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[MATH-1033] Fix input parameter check in KalmanFilter. Thanks to Yuan Qu.

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git-svn-id: https://svn.apache.org/repos/asf/commons/proper/math/trunk@1531430 13f79535-47bb-0310-9956-ffa450edef68
This commit is contained in:
Thomas Neidhart 2013-10-11 21:39:09 +00:00
parent 1146cf6a60
commit c2801940ef
2 changed files with 12 additions and 7 deletions
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4
src/changes/changes.xml
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@ -51,6 +51,10 @@ If the output is not quite correct, check for invisible trailing spaces!
</properties> </properties>
<body> <body>
<release version="x.y" date="TBD" description="TBD"> <release version="x.y" date="TBD" description="TBD">
<action dev="tn" type="fix" issue="MATH-1033" due-to="Yuan Qu">
The "KalmanFilter" wrongly enforced a column dimension of 1 for
the provided control and measurement noise matrix.
</action>
<action dev="tn" type="fix" issue="MATH-1037" due-to="Aleksei Dievskii"> <action dev="tn" type="fix" issue="MATH-1037" due-to="Aleksei Dievskii">
Fix a typo in the "GeometricDistributionTest" and ensure that a meaningful Fix a typo in the "GeometricDistributionTest" and ensure that a meaningful
tolerance value is used when comparing test results with expected values. tolerance value is used when comparing test results with expected values.

15
src/main/java/org/apache/commons/math3/filter/KalmanFilter.java
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@ -182,14 +182,15 @@ public class KalmanFilter {
} }
// row dimension of B must be equal to A // row dimension of B must be equal to A
// if no control matrix is available, the row and column dimension will be 0
if (controlMatrix != null && if (controlMatrix != null &&
controlMatrix.getRowDimension() > 0 && controlMatrix.getRowDimension() > 0 &&
controlMatrix.getColumnDimension() > 0 && controlMatrix.getColumnDimension() > 0 &&
(controlMatrix.getRowDimension() != transitionMatrix.getRowDimension() || controlMatrix.getRowDimension() != transitionMatrix.getRowDimension()) {
controlMatrix.getColumnDimension() != 1)) {
throw new MatrixDimensionMismatchException(controlMatrix.getRowDimension(), throw new MatrixDimensionMismatchException(controlMatrix.getRowDimension(),
controlMatrix.getColumnDimension(), controlMatrix.getColumnDimension(),
transitionMatrix.getRowDimension(), 1); transitionMatrix.getRowDimension(),
controlMatrix.getColumnDimension());
} }
// Q must be equal to A // Q must be equal to A
@ -204,11 +205,11 @@ public class KalmanFilter {
} }
// row dimension of R must be equal to row dimension of H // row dimension of R must be equal to row dimension of H
if (measNoise.getRowDimension() != measurementMatrix.getRowDimension() || if (measNoise.getRowDimension() != measurementMatrix.getRowDimension()) {
measNoise.getColumnDimension() != 1) {
throw new MatrixDimensionMismatchException(measNoise.getRowDimension(), throw new MatrixDimensionMismatchException(measNoise.getRowDimension(),
measNoise.getColumnDimension(), measNoise.getColumnDimension(),
measurementMatrix.getRowDimension(), 1); measurementMatrix.getRowDimension(),
measNoise.getColumnDimension());
} }
} }
@ -356,7 +357,7 @@ public class KalmanFilter {
measurementMatrix.getRowDimension()); measurementMatrix.getRowDimension());
} }
// S = H * P(k) - * H' + R // S = H * P(k) * H' + R
RealMatrix s = measurementMatrix.multiply(errorCovariance) RealMatrix s = measurementMatrix.multiply(errorCovariance)
.multiply(measurementMatrixT) .multiply(measurementMatrixT)
.add(measurementModel.getMeasurementNoise()); .add(measurementModel.getMeasurementNoise());