Java Code Examples for org.apache.commons.math3.exception.util.LocalizedFormats#NUMBER_OF_INTERPOLATION_POINTS
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org.apache.commons.math3.exception.util.LocalizedFormats#NUMBER_OF_INTERPOLATION_POINTS .
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Example 1
| Source File: BOBYQAOptimizer.java From astor with GNU General Public License v2.0 | 4 votes |
|
/**
* Performs validity checks.
*
* @param lowerBound Lower bounds (constraints) of the objective variables.
* @param upperBound Upperer bounds (constraints) of the objective variables.
*/
private void setup(double[] lowerBound,
double[] upperBound) {
printMethod(); // XXX
double[] init = getStartPoint();
final int dimension = init.length;
// Check problem dimension.
if (dimension < MINIMUM_PROBLEM_DIMENSION) {
throw new NumberIsTooSmallException(dimension, MINIMUM_PROBLEM_DIMENSION, true);
}
// Check number of interpolation points.
final int[] nPointsInterval = { dimension + 2, (dimension + 2) * (dimension + 1) / 2 };
if (numberOfInterpolationPoints < nPointsInterval[0] ||
numberOfInterpolationPoints > nPointsInterval[1]) {
throw new OutOfRangeException(LocalizedFormats.NUMBER_OF_INTERPOLATION_POINTS,
numberOfInterpolationPoints,
nPointsInterval[0],
nPointsInterval[1]);
}
// Initialize bound differences.
boundDifference = new double[dimension];
double requiredMinDiff = 2 * initialTrustRegionRadius;
double minDiff = Double.POSITIVE_INFINITY;
for (int i = 0; i < dimension; i++) {
boundDifference[i] = upperBound[i] - lowerBound[i];
minDiff = FastMath.min(minDiff, boundDifference[i]);
}
if (minDiff < requiredMinDiff) {
initialTrustRegionRadius = minDiff / 3.0;
}
// Initialize the data structures used by the "bobyqa" method.
bMatrix = new Array2DRowRealMatrix(dimension + numberOfInterpolationPoints,
dimension);
zMatrix = new Array2DRowRealMatrix(numberOfInterpolationPoints,
numberOfInterpolationPoints - dimension - 1);
interpolationPoints = new Array2DRowRealMatrix(numberOfInterpolationPoints,
dimension);
originShift = new ArrayRealVector(dimension);
fAtInterpolationPoints = new ArrayRealVector(numberOfInterpolationPoints);
trustRegionCenterOffset = new ArrayRealVector(dimension);
gradientAtTrustRegionCenter = new ArrayRealVector(dimension);
lowerDifference = new ArrayRealVector(dimension);
upperDifference = new ArrayRealVector(dimension);
modelSecondDerivativesParameters = new ArrayRealVector(numberOfInterpolationPoints);
newPoint = new ArrayRealVector(dimension);
alternativeNewPoint = new ArrayRealVector(dimension);
trialStepPoint = new ArrayRealVector(dimension);
lagrangeValuesAtNewPoint = new ArrayRealVector(dimension + numberOfInterpolationPoints);
modelSecondDerivativesValues = new ArrayRealVector(dimension * (dimension + 1) / 2);
}
Example 2
| Source File: BOBYQAOptimizer.java From astor with GNU General Public License v2.0 | 4 votes |
|
/**
* Performs validity checks.
*
* @param lowerBound Lower bounds (constraints) of the objective variables.
* @param upperBound Upperer bounds (constraints) of the objective variables.
*/
private void setup(double[] lowerBound,
double[] upperBound) {
printMethod(); // XXX
double[] init = getStartPoint();
final int dimension = init.length;
// Check problem dimension.
if (dimension < MINIMUM_PROBLEM_DIMENSION) {
throw new NumberIsTooSmallException(dimension, MINIMUM_PROBLEM_DIMENSION, true);
}
// Check number of interpolation points.
final int[] nPointsInterval = { dimension + 2, (dimension + 2) * (dimension + 1) / 2 };
if (numberOfInterpolationPoints < nPointsInterval[0] ||
numberOfInterpolationPoints > nPointsInterval[1]) {
throw new OutOfRangeException(LocalizedFormats.NUMBER_OF_INTERPOLATION_POINTS,
numberOfInterpolationPoints,
nPointsInterval[0],
nPointsInterval[1]);
}
// Initialize bound differences.
boundDifference = new double[dimension];
double requiredMinDiff = 2 * initialTrustRegionRadius;
double minDiff = Double.POSITIVE_INFINITY;
for (int i = 0; i < dimension; i++) {
boundDifference[i] = upperBound[i] - lowerBound[i];
minDiff = FastMath.min(minDiff, boundDifference[i]);
}
if (minDiff < requiredMinDiff) {
initialTrustRegionRadius = minDiff / 3.0;
}
// Initialize the data structures used by the "bobyqa" method.
