org.apache.commons.math3.exception.OutOfRangeException Java Examples
The following examples show how to use
org.apache.commons.math3.exception.OutOfRangeException.
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Example #1
| Source File: 1_ElitisticListPopulation.java From SimFix with GNU General Public License v2.0 | 6 votes |
|
/**
* Creates a new ElitisticListPopulation instance.
*
* @param chromosomes list of chromosomes in the population
* @param populationLimit maximal size of the population
* @param elitismRate how many best chromosomes will be directly transferred to the
* next generation [in %]
* @throws OutOfRangeException if the elitism rate is outside the [0, 1] range
*/
public ElitisticListPopulation(final List<Chromosome> chromosomes,
final int populationLimit,
final double elitismRate) {
// start of generated patch
super(chromosomes,populationLimit);
if(elitismRate<0||elitismRate>1){
throw new OutOfRangeException(LocalizedFormats.ELITISM_RATE,elitismRate,0,1);
}
this.elitismRate=elitismRate;
// end of generated patch
/* start of original code
super(chromosomes, populationLimit);
this.elitismRate = elitismRate;
end of original code*/
}
Example #2
| Source File: Math_6_CMAESOptimizer_s.java From coming with MIT License | 6 votes |
|
/**
* Checks dimensions and values of boundaries and inputSigma if defined.
*/
private void checkParameters() {
final double[] init = getStartPoint();
final double[] lB = getLowerBound();
final double[] uB = getUpperBound();
if (inputSigma != null) {
if (inputSigma.length != init.length) {
throw new DimensionMismatchException(inputSigma.length, init.length);
}
for (int i = 0; i < init.length; i++) {
if (inputSigma[i] > uB[i] - lB[i]) {
throw new OutOfRangeException(inputSigma[i], 0, uB[i] - lB[i]);
}
}
}
}
Example #3
| Source File: 1_ElitisticListPopulation.java From SimFix with GNU General Public License v2.0 | 6 votes |
|
/**
* Creates a new ElitisticListPopulation instance.
*
* @param chromosomes list of chromosomes in the population
* @param populationLimit maximal size of the population
* @param elitismRate how many best chromosomes will be directly transferred to the
* next generation [in %]
* @throws OutOfRangeException if the elitism rate is outside the [0, 1] range
*/
public ElitisticListPopulation(final List<Chromosome> chromosomes,
final int populationLimit,
final double elitismRate) {
// start of generated patch
super(chromosomes,populationLimit);
if(elitismRate<0||elitismRate>1){
throw new OutOfRangeException(LocalizedFormats.ELITISM_RATE,elitismRate,0,1);
}
this.elitismRate=elitismRate;
// end of generated patch
/* start of original code
super(chromosomes, populationLimit);
this.elitismRate = elitismRate;
end of original code*/
}
Example #4
| Source File: Math_6_CMAESOptimizer_t.java From coming with MIT License | 6 votes |
|
/**
* Checks dimensions and values of boundaries and inputSigma if defined.
*/
private void checkParameters() {
final double[] init = getStartPoint();
final double[] lB = getLowerBound();
final double[] uB = getUpperBound();
if (inputSigma != null) {
if (inputSigma.length != init.length) {
throw new DimensionMismatchException(inputSigma.length, init.length);
}
for (int i = 0; i < init.length; i++) {
if (inputSigma[i] > uB[i] - lB[i]) {
throw new OutOfRangeException(inputSigma[i], 0, uB[i] - lB[i]);
}
}
}
}
Example #5
| Source File: PseudoSpectrumDataSet.java From mzmine2 with GNU General Public License v2.0 | 5 votes |
|
public void addDP(int series, double x, double y, String ann) {
if (series >= getSeriesCount())
throw new OutOfRangeException(series, 0, getSeriesCount());
XYDataItem dp = new XYDataItem(x, y);
getSeries(series).add(dp);
if (ann != null) {
addAnnotation(dp, ann);
}
}
Example #6
| Source File: Cardumen_00256_t.java From coming with MIT License | 4 votes |
|
/**
* {@inheritDoc}
*
* The default implementation returns
* <ul>
* <li>{@link #getSupportLowerBound()} for {@code p = 0},</li>
* <li>{@link #getSupportUpperBound()} for {@code p = 1}, and</li>
* <li>{@link #solveInverseCumulativeProbability(double, int, int)} for
* {@code 0 < p < 1}.</li>
* </ul>
*/
public int inverseCumulativeProbability(final double p) throws OutOfRangeException {
if (p < 0.0 || p > 1.0) {
throw new OutOfRangeException(p, 0, 1);
}
int lower = getSupportLowerBound();
if (p == 0.0) {
return lower;
}
if (lower == Integer.MIN_VALUE) {
if (checkedCumulativeProbability(lower) >= p) {
return lower;
}
} else {
lower -= 1; // this ensures cumulativeProbability(lower) < p, which
// is important for the solving step
}
int upper = getSupportUpperBound();
if (p == 1.0) {
return upper;
}
// use the one-sided Chebyshev inequality to narrow the bracket
// cf. AbstractRealDistribution.inverseCumulativeProbability(double)
final double mu = getNumericalMean();
final double sigma = FastMath.sqrt(getNumericalVariance());
final boolean chebyshevApplies = !(Double.isInfinite(mu) || Double.isNaN(mu) ||
Double.isInfinite(sigma) || Double.isNaN(sigma) || sigma == 0.0);
if (chebyshevApplies) {
double k = FastMath.sqrt((1.0 - p) / p);
double tmp = mu - k * sigma;
if (tmp > lower) {
lower = ((int) Math.ceil(tmp)) - 1;
}
k = 1.0 / k;
tmp = mu + k * sigma;
if ((java.lang.Double.isInfinite(p)) || (java.lang.Double.isNaN(p))) {
upper = ((int) Math.ceil(tmp)) - 1;
}
}
return solveInverseCumulativeProbability(p, lower, upper);
}
Example #7
| Source File: Cardumen_00105_t.java From coming with MIT License | 4 votes |
|
/**
* Checks dimensions and values of boundaries and inputSigma if defined.
