diff --git a/src/main/java/org/apache/commons/math3/ode/MultistepFieldIntegrator.java b/src/main/java/org/apache/commons/math3/ode/MultistepFieldIntegrator.java index b86fc0539..0d257a9f1 100644 --- a/src/main/java/org/apache/commons/math3/ode/MultistepFieldIntegrator.java +++ b/src/main/java/org/apache/commons/math3/ode/MultistepFieldIntegrator.java @@ -316,6 +316,33 @@ public abstract class MultistepFieldIntegrator> return nSteps; } + /** Rescale the instance. + *

Since the scaled and Nordsieck arrays are shared with the caller, + * this method has the side effect of rescaling this arrays in the caller too.

+ * @param newStepSize new step size to use in the scaled and Nordsieck arrays + */ + protected void rescale(final T newStepSize) { + + final T ratio = newStepSize.divide(getStepSize()); + for (int i = 0; i < scaled.length; ++i) { + scaled[i] = scaled[i].multiply(ratio); + } + + final T[][] nData = nordsieck.getDataRef(); + T power = ratio; + for (int i = 0; i < nData.length; ++i) { + power = power.multiply(ratio); + final T[] nDataI = nData[i]; + for (int j = 0; j < nDataI.length; ++j) { + nDataI[j] = nDataI[j].multiply(power); + } + } + + setStepSize(newStepSize); + + } + + /** Compute step grow/shrink factor according to normalized error. * @param error normalized error of the current step * @return grow/shrink factor for next step diff --git a/src/main/java/org/apache/commons/math3/ode/nonstiff/AdamsBashforthFieldIntegrator.java b/src/main/java/org/apache/commons/math3/ode/nonstiff/AdamsBashforthFieldIntegrator.java index 7eeb8df33..bec334377 100644 --- a/src/main/java/org/apache/commons/math3/ode/nonstiff/AdamsBashforthFieldIntegrator.java +++ b/src/main/java/org/apache/commons/math3/ode/nonstiff/AdamsBashforthFieldIntegrator.java @@ -255,9 +255,11 @@ public class AdamsBashforthFieldIntegrator> extend start(equations, getStepStart(), finalTime); // reuse the step that was chosen by the starter integrator - AdamsFieldStepInterpolator interpolator = - new AdamsFieldStepInterpolator(getStepSize(), getStepStart(), scaled, nordsieck, - forward, equations.getMapper()); + FieldODEStateAndDerivative stepStart = getStepStart(); + FieldODEStateAndDerivative stepEnd = + AdamsFieldStepInterpolator.taylor(stepStart, + stepStart.getTime().add(getStepSize()), + getStepSize(), scaled, nordsieck); // main integration loop setIsLastStep(false); @@ -270,7 +272,6 @@ public class AdamsBashforthFieldIntegrator> extend while (error.subtract(1.0).getReal() >= 0.0) { // predict a first estimate of the state at step end - final FieldODEStateAndDerivative stepEnd = interpolator.getCurrentState(); predictedY = stepEnd.getState(); // evaluate the derivative @@ -290,26 +291,32 @@ public class AdamsBashforthFieldIntegrator> extend // reject the step and attempt to reduce error by stepsize control final T factor = computeStepGrowShrinkFactor(error); rescale(filterStep(getStepSize().multiply(factor), forward, false)); - interpolator = new AdamsFieldStepInterpolator(getStepSize(), getStepStart(), scaled, nordsieck, - forward, equations.getMapper()); + stepEnd = AdamsFieldStepInterpolator.taylor(getStepStart(), + getStepStart().getTime().add(getStepSize()), + getStepSize(), + scaled, + nordsieck); } } // discrete events handling - System.arraycopy(predictedY, 0, y, 0, y.length); - setStepStart(acceptStep(interpolator, finalTime)); + setStepStart(acceptStep(new AdamsFieldStepInterpolator(getStepSize(), stepEnd, + predictedScaled, predictedNordsieck, forward, + getStepStart(), stepEnd, + equations.getMapper()), + finalTime)); scaled = predictedScaled; nordsieck = predictedNordsieck; if (!isLastStep()) { + System.arraycopy(predictedY, 0, y, 0, y.length); + if (resetOccurred()) { // some events handler has triggered changes that // invalidate the derivatives, we need to restart from scratch start(equations, getStepStart(), finalTime); - interpolator = new AdamsFieldStepInterpolator(getStepSize(), getStepStart(), scaled, nordsieck, - forward, equations.getMapper()); } // stepsize control for next step @@ -330,8 +337,8 @@ public class AdamsBashforthFieldIntegrator> extend } rescale(hNew); - interpolator = new AdamsFieldStepInterpolator(getStepSize(), getStepStart(), scaled, nordsieck, - forward, equations.getMapper()); + stepEnd = AdamsFieldStepInterpolator.taylor(getStepStart(), getStepStart().getTime().add(getStepSize()), + getStepSize(), scaled, nordsieck); } @@ -344,31 +351,4 @@ public class AdamsBashforthFieldIntegrator> extend } - /** Rescale the instance. - *

Since the scaled and Nordsieck arrays are shared with the caller, - * this method has the side effect of rescaling this arrays in the caller too.

