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Forbid if/else/do/while/for without braces. 

git-svn-id: https://svn.apache.org/repos/asf/commons/proper/math/trunk@1139906 13f79535-47bb-0310-9956-ffa450edef68
This commit is contained in:
Luc Maisonobe 2011-06-26 18:42:32 +00:00
parent d803dbac0e
commit c56bc8fa33
24 changed files with 262 additions and 138 deletions
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7
checkstyle.xml
View File

@ -34,7 +34,10 @@
<module name="OperatorWrap">
<property name="option" value="eol"/>
</module>
<!-- No if/else/do/for/while without braces -->
<module name="NeedBraces"/>
<!-- Interfaces must be types (not just constants) -->
<module name="InterfaceIsType"/>
@ -58,7 +61,7 @@
<module name="VisibilityModifier">
<property name="protectedAllowed" value="true"/>
</module>
<!-- Require hash code override when equals is -->
<module name="EqualsHashCode"/>

3
src/main/java/org/apache/commons/math/dfp/Dfp.java
View File

@ -385,8 +385,9 @@ public class Dfp implements FieldElement<Dfp> {
negative = true;
continue;
}
if (fpexp.charAt(i) >= '0' && fpexp.charAt(i) <= '9')
if (fpexp.charAt(i) >= '0' && fpexp.charAt(i) <= '9') {
sciexp = sciexp * 10 + fpexp.charAt(i) - '0';
}
}
if (negative) {

3
src/main/java/org/apache/commons/math/dfp/DfpMath.java
View File

@ -684,8 +684,9 @@ public class DfpMath {
fact = fact.divide((i-1)*i); // 1 over fact
y = y.add(x.multiply(fact));
if (y.equals(py))
if (y.equals(py)) {
break;
}
py = new Dfp(y);
}

6
src/main/java/org/apache/commons/math/distribution/GammaDistributionImpl.java
View File

@ -154,9 +154,11 @@ public class GammaDistributionImpl extends AbstractContinuousDistribution
*/
@Override
public double density(double x) {
if (x < 0) return 0;
if (x < 0) {
return 0;
}
return FastMath.pow(x / beta, alpha - 1) / beta *
FastMath.exp(-x / beta) / FastMath.exp(Gamma.logGamma(alpha));
FastMath.exp(-x / beta) / FastMath.exp(Gamma.logGamma(alpha));
}
/**

5
src/main/java/org/apache/commons/math/distribution/KolmogorovSmirnovDistributionImpl.java
View File

@ -305,10 +305,11 @@ public class KolmogorovSmirnovDistributionImpl implements KolmogorovSmirnovDistr
*/
for (int i = 0; i < m; ++i) {
for (int j = 0; j < m; ++j) {
if (i - j + 1 < 0)
if (i - j + 1 < 0) {
Hdata[i][j] = BigFraction.ZERO;
else
} else {
Hdata[i][j] = BigFraction.ONE;
}
}
}

19
src/main/java/org/apache/commons/math/genetics/BinaryChromosome.java
View File

@ -49,11 +49,13 @@ public abstract class BinaryChromosome extends AbstractListChromosome<Integer> {
* {@inheritDoc}
*/
@Override
protected void checkValidity(List<Integer> chromosomeRepresentation) throws InvalidRepresentationException {
protected void checkValidity(List<Integer> chromosomeRepresentation)
throws InvalidRepresentationException {
for (int i : chromosomeRepresentation) {
if (i < 0 || i >1)
throw new InvalidRepresentationException(
LocalizedFormats.INVALID_BINARY_DIGIT, i);
if (i < 0 || i >1) {
throw new InvalidRepresentationException(LocalizedFormats.INVALID_BINARY_DIGIT,
i);
}
}
}
@ -77,16 +79,19 @@ public abstract class BinaryChromosome extends AbstractListChromosome<Integer> {
@Override
protected boolean isSame(Chromosome another) {
// type check
if (! (another instanceof BinaryChromosome))
if (! (another instanceof BinaryChromosome)) {
return false;
}
BinaryChromosome anotherBc = (BinaryChromosome) another;
// size check
if (getLength() != anotherBc.getLength())
if (getLength() != anotherBc.getLength()) {
return false;
}
for (int i=0; i< getRepresentation().size(); i++) {
if (!(getRepresentation().get(i).equals(anotherBc.getRepresentation().get(i))))
if (!(getRepresentation().get(i).equals(anotherBc.getRepresentation().get(i)))) {
return false;
}
}
// all is ok
return true;

3
src/main/java/org/apache/commons/math/genetics/Chromosome.java
View File

@ -88,8 +88,9 @@ public abstract class Chromosome implements Comparable<Chromosome>,Fitness {
*/
protected Chromosome findSameChromosome(Population population) {
for (Chromosome anotherChr : population) {
if (this.isSame(anotherChr))
if (this.isSame(anotherChr)) {
return anotherChr;
}
}
return null;
}

