DualQuadricRobustEstimator.java
/*
* Copyright (C) 2015 Alberto Irurueta Carro (alberto@irurueta.com)
*
* Licensed 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 com.irurueta.geometry.estimators;
import com.irurueta.algebra.AlgebraException;
import com.irurueta.algebra.Matrix;
import com.irurueta.geometry.DualQuadric;
import com.irurueta.geometry.Plane;
import com.irurueta.numerical.robust.RobustEstimatorException;
import com.irurueta.numerical.robust.RobustEstimatorMethod;
import java.util.List;
/**
* This is an abstract class for algorithms to robustly find the best dual
* quadric that fits in a collection of 3D planes.
* Implementations of this class should be able to detect and discard outliers
* in order to find the best solution.
*/
@SuppressWarnings("DuplicatedCode")
public abstract class DualQuadricRobustEstimator {
/**
* Minimum number of 3D planes required to estimate a Dual Quadric.
*/
public static final int MINIMUM_SIZE = 9;
/**
* Default amount of progress variation before notifying a change in
* estimation progress. By default, this is set to 5%.
*/
public static final float DEFAULT_PROGRESS_DELTA = 0.05f;
/**
* Minimum allowed value for progress delta.
*/
public static final float MIN_PROGRESS_DELTA = 0.0f;
/**
* Maximum allowed value for progress delta.
*/
public static final float MAX_PROGRESS_DELTA = 1.0f;
/**
* Constant defining default confidence of the estimated result, which is
* 99%. This means that with a probability of 99% estimation will be
* accurate because chosen sub-samples will be inliers.
*/
public static final double DEFAULT_CONFIDENCE = 0.99;
/**
* Default maximum allowed number of iterations.
*/
public static final int DEFAULT_MAX_ITERATIONS = 5000;
/**
* Minimum allowed confidence value.
*/
public static final double MIN_CONFIDENCE = 0.0;
/**
* Maximum allowed confidence value.
*/
public static final double MAX_CONFIDENCE = 1.0;
/**
* Minimum allowed number of iterations.
*/
public static final int MIN_ITERATIONS = 1;
/**
* Default robust estimator method when none is provided.
*/
public static final RobustEstimatorMethod DEFAULT_ROBUST_METHOD = RobustEstimatorMethod.PROMEDS;
/**
* Listener to be notified of events such as when estimation starts, ends
* or its progress significantly changes.
*/
protected DualQuadricRobustEstimatorListener listener;
/**
* Indicates if this estimator is locked because an estimation is being
* computed.
*/
protected volatile boolean locked;
/**
* Amount of progress variation before notifying a progress change during
* estimation.
*/
protected float progressDelta;
/**
* Amount of confidence expressed as a value between 0.0 and 1.0 (which is
* equivalent to 100%). The amount of confidence indicates the probability
* that the estimated result is correct. Usually this value will be close
* to 1.0, but not exactly 1.0.
*/
protected double confidence;
/**
* Maximum allowed number of iterations. When the maximum number of
* iterations is exceeded, result will not be available, however an
* approximate result will be available for retrieval.
*/
protected int maxIterations;
/**
* List of planes to be used to estimate a dual quadric. Provided list must
* have a size greater or equal than MINIMUM_SIZE.
*/
protected List<Plane> planes;
/**
* Matrix representation of a 3D plane to be reused when computing
* residuals
*/
private Matrix testPlane;
/**
* Matrix representation of a dual quadric to be reused when computing
* residuals.
*/
private Matrix testDualQ;
/**
* Constructor.
*/
protected DualQuadricRobustEstimator() {
progressDelta = DEFAULT_PROGRESS_DELTA;
confidence = DEFAULT_CONFIDENCE;
maxIterations = DEFAULT_MAX_ITERATIONS;
}
/**
* Constructor.
*
* @param listener listener to be notified of events such as when estimation
* starts, ends or its progress significantly changes.
*/
protected DualQuadricRobustEstimator(final DualQuadricRobustEstimatorListener listener) {
this.listener = listener;
progressDelta = DEFAULT_PROGRESS_DELTA;
confidence = DEFAULT_CONFIDENCE;
maxIterations = DEFAULT_MAX_ITERATIONS;
}
/**
* Constructor with lines.