*/
private void checkParameters() {
final double[] init = getStartPoint();
final double[] lB = getLowerBound();
final double[] uB = getUpperBound();
// Checks whether there is at least one finite bound value.
boolean hasFiniteBounds = false;
for (int i = 0; i < lB.length; i++) {
if (!Double.isInfinite(lB[i]) ||
!Double.isInfinite(uB[i])) {
hasFiniteBounds = true;
break;
}
}
// Checks whether there is at least one infinite bound value.
boolean hasInfiniteBounds = false;
if (hasFiniteBounds) {
for (int i = 0; i < lB.length; i++) {
if (Double.isInfinite(lB[i]) ||
Double.isInfinite(uB[i])) {
hasInfiniteBounds = true;
break;
}
}
if (hasInfiniteBounds) {
// If there is at least one finite bound, none can be infinite,
// because mixed cases are not supported by the current code.
throw new MathUnsupportedOperationException();
} else {
// Convert API to internal handling of boundaries.
boundaries = new double[2][];
boundaries[0] = lB;
boundaries[1] = uB;
// Abort early if the normalization will overflow (cf. "encode" method).
for (int i = 0; i < lB.length; i++) {
if (Double.isInfinite(boundaries[1][i] - boundaries[0][i])) {
final double max = Double.MAX_VALUE + boundaries[0][i];
final NumberIsTooLargeException e
= new NumberIsTooLargeException(boundaries[1][i],
max,
true);
e.getContext().addMessage(LocalizedFormats.OVERFLOW);
e.getContext().addMessage(LocalizedFormats.INDEX, i);
throw e;
}
}
}
} else {
// Convert API to internal handling of boundaries.
boundaries = null;
}
if (inputSigma != null) {
if (inputSigma.length != init.length) {
throw new DimensionMismatchException(inputSigma.length, init.length);
}
for (int i = 0; i < init.length; i++) {
if (inputSigma[i] < 0) {
throw new NotPositiveException(inputSigma[i]);
}
if (boundaries != null) {
if (inputSigma[i] > boundaries[1][i] - boundaries[0][i]) {
throw new OutOfRangeException(inputSigma[i], 0, boundaries[1][i] - boundaries[0][i]);
}
}
}
}
}
Example #8
| Source File: jMutRepair_008_t.java From coming with MIT License | 4 votes |
|
/**
* {@inheritDoc}
*
* The default implementation returns
* <ul>
* <li>{@link #getSupportLowerBound()} for {@code p = 0},</li>
* <li>{@link #getSupportUpperBound()} for {@code p = 1}, and</li>
* <li>{@link #solveInverseCumulativeProbability(double, int, int)} for
* {@code 0 < p < 1}.</li>
* </ul>
*/
public int inverseCumulativeProbability(final double p) throws OutOfRangeException {
if (p < 0.0 || p > 1.0) {
throw new OutOfRangeException(p, 0, 1);
}
int lower = getSupportLowerBound();
if (p == 0.0) {
return lower;
}
if (lower == Integer.MIN_VALUE) {
if (checkedCumulativeProbability(lower) >= p) {
return lower;
}
} else {
lower -= 1; // this ensures cumulativeProbability(lower) < p, which
// is important for the solving step
}
int upper = getSupportUpperBound();
if (p == 1.0) {
return upper;
}
// use the one-sided Chebyshev inequality to narrow the bracket
// cf. AbstractRealDistribution.inverseCumulativeProbability(double)
final double mu = getNumericalMean();
final double sigma = FastMath.sqrt(getNumericalVariance());
final boolean chebyshevApplies = !(Double.isInfinite(mu) || Double.isNaN(mu) ||
Double.isInfinite(sigma) || Double.isNaN(sigma) || sigma == 0.0);
if (chebyshevApplies) {
double k = FastMath.sqrt((1.0 - p) / p);
double tmp = mu - k * sigma;
if (tmp > lower) {
lower = ((int) Math.ceil(tmp)) - 1;
}
k = 1.0 / k;
tmp = mu + k * sigma;
if (tmp == upper) {
upper = ((int) Math.ceil(tmp)) - 1;
}
}
return solveInverseCumulativeProbability(p, lower, upper);
}
Example #9
| Source File: Elixir_0021_s.java From coming with MIT License | 4 votes |
|
/**
* Checks dimensions and values of boundaries and inputSigma if defined.
*/
private void checkParameters() {
final double[] init = getStartPoint();
final double[] lB = getLowerBound();
final double[] uB = getUpperBound();
// Checks whether there is at least one finite bound value.
boolean hasFiniteBounds = false;
for (int i = 0; i < lB.length; i++) {
if (!Double.isInfinite(lB[i]) ||
!Double.isInfinite(uB[i])) {
hasFiniteBounds = true;
break;
}
}
// Checks whether there is at least one infinite bound value.
boolean hasInfiniteBounds = false;
if (hasFiniteBounds) {
for (int i = 0; i < lB.length; i++) {
if (Double.isInfinite(lB[i]) ||
Double.isInfinite(uB[i])) {
hasInfiniteBounds = true;
break;
}
}
if (hasInfiniteBounds) {
// If there is at least one finite bound, none can be infinite,
// because mixed cases are not supported by the current code.
throw new MathUnsupportedOperationException();
} else {
// Convert API to internal handling of boundaries.
boundaries = new double[2][];
boundaries[0] = lB;
boundaries[1] = uB;
}
} else {
// Convert API to internal handling of boundaries.
boundaries = null;
}
if (inputSigma != null) {
if (inputSigma.length != init.length) {
throw new DimensionMismatchException(inputSigma.length, init.length);
}
for (int i = 0; i < init.length; i++) {
if (inputSigma[i] < 0) {
throw new NotPositiveException(inputSigma[i]);
}
if (boundaries != null) {
if (inputSigma[i] > boundaries[1][i] - boundaries[0][i]) {
throw new OutOfRangeException(inputSigma[i], 0, boundaries[1][i] - boundaries[0][i]);
}
}
}
}
}
Example #10
| Source File: Cardumen_0037_s.java From coming with MIT License | 4 votes |
|
/**
* Checks dimensions and values of boundaries and inputSigma if defined.
*/
private void checkParameters() {
final double[] init = getStartPoint();
final double[] lB = getLowerBound();
final double[] uB = getUpperBound();
// Checks whether there is at least one finite bound value.
boolean hasFiniteBounds = false;
for (int i = 0; i < lB.length; i++) {
if (!Double.isInfinite(lB[i]) ||
!Double.isInfinite(uB[i])) {
hasFiniteBounds = true;
break;
}
}
// Checks whether there is at least one infinite bound value.
boolean hasInfiniteBounds = false;
if (hasFiniteBounds) {
for (int i = 0; i < lB.length; i++) {
if (Double.isInfinite(lB[i]) ||
Double.isInfinite(uB[i])) {
hasInfiniteBounds = true;
break;
}
}
if (hasInfiniteBounds) {
// If there is at least one finite bound, none can be infinite,
// because mixed cases are not supported by the current code.
throw new MathUnsupportedOperationException();
} else {
// Convert API to internal handling of boundaries.
boundaries = new double[2][];
boundaries[0] = lB;
boundaries[1] = uB;
}
} else {
// Convert API to internal handling of boundaries.
