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wrap lines *after* operator, to keep checkstyle happy 

git-svn-id: https://svn.apache.org/repos/asf/commons/proper/math/trunk@613600 13f79535-47bb-0310-9956-ffa450edef68
This commit is contained in:
Luc Maisonobe 2008-01-20 16:35:54 +00:00
parent ab1f56eacb
commit 540babda6c
22 changed files with 183 additions and 200 deletions
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32
src/java/org/apache/commons/math/MessagesResources_fr.java
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@ -124,25 +124,25 @@ public class MessagesResources_fr
// org.apache.commons.math.ode.AdaptiveStepsizeIntegrator // org.apache.commons.math.ode.AdaptiveStepsizeIntegrator
{ "minimal step size ({0}) reached, integration needs {1}", { "minimal step size ({0}) reached, integration needs {1}",
"pas minimal ({0}) atteint, l''int\u00e9gration n\u00e9cessite {1}" }, "pas minimal ({0}) atteint, l''int\u00e9gration n\u00e9cessite {1}" },
{ "dimensions mismatch: state vector has dimension {0}," { "dimensions mismatch: state vector has dimension {0}," +
+ " absolute tolerance vector has dimension {1}", " absolute tolerance vector has dimension {1}",
"incompatibilit\u00e9 de dimensions entre le vecteur d''\u00e9tat ({0})," "incompatibilit\u00e9 de dimensions entre le vecteur d''\u00e9tat ({0})," +
+ " et le vecteur de tol\u00e9rance absolue ({1})" }, " et le vecteur de tol\u00e9rance absolue ({1})" },
{ "dimensions mismatch: state vector has dimension {0}," { "dimensions mismatch: state vector has dimension {0}," +
+ " relative tolerance vector has dimension {1}", " relative tolerance vector has dimension {1}",
"incompatibilit\u00e9 de dimensions entre le vecteur d''\u00e9tat ({0})," "incompatibilit\u00e9 de dimensions entre le vecteur d''\u00e9tat ({0})," +
+ " et le vecteur de tol\u00e9rance relative ({1})" }, " et le vecteur de tol\u00e9rance relative ({1})" },
// org.apache.commons.math.ode.AdaptiveStepsizeIntegrator, // org.apache.commons.math.ode.AdaptiveStepsizeIntegrator,
// org.apache.commons.math.ode.RungeKuttaIntegrator // org.apache.commons.math.ode.RungeKuttaIntegrator
{ "dimensions mismatch: ODE problem has dimension {0}," { "dimensions mismatch: ODE problem has dimension {0}," +
+ " initial state vector has dimension {1}", " initial state vector has dimension {1}",
"incompatibilit\u00e9 de dimensions entre le probl\u00e8me ODE ({0})," "incompatibilit\u00e9 de dimensions entre le probl\u00e8me ODE ({0})," +
+ " et le vecteur d''\u00e9tat initial ({1})" }, " et le vecteur d''\u00e9tat initial ({1})" },
{ "dimensions mismatch: ODE problem has dimension {0}," { "dimensions mismatch: ODE problem has dimension {0}," +
+ " final state vector has dimension {1}", " final state vector has dimension {1}",
"incompatibilit\u00e9 de dimensions entre le probl\u00e8me ODE ({0})," "incompatibilit\u00e9 de dimensions entre le probl\u00e8me ODE ({0})," +
+ " et le vecteur d''\u00e9tat final ({1})" }, " et le vecteur d''\u00e9tat final ({1})" },
{ "too small integration interval: length = {0}", { "too small integration interval: length = {0}",
"intervalle d''int\u00e9gration trop petit : {0}" }, "intervalle d''int\u00e9gration trop petit : {0}" },

6
src/java/org/apache/commons/math/analysis/BrentSolver.java
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@ -65,9 +65,9 @@ public class BrentSolver extends UnivariateRealSolverImpl {
throws MaxIterationsExceededException, FunctionEvaluationException { throws MaxIterationsExceededException, FunctionEvaluationException {
if (((initial - min) * (max -initial)) < 0) { if (((initial - min) * (max -initial)) < 0) {
throw new IllegalArgumentException("Initial guess is not in search" throw new IllegalArgumentException("Initial guess is not in search" +
+ " interval." + " Initial: " + initial " interval." + " Initial: " + initial +
+ " Endpoints: [" + min + "," + max + "]"); " Endpoints: [" + min + "," + max + "]");
} }
// return the initial guess if it is good enough // return the initial guess if it is good enough

8
src/java/org/apache/commons/math/distribution/PascalDistributionImpl.java
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@ -146,10 +146,10 @@ public class PascalDistributionImpl extends AbstractIntegerDistribution
if (x < 0) { if (x < 0) {
ret = 0.0; ret = 0.0;
} else { } else {
ret = MathUtils.binomialCoefficientDouble(x ret = MathUtils.binomialCoefficientDouble(x +
+ getNumberOfSuccesses() - 1, getNumberOfSuccesses() - 1) getNumberOfSuccesses() - 1, getNumberOfSuccesses() - 1) *
* Math.pow(getProbabilityOfSuccess(), getNumberOfSuccesses()) Math.pow(getProbabilityOfSuccess(), getNumberOfSuccesses()) *
* Math.pow(1.0 - getProbabilityOfSuccess(), x); Math.pow(1.0 - getProbabilityOfSuccess(), x);
} }
return ret; return ret;
} }

6
src/java/org/apache/commons/math/estimation/GaussNewtonEstimator.java
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@ -164,9 +164,9 @@ public class GaussNewtonEstimator extends AbstractEstimator implements Serializa
previous = cost; previous = cost;
updateResidualsAndCost(); updateResidualsAndCost();
} while ((getCostEvaluations() < 2) } while ((getCostEvaluations() < 2) ||
|| (Math.abs(previous - cost) > (cost * steadyStateThreshold) (Math.abs(previous - cost) > (cost * steadyStateThreshold) &&
&& (Math.abs(cost) > convergence))); (Math.abs(cost) > convergence)));
} }