- * @param newStepSize new step size to use in the scaled and Nordsieck arrays - */ - public void rescale(final T newStepSize) { - - final T ratio = newStepSize.divide(getStepSize()); - for (int i = 0; i < scaled.length; ++i) { - scaled[i] = scaled[i].multiply(ratio); - } - - final T[][] nData = nordsieck.getDataRef(); - T power = ratio; - for (int i = 0; i < nData.length; ++i) { - power = power.multiply(ratio); - final T[] nDataI = nData[i]; - for (int j = 0; j < nDataI.length; ++j) { - nDataI[j] = nDataI[j].multiply(power); - } - } - - setStepSize(newStepSize); - - } - - } diff --git a/src/main/java/org/apache/commons/math3/ode/nonstiff/AdamsFieldStepInterpolator.java b/src/main/java/org/apache/commons/math3/ode/nonstiff/AdamsFieldStepInterpolator.java index 9f282c098..f49ab1e3b 100644 --- a/src/main/java/org/apache/commons/math3/ode/nonstiff/AdamsFieldStepInterpolator.java +++ b/src/main/java/org/apache/commons/math3/ode/nonstiff/AdamsFieldStepInterpolator.java @@ -43,6 +43,14 @@ class AdamsFieldStepInterpolator> extends Abstract /** Step size used in the first scaled derivative and Nordsieck vector. */ private T scalingH; + /** Reference state. + *

Sometimes, the reference state is the same as globalPreviousState, + * sometimes it is the same as globalCurrentState, so we use a separate + * field to avoid any confusion. + *