3
src/main/java/org/apache/commons/math/genetics/ElitisticListPopulation.java
View File

@ -94,8 +94,9 @@ public class ElitisticListPopulation extends ListPopulation {
* next generation [in %]
*/
public void setElitismRate(double elitismRate) {
if (elitismRate < 0 || elitismRate > 1)
if (elitismRate < 0 || elitismRate > 1) {
throw new IllegalArgumentException("Elitism rate has to be in [0,1]");
}
this.elitismRate = elitismRate;
}

3
src/main/java/org/apache/commons/math/genetics/FixedGenerationCount.java
View File

@ -39,8 +39,9 @@ public class FixedGenerationCount implements StoppingCondition {
* @param maxGenerations number of generations to evolve
*/
public FixedGenerationCount(int maxGenerations) {
if (maxGenerations <= 0)
if (maxGenerations <= 0) {
throw new IllegalArgumentException("The number of generations has to be >= 0");
}
this.maxGenerations = maxGenerations;
}

3
src/main/java/org/apache/commons/math/genetics/OnePointCrossover.java
View File

@ -84,8 +84,9 @@ public class OnePointCrossover<T> implements CrossoverPolicy {
*/
private ChromosomePair crossover(AbstractListChromosome<T> first, AbstractListChromosome<T> second) {
int length = first.getLength();
if (length != second.getLength())
if (length != second.getLength()) {
throw new IllegalArgumentException("Both chromosomes must have same lengths.");
}
// array representations of the parents
List<T> parent1Rep = first.getRepresentation();

9
src/main/java/org/apache/commons/math/genetics/RandomKey.java
View File

@ -149,12 +149,14 @@ public abstract class RandomKey<T> extends AbstractListChromosome<Double> implem
@Override
protected boolean isSame(Chromosome another) {
// type check
if (! (another instanceof RandomKey<?>))
if (! (another instanceof RandomKey<?>)) {
return false;
}
RandomKey<?> anotherRk = (RandomKey<?>) another;
// size check
if (getLength() != anotherRk.getLength())
if (getLength() != anotherRk.getLength()) {
return false;
}
// two different representations can still encode the same permutation
// the ordering is what counts
@ -162,8 +164,9 @@ public abstract class RandomKey<T> extends AbstractListChromosome<Double> implem
List<Integer> anotherPerm = anotherRk.baseSeqPermutation;
for (int i=0; i<getLength(); i++) {
if (thisPerm.get(i) != anotherPerm.get(i))
if (thisPerm.get(i) != anotherPerm.get(i)) {
return false;
}
}
// the permutations are the same
return true;

3
src/main/java/org/apache/commons/math/genetics/TournamentSelection.java
View File

@ -70,8 +70,9 @@ public class TournamentSelection implements SelectionPolicy {
* @return the selected chromosome.
*/
private Chromosome tournament(ListPopulation population) {
if (population.getPopulationSize() < this.arity)
if (population.getPopulationSize() < this.arity) {
throw new IllegalArgumentException("Tournament arity cannot be bigger than population size.");
}
// auxiliary population
ListPopulation tournamentPopulation = new ListPopulation(this.arity) {
public Population nextGeneration() {

5
src/main/java/org/apache/commons/math/geometry/euclidean/threed/Rotation.java
View File

@ -1018,8 +1018,9 @@ public class Rotation implements Serializable {
corr20 * corr20 + corr21 * corr21 + corr22 * corr22;
// convergence test
if (FastMath.abs(fn1 - fn) <= threshold)
return o;
if (FastMath.abs(fn1 - fn) <= threshold) {
return o;
}
// prepare next iteration
x00 = o0[0];

3
src/main/java/org/apache/commons/math/linear/EigenDecompositionImpl.java
View File

@ -556,8 +556,9 @@ public class EigenDecompositionImpl implements EigenDecomposition {
z[ia][i] = c * z[ia][i] - s * p;
}
}
if (t == 0.0 && i >= j)
if (t == 0.0 && i >= j) {
continue;
}
realEigenvalues[j] -= u;
e[j] = q;
e[m] = 0.0;

10
src/main/java/org/apache/commons/math/linear/SparseFieldVector.java
View File

@ -441,10 +441,11 @@ public class SparseFieldVector<T extends FieldElement<T>> implements FieldVector
/** {@inheritDoc} */
public FieldMatrix<T> outerProduct(FieldVector<T> v) {
if(v instanceof SparseFieldVector<?>)
if (v instanceof SparseFieldVector<?>) {
return outerProduct((SparseFieldVector<T>)v);
else
} else {
return outerProduct(v.toArray());
}
}
/** {@inheritDoc} */
@ -515,10 +516,11 @@ public class SparseFieldVector<T extends FieldElement<T>> implements FieldVector
/** {@inheritDoc} */
public FieldVector<T> subtract(FieldVector<T> v) {
if(v instanceof SparseFieldVector<?>)
if (v instanceof SparseFieldVector<?>) {
return subtract((SparseFieldVector<T>)v);
else
} else {
return subtract(v.toArray());
}
}
/** {@inheritDoc} */