35
src/java/org/apache/commons/math/estimation/LevenbergMarquardtEstimator.java
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@ -257,8 +257,7 @@ public class LevenbergMarquardtEstimator extends AbstractEstimator implements Se
xNorm = Math.sqrt(xNorm); xNorm = Math.sqrt(xNorm);
// initialize the step bound delta // initialize the step bound delta
delta = (xNorm == 0) delta = (xNorm == 0) ? initialStepBoundFactor : (initialStepBoundFactor * xNorm);
? initialStepBoundFactor : (initialStepBoundFactor * xNorm);
} }
@ -388,30 +387,28 @@ public class LevenbergMarquardtEstimator extends AbstractEstimator implements Se
} }
// tests for convergence. // tests for convergence.
if (((Math.abs(actRed) <= costRelativeTolerance) if (((Math.abs(actRed) <= costRelativeTolerance) &&
&& (preRed <= costRelativeTolerance) (preRed <= costRelativeTolerance) &&
&& (ratio <= 2.0)) (ratio <= 2.0)) ||
|| (delta <= parRelativeTolerance * xNorm)) { (delta <= parRelativeTolerance * xNorm)) {
return; return;
} }
// tests for termination and stringent tolerances // tests for termination and stringent tolerances
// (2.2204e-16 is the machine epsilon for IEEE754) // (2.2204e-16 is the machine epsilon for IEEE754)
if ((Math.abs(actRed) <= 2.2204e-16) if ((Math.abs(actRed) <= 2.2204e-16) && (preRed <= 2.2204e-16) && (ratio <= 2.0)) {
&& (preRed <= 2.2204e-16) throw new EstimationException("cost relative tolerance is too small ({0})," +
&& (ratio <= 2.0)) { " no further reduction in the" +
throw new EstimationException("cost relative tolerance is too small ({0})," " sum of squares is possible",
+ " no further reduction in the"
+ " sum of squares is possible",
new Object[] { new Double(costRelativeTolerance) }); new Object[] { new Double(costRelativeTolerance) });
} else if (delta <= 2.2204e-16 * xNorm) { } else if (delta <= 2.2204e-16 * xNorm) {
throw new EstimationException("parameters relative tolerance is too small" throw new EstimationException("parameters relative tolerance is too small" +
+ " ({0}), no further improvement in" " ({0}), no further improvement in" +
+ " the approximate solution is possible", " the approximate solution is possible",
new Object[] { new Double(parRelativeTolerance) }); new Object[] { new Double(parRelativeTolerance) });
} else if (maxCosine <= 2.2204e-16) { } else if (maxCosine <= 2.2204e-16) {
throw new EstimationException("orthogonality tolerance is too small ({0})," throw new EstimationException("orthogonality tolerance is too small ({0})," +
+ " solution is orthogonal to the jacobian", " solution is orthogonal to the jacobian",
new Object[] { new Double(orthoTolerance) }); new Object[] { new Double(orthoTolerance) });
} }
@ -553,8 +550,8 @@ public class LevenbergMarquardtEstimator extends AbstractEstimator implements Se
// if the function is small enough, accept the current value // if the function is small enough, accept the current value
// of lmPar, also test for the exceptional cases where parl is zero // of lmPar, also test for the exceptional cases where parl is zero
if ((Math.abs(fp) <= 0.1 * delta) if ((Math.abs(fp) <= 0.1 * delta) ||
|| ((parl == 0) && (fp <= previousFP) && (previousFP < 0))) { ((parl == 0) && (fp <= previousFP) && (previousFP < 0))) {
return; return;
} }