+ */ + private final FieldODEStateAndDerivative reference; + /** First scaled derivative. */ private final T[] scaled; @@ -51,22 +59,7 @@ class AdamsFieldStepInterpolator> extends Abstract /** Simple constructor. * @param stepSize step size used in the scaled and Nordsieck arrays - * @param referenceState reference state from which Taylor expansion are estimated - * @param scaled first scaled derivative - * @param nordsieck Nordsieck vector - * @param isForward integration direction indicator - * @param equationsMapper mapper for ODE equations primary and secondary components - */ - AdamsFieldStepInterpolator(final T stepSize, final FieldODEStateAndDerivative referenceState, - final T[] scaled, final Array2DRowFieldMatrix nordsieck, - final boolean isForward, final FieldEquationsMapper equationsMapper) { - this(stepSize, scaled, nordsieck, isForward, - referenceState, taylor(referenceState, referenceState.getTime().add(stepSize), stepSize, scaled, nordsieck), - equationsMapper); - } - - /** Simple constructor. - * @param stepSize step size used in the scaled and Nordsieck arrays + * @param reference reference state from which Taylor expansion are estimated * @param scaled first scaled derivative * @param nordsieck Nordsieck vector * @param isForward integration direction indicator @@ -74,19 +67,20 @@ class AdamsFieldStepInterpolator> extends Abstract * @param globalCurrentState end of the global step * @param equationsMapper mapper for ODE equations primary and secondary components */ - private AdamsFieldStepInterpolator(final T stepSize, final T[] scaled, - final Array2DRowFieldMatrix nordsieck, - final boolean isForward, - final FieldODEStateAndDerivative globalPreviousState, - final FieldODEStateAndDerivative globalCurrentState, - final FieldEquationsMapper equationsMapper) { - this(stepSize, scaled, nordsieck, + AdamsFieldStepInterpolator(final T stepSize, final FieldODEStateAndDerivative reference, + final T[] scaled, final Array2DRowFieldMatrix nordsieck, + final boolean isForward, + final FieldODEStateAndDerivative globalPreviousState, + final FieldODEStateAndDerivative globalCurrentState, + final FieldEquationsMapper equationsMapper) { + this(stepSize, reference, scaled, nordsieck, isForward, globalPreviousState, globalCurrentState, globalPreviousState, globalCurrentState, equationsMapper); } /** Simple constructor. * @param stepSize step size used in the scaled and Nordsieck arrays + * @param reference reference state from which Taylor expansion are estimated * @param scaled first scaled derivative * @param nordsieck Nordsieck vector * @param isForward integration direction indicator @@ -96,8 +90,8 @@ class AdamsFieldStepInterpolator> extends Abstract * @param softCurrentState end of the restricted step * @param equationsMapper mapper for ODE equations primary and secondary components */ - private AdamsFieldStepInterpolator(final T stepSize, final T[] scaled, - final Array2DRowFieldMatrix nordsieck, + private AdamsFieldStepInterpolator(final T stepSize, final FieldODEStateAndDerivative reference, + final T[] scaled, final Array2DRowFieldMatrix nordsieck, final boolean isForward, final FieldODEStateAndDerivative globalPreviousState, final FieldODEStateAndDerivative globalCurrentState, @@ -107,6 +101,7 @@ class AdamsFieldStepInterpolator> extends Abstract super(isForward, globalPreviousState, globalCurrentState, softPreviousState, softCurrentState, equationsMapper); this.scalingH = stepSize; + this.reference = reference; this.scaled = scaled.clone(); this.nordsieck = new Array2DRowFieldMatrix(nordsieck.getData(), false); } @@ -126,7 +121,7 @@ class AdamsFieldStepInterpolator> extends Abstract FieldODEStateAndDerivative newSoftPreviousState, FieldODEStateAndDerivative newSoftCurrentState, FieldEquationsMapper newMapper) { - return new AdamsFieldStepInterpolator(scalingH, scaled, nordsieck, + return new AdamsFieldStepInterpolator(scalingH, reference, scaled, nordsieck, newForward, newGlobalPreviousState, newGlobalCurrentState, newSoftPreviousState, newSoftCurrentState, @@ -139,11 +134,11 @@ class AdamsFieldStepInterpolator> extends Abstract protected FieldODEStateAndDerivative computeInterpolatedStateAndDerivatives(final FieldEquationsMapper equationsMapper, final T time, final T theta, final T thetaH, final T oneMinusThetaH) { - return taylor(getPreviousState(), time, scalingH, scaled, nordsieck); + return taylor(reference, time, scalingH, scaled, nordsieck); } /** Estimate state by applying Taylor formula. - * @param referenceState reference state + * @param reference reference state * @param time time at which state must be estimated * @param stepSize step size used in the scaled and Nordsieck arrays * @param scaled first scaled derivative @@ -151,12 +146,12 @@ class AdamsFieldStepInterpolator> extends Abstract * @return estimated state * @param the type of the field elements */ - private static > FieldODEStateAndDerivative taylor(final FieldODEStateAndDerivative referenceState, - final S time, final S stepSize, - final S[] scaled, - final Array2DRowFieldMatrix nordsieck) { + public static > FieldODEStateAndDerivative taylor(final FieldODEStateAndDerivative reference, + final S time, final S stepSize, + final S[] scaled, + final Array2DRowFieldMatrix nordsieck) { - final S x = time.subtract(referenceState.getTime()); + final S x = time.subtract(reference.getTime()); final S normalizedAbscissa = x.divide(stepSize); S[] stateVariation = MathArrays.buildArray(time.getField(), scaled.length); @@ -178,7 +173,7 @@ class AdamsFieldStepInterpolator> extends Abstract } } - S[] estimatedState = referenceState.getState(); + S[] estimatedState = reference.getState(); for (int j = 0; j < stateVariation.length; ++j) { stateVariation[j] = stateVariation[j].add(scaled[j].multiply(normalizedAbscissa)); estimatedState[j] = estimatedState[j].add(stateVariation[j]); diff --git a/src/main/java/org/apache/commons/math3/ode/nonstiff/AdamsMoultonFieldIntegrator.java b/src/main/java/org/apache/commons/math3/ode/nonstiff/AdamsMoultonFieldIntegrator.java new file mode 100644 index 000000000..2594321fb --- /dev/null +++ b/src/main/java/org/apache/commons/math3/ode/nonstiff/AdamsMoultonFieldIntegrator.java @@ -0,0 +1,416 @@ +/* + * Licensed to the Apache Software Foundation (ASF) under one or more + * contributor license agreements. See the NOTICE file distributed with + * this work for additional information regarding copyright ownership. + * The ASF licenses this file to You under the Apache License, Version 2.0 + * (the "License"); you may not use this file except in compliance with + * the License. You may obtain a copy of the License at + * + * http://www.apache.org/licenses/LICENSE-2.0 + * + * Unless required by applicable law or agreed to in writing, software + * distributed under the License is distributed on an "AS IS" BASIS, + * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. + * See the License for the specific language governing permissions and + * limitations under the License. + */ + +package org.apache.commons.math3.ode.nonstiff; + +import java.util.Arrays; + +import org.apache.commons.math3.Field; +import org.apache.commons.math3.RealFieldElement; +import org.apache.commons.math3.exception.DimensionMismatchException; +import org.apache.commons.math3.exception.MaxCountExceededException; +import org.apache.commons.math3.exception.NoBracketingException; +import org.apache.commons.math3.exception.NumberIsTooSmallException; +import org.apache.commons.math3.linear.Array2DRowFieldMatrix; +import org.apache.commons.math3.linear.FieldMatrixPreservingVisitor; +import org.apache.commons.math3.ode.FieldExpandableODE; +import org.apache.commons.math3.ode.FieldODEState; +import org.apache.commons.math3.ode.FieldODEStateAndDerivative; +import org.apache.commons.math3.util.MathArrays; +import org.apache.commons.math3.util.MathUtils; + + +/** + * This class implements implicit Adams-Moulton integrators for Ordinary + * Differential Equations. + * + *