13
src/main/java/org/apache/commons/math/ode/sampling/StepNormalizer.java
View File

@ -208,7 +208,9 @@ public class StepNormalizer implements StepHandler {
// Take the integration direction into account.
forward = interpolator.getCurrentTime() >= lastTime;
if (!forward) h = -h;
if (!forward) {
h = -h;
}
}
double nextTime = (mode == StepNormalizerMode.INCREMENT) ?
@ -252,8 +254,9 @@ public class StepNormalizer implements StepHandler {
*/
private boolean isNextInStep(double nextTime,
StepInterpolator interpolator) {
return forward ? nextTime <= interpolator.getCurrentTime()
: nextTime >= interpolator.getCurrentTime();
return forward ?
nextTime <= interpolator.getCurrentTime() :
nextTime >= interpolator.getCurrentTime();
}
/**
@ -263,7 +266,9 @@ public class StepNormalizer implements StepHandler {
* caller if the underlying user function triggers one
*/
private void doNormalizedStep(boolean isLast) throws MathUserException {
if (!bounds.firstIncluded() && firstTime == lastTime) return;
if (!bounds.firstIncluded() && firstTime == lastTime) {
return;
}
handler.handleStep(lastTime, lastState, lastDerivatives, isLast);
}

237
src/main/java/org/apache/commons/math/optimization/direct/CMAESOptimizer.java
View File