46
src/java/org/apache/commons/math/geometry/Rotation.java
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@ -192,10 +192,10 @@ public class Rotation implements Serializable {
throws NotARotationMatrixException { throws NotARotationMatrixException {
// dimension check // dimension check
if ((m.length != 3) || (m[0].length != 3) if ((m.length != 3) || (m[0].length != 3) ||
|| (m[1].length != 3) || (m[2].length != 3)) { (m[1].length != 3) || (m[2].length != 3)) {
throw new NotARotationMatrixException("a {0}x{1} matrix" throw new NotARotationMatrixException("a {0}x{1} matrix" +
+ " cannot be a rotation matrix", " cannot be a rotation matrix",
new String[] { new String[] {
Integer.toString(m.length), Integer.toString(m.length),
Integer.toString(m[0].length) Integer.toString(m[0].length)
@ -206,12 +206,12 @@ public class Rotation implements Serializable {
double[][] ort = orthogonalizeMatrix(m, threshold); double[][] ort = orthogonalizeMatrix(m, threshold);
// check the sign of the determinant // check the sign of the determinant
double det = ort[0][0] * (ort[1][1] * ort[2][2] - ort[2][1] * ort[1][2]) double det = ort[0][0] * (ort[1][1] * ort[2][2] - ort[2][1] * ort[1][2]) -
- ort[1][0] * (ort[0][1] * ort[2][2] - ort[2][1] * ort[0][2]) ort[1][0] * (ort[0][1] * ort[2][2] - ort[2][1] * ort[0][2]) +
+ ort[2][0] * (ort[0][1] * ort[1][2] - ort[1][1] * ort[0][2]); ort[2][0] * (ort[0][1] * ort[1][2] - ort[1][1] * ort[0][2]);
if (det < 0.0) { if (det < 0.0) {
throw new NotARotationMatrixException("the closest orthogonal matrix" throw new NotARotationMatrixException("the closest orthogonal matrix" +
+ " has a negative determinant {0}", " has a negative determinant {0}",
new String[] { new String[] {
Double.toString(det) Double.toString(det)
}); });
@ -337,9 +337,9 @@ public class Rotation implements Serializable {
Vector3D k = new Vector3D(dy1 * dz2 - dz1 * dy2, Vector3D k = new Vector3D(dy1 * dz2 - dz1 * dy2,
dz1 * dx2 - dx1 * dz2, dz1 * dx2 - dx1 * dz2,
dx1 * dy2 - dy1 * dx2); dx1 * dy2 - dy1 * dx2);
double c = k.getX() * (u1y * u2z - u1z * u2y) double c = k.getX() * (u1y * u2z - u1z * u2y) +
+ k.getY() * (u1z * u2x - u1x * u2z) k.getY() * (u1z * u2x - u1x * u2z) +
+ k.getZ() * (u1x * u2y - u1y * u2x); k.getZ() * (u1x * u2y - u1y * u2x);
if (c == 0) { if (c == 0) {
// the (q1, q2, q3) vector is in the (u1, u2) plane // the (q1, q2, q3) vector is in the (u1, u2) plane
@ -359,9 +359,9 @@ public class Rotation implements Serializable {
k = new Vector3D(dy1 * dz3 - dz1 * dy3, k = new Vector3D(dy1 * dz3 - dz1 * dy3,
dz1 * dx3 - dx1 * dz3, dz1 * dx3 - dx1 * dz3,
dx1 * dy3 - dy1 * dx3); dx1 * dy3 - dy1 * dx3);
c = k.getX() * (u1y * u3z - u1z * u3y) c = k.getX() * (u1y * u3z - u1z * u3y) +
+ k.getY() * (u1z * u3x - u1x * u3z) k.getY() * (u1z * u3x - u1x * u3z) +
+ k.getZ() * (u1x * u3y - u1y * u3x); k.getZ() * (u1x * u3y - u1y * u3x);
if (c == 0) { if (c == 0) {
// the (q1, q2, q3) vector is aligned with u1: // the (q1, q2, q3) vector is aligned with u1:
@ -369,9 +369,9 @@ public class Rotation implements Serializable {
k = new Vector3D(dy2 * dz3 - dz2 * dy3, k = new Vector3D(dy2 * dz3 - dz2 * dy3,
dz2 * dx3 - dx2 * dz3, dz2 * dx3 - dx2 * dz3,
dx2 * dy3 - dy2 * dx3); dx2 * dy3 - dy2 * dx3);
c = k.getX() * (u2y * u3z - u2z * u3y) c = k.getX() * (u2y * u3z - u2z * u3y) +
+ k.getY() * (u2z * u3x - u2x * u3z) k.getY() * (u2z * u3x - u2x * u3z) +
+ k.getZ() * (u2x * u3y - u2y * u3x); k.getZ() * (u2x * u3y - u2y * u3x);
if (c == 0) { if (c == 0) {
// the (q1, q2, q3) vector is aligned with everything // the (q1, q2, q3) vector is aligned with everything
@ -986,9 +986,9 @@ public class Rotation implements Serializable {
double corr22 = o2[2] - m2[2]; double corr22 = o2[2] - m2[2];
// Frobenius norm of the correction // Frobenius norm of the correction
fn1 = corr00 * corr00 + corr01 * corr01 + corr02 * corr02 fn1 = corr00 * corr00 + corr01 * corr01 + corr02 * corr02 +
+ corr10 * corr10 + corr11 * corr11 + corr12 * corr12 corr10 * corr10 + corr11 * corr11 + corr12 * corr12 +
+ corr20 * corr20 + corr21 * corr21 + corr22 * corr22; corr20 * corr20 + corr21 * corr21 + corr22 * corr22;
// convergence test // convergence test
if (Math.abs(fn1 - fn) <= threshold) if (Math.abs(fn1 - fn) <= threshold)
@ -1009,8 +1009,8 @@ public class Rotation implements Serializable {
} }
// the algorithm did not converge after 10 iterations // the algorithm did not converge after 10 iterations
throw new NotARotationMatrixException("unable to orthogonalize matrix" throw new NotARotationMatrixException("unable to orthogonalize matrix" +
+ " in {0} iterations", " in {0} iterations",
new String[] { new String[] {
Integer.toString(i - 1) Integer.toString(i - 1)
}); });

8
src/java/org/apache/commons/math/ode/ClassicalRungeKuttaStepInterpolator.java
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@ -95,10 +95,10 @@ class ClassicalRungeKuttaStepInterpolator
double coeff4 = s * ((-fourTheta - 1) * theta - 1); double coeff4 = s * ((-fourTheta - 1) * theta - 1);
for (int i = 0; i < interpolatedState.length; ++i) { for (int i = 0; i < interpolatedState.length; ++i) {
interpolatedState[i] = currentState[i] interpolatedState[i] = currentState[i] +
+ coeff1 * yDotK[0][i] coeff1 * yDotK[0][i] +
+ coeff23 * (yDotK[1][i] + yDotK[2][i]) coeff23 * (yDotK[1][i] + yDotK[2][i]) +
+ coeff4 * yDotK[3][i]; coeff4 * yDotK[3][i];
} }
} }

16
src/java/org/apache/commons/math/ode/ContinuousOutputModel.java
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@ -286,10 +286,10 @@ public class ContinuousOutputModel
double dt1 = time - tMax; double dt1 = time - tMax;
double dt2 = time - tMed; double dt2 = time - tMed;
double dt3 = time - tMin; double dt3 = time - tMin;
double iLagrange = ( (dt2 * dt3 * d23) * iMax double iLagrange = ((dt2 * dt3 * d23) * iMax -
- (dt1 * dt3 * d13) * iMed (dt1 * dt3 * d13) * iMed +
+ (dt1 * dt2 * d12) * iMin) (dt1 * dt2 * d12) * iMin) /
/ (d12 * d23 * d13); (d12 * d23 * d13);
index = (int) Math.rint(iLagrange); index = (int) Math.rint(iLagrange);
} }
@ -306,8 +306,8 @@ public class ContinuousOutputModel
// now the table slice is very small, we perform an iterative search // now the table slice is very small, we perform an iterative search
index = iMin; index = iMin;
while ((index <= iMax) while ((index <= iMax) &&
&& (locatePoint(time, (StepInterpolator) steps.get(index)) > 0)) { (locatePoint(time, (StepInterpolator) steps.get(index)) > 0)) {
++index; ++index;
} }
@ -316,8 +316,8 @@ public class ContinuousOutputModel
si.setInterpolatedTime(time); si.setInterpolatedTime(time);
} catch (DerivativeException de) { } catch (DerivativeException de) {
throw new RuntimeException("unexpected DerivativeException caught: " throw new RuntimeException("unexpected DerivativeException caught: " +
+ de.getMessage()); de.getMessage());
} }
} }