boundaries = null;
}
if (inputSigma != null) {
if (inputSigma.length != init.length) {
throw new DimensionMismatchException(inputSigma.length, init.length);
}
for (int i = 0; i < init.length; i++) {
if (inputSigma[i] < 0) {
throw new NotPositiveException(inputSigma[i]);
}
if (boundaries != null) {
if (inputSigma[i] > boundaries[1][i] - boundaries[0][i]) {
throw new OutOfRangeException(inputSigma[i], 0, boundaries[1][i] - boundaries[0][i]);
}
}
}
}
}
Example #11
| Source File: JGenProg2017_00130_s.java From coming with MIT License | 4 votes |
|
/**
* {@inheritDoc}
*
* The default implementation returns
* <ul>
* <li>{@link #getSupportLowerBound()} for {@code p = 0},</li>
* <li>{@link #getSupportUpperBound()} for {@code p = 1}, and</li>
* <li>{@link #solveInverseCumulativeProbability(double, int, int)} for
* {@code 0 < p < 1}.</li>
* </ul>
*/
public int inverseCumulativeProbability(final double p) throws OutOfRangeException {
if (p < 0.0 || p > 1.0) {
throw new OutOfRangeException(p, 0, 1);
}
int lower = getSupportLowerBound();
if (p == 0.0) {
return lower;
}
if (lower == Integer.MIN_VALUE) {
if (checkedCumulativeProbability(lower) >= p) {
return lower;
}
} else {
lower -= 1; // this ensures cumulativeProbability(lower) < p, which
// is important for the solving step
}
int upper = getSupportUpperBound();
if (p == 1.0) {
return upper;
}
// use the one-sided Chebyshev inequality to narrow the bracket
// cf. AbstractRealDistribution.inverseCumulativeProbability(double)
final double mu = getNumericalMean();
final double sigma = FastMath.sqrt(getNumericalVariance());
final boolean chebyshevApplies = !(Double.isInfinite(mu) || Double.isNaN(mu) ||
Double.isInfinite(sigma) || Double.isNaN(sigma) || sigma == 0.0);
if (chebyshevApplies) {
double k = FastMath.sqrt((1.0 - p) / p);
double tmp = mu - k * sigma;
if (tmp > lower) {
lower = ((int) Math.ceil(tmp)) - 1;
}
k = 1.0 / k;
tmp = mu + k * sigma;
if (tmp < upper) {
upper = ((int) Math.ceil(tmp)) - 1;
}
}
return solveInverseCumulativeProbability(p, lower, upper);
}
Example #12
| Source File: Cardumen_00213_s.java From coming with MIT License | 4 votes |
|
/**
* Checks dimensions and values of boundaries and inputSigma if defined.
*/
private void checkParameters() {
final double[] init = getStartPoint();
final double[] lB = getLowerBound();
final double[] uB = getUpperBound();
// Checks whether there is at least one finite bound value.
boolean hasFiniteBounds = false;
for (int i = 0; i < lB.length; i++) {
if (!Double.isInfinite(lB[i]) ||
!Double.isInfinite(uB[i])) {
hasFiniteBounds = true;
break;
}
}
// Checks whether there is at least one infinite bound value.
boolean hasInfiniteBounds = false;
if (hasFiniteBounds) {
for (int i = 0; i < lB.length; i++) {
if (Double.isInfinite(lB[i]) ||
Double.isInfinite(uB[i])) {
hasInfiniteBounds = true;
break;
}
}
if (hasInfiniteBounds) {
// If there is at least one finite bound, none can be infinite,
// because mixed cases are not supported by the current code.
throw new MathUnsupportedOperationException();
} else {
// Convert API to internal handling of boundaries.
boundaries = new double[2][];
boundaries[0] = lB;
boundaries[1] = uB;
}
} else {
// Convert API to internal handling of boundaries.
boundaries = null;
}
if (inputSigma != null) {
if (inputSigma.length != init.length) {
throw new DimensionMismatchException(inputSigma.length, init.length);
}
for (int i = 0; i < init.length; i++) {
if (inputSigma[i] < 0) {
throw new NotPositiveException(inputSigma[i]);
}
if (boundaries != null) {
if (inputSigma[i] > boundaries[1][i] - boundaries[0][i]) {
throw new OutOfRangeException(inputSigma[i], 0, boundaries[1][i] - boundaries[0][i]);
}
}
}
}
}
Example #13
| Source File: JGenProg2017_0089_s.java From coming with MIT License | 4 votes |
|
/**
* Checks dimensions and values of boundaries and inputSigma if defined.
*/
private void checkParameters() {
final double[] init = getStartPoint();
final double[] lB = getLowerBound();
final double[] uB = getUpperBound();
// Checks whether there is at least one finite bound value.
boolean hasFiniteBounds = false;
for (int i = 0; i < lB.length; i++) {
if (!Double.isInfinite(lB[i]) ||
!Double.isInfinite(uB[i])) {
hasFiniteBounds = true;
break;
}
}
// Checks whether there is at least one infinite bound value.
boolean hasInfiniteBounds = false;
if (hasFiniteBounds) {
for (int i = 0; i < lB.length; i++) {
if (Double.isInfinite(lB[i]) ||
Double.isInfinite(uB[i])) {
hasInfiniteBounds = true;
break;
}
}
if (hasInfiniteBounds) {
// If there is at least one finite bound, none can be infinite,
// because mixed cases are not supported by the current code.
throw new MathUnsupportedOperationException();
} else {
// Convert API to internal handling of boundaries.
boundaries = new double[2][];
boundaries[0] = lB;
boundaries[1] = uB;
}
} else {
// Convert API to internal handling of boundaries.
