDiagonal) {
final PhysicalStore<Double> tmpCopyQ = tmpQ.copy();
final double tmpLargest = tmpCopyQ.aggregateAll(Aggregator.LARGEST);
final double tmpRelativelySmall = MACHINE_DOUBLE_ERROR * tmpLargest;
final double tmpPracticalLimit = MACHINE_DOUBLE_ERROR + IS_ZERO;
final double tmpSmallToAdd = Math.max(tmpRelativelySmall, tmpPracticalLimit);
final UnaryFunction<Double> tmpFunc = ADD.second(tmpSmallToAdd);
tmpCopyQ.modifyDiagonal(0, 0, tmpFunc);
tmpQ = tmpCopyQ;
}
if (this.hasEqualityConstraints()) {
final MatrixStore<Double> tmpAE = this.getAE();
final MatrixStore<Double> tmpBE = this.getBE();
final int tmpZeroSize = tmpAE.getRowDim();
final MatrixStore<Double> tmpUpperLeftAE = tmpQ;
final MatrixStore<Double> tmpUpperRightAE = tmpAE.builder().transpose().build();
final MatrixStore<Double> tmpLowerLefAE = tmpAE;
final MatrixStore<Double> tmpLowerRightAE = ZeroStore.makePrimitive(tmpZeroSize, tmpZeroSize);
final MatrixStore<Double> tmpSubAE =
new AboveBelowStore<Double>(
new LeftRightStore<Double>(tmpUpperLeftAE, tmpUpperRightAE),
new LeftRightStore<Double>(tmpLowerLefAE, tmpLowerRightAE));
final MatrixStore<Double> tmpUpperBE = tmpC;
final MatrixStore<Double> tmpLowerBE = tmpBE;
final MatrixStore<Double> tmpSubBE = new AboveBelowStore<Double>(tmpUpperBE, tmpLowerBE);
return new Builder().equalities(tmpSubAE, tmpSubBE).build(options);
} else {
return new Builder().equalities(tmpQ, tmpC).build(options);
}
}
private void extractSolution(final QuadraticSolver aSolver) {
final MatrixStore<Double> tmpSolutionX = aSolver.getSolutionX();
final int tmpCountVariables = this.countVariables();
final int tmpCountEqualityConstraints = this.countEqualityConstraints();
for (int i = 0; i < tmpCountVariables; i++) {
this.setX(i, tmpSolutionX.doubleValue(i));
}
for (int i = 0; i < tmpCountEqualityConstraints; i++) {
this.setLE(i, tmpSolutionX.doubleValue(tmpCountVariables + i));
}
}