@ -372,14 +372,16 @@ public class CMAESOptimizer extends
for (int k = 0; k < lambda; k++) {
RealMatrix arxk = null;
for (int i = 0; i < checkFeasableCount+1; i++) {
if (diagonalOnly <= 0)
if (diagonalOnly <= 0) {
arxk = xmean.add(BD.multiply(arz.getColumnMatrix(k))
.scalarMultiply(sigma)); // m + sig * Normal(0,C)
else
} else {
arxk = xmean.add(times(diagD,arz.getColumnMatrix(k))
.scalarMultiply(sigma));
if (i >= checkFeasableCount || fitfun.isFeasible(arxk.getColumn(0)))
}
if (i >= checkFeasableCount || fitfun.isFeasible(arxk.getColumn(0))) {
break;
}
// regenerate random arguments for row
arz.setColumn(k, randn(dimension));
}
@ -399,10 +401,11 @@ public class CMAESOptimizer extends
RealMatrix bestArz = selectColumns(arz, MathUtils.copyOf(arindex, mu));
RealMatrix zmean = bestArz.multiply(weights);
boolean hsig = updateEvolutionPaths(zmean, xold);
if (diagonalOnly <= 0)
if (diagonalOnly <= 0) {
updateCovariance(hsig, bestArx, arz, arindex, xold);
else
} else {
updateCovarianceDiagonalOnly(hsig, bestArz, xold);
}
// Adapt step size sigma - Eq. (5)
sigma *= Math.exp(Math.min(1.0,(normps/chiN - 1.)*cs/damps));
double bestFitness = fitness[arindex[0]];
@ -414,56 +417,66 @@ public class CMAESOptimizer extends
fitfun.decode(bestArx.getColumn(0)),
isMinimize ? bestFitness : -bestFitness);
if (getConvergenceChecker() != null && lastResult != null) {
if (getConvergenceChecker().converged(
iterations, optimum, lastResult))
if (getConvergenceChecker().converged(iterations, optimum, lastResult)) {
break generationLoop;
}
}
}
// handle termination criteria
// Break, if fitness is good enough
if (stopfitness != 0) { // only if stopfitness is defined
if (bestFitness < (isMinimize ? stopfitness : -stopfitness))
if (bestFitness < (isMinimize ? stopfitness : -stopfitness)) {
break generationLoop;
}
}
double[] sqrtDiagC = sqrt(diagC).getColumn(0);
double[] pcCol = pc.getColumn(0);
for (int i = 0; i < dimension; i++) {
if (sigma*(Math.max(Math.abs(pcCol[i]), sqrtDiagC[i])) > stopTolX)
if (sigma*(Math.max(Math.abs(pcCol[i]), sqrtDiagC[i])) > stopTolX) {
break;
if (i >= dimension-1)
}
if (i >= dimension-1) {
break generationLoop;
}
}
for (int i = 0; i < dimension; i++)
if (sigma*sqrtDiagC[i] > stopTolUpX)
for (int i = 0; i < dimension; i++) {
if (sigma*sqrtDiagC[i] > stopTolUpX) {
break generationLoop;
}
}
double historyBest = min(fitnessHistory);
double historyWorst = max(fitnessHistory);
if (iterations > 2 && Math.max(historyWorst, worstFitness) -
Math.min(historyBest, bestFitness) < stopTolFun)
Math.min(historyBest, bestFitness) < stopTolFun) {
break generationLoop;
}
if (iterations > fitnessHistory.length &&
historyWorst-historyBest < stopTolHistFun)
historyWorst-historyBest < stopTolHistFun) {
break generationLoop;
}
// condition number of the covariance matrix exceeds 1e14
if (max(diagD)/min(diagD) > 1e7)
if (max(diagD)/min(diagD) > 1e7) {
break generationLoop;
}
// user defined termination
if (getConvergenceChecker() != null) {
RealPointValuePair current =
new RealPointValuePair(bestArx.getColumn(0),
isMinimize ? bestFitness : -bestFitness);
if (lastResult != null &&
getConvergenceChecker().converged(
iterations, current, lastResult))
getConvergenceChecker().converged(iterations, current, lastResult)) {
break generationLoop;
}
lastResult = current;
}
// Adjust step size in case of equal function values (flat fitness)
if (bestValue == fitness[arindex[(int)(0.1+lambda/4.)]])
if (bestValue == fitness[arindex[(int)(0.1+lambda/4.)]]) {
sigma = sigma * Math.exp(0.2+cs/damps);
}
if (iterations > 2 && Math.max(historyWorst, bestFitness) -
Math.min(historyBest, bestFitness) == 0)
Math.min(historyBest, bestFitness) == 0) {
sigma = sigma * Math.exp(0.2+cs/damps);
}
// store best in history
push(fitnessHistory,bestFitness);
fitfun.setValueRange(worstFitness-bestFitness);
@ -483,37 +496,45 @@ public class CMAESOptimizer extends
private void checkParameters() {
double[] init = getStartPoint();
if (boundaries != null) {
if (boundaries.length != 2)
if (boundaries.length != 2) {
throw new MultiDimensionMismatchException(
new Integer[] { boundaries.length },
new Integer[] { 2 });
if (boundaries[0] == null || boundaries[1] == null)
}
if (boundaries[0] == null || boundaries[1] == null) {
throw new NoDataException();
if (boundaries[0].length != init.length)
}
if (boundaries[0].length != init.length) {
throw new MultiDimensionMismatchException(
new Integer[] { boundaries[0].length },
new Integer[] { init.length });
if (boundaries[1].length != init.length)