boundaries = null;
}
if (inputSigma != null) {
if (inputSigma.length != init.length) {
throw new DimensionMismatchException(inputSigma.length, init.length);
}
for (int i = 0; i < init.length; i++) {
if (inputSigma[i] < 0) {
throw new NotPositiveException(inputSigma[i]);
}
if (boundaries != null) {
if (inputSigma[i] > boundaries[1][i] - boundaries[0][i]) {
throw new OutOfRangeException(inputSigma[i], 0, boundaries[1][i] - boundaries[0][i]);
}
}
}
}
}
Example #14
| Source File: jMutRepair_0041_s.java From coming with MIT License | 4 votes |
|
/**
* {@inheritDoc}
*
* The default implementation returns
* <ul>
* <li>{@link #getSupportLowerBound()} for {@code p = 0},</li>
* <li>{@link #getSupportUpperBound()} for {@code p = 1}, and</li>
* <li>{@link #solveInverseCumulativeProbability(double, int, int)} for
* {@code 0 < p < 1}.</li>
* </ul>
*/
public int inverseCumulativeProbability(final double p) throws OutOfRangeException {
if (p < 0.0 || p > 1.0) {
throw new OutOfRangeException(p, 0, 1);
}
int lower = getSupportLowerBound();
if (p == 0.0) {
return lower;
}
if (lower == Integer.MIN_VALUE) {
if (checkedCumulativeProbability(lower) >= p) {
return lower;
}
} else {
lower -= 1; // this ensures cumulativeProbability(lower) < p, which
// is important for the solving step
}
int upper = getSupportUpperBound();
if (p == 1.0) {
return upper;
}
// use the one-sided Chebyshev inequality to narrow the bracket
// cf. AbstractRealDistribution.inverseCumulativeProbability(double)
final double mu = getNumericalMean();
final double sigma = FastMath.sqrt(getNumericalVariance());
final boolean chebyshevApplies = !(Double.isInfinite(mu) || Double.isNaN(mu) ||
Double.isInfinite(sigma) || Double.isNaN(sigma) || sigma == 0.0);
if (chebyshevApplies) {
double k = FastMath.sqrt((1.0 - p) / p);
double tmp = mu - k * sigma;
if (tmp > lower) {
lower = ((int) Math.ceil(tmp)) - 1;
}
k = 1.0 / k;
tmp = mu + k * sigma;
if (tmp < upper) {
upper = ((int) Math.ceil(tmp)) - 1;
}
}
return solveInverseCumulativeProbability(p, lower, upper);
}
Example #15
| Source File: JGenProg2017_00130_t.java From coming with MIT License | 4 votes |
|
/**
* {@inheritDoc}
*
* The default implementation returns
* <ul>
* <li>{@link #getSupportLowerBound()} for {@code p = 0},</li>
* <li>{@link #getSupportUpperBound()} for {@code p = 1}, and</li>
* <li>{@link #solveInverseCumulativeProbability(double, int, int)} for
* {@code 0 < p < 1}.</li>
* </ul>
*/
public int inverseCumulativeProbability(final double p) throws OutOfRangeException {
if (p < 0.0 || p > 1.0) {
throw new OutOfRangeException(p, 0, 1);
}
int lower = getSupportLowerBound();
if (p == 0.0) {
return lower;
}
if (lower == Integer.MIN_VALUE) {
if (checkedCumulativeProbability(lower) >= p) {
return lower;
}
} else {
lower -= 1; // this ensures cumulativeProbability(lower) < p, which
// is important for the solving step
}
int upper = getSupportUpperBound();
if (p == 1.0) {
return upper;
}
// use the one-sided Chebyshev inequality to narrow the bracket
// cf. AbstractRealDistribution.inverseCumulativeProbability(double)
final double mu = getNumericalMean();
final double sigma = FastMath.sqrt(getNumericalVariance());
final boolean chebyshevApplies = !(Double.isInfinite(mu) || Double.isNaN(mu) ||
Double.isInfinite(sigma) || Double.isNaN(sigma) || sigma == 0.0);
if (chebyshevApplies) {
double k = FastMath.sqrt((1.0 - p) / p);
double tmp = mu - k * sigma;
if (tmp > lower) {
lower = ((int) Math.ceil(tmp)) - 1;
}
k = 1.0 / k;
tmp = mu + k * sigma;
if (java.lang.Double.isInfinite(p)) {
throw new org.apache.commons.math3.exception.NotFiniteNumberException(p);
}
}
return solveInverseCumulativeProbability(p, lower, upper);
}
Example #16
| Source File: JGenProg2017_0020_s.java From coming with MIT License | 4 votes |
|
/**
* Checks dimensions and values of boundaries and inputSigma if defined.
*/
private void checkParameters() {
final double[] init = getStartPoint();
final double[] lB = getLowerBound();
final double[] uB = getUpperBound();
// Checks whether there is at least one finite bound value.
boolean hasFiniteBounds = false;
for (int i = 0; i < lB.length; i++) {
if (!Double.isInfinite(lB[i]) ||
!Double.isInfinite(uB[i])) {
hasFiniteBounds = true;
break;
}
}
// Checks whether there is at least one infinite bound value.
boolean hasInfiniteBounds = false;
if (hasFiniteBounds) {
for (int i = 0; i < lB.length; i++) {
if (Double.isInfinite(lB[i]) ||
Double.isInfinite(uB[i])) {
hasInfiniteBounds = true;
break;
}
}
if (hasInfiniteBounds) {
// If there is at least one finite bound, none can be infinite,
// because mixed cases are not supported by the current code.
throw new MathUnsupportedOperationException();
} else {
// Convert API to internal handling of boundaries.
boundaries = new double[2][];
boundaries[0] = lB;
boundaries[1] = uB;
}
} else {
// Convert API to internal handling of boundaries.
boundaries = null;
}
if (inputSigma != null) {
if (inputSigma.length != init.length) {
throw new DimensionMismatchException(inputSigma.length, init.length);
}
for (int i = 0; i < init.length; i++) {
if (inputSigma[i] < 0) {
throw new NotPositiveException(inputSigma[i]);
}
if (boundaries != null) {
if (inputSigma[i] > boundaries[1][i] - boundaries[0][i]) {
throw new OutOfRangeException(inputSigma[i], 0, boundaries[1][i] - boundaries[0][i]);
}
}
}
}
}
Example #17
| Source File: Nopol2017_0063_t.java From coming with MIT License | 4 votes |
|
/**
* {@inheritDoc}
*
* The default implementation returns
* <ul>
* <li>{@link #getSupportLowerBound()} for {@code p = 0},</li>
* <li>{@link #getSupportUpperBound()} for {@code p = 1}, and</li>
* <li>{@link #solveInverseCumulativeProbability(double, int, int)} for
* {@code 0 < p < 1}.</li>
* </ul>
*/
public int inverseCumulativeProbability(final double p) throws OutOfRangeException {
if (p < 0.0 || p > 1.0) {
throw new OutOfRangeException(p, 0, 1);
}
int lower = getSupportLowerBound();
if (p == 0.0) {
return lower;
}
if (lower == Integer.MIN_VALUE) {
if (checkedCumulativeProbability(lower) >= p) {
return lower;
}
} else {
lower -= 1; // this ensures cumulativeProbability(lower) < p, which
// is important for the solving step
}
int upper = getSupportUpperBound();
if (p == 1.0) {
return upper;
}
// use the one-sided Chebyshev inequality to narrow the bracket
// cf. AbstractRealDistribution.inverseCumulativeProbability(double)
final double mu = getNumericalMean();
final double sigma = FastMath.sqrt(getNumericalVariance());
final boolean chebyshevApplies = !(Double.isInfinite(mu) || Double.isNaN(mu) ||
Double.isInfinite(sigma) || Double.isNaN(sigma) || sigma == 0.0);
if (chebyshevApplies) {
double k = FastMath.sqrt((1.0 - p) / p);
double tmp = mu - k * sigma;
if (tmp > lower) {
lower = ((int) Math.ceil(tmp)) - 1;
}
k = 1.0 / k;
tmp = mu + k * sigma;
if (tmp < upper) {
if (tmp == -1) {
upper = ((int) Math.ceil(tmp)) - 1;
}
}
}
return solveInverseCumulativeProbability(p, lower, upper);
}
Example #18
| Source File: Cardumen_00105_s.java From coming with MIT License | 4 votes |
|
/**
* Checks dimensions and values of boundaries and inputSigma if defined.