Adams-Moulton methods (in fact due to Adams alone) are implicit + * multistep ODE solvers. This implementation is a variation of the classical + * one: it uses adaptive stepsize to implement error control, whereas + * classical implementations are fixed step size. The value of state vector + * at step n+1 is a simple combination of the value at step n and of the + * derivatives at steps n+1, n, n-1 ... Since y'n+1 is needed to + * compute yn+1, another method must be used to compute a first + * estimate of yn+1, then compute y'n+1, then compute + * a final estimate of yn+1 using the following formulas. Depending + * on the number k of previous steps one wants to use for computing the next + * value, different formulas are available for the final estimate:

+ *
    + *
  • k = 1: yn+1 = yn + h y'n+1
    • + *
  • k = 2: yn+1 = yn + h (y'n+1+y'n)/2
    • + *
  • k = 3: yn+1 = yn + h (5y'n+1+8y'n-y'n-1)/12
    • + *
  • k = 4: yn+1 = yn + h (9y'n+1+19y'n-5y'n-1+y'n-2)/24
    • + *
  • ...
    • + *
+ * + *

A k-steps Adams-Moulton method is of order k+1.

+ * + *

Implementation details

+ * + *

We define scaled derivatives si(n) at step n as: + * 

+ * s1(n) = h y'n for first derivative
+ * s2(n) = h2/2 y''n for second derivative
+ * s3(n) = h3/6 y'''n for third derivative
+ * ...
+ * sk(n) = hk/k! y(k)n for kth derivative
+ *

+ * + *

The definitions above use the classical representation with several previous first + * derivatives. Lets define + * 

+ *   qn = [ s1(n-1) s1(n-2) ... s1(n-(k-1)) ]T
+ *
+ * (we omit the k index in the notation for clarity). With these definitions, + * Adams-Moulton methods can be written: + *
    + *
  • k = 1: yn+1 = yn + s1(n+1)
    • + *
  • k = 2: yn+1 = yn + 1/2 s1(n+1) + [ 1/2 ] qn+1
    • + *
  • k = 3: yn+1 = yn + 5/12 s1(n+1) + [ 8/12 -1/12 ] qn+1
    • + *
  • k = 4: yn+1 = yn + 9/24 s1(n+1) + [ 19/24 -5/24 1/24 ] qn+1
    • + *
  • ...
    • + *

+ * + *

Instead of using the classical representation with first derivatives only (yn, + * s1(n+1) and qn+1), our implementation uses the Nordsieck vector with + * higher degrees scaled derivatives all taken at the same step (yn, s1(n) + * and rn) where rn is defined as: + * 

+ * rn = [ s2(n), s3(n) ... sk(n) ]T
+ *
+ * (here again we omit the k index in the notation for clarity) + *

+ * + *

Taylor series formulas show that for any index offset i, s1(n-i) can be + * computed from s1(n), s2(n) ... sk(n), the formula being exact + * for degree k polynomials. + * 

+ * s1(n-i) = s1(n) + ∑j>0 (j+1) (-i)j sj+1(n)
+ *
+ * The previous formula can be used with several values for i to compute the transform between + * classical representation and Nordsieck vector. The transform between rn + * and qn resulting from the Taylor series formulas above is: + * 
+ * qn = s1(n) u + P rn
+ *
+ * where u is the [ 1 1 ... 1 ]T vector and P is the (k-1)×(k-1) matrix built + * with the (j+1) (-i)j terms with i being the row number starting from 1 and j being + * the column number starting from 1: + * 
+ *        [  -2   3   -4    5  ... ]
+ *        [  -4  12  -32   80  ... ]
+ *   P =  [  -6  27 -108  405  ... ]
+ *        [  -8  48 -256 1280  ... ]
+ *        [          ...           ]
+ *

+ * + *

Using the Nordsieck vector has several advantages: + *

    + *
  • it greatly simplifies step interpolation as the interpolator mainly applies + * Taylor series formulas,
    • + *
  • it simplifies step changes that occur when discrete events that truncate + * the step are triggered,
    • + *
  • it allows to extend the methods in order to support adaptive stepsize.
    • + *

+ * + *

The predicted Nordsieck vector at step n+1 is computed from the Nordsieck vector at step + * n as follows: + *

    + *
  • Yn+1 = yn + s1(n) + uT rn
    • + *
  • S1(n+1) = h f(tn+1, Yn+1)
    • + *
  • Rn+1 = (s1(n) - S1(n+1)) P-1 u + P-1 A P rn
    • + *
+ * where A is a rows shifting matrix (the lower left part is an identity matrix): + * 
+ *        [ 0 0   ...  0 0 | 0 ]
+ *        [ ---------------+---]
+ *        [ 1 0   ...  0 0 | 0 ]
+ *    A = [ 0 1   ...  0 0 | 0 ]
+ *        [       ...      | 0 ]
+ *        [ 0 0   ...  1 0 | 0 ]
+ *        [ 0 0   ...  0 1 | 0 ]
+ *
+ * From this predicted vector, the corrected vector is computed as follows: + *
    + *
  • yn+1 = yn + S1(n+1) + [ -1 +1 -1 +1 ... ±1 ] rn+1
    • + *
  • s1(n+1) = h f(tn+1, yn+1)
    • + *
  • rn+1 = Rn+1 + (s1(n+1) - S1(n+1)) P-1 u
    • + *
+ * where the upper case Yn+1, S1(n+1) and Rn+1 represent the + * predicted states whereas the lower case yn+1, sn+1 and rn+1 + * represent the corrected states.