bMatrix = new Array2DRowRealMatrix(dimension + numberOfInterpolationPoints,
dimension);
zMatrix = new Array2DRowRealMatrix(numberOfInterpolationPoints,
numberOfInterpolationPoints - dimension - 1);
interpolationPoints = new Array2DRowRealMatrix(numberOfInterpolationPoints,
dimension);
originShift = new ArrayRealVector(dimension);
fAtInterpolationPoints = new ArrayRealVector(numberOfInterpolationPoints);
trustRegionCenterOffset = new ArrayRealVector(dimension);
gradientAtTrustRegionCenter = new ArrayRealVector(dimension);
lowerDifference = new ArrayRealVector(dimension);
upperDifference = new ArrayRealVector(dimension);
modelSecondDerivativesParameters = new ArrayRealVector(numberOfInterpolationPoints);
newPoint = new ArrayRealVector(dimension);
alternativeNewPoint = new ArrayRealVector(dimension);
trialStepPoint = new ArrayRealVector(dimension);
lagrangeValuesAtNewPoint = new ArrayRealVector(dimension + numberOfInterpolationPoints);
modelSecondDerivativesValues = new ArrayRealVector(dimension * (dimension + 1) / 2);
}
Example 3
| Source File: BOBYQAOptimizer.java From astor with GNU General Public License v2.0 | 4 votes |
|
/**
* Performs validity checks.
*
* @param lowerBound Lower bounds (constraints) of the objective variables.
* @param upperBound Upperer bounds (constraints) of the objective variables.
*/
private void setup(double[] lowerBound,
double[] upperBound) {
printMethod(); // XXX
double[] init = getStartPoint();
final int dimension = init.length;
// Check problem dimension.
if (dimension < MINIMUM_PROBLEM_DIMENSION) {
throw new NumberIsTooSmallException(dimension, MINIMUM_PROBLEM_DIMENSION, true);
}
// Check number of interpolation points.
final int[] nPointsInterval = { dimension + 2, (dimension + 2) * (dimension + 1) / 2 };
if (numberOfInterpolationPoints < nPointsInterval[0] ||
numberOfInterpolationPoints > nPointsInterval[1]) {
throw new OutOfRangeException(LocalizedFormats.NUMBER_OF_INTERPOLATION_POINTS,
numberOfInterpolationPoints,
nPointsInterval[0],
nPointsInterval[1]);
}
// Initialize bound differences.
boundDifference = new double[dimension];
double requiredMinDiff = 2 * initialTrustRegionRadius;
double minDiff = Double.POSITIVE_INFINITY;
for (int i = 0; i < dimension; i++) {
boundDifference[i] = upperBound[i] - lowerBound[i];
minDiff = Math.min(minDiff, boundDifference[i]);
}
if (minDiff < requiredMinDiff) {
initialTrustRegionRadius = minDiff / 3.0;
}
// Initialize the data structures used by the "bobyqa" method.
bMatrix = new Array2DRowRealMatrix(dimension + numberOfInterpolationPoints,
dimension);
zMatrix = new Array2DRowRealMatrix(numberOfInterpolationPoints,
numberOfInterpolationPoints - dimension - 1);
interpolationPoints = new Array2DRowRealMatrix(numberOfInterpolationPoints,
dimension);
originShift = new ArrayRealVector(dimension);
fAtInterpolationPoints = new ArrayRealVector(numberOfInterpolationPoints);
trustRegionCenterOffset = new ArrayRealVector(dimension);
gradientAtTrustRegionCenter = new ArrayRealVector(dimension);
lowerDifference = new ArrayRealVector(dimension);
upperDifference = new ArrayRealVector(dimension);
modelSecondDerivativesParameters = new ArrayRealVector(numberOfInterpolationPoints);
newPoint = new ArrayRealVector(dimension);
alternativeNewPoint = new ArrayRealVector(dimension);
trialStepPoint = new ArrayRealVector(dimension);
lagrangeValuesAtNewPoint = new ArrayRealVector(dimension + numberOfInterpolationPoints);
modelSecondDerivativesValues = new ArrayRealVector(dimension * (dimension + 1) / 2);
}
Example 4
| Source File: BOBYQAOptimizer.java From astor with GNU General Public License v2.0 | 4 votes |
|
/**
* Performs validity checks.
*
* @param lowerBound Lower bounds (constraints) of the objective variables.
* @param upperBound Upperer bounds (constraints) of the objective variables.