12
src/java/org/apache/commons/math/ode/DormandPrince54Integrator.java
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@ -132,14 +132,14 @@ public class DormandPrince54Integrator
double error = 0; double error = 0;
for (int j = 0; j < y0.length; ++j) { for (int j = 0; j < y0.length; ++j) {
double errSum = e1 * yDotK[0][j] + e3 * yDotK[2][j] double errSum = e1 * yDotK[0][j] + e3 * yDotK[2][j] +
+ e4 * yDotK[3][j] + e5 * yDotK[4][j] e4 * yDotK[3][j] + e5 * yDotK[4][j] +
+ e6 * yDotK[5][j] + e7 * yDotK[6][j]; e6 * yDotK[5][j] + e7 * yDotK[6][j];
double yScale = Math.max(Math.abs(y0[j]), Math.abs(y1[j])); double yScale = Math.max(Math.abs(y0[j]), Math.abs(y1[j]));
double tol = (vecAbsoluteTolerance == null) double tol = (vecAbsoluteTolerance == null) ?
? (scalAbsoluteTolerance + scalRelativeTolerance * yScale) (scalAbsoluteTolerance + scalRelativeTolerance * yScale) :
: (vecAbsoluteTolerance[j] + vecRelativeTolerance[j] * yScale); (vecAbsoluteTolerance[j] + vecRelativeTolerance[j] * yScale);
double ratio = h * errSum / tol; double ratio = h * errSum / tol;
error += ratio * ratio; error += ratio * ratio;

15
src/java/org/apache/commons/math/ode/DormandPrince54StepInterpolator.java
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@ -135,12 +135,12 @@ class DormandPrince54StepInterpolator
// we need to compute the interpolation vectors for this time step // we need to compute the interpolation vectors for this time step
for (int i = 0; i < interpolatedState.length; ++i) { for (int i = 0; i < interpolatedState.length; ++i) {
v1[i] = h * (a70 * yDotK[0][i] + a72 * yDotK[2][i] + a73 * yDotK[3][i] v1[i] = h * (a70 * yDotK[0][i] + a72 * yDotK[2][i] + a73 * yDotK[3][i] +
+ a74 * yDotK[4][i] + a75 * yDotK[5][i]); a74 * yDotK[4][i] + a75 * yDotK[5][i]);
v2[i] = h * yDotK[0][i] - v1[i]; v2[i] = h * yDotK[0][i] - v1[i];
v3[i] = v1[i] - v2[i] - h * yDotK[6][i]; v3[i] = v1[i] - v2[i] - h * yDotK[6][i];
v4[i] = h * (d0 * yDotK[0][i] + d2 * yDotK[2][i] + d3 * yDotK[3][i] v4[i] = h * (d0 * yDotK[0][i] + d2 * yDotK[2][i] + d3 * yDotK[3][i] +
+ d4 * yDotK[4][i] + d5 * yDotK[5][i] + d6 * yDotK[6][i]); d4 * yDotK[4][i] + d5 * yDotK[5][i] + d6 * yDotK[6][i]);
} }
vectorsInitialized = true; vectorsInitialized = true;
@ -150,11 +150,8 @@ class DormandPrince54StepInterpolator
// interpolate // interpolate
double eta = oneMinusThetaH / h; double eta = oneMinusThetaH / h;
for (int i = 0; i < interpolatedState.length; ++i) { for (int i = 0; i < interpolatedState.length; ++i) {
interpolatedState[i] = currentState[i] interpolatedState[i] = currentState[i] -
- eta * (v1[i] eta * (v1[i] - theta * (v2[i] + theta * (v3[i] + eta * v4[i])));
- theta * (v2[i]
+ theta * (v3[i]
+ eta * v4[i])));
} }
} }

22
src/java/org/apache/commons/math/ode/DormandPrince853Integrator.java
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@ -226,19 +226,19 @@ public class DormandPrince853Integrator
double error2 = 0; double error2 = 0;
for (int j = 0; j < y0.length; ++j) { for (int j = 0; j < y0.length; ++j) {
double errSum1 = e1_01 * yDotK[0][j] + e1_06 * yDotK[5][j] double errSum1 = e1_01 * yDotK[0][j] + e1_06 * yDotK[5][j] +
+ e1_07 * yDotK[6][j] + e1_08 * yDotK[7][j] e1_07 * yDotK[6][j] + e1_08 * yDotK[7][j] +
+ e1_09 * yDotK[8][j] + e1_10 * yDotK[9][j] e1_09 * yDotK[8][j] + e1_10 * yDotK[9][j] +
+ e1_11 * yDotK[10][j] + e1_12 * yDotK[11][j]; e1_11 * yDotK[10][j] + e1_12 * yDotK[11][j];
double errSum2 = e2_01 * yDotK[0][j] + e2_06 * yDotK[5][j] double errSum2 = e2_01 * yDotK[0][j] + e2_06 * yDotK[5][j] +
+ e2_07 * yDotK[6][j] + e2_08 * yDotK[7][j] e2_07 * yDotK[6][j] + e2_08 * yDotK[7][j] +
+ e2_09 * yDotK[8][j] + e2_10 * yDotK[9][j] e2_09 * yDotK[8][j] + e2_10 * yDotK[9][j] +
+ e2_11 * yDotK[10][j] + e2_12 * yDotK[11][j]; e2_11 * yDotK[10][j] + e2_12 * yDotK[11][j];
double yScale = Math.max(Math.abs(y0[j]), Math.abs(y1[j])); double yScale = Math.max(Math.abs(y0[j]), Math.abs(y1[j]));
double tol = (vecAbsoluteTolerance == null) double tol = (vecAbsoluteTolerance == null) ?
? (scalAbsoluteTolerance + scalRelativeTolerance * yScale) (scalAbsoluteTolerance + scalRelativeTolerance * yScale) :
: (vecAbsoluteTolerance[j] + vecRelativeTolerance[j] * yScale); (vecAbsoluteTolerance[j] + vecRelativeTolerance[j] * yScale);
double ratio1 = errSum1 / tol; double ratio1 = errSum1 / tol;
error1 += ratio1 * ratio1; error1 += ratio1 * ratio1;
double ratio2 = errSum2 / tol; double ratio2 = errSum2 / tol;