}
if (boundaries[1].length != init.length) {
throw new MultiDimensionMismatchException(
new Integer[] { boundaries[1].length },
new Integer[] { init.length });
}
for (int i = 0; i < init.length; i++) {
if (boundaries[0][i] > init[i] || boundaries[1][i] < init[i])
if (boundaries[0][i] > init[i] || boundaries[1][i] < init[i]) {
throw new OutOfRangeException(init[i], boundaries[0][i],
boundaries[1][i]);
}
}
}
if (inputSigma != null) {
if (inputSigma.length != init.length)
if (inputSigma.length != init.length) {
throw new MultiDimensionMismatchException(
new Integer[] { inputSigma.length },
new Integer[] { init.length });
}
for (int i = 0; i < init.length; i++) {
if (inputSigma[i] < 0)
if (inputSigma[i] < 0) {
throw new NotPositiveException(inputSigma[i]);
}
if (boundaries != null) {
if (inputSigma[i] > 1.0)
if (inputSigma[i] > 1.0) {
throw new OutOfRangeException(inputSigma[i], 0, 1.0);
}
}
}
}
@ -527,12 +548,14 @@ public class CMAESOptimizer extends
*/
private void initializeCMA(double[] guess) {
if (lambda <= 0)
if (lambda <= 0) {
lambda = 4 + (int) (3. * Math.log(dimension));
}
// initialize sigma
double[][] sigmaArray = new double[guess.length][1];
for (int i = 0; i < guess.length; i++)
for (int i = 0; i < guess.length; i++) {
sigmaArray[i][0] = inputSigma != null ? inputSigma[i] : 0.3;
}
RealMatrix insigma = new Array2DRowRealMatrix(sigmaArray, false);
sigma = max(insigma); // overall standard deviation
@ -587,8 +610,9 @@ public class CMAESOptimizer extends
C = B.multiply(diag(square(D)).multiply(B.transpose())); // covariance
historySize = 10 + (int) (3. * 10. * dimension / lambda);
fitnessHistory = new double[historySize]; // history of fitness values
for (int i = 0; i < historySize; i++)
for (int i = 0; i < historySize; i++) {
fitnessHistory[i] = Double.MAX_VALUE;
}
}
/**
@ -610,9 +634,10 @@ public class CMAESOptimizer extends
Math.sqrt(1. - Math.pow(1. - cs, 2. * iterations)) /
chiN < 1.4 + 2. / (dimension + 1.);
pc = pc.scalarMultiply(1. - cc);
if (hsig)
if (hsig) {
pc = pc.add(xmean.subtract(xold).scalarMultiply(
Math.sqrt(cc * (2. - cc) * mueff) / sigma));
}
return hsig;
}
@ -699,8 +724,9 @@ public class CMAESOptimizer extends
// check and set learning rate negccov
double negcovMax = (1. - negminresidualvariance) /
square(arnormsInv).multiply(weights).getEntry(0, 0);
if (negccov > negcovMax)
if (negccov > negcovMax) {
negccov = negcovMax;
}
arzneg = times(arzneg, repmat(arnormsInv, dimension, 1));
RealMatrix artmp = BD.multiply(arzneg);
RealMatrix Cneg = artmp.multiply(diag(weights)).multiply(
@ -748,9 +774,11 @@ public class CMAESOptimizer extends
D = eig.getD();
diagD = diag(D);
if (min(diagD) <= 0) {
for (int i = 0; i < dimension; i++)
if (diagD.getEntry(i, 0) < 0)
for (int i = 0; i < dimension; i++) {
if (diagD.getEntry(i, 0) < 0) {
diagD.setEntry(i, 0, 0.);
}
}
double tfac = max(diagD) / 1e14;
C = C.add(eye(dimension, dimension).scalarMultiply(tfac));
diagD = diagD.add(ones(dimension, 1).scalarMultiply(tfac));
@ -775,8 +803,9 @@ public class CMAESOptimizer extends
* current best fitness value
*/
private static void push(double[] vals, double val) {
for (int i = vals.length-1; i > 0; i--)
for (int i = vals.length-1; i > 0; i--) {
vals[i] = vals[i-1];
}
vals[0] = val;
}
@ -789,12 +818,14 @@ public class CMAESOptimizer extends
*/
private int[] sortedIndices(final double[] doubles) {
DoubleIndex[] dis = new DoubleIndex[doubles.length];
for (int i = 0; i < doubles.length; i++)
for (int i = 0; i < doubles.length; i++) {
dis[i] = new DoubleIndex(doubles[i], i);
}
Arrays.sort(dis);
int[] indices = new int[doubles.length];
for (int i = 0; i < doubles.length; i++)
for (int i = 0; i < doubles.length; i++) {
indices[i] = dis[i].index;
}
return indices;
}
@ -854,8 +885,9 @@ public class CMAESOptimizer extends
* @return Normalized objective variables.
*/
public double[] encode(final double[] x) {
if (boundaries == null)
if (boundaries == null) {
return x;
}
double[] res = new double[x.length];
for (int i = 0; i < x.length; i++) {
double diff = boundaries[1][i] - boundaries[0][i];
@ -870,8 +902,9 @@ public class CMAESOptimizer extends
* @return Original objective variables.
*/
public double[] decode(final double[] x) {
if (boundaries == null)
if (boundaries == null) {
return x;
}
double[] res = new double[x.length];
for (int i = 0; i < x.length; i++) {
double diff = boundaries[1][i] - boundaries[0][i];
@ -892,9 +925,10 @@ public class CMAESOptimizer extends
value = CMAESOptimizer.this