*/
private void setup(double[] lowerBound,
double[] upperBound) {
printMethod(); // XXX
double[] init = getStartPoint();
final int dimension = init.length;
// Check problem dimension.
if (dimension < MINIMUM_PROBLEM_DIMENSION) {
throw new NumberIsTooSmallException(dimension, MINIMUM_PROBLEM_DIMENSION, true);
}
// Check number of interpolation points.
final int[] nPointsInterval = { dimension + 2, (dimension + 2) * (dimension + 1) / 2 };
if (numberOfInterpolationPoints < nPointsInterval[0] ||
numberOfInterpolationPoints > nPointsInterval[1]) {
throw new OutOfRangeException(LocalizedFormats.NUMBER_OF_INTERPOLATION_POINTS,
numberOfInterpolationPoints,
nPointsInterval[0],
nPointsInterval[1]);
}
// Initialize bound differences.
boundDifference = new double[dimension];
double requiredMinDiff = 2 * initialTrustRegionRadius;
double minDiff = Double.POSITIVE_INFINITY;
for (int i = 0; i < dimension; i++) {
boundDifference[i] = upperBound[i] - lowerBound[i];
minDiff = Math.min(minDiff, boundDifference[i]);
}
if (minDiff < requiredMinDiff) {
initialTrustRegionRadius = minDiff / 3.0;
}
// Initialize the data structures used by the "bobyqa" method.
bMatrix = new Array2DRowRealMatrix(dimension + numberOfInterpolationPoints,
dimension);
zMatrix = new Array2DRowRealMatrix(numberOfInterpolationPoints,
numberOfInterpolationPoints - dimension - 1);
interpolationPoints = new Array2DRowRealMatrix(numberOfInterpolationPoints,
dimension);
originShift = new ArrayRealVector(dimension);
fAtInterpolationPoints = new ArrayRealVector(numberOfInterpolationPoints);
trustRegionCenterOffset = new ArrayRealVector(dimension);
gradientAtTrustRegionCenter = new ArrayRealVector(dimension);
lowerDifference = new ArrayRealVector(dimension);
upperDifference = new ArrayRealVector(dimension);
modelSecondDerivativesParameters = new ArrayRealVector(numberOfInterpolationPoints);
newPoint = new ArrayRealVector(dimension);
alternativeNewPoint = new ArrayRealVector(dimension);
trialStepPoint = new ArrayRealVector(dimension);
lagrangeValuesAtNewPoint = new ArrayRealVector(dimension + numberOfInterpolationPoints);
modelSecondDerivativesValues = new ArrayRealVector(dimension * (dimension + 1) / 2);
}
Example 5
| Source File: BOBYQAOptimizer.java From astor with GNU General Public License v2.0 | 4 votes |
|
/**
* Performs validity checks.
*
* @param lowerBound Lower bounds (constraints) of the objective variables.
* @param upperBound Upperer bounds (constraints) of the objective variables.
*/
private void setup(double[] lowerBound,
double[] upperBound) {
printMethod(); // XXX
double[] init = getStartPoint();
final int dimension = init.length;
// Check problem dimension.
if (dimension < MINIMUM_PROBLEM_DIMENSION) {
throw new NumberIsTooSmallException(dimension, MINIMUM_PROBLEM_DIMENSION, true);
}
// Check number of interpolation points.
final int[] nPointsInterval = { dimension + 2, (dimension + 2) * (dimension + 1) / 2 };
if (numberOfInterpolationPoints < nPointsInterval[0] ||
numberOfInterpolationPoints > nPointsInterval[1]) {
throw new OutOfRangeException(LocalizedFormats.NUMBER_OF_INTERPOLATION_POINTS,
numberOfInterpolationPoints,
nPointsInterval[0],
nPointsInterval[1]);
}
// Initialize bound differences.
boundDifference = new double[dimension];
double requiredMinDiff = 2 * initialTrustRegionRadius;
double minDiff = Double.POSITIVE_INFINITY;
for (int i = 0; i < dimension; i++) {
boundDifference[i] = upperBound[i] - lowerBound[i];
minDiff = Math.min(minDiff, boundDifference[i]);
}
if (minDiff < requiredMinDiff) {
initialTrustRegionRadius = minDiff / 3.0;
}
// Initialize the data structures used by the "bobyqa" method.
bMatrix = new Array2DRowRealMatrix(dimension + numberOfInterpolationPoints,
dimension);
zMatrix = new Array2DRowRealMatrix(numberOfInterpolationPoints,
numberOfInterpolationPoints - dimension - 1);
interpolationPoints = new Array2DRowRealMatrix(numberOfInterpolationPoints,
dimension);
originShift = new ArrayRealVector(dimension);
fAtInterpolationPoints = new ArrayRealVector(numberOfInterpolationPoints);
trustRegionCenterOffset = new ArrayRealVector(dimension);
gradientAtTrustRegionCenter = new ArrayRealVector(dimension);
lowerDifference = new ArrayRealVector(dimension);
upperDifference = new ArrayRealVector(dimension);
modelSecondDerivativesParameters = new ArrayRealVector(numberOfInterpolationPoints);
newPoint = new ArrayRealVector(dimension);
alternativeNewPoint = new ArrayRealVector(dimension);
trialStepPoint = new ArrayRealVector(dimension);
lagrangeValuesAtNewPoint = new ArrayRealVector(dimension + numberOfInterpolationPoints);
modelSecondDerivativesValues = new ArrayRealVector(dimension * (dimension + 1) / 2);
}
Example 6
| Source File: BOBYQAOptimizer.java From astor with GNU General Public License v2.0 | 4 votes |
|
/**
* Performs validity checks.