*
* @param planes planes to estimate a dual quadric.
* @throws IllegalArgumentException if provided list of planes don't have
* a size greater or equal than MINIMUM_SIZE.
*/
protected DualQuadricRobustEstimator(final List<Plane> planes) {
progressDelta = DEFAULT_PROGRESS_DELTA;
confidence = DEFAULT_CONFIDENCE;
maxIterations = DEFAULT_MAX_ITERATIONS;
internalSetPlanes(planes);
}
/**
* Constructor.
*
* @param listener listener to be notified of events such as when estimation
* starts, ends or its progress significantly changes.
* @param planes planes to estimate a dual quadric.
* @throws IllegalArgumentException if provided list of planes don't have a
* size greater or equal than MINIMUM_SIZE.
*/
protected DualQuadricRobustEstimator(final DualQuadricRobustEstimatorListener listener, final List<Plane> planes) {
this.listener = listener;
progressDelta = DEFAULT_PROGRESS_DELTA;
confidence = DEFAULT_CONFIDENCE;
maxIterations = DEFAULT_MAX_ITERATIONS;
internalSetPlanes(planes);
}
/**
* Returns reference to listener to be notified of events such as when
* estimation starts, ends or its progress significantly changes.
*
* @return listener to be notified of events.
*/
public DualQuadricRobustEstimatorListener getListener() {
return listener;
}
/**
* Sets listener to be notified of events such as when estimation starts,
* ends or its progress significantly changes.
*
* @param listener listener to be notified of events.
* @throws LockedException if robust estimator is locked.
*/
public void setListener(final DualQuadricRobustEstimatorListener listener) throws LockedException {
if (isLocked()) {
throw new LockedException();
}
this.listener = listener;
}
/**
* Indicates whether listener has been provided and is available for
* retrieval.
*
* @return true if available, false otherwise.
*/
public boolean isListenerAvailable() {
return listener != null;
}
/**
* Indicates if this instance is locked because estimation is being computed.
*
* @return true if locked, false otherwise.
*/
public boolean isLocked() {
return locked;
}
/**
* Returns amount of progress variation before notifying a progress change
* during estimation.
*
* @return amount of progress variation before notifying a progress change
* during estimation.
*/
public float getProgressDelta() {
return progressDelta;
}
/**
* Sets amount of progress variation before notifying a progress change
* during estimation.
*
* @param progressDelta amount of progress variation before notifying a
* progress change during estimation.
* @throws IllegalArgumentException if progress delta is less than zero or
* greater than 1.
* @throws LockedException if this estimator is locked because an estimation
* is being computed.
*/
public void setProgressDelta(final float progressDelta) throws LockedException {
if (isLocked()) {
throw new LockedException();
}
if (progressDelta < MIN_PROGRESS_DELTA || progressDelta > MAX_PROGRESS_DELTA) {
throw new IllegalArgumentException();
}
this.progressDelta = progressDelta;
}
/**
* Returns amount of confidence expressed as a value between 0.0 and 1.0
* (which is equivalent to 100%). The amount of confidence indicates that
* probability that the estimated result is correct. Usually this value will
* be close to 1.0, but not exactly 1.0.
*
* @return amount of confidence as a value between 0.0 and 1.0.
*/
public double getConfidence() {
return confidence;
}
/**
* Sets amount of confidence expressed as a value between 0.0 and 1.0 (which
* is equivalent to 100%). The amount of confidence indicates the
* probability that the estimated result is correct. Usually this value will
* be close to 1.0, but not exactly 1.0.
*
* @param confidence confidence to be set as a value between 0.0 and 1.0.
* @throws IllegalArgumentException if provided value is not between 0.0 and
* 1.0.
* @throws LockedException if this estimator is locked because an estimator
* is being computed.