52
src/java/org/apache/commons/math/ode/DormandPrince853StepInterpolator.java
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@ -172,18 +172,18 @@ class DormandPrince853StepInterpolator
// compute the interpolation vectors for this time step // compute the interpolation vectors for this time step
for (int i = 0; i < interpolatedState.length; ++i) { for (int i = 0; i < interpolatedState.length; ++i) {
v[0][i] = h * (b_01 * yDotK[0][i] + b_06 * yDotK[5][i] + b_07 * yDotK[6][i] v[0][i] = h * (b_01 * yDotK[0][i] + b_06 * yDotK[5][i] + b_07 * yDotK[6][i] +
+ b_08 * yDotK[7][i] + b_09 * yDotK[8][i] + b_10 * yDotK[9][i] b_08 * yDotK[7][i] + b_09 * yDotK[8][i] + b_10 * yDotK[9][i] +
+ b_11 * yDotK[10][i] + b_12 * yDotK[11][i]); b_11 * yDotK[10][i] + b_12 * yDotK[11][i]);
v[1][i] = h * yDotK[0][i] - v[0][i]; v[1][i] = h * yDotK[0][i] - v[0][i];
v[2][i] = v[0][i] - v[1][i] - h * yDotK[12][i]; v[2][i] = v[0][i] - v[1][i] - h * yDotK[12][i];
for (int k = 0; k < d.length; ++k) { for (int k = 0; k < d.length; ++k) {
v[k+3][i] = h * (d[k][0] * yDotK[0][i] + d[k][1] * yDotK[5][i] + d[k][2] * yDotK[6][i] v[k+3][i] = h * (d[k][0] * yDotK[0][i] + d[k][1] * yDotK[5][i] + d[k][2] * yDotK[6][i] +
+ d[k][3] * yDotK[7][i] + d[k][4] * yDotK[8][i] + d[k][5] * yDotK[9][i] d[k][3] * yDotK[7][i] + d[k][4] * yDotK[8][i] + d[k][5] * yDotK[9][i] +
+ d[k][6] * yDotK[10][i] + d[k][7] * yDotK[11][i] + d[k][8] * yDotK[12][i] d[k][6] * yDotK[10][i] + d[k][7] * yDotK[11][i] + d[k][8] * yDotK[12][i] +
+ d[k][9] * yDotKLast[0][i] d[k][9] * yDotKLast[0][i] +
+ d[k][10] * yDotKLast[1][i] d[k][10] * yDotKLast[1][i] +
+ d[k][11] * yDotKLast[2][i]); d[k][11] * yDotKLast[2][i]);
} }
} }
@ -194,14 +194,10 @@ class DormandPrince853StepInterpolator
double eta = oneMinusThetaH / h; double eta = oneMinusThetaH / h;
for (int i = 0; i < interpolatedState.length; ++i) { for (int i = 0; i < interpolatedState.length; ++i) {
interpolatedState[i] = currentState[i] interpolatedState[i] =
- eta * (v[0][i] currentState[i] - eta * (v[0][i] - theta * (v[1][i] +
- theta * (v[1][i] theta * (v[2][i] + eta * (v[3][i] + theta * (v[4][i] +
+ theta * (v[2][i] eta * (v[5][i] + theta * (v[6][i])))))));
+ eta * (v[3][i]
+ theta * (v[4][i]
+ eta * (v[5][i]
+ theta * (v[6][i])))))));
} }
} }
@ -225,29 +221,29 @@ class DormandPrince853StepInterpolator
// k14 // k14
for (int j = 0; j < currentState.length; ++j) { for (int j = 0; j < currentState.length; ++j) {
s = k14_01 * yDotK[0][j] + k14_06 * yDotK[5][j] + k14_07 * yDotK[6][j] s = k14_01 * yDotK[0][j] + k14_06 * yDotK[5][j] + k14_07 * yDotK[6][j] +
+ k14_08 * yDotK[7][j] + k14_09 * yDotK[8][j] + k14_10 * yDotK[9][j] k14_08 * yDotK[7][j] + k14_09 * yDotK[8][j] + k14_10 * yDotK[9][j] +
+ k14_11 * yDotK[10][j] + k14_12 * yDotK[11][j] + k14_13 * yDotK[12][j]; k14_11 * yDotK[10][j] + k14_12 * yDotK[11][j] + k14_13 * yDotK[12][j];
yTmp[j] = currentState[j] + h * s; yTmp[j] = currentState[j] + h * s;
} }
equations.computeDerivatives(previousTime + c14 * h, yTmp, yDotKLast[0]); equations.computeDerivatives(previousTime + c14 * h, yTmp, yDotKLast[0]);
// k15 // k15
for (int j = 0; j < currentState.length; ++j) { for (int j = 0; j < currentState.length; ++j) {
s = k15_01 * yDotK[0][j] + k15_06 * yDotK[5][j] + k15_07 * yDotK[6][j] s = k15_01 * yDotK[0][j] + k15_06 * yDotK[5][j] + k15_07 * yDotK[6][j] +
+ k15_08 * yDotK[7][j] + k15_09 * yDotK[8][j] + k15_10 * yDotK[9][j] k15_08 * yDotK[7][j] + k15_09 * yDotK[8][j] + k15_10 * yDotK[9][j] +
+ k15_11 * yDotK[10][j] + k15_12 * yDotK[11][j] + k15_13 * yDotK[12][j] k15_11 * yDotK[10][j] + k15_12 * yDotK[11][j] + k15_13 * yDotK[12][j] +
+ k15_14 * yDotKLast[0][j]; k15_14 * yDotKLast[0][j];
yTmp[j] = currentState[j] + h * s; yTmp[j] = currentState[j] + h * s;
} }
equations.computeDerivatives(previousTime + c15 * h, yTmp, yDotKLast[1]); equations.computeDerivatives(previousTime + c15 * h, yTmp, yDotKLast[1]);
// k16 // k16
for (int j = 0; j < currentState.length; ++j) { for (int j = 0; j < currentState.length; ++j) {
s = k16_01 * yDotK[0][j] + k16_06 * yDotK[5][j] + k16_07 * yDotK[6][j] s = k16_01 * yDotK[0][j] + k16_06 * yDotK[5][j] + k16_07 * yDotK[6][j] +
+ k16_08 * yDotK[7][j] + k16_09 * yDotK[8][j] + k16_10 * yDotK[9][j] k16_08 * yDotK[7][j] + k16_09 * yDotK[8][j] + k16_10 * yDotK[9][j] +
+ k16_11 * yDotK[10][j] + k16_12 * yDotK[11][j] + k16_13 * yDotK[12][j] k16_11 * yDotK[10][j] + k16_12 * yDotK[11][j] + k16_13 * yDotK[12][j] +
+ k16_14 * yDotKLast[0][j] + k16_15 * yDotKLast[1][j]; k16_14 * yDotKLast[0][j] + k16_15 * yDotKLast[1][j];
yTmp[j] = currentState[j] + h * s; yTmp[j] = currentState[j] + h * s;
} }
equations.computeDerivatives(previousTime + c16 * h, yTmp, yDotKLast[2]); equations.computeDerivatives(previousTime + c16 * h, yTmp, yDotKLast[2]);