*
* @param lowerBound Lower bounds (constraints) of the objective variables.
* @param upperBound Upperer bounds (constraints) of the objective variables.
*/
private void setup(double[] lowerBound,
double[] upperBound) {
printMethod(); // XXX
double[] init = getStartPoint();
final int dimension = init.length;
// Check problem dimension.
if (dimension < MINIMUM_PROBLEM_DIMENSION) {
throw new NumberIsTooSmallException(dimension, MINIMUM_PROBLEM_DIMENSION, true);
}
// Check number of interpolation points.
final int[] nPointsInterval = { dimension + 2, (dimension + 2) * (dimension + 1) / 2 };
if (numberOfInterpolationPoints < nPointsInterval[0] ||
numberOfInterpolationPoints > nPointsInterval[1]) {
throw new OutOfRangeException(LocalizedFormats.NUMBER_OF_INTERPOLATION_POINTS,
numberOfInterpolationPoints,
nPointsInterval[0],
nPointsInterval[1]);
}
// Initialize bound differences.
boundDifference = new double[dimension];
double requiredMinDiff = 2 * initialTrustRegionRadius;
double minDiff = Double.POSITIVE_INFINITY;
for (int i = 0; i < dimension; i++) {
boundDifference[i] = upperBound[i] - lowerBound[i];
minDiff = Math.min(minDiff, boundDifference[i]);
}
if (minDiff < requiredMinDiff) {
initialTrustRegionRadius = minDiff / 3.0;
}
// Initialize the data structures used by the "bobyqa" method.
bMatrix = new Array2DRowRealMatrix(dimension + numberOfInterpolationPoints,
dimension);
zMatrix = new Array2DRowRealMatrix(numberOfInterpolationPoints,
numberOfInterpolationPoints - dimension - 1);
interpolationPoints = new Array2DRowRealMatrix(numberOfInterpolationPoints,
dimension);
originShift = new ArrayRealVector(dimension);
fAtInterpolationPoints = new ArrayRealVector(numberOfInterpolationPoints);
trustRegionCenterOffset = new ArrayRealVector(dimension);
gradientAtTrustRegionCenter = new ArrayRealVector(dimension);
lowerDifference = new ArrayRealVector(dimension);
upperDifference = new ArrayRealVector(dimension);
modelSecondDerivativesParameters = new ArrayRealVector(numberOfInterpolationPoints);
newPoint = new ArrayRealVector(dimension);
alternativeNewPoint = new ArrayRealVector(dimension);
trialStepPoint = new ArrayRealVector(dimension);
lagrangeValuesAtNewPoint = new ArrayRealVector(dimension + numberOfInterpolationPoints);
modelSecondDerivativesValues = new ArrayRealVector(dimension * (dimension + 1) / 2);
}
Example 7
| Source File: BOBYQAOptimizer.java From astor with GNU General Public License v2.0 | 4 votes |
|
/**
* Performs validity checks.
*
* @param lowerBound Lower bounds (constraints) of the objective variables.
* @param upperBound Upperer bounds (constraints) of the objective variables.
*/
private void setup(double[] lowerBound,
double[] upperBound) {
printMethod(); // XXX
double[] init = getStartPoint();
final int dimension = init.length;
// Check problem dimension.
if (dimension < MINIMUM_PROBLEM_DIMENSION) {
throw new NumberIsTooSmallException(dimension, MINIMUM_PROBLEM_DIMENSION, true);
}
// Check number of interpolation points.
final int[] nPointsInterval = { dimension + 2, (dimension + 2) * (dimension + 1) / 2 };
if (numberOfInterpolationPoints < nPointsInterval[0] ||
numberOfInterpolationPoints > nPointsInterval[1]) {
throw new OutOfRangeException(LocalizedFormats.NUMBER_OF_INTERPOLATION_POINTS,
numberOfInterpolationPoints,
nPointsInterval[0],
nPointsInterval[1]);
}
// Initialize bound differences.