*/
public void setConfidence(final double confidence) throws LockedException {
if (isLocked()) {
throw new LockedException();
}
if (confidence < MIN_CONFIDENCE || confidence > MAX_CONFIDENCE) {
throw new IllegalArgumentException();
}
this.confidence = confidence;
}
/**
* Returns maximum allowed number of iterations. If maximum allowed number
* of iterations is achieved without converging to a result when calling
* estimate(), a RobustEstimatorException will be raised.
*
* @return maximum allowed number of iterations.
*/
public int getMaxIterations() {
return maxIterations;
}
/**
* Sets maximum allowed number of iterations. When the maximum number of
* iterations is exceeded, result will not be available, however an
* approximate result will be available for retrieval.
*
* @param maxIterations maximum allowed number of iterations to be set.
* @throws IllegalArgumentException if provided value is less than 1.
* @throws LockedException if this estimator is locked because an estimation
* is being computed.
*/
public void setMaxIterations(final int maxIterations) throws LockedException {
if (isLocked()) {
throw new LockedException();
}
if (maxIterations < MIN_ITERATIONS) {
throw new IllegalArgumentException();
}
this.maxIterations = maxIterations;
}
/**
* Returns list of planes to be used to estimate a dual quadric.
* Provided list have a size greater or equal than MINIMUM_SIZE.
*
* @return list of planes to be used to estimate a dual quadric.
*/
public List<Plane> getPlanes() {
return planes;
}
/**
* Sets list of planes to be used to estimate a dual quadric.
* Provided list must have a size greater or equal than MINIMUM_SIZE.
*
* @param planes list of planes to be used to estimate a dual quadric.
* @throws IllegalArgumentException if provided list of planes doesn't have
* a size greater or equal than MINIMUM_SIZE.
* @throws LockedException if estimator is locked because a computation is
* already in progress.
*/
public void setPlanes(final List<Plane> planes) throws LockedException {
if (isLocked()) {
throw new LockedException();
}
internalSetPlanes(planes);
}
/**
* Indicates if estimator is ready to start the dual quadric estimation.
* This is true when MINIMUM_SIZE lines are available.
*
* @return true if estimator is ready, false otherwise.
*/
public boolean isReady() {
return planes != null && planes.size() >= MINIMUM_SIZE;
}
/**
* Returns quality scores corresponding to each plane.
* The larger the score value the better the quality of the plane measure.
* This implementation always return null.
* Subclasses using quality scores must implement proper behaviour.
*
* @return quality scores corresponding to each plane.
*/
public double[] getQualityScores() {
return null;
}
/**
* Sets quality scores corresponding to each plane.
* The larger the score value the better the quality of the matching.
* This implementation makes no action.
* Subclasses using quality scores must implement proper behaviour.
*
* @param qualityScores quality scores corresponding to each plane.
* @throws LockedException if robust estimator is locked because an
* estimation is already in progress.
* @throws IllegalArgumentException if provided quality scores length is
* smaller than MINIMUM_SIZE (i.e. 9 samples).
*/
public void setQualityScores(final double[] qualityScores) throws LockedException {
}
/**
* Creates a dual quadric robust estimator based on plane samples and using
* provided robust estimator method.
*
* @param method method of a robust estimator algorithm to estimate bes dual
* quadric.
* @return an instance of a dual quadric robust estimator.
*/
public static DualQuadricRobustEstimator create(final RobustEstimatorMethod method) {
return switch (method) {
case LMEDS -> new LMedSDualQuadricRobustEstimator();
case MSAC -> new MSACDualQuadricRobustEstimator();
case PROSAC -> new PROSACDualQuadricRobustEstimator();
case PROMEDS -> new PROMedSDualQuadricRobustEstimator();
default -> new RANSACDualQuadricRobustEstimator();
};
}
/**
* Creates a dual quadric robust estimator based on plane samples and using
* provided planes and robust estimator method.
*
* @param planes 3D planes to estimate a dual quadric.
* @param method method of a robust estimator algorithm to estimate the best
* dual quadric.
* @return an instance of a dual quadric robust estimator.
* @throws IllegalArgumentException if provided list of planes don't have a
* size greater or equal than MINIMUM_SIZE.