*/
private void checkParameters() {
final double[] init = getStartPoint();
final double[] lB = getLowerBound();
final double[] uB = getUpperBound();
// Checks whether there is at least one finite bound value.
boolean hasFiniteBounds = false;
for (int i = 0; i < lB.length; i++) {
if (!Double.isInfinite(lB[i]) ||
!Double.isInfinite(uB[i])) {
hasFiniteBounds = true;
break;
}
}
// Checks whether there is at least one infinite bound value.
boolean hasInfiniteBounds = false;
if (hasFiniteBounds) {
for (int i = 0; i < lB.length; i++) {
if (Double.isInfinite(lB[i]) ||
Double.isInfinite(uB[i])) {
hasInfiniteBounds = true;
break;
}
}
if (hasInfiniteBounds) {
// If there is at least one finite bound, none can be infinite,
// because mixed cases are not supported by the current code.
throw new MathUnsupportedOperationException();
} else {
// Convert API to internal handling of boundaries.
boundaries = new double[2][];
boundaries[0] = lB;
boundaries[1] = uB;
// Abort early if the normalization will overflow (cf. "encode" method).
for (int i = 0; i < lB.length; i++) {
if (Double.isInfinite(boundaries[1][i] - boundaries[0][i])) {
final double max = Double.MAX_VALUE + boundaries[0][i];
final NumberIsTooLargeException e
= new NumberIsTooLargeException(boundaries[1][i],
max,
true);
e.getContext().addMessage(LocalizedFormats.OVERFLOW);
e.getContext().addMessage(LocalizedFormats.INDEX, i);
throw e;
}
}
}
} else {
// Convert API to internal handling of boundaries.
boundaries = null;
}
if (inputSigma != null) {
if (inputSigma.length != init.length) {
throw new DimensionMismatchException(inputSigma.length, init.length);
}
for (int i = 0; i < init.length; i++) {
if (inputSigma[i] < 0) {
throw new NotPositiveException(inputSigma[i]);
}
if (boundaries != null) {
if (inputSigma[i] > boundaries[1][i] - boundaries[0][i]) {
throw new OutOfRangeException(inputSigma[i], 0, boundaries[1][i] - boundaries[0][i]);
}
}
}
}
}
Example #19
| Source File: Cardumen_0035_t.java From coming with MIT License | 4 votes |
|
/**
* Checks dimensions and values of boundaries and inputSigma if defined.
*/
private void checkParameters() {
final double[] init = getStartPoint();
final double[] lB = getLowerBound();
final double[] uB = getUpperBound();
// Checks whether there is at least one finite bound value.
boolean hasFiniteBounds = false;
for (int i = 0; i < lB.length; i++) {
if (!Double.isInfinite(lB[i]) ||
!Double.isInfinite(uB[i])) {
hasFiniteBounds = true;
break;
}
}
// Checks whether there is at least one infinite bound value.
boolean hasInfiniteBounds = false;
if (hasFiniteBounds) {
for (int i = 0; i < lB.length; i++) {
if (Double.isInfinite(lB[i]) ||
Double.isInfinite(uB[i])) {
hasInfiniteBounds = true;
break;
}
}
if (hasInfiniteBounds) {
// If there is at least one finite bound, none can be infinite,
// because mixed cases are not supported by the current code.
throw new MathUnsupportedOperationException();
} else {
// Convert API to internal handling of boundaries.
boundaries = new double[2][];
boundaries[0] = lB;
boundaries[1] = uB;
// Abort early if the normalization will overflow (cf. "encode" method).
for (int i = 0; i < lB.length; i++) {
if (Double.isInfinite(boundaries[1][i] - boundaries[0][i])) {
final double max = Double.MAX_VALUE + boundaries[0][i];
final NumberIsTooLargeException e
= new NumberIsTooLargeException(boundaries[1][i],
max,
true);
e.getContext().addMessage(LocalizedFormats.OVERFLOW);
e.getContext().addMessage(LocalizedFormats.INDEX, i);
throw e;
}
}
}
} else {
// Convert API to internal handling of boundaries.
boundaries = null;
}
if (inputSigma != null) {
if (inputSigma.length != init.length) {
throw new DimensionMismatchException(inputSigma.length, init.length);
}
for (int i = 0; i < init.length; i++) {
if (inputSigma[i] < 0) {
throw new NotPositiveException(inputSigma[i]);
}
if (boundaries != null) {
if (inputSigma[i] > boundaries[1][i] - boundaries[0][i]) {
throw new OutOfRangeException(inputSigma[i], 0, boundaries[1][i] - boundaries[0][i]);
}
}
}
}
}
Example #20
| Source File: Math_19_CMAESOptimizer_s.java From coming with MIT License | 4 votes |
|
/**
* Checks dimensions and values of boundaries and inputSigma if defined.
*/
private void checkParameters() {
final double[] init = getStartPoint();
final double[] lB = getLowerBound();
final double[] uB = getUpperBound();
// Checks whether there is at least one finite bound value.
boolean hasFiniteBounds = false;
for (int i = 0; i < lB.length; i++) {
if (!Double.isInfinite(lB[i]) ||
!Double.isInfinite(uB[i])) {
hasFiniteBounds = true;
break;
}
}
// Checks whether there is at least one infinite bound value.
boolean hasInfiniteBounds = false;
if (hasFiniteBounds) {
for (int i = 0; i < lB.length; i++) {
if (Double.isInfinite(lB[i]) ||
Double.isInfinite(uB[i])) {
hasInfiniteBounds = true;
break;
}
}
if (hasInfiniteBounds) {
// If there is at least one finite bound, none can be infinite,
// because mixed cases are not supported by the current code.
throw new MathUnsupportedOperationException();
} else {
// Convert API to internal handling of boundaries.
boundaries = new double[2][];
boundaries[0] = lB;
boundaries[1] = uB;
// Abort early if the normalization will overflow (cf. "encode" method).