boundDifference = new double[dimension];
double requiredMinDiff = 2 * initialTrustRegionRadius;
double minDiff = Double.POSITIVE_INFINITY;
for (int i = 0; i < dimension; i++) {
boundDifference[i] = upperBound[i] - lowerBound[i];
minDiff = Math.min(minDiff, boundDifference[i]);
}
if (minDiff < requiredMinDiff) {
initialTrustRegionRadius = minDiff / 3.0;
}
// Initialize the data structures used by the "bobyqa" method.
bMatrix = new Array2DRowRealMatrix(dimension + numberOfInterpolationPoints,
dimension);
zMatrix = new Array2DRowRealMatrix(numberOfInterpolationPoints,
numberOfInterpolationPoints - dimension - 1);
interpolationPoints = new Array2DRowRealMatrix(numberOfInterpolationPoints,
dimension);
originShift = new ArrayRealVector(dimension);
fAtInterpolationPoints = new ArrayRealVector(numberOfInterpolationPoints);
trustRegionCenterOffset = new ArrayRealVector(dimension);
gradientAtTrustRegionCenter = new ArrayRealVector(dimension);
lowerDifference = new ArrayRealVector(dimension);
upperDifference = new ArrayRealVector(dimension);
modelSecondDerivativesParameters = new ArrayRealVector(numberOfInterpolationPoints);
newPoint = new ArrayRealVector(dimension);
alternativeNewPoint = new ArrayRealVector(dimension);
trialStepPoint = new ArrayRealVector(dimension);
lagrangeValuesAtNewPoint = new ArrayRealVector(dimension + numberOfInterpolationPoints);
modelSecondDerivativesValues = new ArrayRealVector(dimension * (dimension + 1) / 2);
}
Example 8
| Source File: BOBYQAOptimizer.java From astor with GNU General Public License v2.0 | 4 votes |
|
/**
* Performs validity checks.
*
* @param lowerBound Lower bounds (constraints) of the objective variables.
* @param upperBound Upperer bounds (constraints) of the objective variables.
*/
private void setup(double[] lowerBound,
double[] upperBound) {
printMethod(); // XXX
double[] init = getStartPoint();
final int dimension = init.length;
// Check problem dimension.
if (dimension < MINIMUM_PROBLEM_DIMENSION) {
throw new NumberIsTooSmallException(dimension, MINIMUM_PROBLEM_DIMENSION, true);
}
// Check number of interpolation points.
final int[] nPointsInterval = { dimension + 2, (dimension + 2) * (dimension + 1) / 2 };
if (numberOfInterpolationPoints < nPointsInterval[0] ||
numberOfInterpolationPoints > nPointsInterval[1]) {
throw new OutOfRangeException(LocalizedFormats.NUMBER_OF_INTERPOLATION_POINTS,
numberOfInterpolationPoints,
nPointsInterval[0],
nPointsInterval[1]);
}
// Initialize bound differences.
boundDifference = new double[dimension];
double requiredMinDiff = 2 * initialTrustRegionRadius;
double minDiff = Double.POSITIVE_INFINITY;
for (int i = 0; i < dimension; i++) {
boundDifference[i] = upperBound[i] - lowerBound[i];
minDiff = Math.min(minDiff, boundDifference[i]);
}
if (minDiff < requiredMinDiff) {
initialTrustRegionRadius = minDiff / 3.0;
}
// Initialize the data structures used by the "bobyqa" method.
bMatrix = new Array2DRowRealMatrix(dimension + numberOfInterpolationPoints,
dimension);
zMatrix = new Array2DRowRealMatrix(numberOfInterpolationPoints,
numberOfInterpolationPoints - dimension - 1);
interpolationPoints = new Array2DRowRealMatrix(numberOfInterpolationPoints,
dimension);
originShift = new ArrayRealVector(dimension);
fAtInterpolationPoints = new ArrayRealVector(numberOfInterpolationPoints);
trustRegionCenterOffset = new ArrayRealVector(dimension);
gradientAtTrustRegionCenter = new ArrayRealVector(dimension);
lowerDifference = new ArrayRealVector(dimension);
upperDifference = new ArrayRealVector(dimension);
modelSecondDerivativesParameters = new ArrayRealVector(numberOfInterpolationPoints);
newPoint = new ArrayRealVector(dimension);
alternativeNewPoint = new ArrayRealVector(dimension);
trialStepPoint = new ArrayRealVector(dimension);
lagrangeValuesAtNewPoint = new ArrayRealVector(dimension + numberOfInterpolationPoints);
modelSecondDerivativesValues = new ArrayRealVector(dimension * (dimension + 1) / 2);
}
Example 9
| Source File: BOBYQAOptimizer.java From astor with GNU General Public License v2.0 | 4 votes |
|
/**
* Performs validity checks.
*
* @param lowerBound Lower bounds (constraints) of the objective variables.
* @param upperBound Upperer bounds (constraints) of the objective variables.