+ * + *

The P-1u vector and the P-1 A P matrix do not depend on the state, + * they only depend on k and therefore are precomputed once for all.

+ * + * @param the type of the field elements + * @since 3.6 + */ +public class AdamsMoultonFieldIntegrator> extends AdamsFieldIntegrator { + + /** Integrator method name. */ + private static final String METHOD_NAME = "Adams-Moulton"; + + /** + * Build an Adams-Moulton integrator with the given order and error control parameters. + * @param field field to which the time and state vector elements belong + * @param nSteps number of steps of the method excluding the one being computed + * @param minStep minimal step (sign is irrelevant, regardless of + * integration direction, forward or backward), the last step can + * be smaller than this + * @param maxStep maximal step (sign is irrelevant, regardless of + * integration direction, forward or backward), the last step can + * be smaller than this + * @param scalAbsoluteTolerance allowed absolute error + * @param scalRelativeTolerance allowed relative error + * @exception NumberIsTooSmallException if order is 1 or less + */ + public AdamsMoultonFieldIntegrator(final Field field, final int nSteps, + final double minStep, final double maxStep, + final double scalAbsoluteTolerance, + final double scalRelativeTolerance) + throws NumberIsTooSmallException { + super(field, METHOD_NAME, nSteps, nSteps + 1, minStep, maxStep, + scalAbsoluteTolerance, scalRelativeTolerance); + } + + /** + * Build an Adams-Moulton integrator with the given order and error control parameters. + * @param field field to which the time and state vector elements belong + * @param nSteps number of steps of the method excluding the one being computed + * @param minStep minimal step (sign is irrelevant, regardless of + * integration direction, forward or backward), the last step can + * be smaller than this + * @param maxStep maximal step (sign is irrelevant, regardless of + * integration direction, forward or backward), the last step can + * be smaller than this + * @param vecAbsoluteTolerance allowed absolute error + * @param vecRelativeTolerance allowed relative error + * @exception IllegalArgumentException if order is 1 or less + */ + public AdamsMoultonFieldIntegrator(final Field field, final int nSteps, + final double minStep, final double maxStep, + final double[] vecAbsoluteTolerance, + final double[] vecRelativeTolerance) + throws IllegalArgumentException { + super(field, METHOD_NAME, nSteps, nSteps + 1, minStep, maxStep, + vecAbsoluteTolerance, vecRelativeTolerance); + } + + /** {@inheritDoc} */ + @Override + public FieldODEStateAndDerivative integrate(final FieldExpandableODE equations, + final FieldODEState initialState, + final T finalTime) + throws NumberIsTooSmallException, DimensionMismatchException, + MaxCountExceededException, NoBracketingException { + + sanityChecks(initialState, finalTime); + final T t0 = initialState.getTime(); + final T[] y = equations.getMapper().mapState(initialState); + setStepStart(initIntegration(equations, t0, y, finalTime)); + final boolean forward = finalTime.subtract(initialState.getTime()).getReal() > 0; + + // compute the initial Nordsieck vector using the configured starter integrator + start(equations, getStepStart(), finalTime); + + // reuse the step that was chosen by the starter integrator + FieldODEStateAndDerivative stepStart = getStepStart(); + FieldODEStateAndDerivative stepEnd = + AdamsFieldStepInterpolator.taylor(stepStart, + stepStart.getTime().add(getStepSize()), + getStepSize(), scaled, nordsieck); + + // main integration loop + setIsLastStep(false); + do { + + T[] predictedY = null; + final T[] predictedScaled = MathArrays.buildArray(getField(), y.length); + Array2DRowFieldMatrix predictedNordsieck = null; + T error = getField().getZero().add(10); + while (error.subtract(1.0).getReal() >= 0.0) { + + // predict a first estimate of the state at step end (P in the PECE sequence) + predictedY = stepEnd.getState(); + + // evaluate a first estimate of the derivative (first E in the PECE sequence) + final T[] yDot = computeDerivatives(stepEnd.getTime(), predictedY); + + // update Nordsieck vector + for (int j = 0; j < predictedScaled.length; ++j) { + predictedScaled[j] = getStepSize().multiply(yDot[j]); + } + predictedNordsieck = updateHighOrderDerivativesPhase1(nordsieck); + updateHighOrderDerivativesPhase2(scaled, predictedScaled, predictedNordsieck); + + // apply correction (C in the PECE sequence) + error = predictedNordsieck.walkInOptimizedOrder(new Corrector(y, predictedScaled, predictedY)); + + if (error.subtract(1.0).getReal() >= 0.0) { + // reject the step and attempt to reduce error by stepsize control + final T factor = computeStepGrowShrinkFactor(error); + rescale(filterStep(getStepSize().multiply(factor), forward, false)); + stepEnd = AdamsFieldStepInterpolator.taylor(getStepStart(), + getStepStart().getTime().add(getStepSize()), + getStepSize(), + scaled, + nordsieck); + } + } + + // evaluate a final estimate of the derivative (second E in the PECE sequence) + final T[] correctedYDot = computeDerivatives(stepEnd.getTime(), predictedY); + + // update Nordsieck vector + final T[] correctedScaled = MathArrays.buildArray(getField(), y.length); + for (int j = 0; j < correctedScaled.length; ++j) { + correctedScaled[j] = getStepSize().multiply(correctedYDot[j]); + } + updateHighOrderDerivativesPhase2(predictedScaled, correctedScaled, predictedNordsieck); + + // discrete events handling + stepEnd = new FieldODEStateAndDerivative(stepEnd.getTime(), predictedY, correctedYDot); + setStepStart(acceptStep(new AdamsFieldStepInterpolator(getStepSize(), stepEnd, + correctedScaled, predictedNordsieck, forward, + getStepStart(), stepEnd, + equations.getMapper()), + finalTime)); + scaled = correctedScaled; + nordsieck = predictedNordsieck; + + if (!isLastStep()) { + + System.arraycopy(predictedY, 0, y, 0, y.length); + + if (resetOccurred()) { + // some events handler has triggered changes that + // invalidate the derivatives, we need to restart from scratch + start(equations, getStepStart(), finalTime); + } + + // stepsize control for next step + final T factor = computeStepGrowShrinkFactor(error); + final T scaledH = getStepSize().multiply(factor); + final T nextT = getStepStart().getTime().add(scaledH); + final boolean nextIsLast = forward ? + nextT.subtract(finalTime).getReal() >= 0 : + nextT.subtract(finalTime).getReal() <= 0; + T hNew = filterStep(scaledH, forward, nextIsLast); + + final T filteredNextT = getStepStart().getTime().add(hNew); + final boolean filteredNextIsLast = forward ? + filteredNextT.subtract(finalTime).getReal() >= 0 : + filteredNextT.subtract(finalTime).getReal() <= 0; + if (filteredNextIsLast) { + hNew = finalTime.subtract(getStepStart().getTime()); + } + + rescale(hNew); + stepEnd = AdamsFieldStepInterpolator.taylor(getStepStart(), getStepStart().getTime().add(getStepSize()), + getStepSize(), scaled, nordsieck); + + } + + } while (!isLastStep()); + + final FieldODEStateAndDerivative finalState = getStepStart(); + setStepStart(null); + setStepSize(null); + return finalState; + + } + + /** Corrector for current state in Adams-Moulton method. + *