*/
public static DualQuadricRobustEstimator create(final List<Plane> planes, final RobustEstimatorMethod method) {
return switch (method) {
case LMEDS -> new LMedSDualQuadricRobustEstimator(planes);
case MSAC -> new MSACDualQuadricRobustEstimator(planes);
case PROSAC -> new PROSACDualQuadricRobustEstimator(planes);
case PROMEDS -> new PROMedSDualQuadricRobustEstimator(planes);
default -> new RANSACDualQuadricRobustEstimator(planes);
};
}
/**
* Creates a dual quadric robust estimator based on plane samples and using
* provided listener.
*
* @param listener listener to be notified of events such as when estimation
* starts, ends or its progress significantly changes.
* @param method method of a robust estimator algorithm to estimate the best
* dual quadric.
* @return an instance of a dual quadric robust estimator.
*/
public static DualQuadricRobustEstimator create(
final DualQuadricRobustEstimatorListener listener, final RobustEstimatorMethod method) {
return switch (method) {
case LMEDS -> new LMedSDualQuadricRobustEstimator(listener);
case MSAC -> new MSACDualQuadricRobustEstimator(listener);
case PROSAC -> new PROSACDualQuadricRobustEstimator(listener);
case PROMEDS -> new PROMedSDualQuadricRobustEstimator(listener);
default -> new RANSACDualQuadricRobustEstimator(listener);
};
}
/**
* Creates a dual quadric robust estimator based on plane samples and using
* provided listener and planes.
*
* @param listener listener to be notified of events such as when estimation
* starts, ends or its progress significantly changes.
* @param planes 3D planes to estimate a dual quadric.
* @param method method of a robust estimator algorithm to estimate the best
* dual quadric.
* @return an instance of a dual quadric robust estimator.
* @throws IllegalArgumentException if provided list of planes don't have a
* size greater or equal than MINIMUM_SIZE.
*/
public static DualQuadricRobustEstimator create(
final DualQuadricRobustEstimatorListener listener, final List<Plane> planes,
final RobustEstimatorMethod method) {
return switch (method) {
case LMEDS -> new LMedSDualQuadricRobustEstimator(listener, planes);
case MSAC -> new MSACDualQuadricRobustEstimator(listener, planes);
case PROSAC -> new PROSACDualQuadricRobustEstimator(listener, planes);
case PROMEDS -> new PROMedSDualQuadricRobustEstimator(listener, planes);
default -> new RANSACDualQuadricRobustEstimator(listener, planes);
};
}
/**
* Creates a dual quadric robust estimator based on plane samples and using
* provided robust estimator method.
*
* @param qualityScores quality scores corresponding to each provided plane.
* @param method method of a robust estimator algorithm to estimate bes dual
* quadric.
* @return an instance of a dual quadric robust estimator.
* @throws IllegalArgumentException if provided quality scores length is
* smaller than MINIMUM_SIZE (i.e. 9 planes).
*/
public static DualQuadricRobustEstimator create(final double[] qualityScores, final RobustEstimatorMethod method) {
return switch (method) {
case LMEDS -> new LMedSDualQuadricRobustEstimator();
case MSAC -> new MSACDualQuadricRobustEstimator();
case PROSAC -> new PROSACDualQuadricRobustEstimator(qualityScores);
case PROMEDS -> new PROMedSDualQuadricRobustEstimator(qualityScores);
default -> new RANSACDualQuadricRobustEstimator();
};
}
/**
* Creates a dual quadric robust estimator method based on plane samples and
* using provided planes and robust estimator method.
*
* @param planes 3D planes to estimate a dual quadric.
* @param qualityScores quality scores corresponding to each provided plane.
* @param method method of a robust estimator algorithm to estimate the best
* dual quadric.
* @return an instance of a dual quadric robust estimator.
* @throws IllegalArgumentException if provided list of planes don't have
* the same size as the list of provided quality scores, or if their size
* is not greater or equal than MINIMUM_SIZE.