}
} else {
// Convert API to internal handling of boundaries.
boundaries = null;
}
if (inputSigma != null) {
if (inputSigma.length != init.length) {
throw new DimensionMismatchException(inputSigma.length, init.length);
}
for (int i = 0; i < init.length; i++) {
if (inputSigma[i] < 0) {
throw new NotPositiveException(inputSigma[i]);
}
if (boundaries != null) {
if (inputSigma[i] > boundaries[1][i] - boundaries[0][i]) {
throw new OutOfRangeException(inputSigma[i], 0, boundaries[1][i] - boundaries[0][i]);
}
}
}
}
}
Example #21
| Source File: JGenProg2017_0058_s.java From coming with MIT License | 4 votes |
|
/**
* {@inheritDoc}
*
* The default implementation returns
* <ul>
* <li>{@link #getSupportLowerBound()} for {@code p = 0},</li>
* <li>{@link #getSupportUpperBound()} for {@code p = 1}, and</li>
* <li>{@link #solveInverseCumulativeProbability(double, int, int)} for
* {@code 0 < p < 1}.</li>
* </ul>
*/
public int inverseCumulativeProbability(final double p) throws OutOfRangeException {
if (p < 0.0 || p > 1.0) {
throw new OutOfRangeException(p, 0, 1);
}
int lower = getSupportLowerBound();
if (p == 0.0) {
return lower;
}
if (lower == Integer.MIN_VALUE) {
if (checkedCumulativeProbability(lower) >= p) {
return lower;
}
} else {
lower -= 1; // this ensures cumulativeProbability(lower) < p, which
// is important for the solving step
}
int upper = getSupportUpperBound();
if (p == 1.0) {
return upper;
}
// use the one-sided Chebyshev inequality to narrow the bracket
// cf. AbstractRealDistribution.inverseCumulativeProbability(double)
final double mu = getNumericalMean();
final double sigma = FastMath.sqrt(getNumericalVariance());
final boolean chebyshevApplies = !(Double.isInfinite(mu) || Double.isNaN(mu) ||
Double.isInfinite(sigma) || Double.isNaN(sigma) || sigma == 0.0);
if (chebyshevApplies) {
double k = FastMath.sqrt((1.0 - p) / p);
double tmp = mu - k * sigma;
if (tmp > lower) {
lower = ((int) Math.ceil(tmp)) - 1;
}
k = 1.0 / k;
tmp = mu + k * sigma;
if (tmp < upper) {
upper = ((int) Math.ceil(tmp)) - 1;
}
}
return solveInverseCumulativeProbability(p, lower, upper);
}
Example #22
| Source File: Cardumen_00107_s.java From coming with MIT License | 4 votes |
|
/**
* Checks dimensions and values of boundaries and inputSigma if defined.
*/
private void checkParameters() {
final double[] init = getStartPoint();
final double[] lB = getLowerBound();
final double[] uB = getUpperBound();
// Checks whether there is at least one finite bound value.
boolean hasFiniteBounds = false;
for (int i = 0; i < lB.length; i++) {
if (!Double.isInfinite(lB[i]) ||
!Double.isInfinite(uB[i])) {
hasFiniteBounds = true;
break;
}
}
// Checks whether there is at least one infinite bound value.
boolean hasInfiniteBounds = false;
if (hasFiniteBounds) {
for (int i = 0; i < lB.length; i++) {
if (Double.isInfinite(lB[i]) ||
Double.isInfinite(uB[i])) {
hasInfiniteBounds = true;
break;
}
}
if (hasInfiniteBounds) {
// If there is at least one finite bound, none can be infinite,
// because mixed cases are not supported by the current code.
throw new MathUnsupportedOperationException();
} else {
// Convert API to internal handling of boundaries.
boundaries = new double[2][];
boundaries[0] = lB;
boundaries[1] = uB;
}
} else {
// Convert API to internal handling of boundaries.
boundaries = null;
}
if (inputSigma != null) {
if (inputSigma.length != init.length) {
throw new DimensionMismatchException(inputSigma.length, init.length);
}
for (int i = 0; i < init.length; i++) {
if (inputSigma[i] < 0) {
throw new NotPositiveException(inputSigma[i]);
}
if (boundaries != null) {
if (inputSigma[i] > boundaries[1][i] - boundaries[0][i]) {
throw new OutOfRangeException(inputSigma[i], 0, boundaries[1][i] - boundaries[0][i]);
}
}
}
}
}
Example #23
| Source File: jMutRepair_0033_s.java From coming with MIT License | 4 votes |
|
/**
* {@inheritDoc}
*
* The default implementation returns
* <ul>
* <li>{@link #getSupportLowerBound()} for {@code p = 0},</li>
* <li>{@link #getSupportUpperBound()} for {@code p = 1}, and</li>
* <li>{@link #solveInverseCumulativeProbability(double, int, int)} for
* {@code 0 < p < 1}.</li>
* </ul>
*/
public int inverseCumulativeProbability(final double p) throws OutOfRangeException {
if (p < 0.0 || p > 1.0) {
throw new OutOfRangeException(p, 0, 1);
}
int lower = getSupportLowerBound();
if (p == 0.0) {
return lower;
}
if (lower == Integer.MIN_VALUE) {
if (checkedCumulativeProbability(lower) >= p) {
return lower;
}
} else {
lower -= 1; // this ensures cumulativeProbability(lower) < p, which
// is important for the solving step
}
int upper = getSupportUpperBound();
if (p == 1.0) {
return upper;
}
// use the one-sided Chebyshev inequality to narrow the bracket
// cf. AbstractRealDistribution.inverseCumulativeProbability(double)
final double mu = getNumericalMean();
final double sigma = FastMath.sqrt(getNumericalVariance());
final boolean chebyshevApplies = !(Double.isInfinite(mu) || Double.isNaN(mu) ||
Double.isInfinite(sigma) || Double.isNaN(sigma) || sigma == 0.0);
if (chebyshevApplies) {
double k = FastMath.sqrt((1.0 - p) / p);
double tmp = mu - k * sigma;
if (tmp > lower) {
lower = ((int) Math.ceil(tmp)) - 1;
}
k = 1.0 / k;
tmp = mu + k * sigma;
if (tmp < upper) {
upper = ((int) Math.ceil(tmp)) - 1;
}
}
return solveInverseCumulativeProbability(p, lower, upper);
}
Example #24
| Source File: jMutRepair_0024_s.java From coming with MIT License | 4 votes |
|
/**
* {@inheritDoc}
*
* The default implementation returns
* <ul>
* <li>{@link #getSupportLowerBound()} for {@code p = 0},</li>
* <li>{@link #getSupportUpperBound()} for {@code p = 1}, and</li>
* <li>{@link #solveInverseCumulativeProbability(double, int, int)} for
* {@code 0 < p < 1}.</li>
* </ul>
*/
public int inverseCumulativeProbability(final double p) throws OutOfRangeException {
if (p < 0.0 || p > 1.0) {
throw new OutOfRangeException(p, 0, 1);
}
int lower = getSupportLowerBound();
if (p == 0.0) {
return lower;
}
if (lower == Integer.MIN_VALUE) {
if (checkedCumulativeProbability(lower) >= p) {
return lower;
}
} else {
lower -= 1; // this ensures cumulativeProbability(lower) < p, which
// is important for the solving step
}
int upper = getSupportUpperBound();
if (p == 1.0) {
return upper;
}
// use the one-sided Chebyshev inequality to narrow the bracket
// cf. AbstractRealDistribution.inverseCumulativeProbability(double)
final double mu = getNumericalMean();
final double sigma = FastMath.sqrt(getNumericalVariance());
final boolean chebyshevApplies = !(Double.isInfinite(mu) || Double.isNaN(mu) ||
Double.isInfinite(sigma) || Double.isNaN(sigma) || sigma == 0.0);
if (chebyshevApplies) {
double k = FastMath.sqrt((1.0 - p) / p);
double tmp = mu - k * sigma;
if (tmp > lower) {
lower = ((int) Math.ceil(tmp)) - 1;
}
k = 1.0 / k;
tmp = mu + k * sigma;
if (tmp < upper) {
upper = ((int) Math.ceil(tmp)) - 1;
}
}
return solveInverseCumulativeProbability(p, lower, upper);
}
Example #25
| Source File: Math_19_CMAESOptimizer_t.java From coming with MIT License | 4 votes |
|
/**
* Checks dimensions and values of boundaries and inputSigma if defined.