+ * This visitor implements the Taylor series formula: + * 

+     * Yn+1 = yn + s1(n+1) + [ -1 +1 -1 +1 ... ±1 ] rn+1
+     *
+ *

+ */ + private class Corrector implements FieldMatrixPreservingVisitor { + + /** Previous state. */ + private final T[] previous; + + /** Current scaled first derivative. */ + private final T[] scaled; + + /** Current state before correction. */ + private final T[] before; + + /** Current state after correction. */ + private final T[] after; + + /** Simple constructor. + * @param previous previous state + * @param scaled current scaled first derivative + * @param state state to correct (will be overwritten after visit) + */ + Corrector(final T[] previous, final T[] scaled, final T[] state) { + this.previous = previous; + this.scaled = scaled; + this.after = state; + this.before = state.clone(); + } + + /** {@inheritDoc} */ + public void start(int rows, int columns, + int startRow, int endRow, int startColumn, int endColumn) { + Arrays.fill(after, getField().getZero()); + } + + /** {@inheritDoc} */ + public void visit(int row, int column, T value) { + if ((row & 0x1) == 0) { + after[column] = after[column].subtract(value); + } else { + after[column] = after[column].add(value); + } + } + + /** + * End visiting the Nordsieck vector. + *

The correction is used to control stepsize. So its amplitude is + * considered to be an error, which must be normalized according to + * error control settings. If the normalized value is greater than 1, + * the correction was too large and the step must be rejected.