*/
private void setup(double[] lowerBound,
double[] upperBound) {
printMethod(); // XXX
double[] init = getStartPoint();
final int dimension = init.length;
// Check problem dimension.
if (dimension < MINIMUM_PROBLEM_DIMENSION) {
throw new NumberIsTooSmallException(dimension, MINIMUM_PROBLEM_DIMENSION, true);
}
// Check number of interpolation points.
final int[] nPointsInterval = { dimension + 2, (dimension + 2) * (dimension + 1) / 2 };
if (numberOfInterpolationPoints < nPointsInterval[0] ||
numberOfInterpolationPoints > nPointsInterval[1]) {
throw new OutOfRangeException(LocalizedFormats.NUMBER_OF_INTERPOLATION_POINTS,
numberOfInterpolationPoints,
nPointsInterval[0],
nPointsInterval[1]);
}
// Initialize bound differences.
boundDifference = new double[dimension];
double requiredMinDiff = 2 * initialTrustRegionRadius;
double minDiff = Double.POSITIVE_INFINITY;
for (int i = 0; i < dimension; i++) {
boundDifference[i] = upperBound[i] - lowerBound[i];
minDiff = Math.min(minDiff, boundDifference[i]);
}
if (minDiff < requiredMinDiff) {
initialTrustRegionRadius = minDiff / 3.0;
}
// Initialize the data structures used by the "bobyqa" method.
bMatrix = new Array2DRowRealMatrix(dimension + numberOfInterpolationPoints,
dimension);
zMatrix = new Array2DRowRealMatrix(numberOfInterpolationPoints,
numberOfInterpolationPoints - dimension - 1);
interpolationPoints = new Array2DRowRealMatrix(numberOfInterpolationPoints,
dimension);
originShift = new ArrayRealVector(dimension);
fAtInterpolationPoints = new ArrayRealVector(numberOfInterpolationPoints);
trustRegionCenterOffset = new ArrayRealVector(dimension);
gradientAtTrustRegionCenter = new ArrayRealVector(dimension);
lowerDifference = new ArrayRealVector(dimension);
upperDifference = new ArrayRealVector(dimension);
modelSecondDerivativesParameters = new ArrayRealVector(numberOfInterpolationPoints);
newPoint = new ArrayRealVector(dimension);
alternativeNewPoint = new ArrayRealVector(dimension);
trialStepPoint = new ArrayRealVector(dimension);
lagrangeValuesAtNewPoint = new ArrayRealVector(dimension + numberOfInterpolationPoints);
modelSecondDerivativesValues = new ArrayRealVector(dimension * (dimension + 1) / 2);
}
Example 10
| Source File: BOBYQAOptimizer.java From astor with GNU General Public License v2.0 | 4 votes |
|
/**
* Performs validity checks.
*
* @param lowerBound Lower bounds (constraints) of the objective variables.
* @param upperBound Upperer bounds (constraints) of the objective variables.
*/
private void setup(double[] lowerBound,
double[] upperBound) {
printMethod(); // XXX
double[] init = getStartPoint();
final int dimension = init.length;
// Check problem dimension.
if (dimension < MINIMUM_PROBLEM_DIMENSION) {
throw new NumberIsTooSmallException(dimension, MINIMUM_PROBLEM_DIMENSION, true);
}
// Check number of interpolation points.
final int[] nPointsInterval = { dimension + 2, (dimension + 2) * (dimension + 1) / 2 };
if (numberOfInterpolationPoints < nPointsInterval[0] ||
numberOfInterpolationPoints > nPointsInterval[1]) {
throw new OutOfRangeException(LocalizedFormats.NUMBER_OF_INTERPOLATION_POINTS,
numberOfInterpolationPoints,
nPointsInterval[0],
nPointsInterval[1]);
}
// Initialize bound differences.
boundDifference = new double[dimension];
double requiredMinDiff = 2 * initialTrustRegionRadius;
double minDiff = Double.POSITIVE_INFINITY;
for (int i = 0; i < dimension; i++) {
boundDifference[i] = upperBound[i] - lowerBound[i];
minDiff = Math.min(minDiff, boundDifference[i]);
}
if (minDiff < requiredMinDiff) {
initialTrustRegionRadius = minDiff / 3.0;
}
// Initialize the data structures used by the "bobyqa" method.