4
src/java/org/apache/commons/math/ode/EmbeddedRungeKuttaIntegrator.java
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@ -220,8 +220,8 @@ public abstract class EmbeddedRungeKuttaIntegrator
stepSize = hNew; stepSize = hNew;
// step adjustment near bounds // step adjustment near bounds
if ((forward && (stepStart + stepSize > t)) if ((forward && (stepStart + stepSize > t)) ||
|| ((! forward) && (stepStart + stepSize < t))) { ((! forward) && (stepStart + stepSize < t))) {
stepSize = t - stepStart; stepSize = t - stepStart;
} }

6
src/java/org/apache/commons/math/ode/GillStepInterpolator.java
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@ -97,9 +97,9 @@ class GillStepInterpolator
double coeff4 = s * (1 + theta * (1 + fourTheta)); double coeff4 = s * (1 + theta * (1 + fourTheta));
for (int i = 0; i < interpolatedState.length; ++i) { for (int i = 0; i < interpolatedState.length; ++i) {
interpolatedState[i] = currentState[i] interpolatedState[i] = currentState[i] -
- coeff1 * yDotK[0][i] - coeff2 * yDotK[1][i] coeff1 * yDotK[0][i] - coeff2 * yDotK[1][i] -
- coeff3 * yDotK[2][i] - coeff4 * yDotK[3][i]; coeff3 * yDotK[2][i] - coeff4 * yDotK[3][i];
} }
} }

66
src/java/org/apache/commons/math/ode/GraggBulirschStoerIntegrator.java
View File