+ * @return the normalized correction, if greater than 1, the step + * must be rejected + */ + public T end() { + + T error = getField().getZero(); + for (int i = 0; i < after.length; ++i) { + after[i] = after[i].add(previous[i].add(scaled[i])); + if (i < mainSetDimension) { + final T yScale = MathUtils.max(previous[i].abs(), after[i].abs()); + final T tol = (vecAbsoluteTolerance == null) ? + yScale.multiply(scalRelativeTolerance).add(scalAbsoluteTolerance) : + yScale.multiply(vecRelativeTolerance[i]).add(vecAbsoluteTolerance[i]); + final T ratio = after[i].subtract(before[i]).divide(tol); // (corrected-predicted)/tol + error = error.add(ratio.multiply(ratio)); + } + } + + return error.divide(mainSetDimension).sqrt(); + + } + } + +} diff --git a/src/test/java/org/apache/commons/math3/ode/nonstiff/AbstractAdamsFieldIntegratorTest.java b/src/test/java/org/apache/commons/math3/ode/nonstiff/AbstractAdamsFieldIntegratorTest.java index 63ab60da8..74a584177 100644 --- a/src/test/java/org/apache/commons/math3/ode/nonstiff/AbstractAdamsFieldIntegratorTest.java +++ b/src/test/java/org/apache/commons/math3/ode/nonstiff/AbstractAdamsFieldIntegratorTest.java @@ -74,10 +74,10 @@ public abstract class AbstractAdamsFieldIntegratorTest { public abstract void testIncreasingTolerance(); protected > void doTestIncreasingTolerance(final Field field, - int ratioMin, int ratioMax) { + double ratioMin, double ratioMax) { int previousCalls = Integer.MAX_VALUE; - for (int i = -12; i < -5; ++i) { + for (int i = -12; i < -2; ++i) { TestFieldProblem1 pb = new TestFieldProblem1(field); double minStep = 0; double maxStep = pb.getFinalTime().subtract(pb.getInitialState().getTime()).getReal(); @@ -106,7 +106,7 @@ public abstract class AbstractAdamsFieldIntegratorTest { @Test(expected = MaxCountExceededException.class) public abstract void exceedMaxEvaluations(); - protected > void doExceedMaxEvaluations(final Field field) { + protected > void doExceedMaxEvaluations(final Field field, final int max) { TestFieldProblem1 pb = new TestFieldProblem1(field); double range = pb.getFinalTime().subtract(pb.getInitialState().getTime()).getReal(); @@ -114,7 +114,7 @@ public abstract class AbstractAdamsFieldIntegratorTest { FirstOrderFieldIntegrator integ = createIntegrator(field, 2, 0, range, 1.0e-12, 1.0e-12); TestFieldProblemHandler handler = new TestFieldProblemHandler(pb, integ); integ.addStepHandler(handler); - integ.setMaxEvaluations(650); + integ.setMaxEvaluations(max); integ.integrate(new FieldExpandableODE(pb), pb.getInitialState(), pb.getFinalTime()); } @@ -132,7 +132,6 @@ public abstract class AbstractAdamsFieldIntegratorTest { double range = pb.getFinalTime().subtract(pb.getInitialState().getTime()).getReal(); AdamsFieldIntegrator integ = createIntegrator(field, 4, 0, range, 1.0e-12, 1.0e-12); - integ.setStarterIntegrator(new PerfectStarter(pb, (integ.getNSteps() + 5) / 2)); TestFieldProblemHandler handler = new TestFieldProblemHandler(pb, integ); integ.addStepHandler(handler); integ.integrate(new FieldExpandableODE(pb), pb.getInitialState(), pb.getFinalTime()); diff --git a/src/test/java/org/apache/commons/math3/ode/nonstiff/AdamsBashforthFieldIntegratorTest.java b/src/test/java/org/apache/commons/math3/ode/nonstiff/AdamsBashforthFieldIntegratorTest.java index e425df66e..9b7c45e33 100644 --- a/src/test/java/org/apache/commons/math3/ode/nonstiff/AdamsBashforthFieldIntegratorTest.java +++ b/src/test/java/org/apache/commons/math3/ode/nonstiff/AdamsBashforthFieldIntegratorTest.java @@ -49,15 +49,15 @@ public class AdamsBashforthFieldIntegratorTest extends AbstractAdamsFieldIntegra @Test public void testIncreasingTolerance() { - // the 7 and 121 factors are only valid for this test + // the 2.6 and 122 factors are only valid for this test // and has been obtained from trial and error // there are no general relationship between local and global errors - doTestIncreasingTolerance(Decimal64Field.getInstance(), 7, 121); + doTestIncreasingTolerance(Decimal64Field.getInstance(), 2.6, 122); } @Test(expected = MaxCountExceededException.class) public void exceedMaxEvaluations() { - doExceedMaxEvaluations(Decimal64Field.getInstance()); + doExceedMaxEvaluations(Decimal64Field.getInstance(), 650); } @Test diff --git a/src/test/java/org/apache/commons/math3/ode/nonstiff/AdamsBashforthIntegratorTest.java b/src/test/java/org/apache/commons/math3/ode/nonstiff/AdamsBashforthIntegratorTest.java index 465d06f9e..acbb4289b 100644 --- a/src/test/java/org/apache/commons/math3/ode/nonstiff/AdamsBashforthIntegratorTest.java +++ b/src/test/java/org/apache/commons/math3/ode/nonstiff/AdamsBashforthIntegratorTest.java @@ -77,7 +77,7 @@ public class AdamsBashforthIntegratorTest { public void testIncreasingTolerance() throws DimensionMismatchException, NumberIsTooSmallException, MaxCountExceededException, NoBracketingException { int previousCalls = Integer.MAX_VALUE; - for (int i = -12; i < -5; ++i) { + for (int i = -12; i < -2; ++i) { TestProblem1 pb = new TestProblem1(); double minStep = 0; double maxStep = pb.getFinalTime() - pb.getInitialTime(); @@ -93,10 +93,10 @@ public class AdamsBashforthIntegratorTest { pb.getInitialTime(), pb.getInitialState(), pb.getFinalTime(), new double[pb.getDimension()]); - // the 8 and 122 factors are only valid for this test + // the 2.6 and 122 factors are only valid for this test // and has been obtained from trial and error // there are no general relationship between local and global errors - Assert.assertTrue(handler.getMaximalValueError() > ( 8 * scalAbsoluteTolerance)); + Assert.assertTrue(handler.getMaximalValueError() > (2.6 * scalAbsoluteTolerance)); Assert.assertTrue(handler.getMaximalValueError() < (122 * scalAbsoluteTolerance)); int calls = pb.getCalls(); diff --git a/src/test/java/org/apache/commons/math3/ode/nonstiff/AdamsMoultonFieldIntegratorTest.java b/src/test/java/org/apache/commons/math3/ode/nonstiff/AdamsMoultonFieldIntegratorTest.java new file mode 100644 index 000000000..2a389b408 --- /dev/null +++ b/src/test/java/org/apache/commons/math3/ode/nonstiff/AdamsMoultonFieldIntegratorTest.java @@ -0,0 +1,78 @@ +/* + * Licensed to the Apache Software Foundation (ASF) under one or more + * contributor license agreements. See the NOTICE file distributed with + * this work for additional information regarding copyright ownership. + * The ASF licenses this file to You under the Apache License, Version 2.0 + * (the "License"); you may not use this file except in compliance with + * the License. You may obtain a copy of the License at + * + * http://www.apache.org/licenses/LICENSE-2.0 + * + * Unless required by applicable law or agreed to in writing, software + * distributed under the License is distributed on an "AS IS" BASIS, + * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. + * See the License for the specific language governing permissions and + * limitations under the License. + */ + +package org.apache.commons.math3.ode.nonstiff; + + +import org.apache.commons.math3.Field; +import org.apache.commons.math3.RealFieldElement; +import org.apache.commons.math3.exception.MathIllegalStateException; +import org.apache.commons.math3.exception.MaxCountExceededException; +import org.apache.commons.math3.exception.NumberIsTooSmallException; +import org.apache.commons.math3.util.Decimal64Field; +import org.junit.Test; + +public class AdamsMoultonFieldIntegratorTest extends AbstractAdamsFieldIntegratorTest { + + protected > AdamsFieldIntegrator + createIntegrator(Field field, final int nSteps, final double minStep, final double maxStep, + final double scalAbsoluteTolerance, final double scalRelativeTolerance) { + return new AdamsMoultonFieldIntegrator(field, nSteps, minStep, maxStep, + scalAbsoluteTolerance, scalRelativeTolerance); + } + + protected > AdamsFieldIntegrator + createIntegrator(Field field, final int nSteps, final double minStep, final double maxStep, + final double[] vecAbsoluteTolerance, final double[] vecRelativeTolerance) { + return new AdamsMoultonFieldIntegrator(field, nSteps, minStep, maxStep, + vecAbsoluteTolerance, vecRelativeTolerance); + } + + @Test(expected=NumberIsTooSmallException.class) + public void testMinStep() { + doDimensionCheck(Decimal64Field.getInstance()); + } + + @Test + public void testIncreasingTolerance() { + // the 0.45 and 8.69 factors are only valid for this test + // and has been obtained from trial and error + // there are no general relationship between local and global errors + doTestIncreasingTolerance(Decimal64Field.getInstance(), 0.45, 8.69); + } + + @Test(expected = MaxCountExceededException.class) + public void exceedMaxEvaluations() { + doExceedMaxEvaluations(Decimal64Field.getInstance(), 650); + } + + @Test + public void backward() { + doBackward(Decimal64Field.getInstance(), 3.0e-9, 3.0e-9, 1.0e-16, "Adams-Moulton"); + } + + @Test + public void polynomial() { + doPolynomial(Decimal64Field.getInstance(), 5, 2.2e-05, 1.1e-11); + } + + @Test(expected=MathIllegalStateException.class) + public void testStartFailure() { + doTestStartFailure(Decimal64Field.getInstance()); + } + +}