.computeObjectiveValue(decode(repaired)) +
penalty(point, repaired);
} else
} else {
value = CMAESOptimizer.this
.computeObjectiveValue(decode(point));
}
return isMinimize ? value : -value;
}
@ -904,13 +938,16 @@ public class CMAESOptimizer extends
* @return True if in bounds
*/
public boolean isFeasible(final double[] x) {
if (boundaries == null)
if (boundaries == null) {
return true;
}
for (int i = 0; i < x.length; i++) {
if (x[i] < 0)
if (x[i] < 0) {
return false;
if (x[i] > 1.0)
}
if (x[i] > 1.0) {
return false;
}
}
return true;
}
@ -931,12 +968,13 @@ public class CMAESOptimizer extends
private double[] repair(final double[] x) {
double[] repaired = new double[x.length];
for (int i = 0; i < x.length; i++) {
if (x[i] < 0)
if (x[i] < 0) {
repaired[i] = 0;
else if (x[i] > 1.0)
} else if (x[i] > 1.0) {
repaired[i] = 1.0;
else
} else {
repaired[i] = x[i];
}
}
return repaired;
}
@ -967,9 +1005,11 @@ public class CMAESOptimizer extends
*/
private static RealMatrix log(final RealMatrix m) {
double[][] d = new double[m.getRowDimension()][m.getColumnDimension()];
for (int r = 0; r < m.getRowDimension(); r++)
for (int c = 0; c < m.getColumnDimension(); c++)
for (int r = 0; r < m.getRowDimension(); r++) {
for (int c = 0; c < m.getColumnDimension(); c++) {
d[r][c] = Math.log(m.getEntry(r, c));
}
}
return new Array2DRowRealMatrix(d, false);
}
@ -980,9 +1020,11 @@ public class CMAESOptimizer extends
*/
private static RealMatrix sqrt(final RealMatrix m) {
double[][] d = new double[m.getRowDimension()][m.getColumnDimension()];
for (int r = 0; r < m.getRowDimension(); r++)
for (int c = 0; c < m.getColumnDimension(); c++)
for (int r = 0; r < m.getRowDimension(); r++) {
for (int c = 0; c < m.getColumnDimension(); c++) {
d[r][c] = Math.sqrt(m.getEntry(r, c));
}
}
return new Array2DRowRealMatrix(d, false);
}
@ -992,11 +1034,12 @@ public class CMAESOptimizer extends
*/
private static RealMatrix square(final RealMatrix m) {
double[][] d = new double[m.getRowDimension()][m.getColumnDimension()];
for (int r = 0; r < m.getRowDimension(); r++)
for (int r = 0; r < m.getRowDimension(); r++) {
for (int c = 0; c < m.getColumnDimension(); c++) {
double e = m.getEntry(r, c);
d[r][c] = e * e;
}
}
return new Array2DRowRealMatrix(d, false);
}
@ -1009,9 +1052,11 @@ public class CMAESOptimizer extends
*/
private static RealMatrix times(final RealMatrix m, final RealMatrix n) {
double[][] d = new double[m.getRowDimension()][m.getColumnDimension()];
for (int r = 0; r < m.getRowDimension(); r++)
for (int c = 0; c < m.getColumnDimension(); c++)
for (int r = 0; r < m.getRowDimension(); r++) {
for (int c = 0; c < m.getColumnDimension(); c++) {
d[r][c] = m.getEntry(r, c)*n.getEntry(r, c);
}
}
return new Array2DRowRealMatrix(d, false);
}
@ -1024,9 +1069,11 @@ public class CMAESOptimizer extends
*/
private static RealMatrix divide(final RealMatrix m, final RealMatrix n) {
double[][] d = new double[m.getRowDimension()][m.getColumnDimension()];
for (int r = 0; r < m.getRowDimension(); r++)
for (int c = 0; c < m.getColumnDimension(); c++)
for (int r = 0; r < m.getRowDimension(); r++) {
for (int c = 0; c < m.getColumnDimension(); c++) {
d[r][c] = m.getEntry(r, c)/n.getEntry(r, c);
}
}
return new Array2DRowRealMatrix(d, false);
}
@ -1037,9 +1084,11 @@ public class CMAESOptimizer extends
*/
private static RealMatrix selectColumns(final RealMatrix m, final int[] cols) {
double[][] d = new double[m.getRowDimension()][cols.length];
for (int r = 0; r < m.getRowDimension(); r++)
for (int c = 0; c < cols.length; c++)
for (int r = 0; r < m.getRowDimension(); r++) {
for (int c = 0; c < cols.length; c++) {
d[r][c] = m.getEntry(r, cols[c]);
}
}
return new Array2DRowRealMatrix(d, false);
}
@ -1050,10 +1099,12 @@ public class CMAESOptimizer extends
*/
private static RealMatrix triu(final RealMatrix m, int k) {
double[][] d = new double[m.getRowDimension()][m.getColumnDimension()];
for (int r = 0; r < m.getRowDimension(); r++)
for (int c = 0; c < m.getColumnDimension(); c++)
for (int r = 0; r < m.getRowDimension(); r++) {
for (int c = 0; c < m.getColumnDimension(); c++) {
d[r][c] = r <= c - k ? m.getEntry(r, c) : 0;
return new Array2DRowRealMatrix(d, false);
}
}
return new Array2DRowRealMatrix(d, false);
}
/**
@ -1065,8 +1116,9 @@ public class CMAESOptimizer extends
double[][] d = new double[1][m.getColumnDimension()];
for (int c = 0; c < m.getColumnDimension(); c++) {
double sum = 0;
for (int r = 0; r < m.getRowDimension(); r++)
for (int r = 0; r < m.getRowDimension(); r++) {