*/
public static DualQuadricRobustEstimator create(
final List<Plane> planes, final double[] qualityScores, final RobustEstimatorMethod method) {
return switch (method) {
case LMEDS -> new LMedSDualQuadricRobustEstimator(planes);
case MSAC -> new MSACDualQuadricRobustEstimator(planes);
case PROSAC -> new PROSACDualQuadricRobustEstimator(planes, qualityScores);
case PROMEDS -> new PROMedSDualQuadricRobustEstimator(planes, qualityScores);
default -> new RANSACDualQuadricRobustEstimator(planes);
};
}
/**
* Creates a dual quadric robust estimator based on plane samples and using
* provided listener.
*
* @param listener listener to be notified of events such as when estimation
* starts, ends or its progress significantly changes.
* @param qualityScores quality scores corresponding to each provided plane.
* @param method method of a robust estimator algorithm to estimate the best
* dual quadric.
* @return an instance of a dual quadric robust estimator.
* @throws IllegalArgumentException if provided quality scores length is
* smaller than MINIMUM_SIZE (i.e. 9 planes).
*/
public static DualQuadricRobustEstimator create(
final DualQuadricRobustEstimatorListener listener, final double[] qualityScores,
final RobustEstimatorMethod method) {
return switch (method) {
case LMEDS -> new LMedSDualQuadricRobustEstimator(listener);
case MSAC -> new MSACDualQuadricRobustEstimator(listener);
case PROSAC -> new PROSACDualQuadricRobustEstimator(listener, qualityScores);
case PROMEDS -> new PROMedSDualQuadricRobustEstimator(listener, qualityScores);
default -> new RANSACDualQuadricRobustEstimator(listener);
};
}
/**
* Creates a dual conic robust estimator based on 3D plane samples and using
* provided listener and planes.
*
* @param listener listener to be notified of events such as when estimation
* starts, ends or its progress significantly changes.
* @param planes 3D planes to estimate a dual quadric.
* @param qualityScores quality scores corresponding to each provided plane.
* @param method method of a robust estimator algorithm to estimate the best
* dual quadric.
* @return an instance of a dual quadric robust estimator.
* @throws IllegalArgumentException if provided list of planes don't have
* the same size as the list of provided quality scores, or it their size is
* not greater or equal than MINIMUM_SIZE.
*/
public static DualQuadricRobustEstimator create(
final DualQuadricRobustEstimatorListener listener, final List<Plane> planes,
final double[] qualityScores, final RobustEstimatorMethod method) {
return switch (method) {
case LMEDS -> new LMedSDualQuadricRobustEstimator(listener, planes);
case MSAC -> new MSACDualQuadricRobustEstimator(listener, planes);
case PROSAC -> new PROSACDualQuadricRobustEstimator(listener, planes, qualityScores);
case PROMEDS -> new PROMedSDualQuadricRobustEstimator(listener, planes, qualityScores);
default -> new RANSACDualQuadricRobustEstimator(listener, planes);
};
}
/**
* Creates a dual quadric robust estimator based on plane samples and using
* default robust estimator method.
*
* @return an instance of a dual quadric robust estimator.
*/
public static DualQuadricRobustEstimator create() {
return create(DEFAULT_ROBUST_METHOD);
}
/**
* Creates a dual quadric robust estimator based on plane samples and using
* provided planes and default robust estimator method.
*
* @param planes 3D planes to estimate a dual quadric.
* @return an instance of a dual quadric robust estimator.
* @throws IllegalArgumentException if provided list of planes doesn't have
* a size greater or equal than MINIMUM_SIZE.
*/
public static DualQuadricRobustEstimator create(final List<Plane> planes) {
return create(planes, DEFAULT_ROBUST_METHOD);
}
/**
* Creates a dual quadric robust estimator based on plane samples and using
* provided listener and default robust estimator method.
*
* @param listener listener to be notified of events such as when estimation
* starts, ends or its progress significantly changes.
* @return an instance of a dual quadric robust estimator.
*/
public static DualQuadricRobustEstimator create(final DualQuadricRobustEstimatorListener listener) {
return create(listener, DEFAULT_ROBUST_METHOD);
}
/**
* Creates a dual quadric robust estimator based on plane samples and using
* provided listener and lines and default robust estimator method.