@ -104,8 +104,7 @@ public class GraggBulirschStoerIntegrator
double scalAbsoluteTolerance, double scalAbsoluteTolerance,
double scalRelativeTolerance) { double scalRelativeTolerance) {
super(minStep, maxStep, scalAbsoluteTolerance, scalRelativeTolerance); super(minStep, maxStep, scalAbsoluteTolerance, scalRelativeTolerance);
denseOutput = (handler.requiresDenseOutput() denseOutput = (handler.requiresDenseOutput() || (! switchesHandler.isEmpty()));
|| (! switchesHandler.isEmpty()));
setStabilityCheck(true, -1, -1, -1); setStabilityCheck(true, -1, -1, -1);
setStepsizeControl(-1, -1, -1, -1); setStepsizeControl(-1, -1, -1, -1);
setOrderControl(-1, -1, -1); setOrderControl(-1, -1, -1);
@ -127,8 +126,7 @@ public class GraggBulirschStoerIntegrator
double[] vecAbsoluteTolerance, double[] vecAbsoluteTolerance,
double[] vecRelativeTolerance) { double[] vecRelativeTolerance) {
super(minStep, maxStep, vecAbsoluteTolerance, vecRelativeTolerance); super(minStep, maxStep, vecAbsoluteTolerance, vecRelativeTolerance);
denseOutput = (handler.requiresDenseOutput() denseOutput = (handler.requiresDenseOutput() || (! switchesHandler.isEmpty()));
|| (! switchesHandler.isEmpty()));
setStabilityCheck(true, -1, -1, -1); setStabilityCheck(true, -1, -1, -1);
setStepsizeControl(-1, -1, -1, -1); setStepsizeControl(-1, -1, -1, -1);
setOrderControl(-1, -1, -1); setOrderControl(-1, -1, -1);
@ -277,8 +275,7 @@ public class GraggBulirschStoerIntegrator
public void setStepHandler (StepHandler handler) { public void setStepHandler (StepHandler handler) {
super.setStepHandler(handler); super.setStepHandler(handler);
denseOutput = (handler.requiresDenseOutput() denseOutput = (handler.requiresDenseOutput() || (! switchesHandler.isEmpty()));
|| (! switchesHandler.isEmpty()));
// reinitialize the arrays // reinitialize the arrays
initializeArrays(); initializeArrays();
@ -299,8 +296,7 @@ public class GraggBulirschStoerIntegrator
double convergence, double convergence,
int maxIterationCount) { int maxIterationCount) {
super.addSwitchingFunction(function, maxCheckInterval, convergence, maxIterationCount); super.addSwitchingFunction(function, maxCheckInterval, convergence, maxIterationCount);
denseOutput = (handler.requiresDenseOutput() denseOutput = (handler.requiresDenseOutput() || (! switchesHandler.isEmpty()));
|| (! switchesHandler.isEmpty()));
// reinitialize the arrays // reinitialize the arrays
initializeArrays(); initializeArrays();
@ -495,8 +491,8 @@ public class GraggBulirschStoerIntegrator
for (int j = 1; j < k; ++j) { for (int j = 1; j < k; ++j) {
for (int i = 0; i < last.length; ++i) { for (int i = 0; i < last.length; ++i) {
// Aitken-Neville's recursive formula // Aitken-Neville's recursive formula
diag[k-j-1][i] = diag[k-j][i] diag[k-j-1][i] = diag[k-j][i] +
+ coeff[k+offset][j-1] * (diag[k-j][i] - diag[k-j-1][i]); coeff[k+offset][j-1] * (diag[k-j][i] - diag[k-j-1][i]);
} }
} }
@ -563,11 +559,9 @@ public class GraggBulirschStoerIntegrator
rescale(y, y, scale); rescale(y, y, scale);
// initial order selection // initial order selection
double log10R = Math.log(Math.max(1.0e-10, double tol =
(vecRelativeTolerance == null) (vecRelativeTolerance == null) ? scalRelativeTolerance : vecRelativeTolerance[0];
? scalRelativeTolerance double log10R = Math.log(Math.max(1.0e-10, tol)) / Math.log(10.0);
: vecRelativeTolerance[0]))
/ Math.log(10.0);
int targetIter = Math.max(1, int targetIter = Math.max(1,
Math.min(sequence.length - 2, Math.min(sequence.length - 2,
(int) Math.floor(0.5 - 0.6 * log10R))); (int) Math.floor(0.5 - 0.6 * log10R)));
@ -625,8 +619,8 @@ public class GraggBulirschStoerIntegrator
stepSize = hNew; stepSize = hNew;
// step adjustment near bounds // step adjustment near bounds
if ((forward && (stepStart + stepSize > t)) if ((forward && (stepStart + stepSize > t)) ||
|| ((! forward) && (stepStart + stepSize < t))) { ((! forward) && (stepStart + stepSize < t))) {
stepSize = t - stepStart; stepSize = t - stepStart;
} }
double nextT = stepStart + stepSize; double nextT = stepStart + stepSize;
@ -698,17 +692,17 @@ public class GraggBulirschStoerIntegrator
// estimate if there is a chance convergence will // estimate if there is a chance convergence will
// be reached on next iteration, using the // be reached on next iteration, using the
// asymptotic evolution of error // asymptotic evolution of error
double ratio = ((double) sequence [k] * sequence[k+1]) double ratio = ((double) sequence [k] * sequence[k+1]) /
/ (sequence[0] * sequence[0]); (sequence[0] * sequence[0]);
if (error > ratio * ratio) { if (error > ratio * ratio) {
// we don't expect to converge on next iteration // we don't expect to converge on next iteration
// we reject the step immediately and reduce order // we reject the step immediately and reduce order
reject = true; reject = true;
loop = false; loop = false;
targetIter = k; targetIter = k;
if ((targetIter > 1) if ((targetIter > 1) &&
&& (costPerTimeUnit[targetIter-1] (costPerTimeUnit[targetIter-1] <
< orderControl1 * costPerTimeUnit[targetIter])) { orderControl1 * costPerTimeUnit[targetIter])) {
--targetIter; --targetIter;
} }
hNew = optimalStep[targetIter]; hNew = optimalStep[targetIter];
@ -731,9 +725,9 @@ public class GraggBulirschStoerIntegrator
// we reject the step immediately // we reject the step immediately
reject = true; reject = true;
loop = false; loop = false;
if ((targetIter > 1) if ((targetIter > 1) &&
&& (costPerTimeUnit[targetIter-1] (costPerTimeUnit[targetIter-1] <
< orderControl1 * costPerTimeUnit[targetIter])) { orderControl1 * costPerTimeUnit[targetIter])) {
--targetIter; --targetIter;
} }
hNew = optimalStep[targetIter]; hNew = optimalStep[targetIter];
@ -744,9 +738,9 @@ public class GraggBulirschStoerIntegrator
case 1 : case 1 :
if (error > 1.0) { if (error > 1.0) {
reject = true; reject = true;
if ((targetIter > 1) if ((targetIter > 1) &&
&& (costPerTimeUnit[targetIter-1] (costPerTimeUnit[targetIter-1] <
< orderControl1 * costPerTimeUnit[targetIter])) { orderControl1 * costPerTimeUnit[targetIter])) {
--targetIter; --targetIter;
} }
hNew = optimalStep[targetIter]; hNew = optimalStep[targetIter];
@ -887,8 +881,8 @@ public class GraggBulirschStoerIntegrator
} }
} else { } else {
optimalIter = k - 1; optimalIter = k - 1;
if ((k > 2) if ((k > 2) &&
&& (costPerTimeUnit[k-2] < orderControl1 * costPerTimeUnit[k-1])) { (costPerTimeUnit[k-2] < orderControl1 * costPerTimeUnit[k-1])) {
optimalIter = k - 2; optimalIter = k - 2;
} }
if (costPerTimeUnit[k] < orderControl2 * costPerTimeUnit[optimalIter]) { if (costPerTimeUnit[k] < orderControl2 * costPerTimeUnit[optimalIter]) {
@ -906,14 +900,14 @@ public class GraggBulirschStoerIntegrator
if (optimalIter <= k) { if (optimalIter <= k) {
hNew = optimalStep[optimalIter]; hNew = optimalStep[optimalIter];
} else { } else {
if ((k < targetIter) if ((k < targetIter) &&
&& (costPerTimeUnit[k] < orderControl2 * costPerTimeUnit[k-1])) { (costPerTimeUnit[k] < orderControl2 * costPerTimeUnit[k-1])) {
hNew = filterStep(optimalStep[k] hNew = filterStep(optimalStep[k] *
* costPerStep[optimalIter+1] / costPerStep[k], costPerStep[optimalIter+1] / costPerStep[k],
false); false);
} else { } else {
hNew = filterStep(optimalStep[k] hNew = filterStep(optimalStep[k] *
* costPerStep[optimalIter] / costPerStep[k], costPerStep[optimalIter] / costPerStep[k],
false); false);
} }
} }

13
src/java/org/apache/commons/math/ode/GraggBulirschStoerStepInterpolator.java
View File