*/
private void checkParameters() {
final double[] init = getStartPoint();
final double[] lB = getLowerBound();
final double[] uB = getUpperBound();
// Checks whether there is at least one finite bound value.
boolean hasFiniteBounds = false;
for (int i = 0; i < lB.length; i++) {
if (!Double.isInfinite(lB[i]) ||
!Double.isInfinite(uB[i])) {
hasFiniteBounds = true;
break;
}
}
// Checks whether there is at least one infinite bound value.
boolean hasInfiniteBounds = false;
if (hasFiniteBounds) {
for (int i = 0; i < lB.length; i++) {
if (Double.isInfinite(lB[i]) ||
Double.isInfinite(uB[i])) {
hasInfiniteBounds = true;
break;
}
}
if (hasInfiniteBounds) {
// If there is at least one finite bound, none can be infinite,
// because mixed cases are not supported by the current code.
throw new MathUnsupportedOperationException();
} else {
// Convert API to internal handling of boundaries.
boundaries = new double[2][];
boundaries[0] = lB;
boundaries[1] = uB;
// Abort early if the normalization will overflow (cf. "encode" method).
for (int i = 0; i < lB.length; i++) {
if (Double.isInfinite(boundaries[1][i] - boundaries[0][i])) {
final double max = Double.MAX_VALUE + boundaries[0][i];
final NumberIsTooLargeException e
= new NumberIsTooLargeException(boundaries[1][i],
max,
true);
e.getContext().addMessage(LocalizedFormats.OVERFLOW);
e.getContext().addMessage(LocalizedFormats.INDEX, i);
throw e;
}
}
}
} else {
// Convert API to internal handling of boundaries.
boundaries = null;
}
if (inputSigma != null) {
if (inputSigma.length != init.length) {
throw new DimensionMismatchException(inputSigma.length, init.length);
}
for (int i = 0; i < init.length; i++) {
if (inputSigma[i] < 0) {
throw new NotPositiveException(inputSigma[i]);
}
if (boundaries != null) {
if (inputSigma[i] > boundaries[1][i] - boundaries[0][i]) {
throw new OutOfRangeException(inputSigma[i], 0, boundaries[1][i] - boundaries[0][i]);
}
}
}
}
}
Example #26
| Source File: Arja_00104_t.java From coming with MIT License | 4 votes |
|
/**
* Checks dimensions and values of boundaries and inputSigma if defined.
*/
private void checkParameters() {
final double[] init = getStartPoint();
final double[] lB = getLowerBound();
final double[] uB = getUpperBound();
// Checks whether there is at least one finite bound value.
boolean hasFiniteBounds = false;
for (int i = 0; i < lB.length; i++) {
if (!Double.isInfinite(lB[i]) ||
!Double.isInfinite(uB[i])) {
hasFiniteBounds = true;
break;
}
}
// Checks whether there is at least one infinite bound value.
boolean hasInfiniteBounds = false;
if (hasFiniteBounds) {
for (int i = 0; i < lB.length; i++) {
if (Double.isInfinite(lB[i]) ||
Double.isInfinite(uB[i])) {
hasInfiniteBounds = true;
break;
}
}
if (hasInfiniteBounds) {
// If there is at least one finite bound, none can be infinite,
// because mixed cases are not supported by the current code.
throw new MathUnsupportedOperationException();
} else {
// Convert API to internal handling of boundaries.
boundaries = new double[2][];
boundaries[0] = lB;
boundaries[1] = uB;
}
} else {
// Convert API to internal handling of boundaries.
boundaries = null;
}
if (inputSigma != null) {
if (inputSigma.length != init.length) {
throw new DimensionMismatchException(inputSigma.length, init.length);
}
for (int i = 0; i < init.length; i++) {
if (inputSigma[i] < 0) {
throw new NotPositiveException(inputSigma[i]);
}
if (boundaries != null) {
if (inputSigma[i] > boundaries[1][i] - boundaries[0][i]) {
throw new OutOfRangeException(inputSigma[i], 0, boundaries[1][i] - boundaries[0][i]);
}
}
}
}
}
Example #27
| Source File: Arja_0055_t.java From coming with MIT License | 4 votes |
|
/**
* Checks dimensions and values of boundaries and inputSigma if defined.