bMatrix = new Array2DRowRealMatrix(dimension + numberOfInterpolationPoints,
dimension);
zMatrix = new Array2DRowRealMatrix(numberOfInterpolationPoints,
numberOfInterpolationPoints - dimension - 1);
interpolationPoints = new Array2DRowRealMatrix(numberOfInterpolationPoints,
dimension);
originShift = new ArrayRealVector(dimension);
fAtInterpolationPoints = new ArrayRealVector(numberOfInterpolationPoints);
trustRegionCenterOffset = new ArrayRealVector(dimension);
gradientAtTrustRegionCenter = new ArrayRealVector(dimension);
lowerDifference = new ArrayRealVector(dimension);
upperDifference = new ArrayRealVector(dimension);
modelSecondDerivativesParameters = new ArrayRealVector(numberOfInterpolationPoints);
newPoint = new ArrayRealVector(dimension);
alternativeNewPoint = new ArrayRealVector(dimension);
trialStepPoint = new ArrayRealVector(dimension);
lagrangeValuesAtNewPoint = new ArrayRealVector(dimension + numberOfInterpolationPoints);
modelSecondDerivativesValues = new ArrayRealVector(dimension * (dimension + 1) / 2);
}
Example 11
| Source File: BOBYQAOptimizer.java From astor with GNU General Public License v2.0 | 4 votes |
|
/**
* Performs validity checks.
*
* @param lowerBound Lower bounds (constraints) of the objective variables.
* @param upperBound Upperer bounds (constraints) of the objective variables.
*/
private void setup(double[] lowerBound,
double[] upperBound) {
printMethod(); // XXX
double[] init = getStartPoint();
final int dimension = init.length;
// Check problem dimension.
if (dimension < MINIMUM_PROBLEM_DIMENSION) {
throw new NumberIsTooSmallException(dimension, MINIMUM_PROBLEM_DIMENSION, true);
}
// Check number of interpolation points.
final int[] nPointsInterval = { dimension + 2, (dimension + 2) * (dimension + 1) / 2 };
if (numberOfInterpolationPoints < nPointsInterval[0] ||
numberOfInterpolationPoints > nPointsInterval[1]) {
throw new OutOfRangeException(LocalizedFormats.NUMBER_OF_INTERPOLATION_POINTS,
numberOfInterpolationPoints,
nPointsInterval[0],
nPointsInterval[1]);
}
// Initialize bound differences.
boundDifference = new double[dimension];
double requiredMinDiff = 2 * initialTrustRegionRadius;
double minDiff = Double.POSITIVE_INFINITY;
for (int i = 0; i < dimension; i++) {
boundDifference[i] = upperBound[i] - lowerBound[i];
minDiff = Math.min(minDiff, boundDifference[i]);
}
if (minDiff < requiredMinDiff) {
initialTrustRegionRadius = minDiff / 3.0;
}
// Initialize the data structures used by the "bobyqa" method.
bMatrix = new Array2DRowRealMatrix(dimension + numberOfInterpolationPoints,
dimension);
zMatrix = new Array2DRowRealMatrix(numberOfInterpolationPoints,
numberOfInterpolationPoints - dimension - 1);
interpolationPoints = new Array2DRowRealMatrix(numberOfInterpolationPoints,
dimension);
originShift = new ArrayRealVector(dimension);
fAtInterpolationPoints = new ArrayRealVector(numberOfInterpolationPoints);
trustRegionCenterOffset = new ArrayRealVector(dimension);
gradientAtTrustRegionCenter = new ArrayRealVector(dimension);
lowerDifference = new ArrayRealVector(dimension);
upperDifference = new ArrayRealVector(dimension);
modelSecondDerivativesParameters = new ArrayRealVector(numberOfInterpolationPoints);
newPoint = new ArrayRealVector(dimension);
alternativeNewPoint = new ArrayRealVector(dimension);
trialStepPoint = new ArrayRealVector(dimension);
lagrangeValuesAtNewPoint = new ArrayRealVector(dimension + numberOfInterpolationPoints);
modelSecondDerivativesValues = new ArrayRealVector(dimension * (dimension + 1) / 2);
}
Example 12
| Source File: BOBYQAOptimizer.java From astor with GNU General Public License v2.0 | 4 votes |
|
/**
* Performs validity checks.
*
* @param lowerBound Lower bounds (constraints) of the objective variables.
* @param upperBound Upperer bounds (constraints) of the objective variables.
*/
private void setup(double[] lowerBound,
double[] upperBound) {
printMethod(); // XXX
double[] init = getStartPoint();
final int dimension = init.length;
// Check problem dimension.
if (dimension < MINIMUM_PROBLEM_DIMENSION) {
throw new NumberIsTooSmallException(dimension, MINIMUM_PROBLEM_DIMENSION, true);
}
// Check number of interpolation points.
final int[] nPointsInterval = { dimension + 2, (dimension + 2) * (dimension + 1) / 2 };
if (numberOfInterpolationPoints < nPointsInterval[0] ||
numberOfInterpolationPoints > nPointsInterval[1]) {
throw new OutOfRangeException(LocalizedFormats.NUMBER_OF_INTERPOLATION_POINTS,
numberOfInterpolationPoints,
nPointsInterval[0],
nPointsInterval[1]);
}
// Initialize bound differences.