sum += m.getEntry(r, c);
}
d[0][c] = sum;
}
return new Array2DRowRealMatrix(d, false);
@ -1081,13 +1133,15 @@ public class CMAESOptimizer extends
private static RealMatrix diag(final RealMatrix m) {
if (m.getColumnDimension() == 1) {
double[][] d = new double[m.getRowDimension()][m.getRowDimension()];
for (int i = 0; i < m.getRowDimension(); i++)
for (int i = 0; i < m.getRowDimension(); i++) {
d[i][i] = m.getEntry(i, 0);
}
return new Array2DRowRealMatrix(d, false);
} else {
double[][] d = new double[m.getRowDimension()][1];
for (int i = 0; i < m.getColumnDimension(); i++)
for (int i = 0; i < m.getColumnDimension(); i++) {
d[i][0] = m.getEntry(i, i);
}
return new Array2DRowRealMatrix(d, false);
}
}
@ -1105,8 +1159,9 @@ public class CMAESOptimizer extends
* Target column.
*/
private static void copyColumn(final RealMatrix m1, int col1, RealMatrix m2, int col2) {
for (int i = 0; i < m1.getRowDimension(); i++)
for (int i = 0; i < m1.getRowDimension(); i++) {
m2.setEntry(i, col2, m1.getEntry(i, col1));
}
}
/**
@ -1118,8 +1173,9 @@ public class CMAESOptimizer extends
*/
private static RealMatrix ones(int n, int m) {
double[][] d = new double[n][m];
for (int r = 0; r < n; r++)
for (int r = 0; r < n; r++) {
Arrays.fill(d[r], 1.0);
}
return new Array2DRowRealMatrix(d, false);
}
@ -1132,9 +1188,11 @@ public class CMAESOptimizer extends
*/
private static RealMatrix eye(int n, int m) {
double[][] d = new double[n][m];
for (int r = 0; r < n; r++)
if (r < m)
for (int r = 0; r < n; r++) {
if (r < m) {
d[r][r] = 1;
}
}
return new Array2DRowRealMatrix(d, false);
}
@ -1162,9 +1220,11 @@ public class CMAESOptimizer extends
int rd = mat.getRowDimension();
int cd = mat.getColumnDimension();
double[][] d = new double[n * rd][m * cd];
for (int r = 0; r < n * rd; r++)
for (int c = 0; c < m * cd; c++)
for (int r = 0; r < n * rd; r++) {
for (int c = 0; c < m * cd; c++) {
d[r][c] = mat.getEntry(r % rd, c % cd);
}
}
return new Array2DRowRealMatrix(d, false);
}
@ -1195,12 +1255,14 @@ public class CMAESOptimizer extends
*/
private static double max(final RealMatrix m) {
double max = -Double.MAX_VALUE;
for (int r = 0; r < m.getRowDimension(); r++)
for (int r = 0; r < m.getRowDimension(); r++) {
for (int c = 0; c < m.getColumnDimension(); c++) {
double e = m.getEntry(r, c);
if (max < e)
if (max < e) {
max = e;
}
}
}
return max;
}
@ -1211,12 +1273,14 @@ public class CMAESOptimizer extends
*/
private static double min(final RealMatrix m) {
double min = Double.MAX_VALUE;
for (int r = 0; r < m.getRowDimension(); r++)
for (int r = 0; r < m.getRowDimension(); r++) {
for (int c = 0; c < m.getColumnDimension(); c++) {
double e = m.getEntry(r, c);
if (min > e)
if (min > e) {
min = e;
}
}
}
return min;
}
@ -1227,9 +1291,11 @@ public class CMAESOptimizer extends
*/
private static double max(final double[] m) {
double max = -Double.MAX_VALUE;
for (int r = 0; r < m.length; r++)
if (max < m[r])
for (int r = 0; r < m.length; r++) {
if (max < m[r]) {
max = m[r];
}
}
return max;
}
@ -1240,9 +1306,11 @@ public class CMAESOptimizer extends
*/
private static double min(final double[] m) {
double min = Double.MAX_VALUE;
for (int r = 0; r < m.length; r++)
if (min > m[r])
for (int r = 0; r < m.length; r++) {
if (min > m[r]) {
min = m[r];
}
}
return min;
}
@ -1253,8 +1321,9 @@ public class CMAESOptimizer extends
*/
private static int[] inverse(final int[] indices) {
int[] inverse = new int[indices.length];
for (int i = 0; i < indices.length; i++)
for (int i = 0; i < indices.length; i++) {
inverse[indices[i]] = i;
}
return inverse;
}
@ -1265,8 +1334,9 @@ public class CMAESOptimizer extends
*/
private static int[] reverse(final int[] indices) {
int[] reverse = new int[indices.length];
for (int i = 0; i < indices.length; i++)
for (int i = 0; i < indices.length; i++) {
reverse[i] = indices[indices.length - i - 1];
}
return reverse;
}
@ -1277,8 +1347,9 @@ public class CMAESOptimizer extends
*/
private double[] randn(int size) {
double[] randn = new double[size];
for (int i = 0; i < size; i++)
for (int i = 0; i < size; i++) {
randn[i] = random.nextGaussian();
}
return randn;
}
@ -1291,9 +1362,11 @@ public class CMAESOptimizer extends
*/
private RealMatrix randn1(int size, int popSize) {
double[][] d = new double[size][popSize];
for (int r = 0; r < size; r++)
for (int c = 0; c < popSize; c++)
for (int r = 0; r < size; r++) {
for (int c = 0; c < popSize; c++) {
d[r][c] = random.nextGaussian();
}
}
return new Array2DRowRealMatrix(d, false);
}
}