*/
private void checkParameters() {
final double[] init = getStartPoint();
final double[] lB = getLowerBound();
final double[] uB = getUpperBound();
// Checks whether there is at least one finite bound value.
boolean hasFiniteBounds = false;
for (int i = 0; i < lB.length; i++) {
if (!Double.isInfinite(lB[i]) ||
!Double.isInfinite(uB[i])) {
hasFiniteBounds = true;
break;
}
}
// Checks whether there is at least one infinite bound value.
boolean hasInfiniteBounds = false;
if (hasFiniteBounds) {
for (int i = 0; i < lB.length; i++) {
if (Double.isInfinite(lB[i]) ||
Double.isInfinite(uB[i])) {
hasInfiniteBounds = true;
break;
}
}
if (hasInfiniteBounds) {
// If there is at least one finite bound, none can be infinite,
// because mixed cases are not supported by the current code.
throw new MathUnsupportedOperationException();
} else {
// Convert API to internal handling of boundaries.
boundaries = new double[2][];
boundaries[0] = lB;
boundaries[1] = uB;
}
} else {
// Convert API to internal handling of boundaries.
boundaries = null;
}
if (inputSigma != null) {
if (inputSigma.length != init.length) {
throw new DimensionMismatchException(inputSigma.length, init.length);
}
for (int i = 0; i < init.length; i++) {
if (inputSigma[i] < 0) {
throw new NotPositiveException(inputSigma[i]);
}
if (boundaries != null) {
if (inputSigma[i] > boundaries[1][i] - boundaries[0][i]) {
throw new OutOfRangeException(inputSigma[i], 0, boundaries[1][i] - boundaries[0][i]);
}
}
}
}
}
Example #28
| Source File: Arja_0078_s.java From coming with MIT License | 4 votes |
|
/**
* {@inheritDoc}
*
* The default implementation returns
* <ul>
* <li>{@link #getSupportLowerBound()} for {@code p = 0},</li>
* <li>{@link #getSupportUpperBound()} for {@code p = 1}, and</li>
* <li>{@link #solveInverseCumulativeProbability(double, int, int)} for
* {@code 0 < p < 1}.</li>
* </ul>
*/
public int inverseCumulativeProbability(final double p) throws OutOfRangeException {
if (p < 0.0 || p > 1.0) {
throw new OutOfRangeException(p, 0, 1);
}
int lower = getSupportLowerBound();
if (p == 0.0) {
return lower;
}
if (lower == Integer.MIN_VALUE) {
if (checkedCumulativeProbability(lower) >= p) {
return lower;
}
} else {
lower -= 1; // this ensures cumulativeProbability(lower) < p, which
// is important for the solving step
}
int upper = getSupportUpperBound();
if (p == 1.0) {
return upper;
}
// use the one-sided Chebyshev inequality to narrow the bracket
// cf. AbstractRealDistribution.inverseCumulativeProbability(double)
final double mu = getNumericalMean();
final double sigma = FastMath.sqrt(getNumericalVariance());
final boolean chebyshevApplies = !(Double.isInfinite(mu) || Double.isNaN(mu) ||
Double.isInfinite(sigma) || Double.isNaN(sigma) || sigma == 0.0);
if (chebyshevApplies) {
double k = FastMath.sqrt((1.0 - p) / p);
double tmp = mu - k * sigma;
if (tmp > lower) {
lower = ((int) Math.ceil(tmp)) - 1;
}
k = 1.0 / k;
tmp = mu + k * sigma;
if (tmp < upper) {
upper = ((int) Math.ceil(tmp)) - 1;
}
}
return solveInverseCumulativeProbability(p, lower, upper);
}
Example #29
| Source File: Arja_0027_t.java From coming with MIT License | 4 votes |
|
/**
* {@inheritDoc}
*
* The default implementation returns
* <ul>
* <li>{@link #getSupportLowerBound()} for {@code p = 0},</li>
* <li>{@link #getSupportUpperBound()} for {@code p = 1}, and</li>
* <li>{@link #solveInverseCumulativeProbability(double, int, int)} for
* {@code 0 < p < 1}.</li>
* </ul>
*/
public int inverseCumulativeProbability(final double p) throws OutOfRangeException {
if (p < 0.0 || p > 1.0) {
throw new OutOfRangeException(p, 0, 1);
}
int lower = getSupportLowerBound();
if (p == 0.0) {
return lower;
}
if (lower == Integer.MIN_VALUE) {
if (checkedCumulativeProbability(lower) >= p) {
return lower;
}
} else {
lower -= 1; // this ensures cumulativeProbability(lower) < p, which
// is important for the solving step
}
int upper = getSupportUpperBound();
if (p == 1.0) {
return upper;
}
// use the one-sided Chebyshev inequality to narrow the bracket
// cf. AbstractRealDistribution.inverseCumulativeProbability(double)
final double mu = getNumericalMean();
final double sigma = FastMath.sqrt(getNumericalVariance());
final boolean chebyshevApplies = !(Double.isInfinite(mu) || Double.isNaN(mu) ||
Double.isInfinite(sigma) || Double.isNaN(sigma) || sigma == 0.0);
if (chebyshevApplies) {
double k = FastMath.sqrt((1.0 - p) / p);
double tmp = mu - k * sigma;
if (tmp > lower) {
lower = ((int) Math.ceil(tmp)) - 1;
}
k = 1.0 / k;
tmp = mu + k * sigma;
if (tmp < upper) {
lower-=1;
}
}
return solveInverseCumulativeProbability(p, lower, upper);
}
Example #30
| Source File: JGenProg2017_0059_s.java From coming with MIT License | 4 votes |
|
/**
* Checks dimensions and values of boundaries and inputSigma if defined.
*/
private void checkParameters() {
final double[] init = getStartPoint();
final double[] lB = getLowerBound();
final double[] uB = getUpperBound();
// Checks whether there is at least one finite bound value.
boolean hasFiniteBounds = false;
for (int i = 0; i < lB.length; i++) {
if (!Double.isInfinite(lB[i]) ||
!Double.isInfinite(uB[i])) {
hasFiniteBounds = true;
break;
}
}
// Checks whether there is at least one infinite bound value.
boolean hasInfiniteBounds = false;
if (hasFiniteBounds) {
for (int i = 0; i < lB.length; i++) {
if (Double.isInfinite(lB[i]) ||
Double.isInfinite(uB[i])) {
hasInfiniteBounds = true;
break;
}
}
if (hasInfiniteBounds) {
// If there is at least one finite bound, none can be infinite,
// because mixed cases are not supported by the current code.
throw new MathUnsupportedOperationException();
} else {
// Convert API to internal handling of boundaries.
boundaries = new double[2][];
boundaries[0] = lB;
boundaries[1] = uB;
}
} else {
// Convert API to internal handling of boundaries.
boundaries = null;
}
if (inputSigma != null) {
if (inputSigma.length != init.length) {
throw new DimensionMismatchException(inputSigma.length, init.length);
}
for (int i = 0; i < init.length; i++) {
if (inputSigma[i] < 0) {
throw new NotPositiveException(inputSigma[i]);
}
if (boundaries != null) {
if (inputSigma[i] > boundaries[1][i] - boundaries[0][i]) {
throw new OutOfRangeException(inputSigma[i], 0, boundaries[1][i] - boundaries[0][i]);
}
}
}
}
}