boundDifference = new double[dimension];
double requiredMinDiff = 2 * initialTrustRegionRadius;
double minDiff = Double.POSITIVE_INFINITY;
for (int i = 0; i < dimension; i++) {
boundDifference[i] = upperBound[i] - lowerBound[i];//
minDiff = FastMath.min(minDiff, boundDifference[i]);
}
if (minDiff < requiredMinDiff) {
initialTrustRegionRadius = minDiff / 3.0;
}
// Initialize the data structures used by the "bobyqa" method.
bMatrix = new Array2DRowRealMatrix(dimension + numberOfInterpolationPoints,
dimension);
zMatrix = new Array2DRowRealMatrix(numberOfInterpolationPoints,
numberOfInterpolationPoints - dimension - 1);
interpolationPoints = new Array2DRowRealMatrix(numberOfInterpolationPoints,
dimension);
originShift = new ArrayRealVector(dimension);
fAtInterpolationPoints = new ArrayRealVector(numberOfInterpolationPoints);
trustRegionCenterOffset = new ArrayRealVector(dimension);
gradientAtTrustRegionCenter = new ArrayRealVector(dimension);
lowerDifference = new ArrayRealVector(dimension);
upperDifference = new ArrayRealVector(dimension);
modelSecondDerivativesParameters = new ArrayRealVector(numberOfInterpolationPoints);
newPoint = new ArrayRealVector(dimension);
alternativeNewPoint = new ArrayRealVector(dimension);
trialStepPoint = new ArrayRealVector(dimension);
lagrangeValuesAtNewPoint = new ArrayRealVector(dimension + numberOfInterpolationPoints);
modelSecondDerivativesValues = new ArrayRealVector(dimension * (dimension + 1) / 2);
}
Example 13
| Source File: BOBYQAOptimizer.java From astor with GNU General Public License v2.0 | 4 votes |
|
/**
* Performs validity checks.
*
* @param lowerBound Lower bounds (constraints) of the objective variables.
* @param upperBound Upperer bounds (constraints) of the objective variables.
*/
private void setup(double[] lowerBound,
double[] upperBound) {
printMethod(); // XXX
double[] init = getStartPoint();
final int dimension = init.length;
// Check problem dimension.
if (dimension < MINIMUM_PROBLEM_DIMENSION) {
throw new NumberIsTooSmallException(dimension, MINIMUM_PROBLEM_DIMENSION, true);
}
// Check number of interpolation points.
final int[] nPointsInterval = { dimension + 2, (dimension + 2) * (dimension + 1) / 2 };
if (numberOfInterpolationPoints < nPointsInterval[0] ||
numberOfInterpolationPoints > nPointsInterval[1]) {
throw new OutOfRangeException(LocalizedFormats.NUMBER_OF_INTERPOLATION_POINTS,
numberOfInterpolationPoints,
nPointsInterval[0],
nPointsInterval[1]);
}
// Initialize bound differences.
boundDifference = new double[dimension];
double requiredMinDiff = 2 * initialTrustRegionRadius;
double minDiff = Double.POSITIVE_INFINITY;
for (int i = 0; i < dimension; i++) {
boundDifference[i] = upperBound[i] - lowerBound[i];
minDiff = FastMath.min(minDiff, boundDifference[i]);
}
if (minDiff < requiredMinDiff) {
initialTrustRegionRadius = minDiff / 3.0;
}
// Initialize the data structures used by the "bobyqa" method.
bMatrix = new Array2DRowRealMatrix(dimension + numberOfInterpolationPoints,
dimension);
zMatrix = new Array2DRowRealMatrix(numberOfInterpolationPoints,
numberOfInterpolationPoints - dimension - 1);
interpolationPoints = new Array2DRowRealMatrix(numberOfInterpolationPoints,
dimension);
originShift = new ArrayRealVector(dimension);
fAtInterpolationPoints = new ArrayRealVector(numberOfInterpolationPoints);
trustRegionCenterOffset = new ArrayRealVector(dimension);
gradientAtTrustRegionCenter = new ArrayRealVector(dimension);
lowerDifference = new ArrayRealVector(dimension);
upperDifference = new ArrayRealVector(dimension);
modelSecondDerivativesParameters = new ArrayRealVector(numberOfInterpolationPoints);
newPoint = new ArrayRealVector(dimension);
alternativeNewPoint = new ArrayRealVector(dimension);
trialStepPoint = new ArrayRealVector(dimension);
lagrangeValuesAtNewPoint = new ArrayRealVector(dimension + numberOfInterpolationPoints);
modelSecondDerivativesValues = new ArrayRealVector(dimension * (dimension + 1) / 2);
}