@ -274,9 +274,8 @@ class GraggBulirschStoerStepInterpolator
for (int j = 4; j <= mu; ++j) { for (int j = 4; j <= mu; ++j) {
double fac1 = 0.5 * j * (j - 1); double fac1 = 0.5 * j * (j - 1);
double fac2 = 2 * fac1 * (j - 2) * (j - 3); double fac2 = 2 * fac1 * (j - 2) * (j - 3);
polynoms[j+4][i] = 16 * (yMidDots[j][i] polynoms[j+4][i] =
+ fac1 * polynoms[j+2][i] 16 * (yMidDots[j][i] + fac1 * polynoms[j+2][i] - fac2 * polynoms[j][i]);
- fac2 * polynoms[j][i]);
} }
} }
@ -324,10 +323,10 @@ class GraggBulirschStoerStepInterpolator
t4 = t4 * t4; t4 = t4 * t4;
for (int i = 0; i < dimension; ++i) { for (int i = 0; i < dimension; ++i) {
interpolatedState[i] = polynoms[0][i] interpolatedState[i] = polynoms[0][i] +
+ theta * (polynoms[1][i] theta * (polynoms[1][i] +
+ oneMinusTheta * (polynoms[2][i] * theta oneMinusTheta * (polynoms[2][i] * theta +
+ polynoms[3][i] * oneMinusTheta)); polynoms[3][i] * oneMinusTheta));
if (currentDegree > 3) { if (currentDegree > 3) {
double c = polynoms[currentDegree][i]; double c = polynoms[currentDegree][i];

6
src/java/org/apache/commons/math/ode/HighamHall54Integrator.java
View File

@ -123,9 +123,9 @@ public class HighamHall54Integrator
} }
double yScale = Math.max(Math.abs(y0[j]), Math.abs(y1[j])); double yScale = Math.max(Math.abs(y0[j]), Math.abs(y1[j]));
double tol = (vecAbsoluteTolerance == null) double tol = (vecAbsoluteTolerance == null) ?
? (scalAbsoluteTolerance + scalRelativeTolerance * yScale) (scalAbsoluteTolerance + scalRelativeTolerance * yScale) :
: (vecAbsoluteTolerance[j] + vecRelativeTolerance[j] * yScale); (vecAbsoluteTolerance[j] + vecRelativeTolerance[j] * yScale);
double ratio = h * errSum / tol; double ratio = h * errSum / tol;
error += ratio * ratio; error += ratio * ratio;

6
src/java/org/apache/commons/math/ode/HighamHall54StepInterpolator.java
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@ -80,9 +80,9 @@ class HighamHall54StepInterpolator
double b5 = h * (-5.0/48.0 + theta2 * (-5.0/16.0 + theta * 5.0/12.0)); double b5 = h * (-5.0/48.0 + theta2 * (-5.0/16.0 + theta * 5.0/12.0));
for (int i = 0; i < interpolatedState.length; ++i) { for (int i = 0; i < interpolatedState.length; ++i) {
interpolatedState[i] = currentState[i] interpolatedState[i] = currentState[i] +
+ b0 * yDotK[0][i] + b2 * yDotK[2][i] + b3 * yDotK[3][i] b0 * yDotK[0][i] + b2 * yDotK[2][i] + b3 * yDotK[3][i] +
+ b4 * yDotK[4][i] + b5 * yDotK[5][i]; b4 * yDotK[4][i] + b5 * yDotK[5][i];
} }
} }

4
src/java/org/apache/commons/math/ode/MidpointStepInterpolator.java
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@ -88,8 +88,8 @@ class MidpointStepInterpolator
double coeff2 = oneMinusThetaH * (1.0 + theta); double coeff2 = oneMinusThetaH * (1.0 + theta);
for (int i = 0; i < interpolatedState.length; ++i) { for (int i = 0; i < interpolatedState.length; ++i) {
interpolatedState[i] = currentState[i] interpolatedState[i] = currentState[i] +
+ coeff1 * yDotK[0][i] - coeff2 * yDotK[1][i]; coeff1 * yDotK[0][i] - coeff2 * yDotK[1][i];
} }
} }

4
src/java/org/apache/commons/math/ode/SwitchState.java
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@ -274,8 +274,8 @@ class SwitchState implements Serializable {
pendingEvent = false; pendingEvent = false;
pendingEventTime = Double.NaN; pendingEventTime = Double.NaN;
return (nextAction == SwitchingFunction.RESET_STATE) return (nextAction == SwitchingFunction.RESET_STATE) ||
|| (nextAction == SwitchingFunction.RESET_DERIVATIVES); (nextAction == SwitchingFunction.RESET_DERIVATIVES);
} }

6
src/java/org/apache/commons/math/ode/ThreeEighthesStepInterpolator.java
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@ -97,9 +97,9 @@ class ThreeEighthesStepInterpolator
double coeff4 = s * (1 + theta + fourTheta2); double coeff4 = s * (1 + theta + fourTheta2);
for (int i = 0; i < interpolatedState.length; ++i) { for (int i = 0; i < interpolatedState.length; ++i) {
interpolatedState[i] = currentState[i] interpolatedState[i] = currentState[i] -
- coeff1 * yDotK[0][i] - coeff2 * yDotK[1][i] coeff1 * yDotK[0][i] - coeff2 * yDotK[1][i] -
- coeff3 * yDotK[2][i] - coeff4 * yDotK[3][i]; coeff3 * yDotK[2][i] - coeff4 * yDotK[3][i];
} }
} }

6
src/java/org/apache/commons/math/optimization/DirectSearchOptimizer.java
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@ -504,9 +504,9 @@ public abstract class DirectSearchOptimizer {
// return the found point given the lowest cost // return the found point given the lowest cost
if (minima[0] == null) { if (minima[0] == null) {
throw new ConvergenceException("none of the {0} start points" throw new ConvergenceException("none of the {0} start points" +
+ " lead to convergence", " lead to convergence",
new String[] { new Object[] {
Integer.toString(starts) Integer.toString(starts)
}); });
} }