12
src/main/java/org/apache/commons/math/stat/Frequency.java
View File

@ -491,16 +491,20 @@ public class Frequency implements Serializable {
/** {@inheritDoc} */
@Override
public boolean equals(Object obj) {
if (this == obj)
if (this == obj) {
return true;
if (!(obj instanceof Frequency))
}
if (!(obj instanceof Frequency)) {
return false;
}
Frequency other = (Frequency) obj;
if (freqTable == null) {
if (other.freqTable != null)
if (other.freqTable != null) {
return false;
} else if (!freqTable.equals(other.freqTable))
}
} else if (!freqTable.equals(other.freqTable)) {
return false;
}
return true;
}

18
src/main/java/org/apache/commons/math/stat/descriptive/moment/VectorialCovariance.java
View File

@ -133,19 +133,25 @@ public class VectorialCovariance implements Serializable {
/** {@inheritDoc} */
@Override
public boolean equals(Object obj) {
if (this == obj)
if (this == obj) {
return true;
if (!(obj instanceof VectorialCovariance))
}
if (!(obj instanceof VectorialCovariance)) {
return false;
}
VectorialCovariance other = (VectorialCovariance) obj;
if (isBiasCorrected != other.isBiasCorrected)
if (isBiasCorrected != other.isBiasCorrected) {
return false;
if (n != other.n)
}
if (n != other.n) {
return false;
if (!Arrays.equals(productsSums, other.productsSums))
}
if (!Arrays.equals(productsSums, other.productsSums)) {
return false;
if (!Arrays.equals(sums, other.sums))
}
if (!Arrays.equals(sums, other.sums)) {
return false;
}
return true;
}

9
src/main/java/org/apache/commons/math/stat/descriptive/moment/VectorialMean.java
View File

@ -90,13 +90,16 @@ public class VectorialMean implements Serializable {
/** {@inheritDoc} */
@Override
public boolean equals(Object obj) {
if (this == obj)
if (this == obj) {
return true;
if (!(obj instanceof VectorialMean))
}
if (!(obj instanceof VectorialMean)) {
return false;
}
VectorialMean other = (VectorialMean) obj;
if (!Arrays.equals(means, other.means))
if (!Arrays.equals(means, other.means)) {
return false;
}
return true;
}

5
src/main/java/org/apache/commons/math/transform/FastFourierTransformer.java
View File

@ -576,10 +576,11 @@ public class FastFourierTransformer implements Serializable {
temp[i] = mdcm.get(subVector);
}
if (forward)
if (forward) {
temp = transform2(temp);
else
} else {
temp = inversetransform2(temp);
}
for (int i = 0; i < dimensionSize[d]; i++) {
subVector[d] = i;

14
src/main/java/org/apache/commons/math/util/FastMath.java
View File

@ -1608,8 +1608,9 @@ public class FastMath {
}
if (y == Double.POSITIVE_INFINITY) {
if (x * x == 1.0)
return Double.NaN;
if (x * x == 1.0) {
return Double.NaN;
}
if (x * x > 1.0) {
return Double.POSITIVE_INFINITY;
@ -2577,8 +2578,9 @@ public class FastMath {
remA = a + b;
remB += -(remA - b - a);
if (remA > 0.0)
if (remA > 0.0) {
break;
}
// Remainder is negative, so decrement k and try again.
// This should only happen if the input is very close
@ -2662,8 +2664,9 @@ public class FastMath {
remA = a + b;
remB += -(remA - b - a);
if (remA > 0.0)
if (remA > 0.0) {
break;
}
// Remainder is negative, so decrement k and try again.
// This should only happen if the input is very close
@ -2757,8 +2760,9 @@ public class FastMath {
remA = a + b;
remB += -(remA - b - a);
if (remA > 0.0)
if (remA > 0.0) {
break;
}
// Remainder is negative, so decrement k and try again.
// This should only happen if the input is very close

3
src/main/java/org/apache/commons/math/util/MathUtils.java
View File

@ -210,8 +210,9 @@ public final class MathUtils {
return n;
}
// Use symmetry for large k
if (k > n / 2)
if (k > n / 2) {
return binomialCoefficient(n, n - k);
}
// We use the formula
// (n choose k) = n! / (n-k)! / k!

4
src/main/java/org/apache/commons/math/util/ResizableDoubleArray.java
View File

@ -502,7 +502,9 @@ public class ResizableDoubleArray implements DoubleArray, Serializable {
} else {
// "Subtract" this number of discarded from numElements
numElements -= i;
if (front) startIndex += i;
if (front) {
startIndex += i;
}
}
if (shouldContract()) {
contract();