*
* @param listener listener to be notified of events such as when estimation
* starts, ends or its progress significantly changes.
* @param planes 3D planes to estimate a dual quadric.
* @return an instance of a dual conic robust estimator.
* @throws IllegalArgumentException if provided list of planes doesn't have
* a size greater or equal than MINIMUM_SIZE.
*/
public static DualQuadricRobustEstimator create(
final DualQuadricRobustEstimatorListener listener, final List<Plane> planes) {
return create(listener, planes, DEFAULT_ROBUST_METHOD);
}
/**
* Creates a dual quadric robust estimator based on 3D plane samples and
* using default robust estimator method.
*
* @param qualityScores quality scores corresponding to each provided plane.
* @return an instance of a dual quadric robust estimator.
* @throws IllegalArgumentException if provided quality scores length is
* smaller than MINIMUM_SIZE (i.e. 9 planes).
*/
public static DualQuadricRobustEstimator create(final double[] qualityScores) {
return create(qualityScores, DEFAULT_ROBUST_METHOD);
}
/**
* Creates a dual quadric robust estimator based on plane samples and using
* provided planes and default estimator method.
*
* @param planes 3D planes to estimate a dual quadric.
* @param qualityScores quality scores corresponding to each provided plane.
* @return an instance of a dual conic robust estimator.
* @throws IllegalArgumentException if provided list of planes don't have the
* same size as the list of provided quality scores, or if their size is not
* greater or equal than MINIMUM_SIZE.
*/
public static DualQuadricRobustEstimator create(final List<Plane> planes, final double[] qualityScores) {
return create(planes, qualityScores, DEFAULT_ROBUST_METHOD);
}
/**
* Creates a dual quadric robust estimator based on plane samples and using
* provided listener and default estimator method.
*
* @param listener listener to be notified of events such as when estimation
* starts, ends or its progress significantly changes.
* @param qualityScores quality scores corresponding to each provided plane
* @return an instance of a dual quadric robust estimator.
* @throws IllegalArgumentException if provided quality scores length is
* smaller than MINIMUM_SIZE (i.e. 9 planes).
*/
public static DualQuadricRobustEstimator create(
final DualQuadricRobustEstimatorListener listener, final double[] qualityScores) {
return create(listener, qualityScores, DEFAULT_ROBUST_METHOD);
}
/**
* Creates a dual quadric robust estimator based on plane samples and using
* provided listener and planes and default estimator method.
*
* @param listener listener to be notified of events such as when estimation
* starts, ends or its progress significantly changes.
* @param planes 3D planes to estimate a dual quadric.
* @param qualityScores quality scores corresponding to each provided plane
* @return an instance of a dual quadric robust estimator.
* @throws IllegalArgumentException if provided list of planes don't have
* the same size as the list of provided quality scores, or if their size is
* not greater or equal than MINIMUM_SIZE.
*/
public static DualQuadricRobustEstimator create(
final DualQuadricRobustEstimatorListener listener, final List<Plane> planes, final double[] qualityScores) {
return create(listener, planes, qualityScores, DEFAULT_ROBUST_METHOD);
}
/**
* Estimates a dual conic using a robust estimator and the best set of 3D
* planes that fit into the locus of the estimated dual quadric found using
* the robust estimator.
*
* @return a dual quadric.
* @throws LockedException if robust estimator is locked because an
* estimation is already in progress.
* @throws NotReadyException if provided input data is not enough to start
* the estimation.
* @throws RobustEstimatorException if estimation fails for any reason (i.e.
* numerical instability, no solution available, etc).
*/
public abstract DualQuadric estimate() throws LockedException, NotReadyException, RobustEstimatorException;
/**
* Returns method being used for robust estimation.
*
* @return method being used for robust estimation.
*/
public abstract RobustEstimatorMethod getMethod();
/**
* Internal method to set list of planes to be used to estimate a dual
* quadric.
* This method does not check whether estimator is locked or not.
*
* @param planes list of planes to be used to estimate a dual quadric.
* @throws IllegalArgumentException if provided list of planes doesn't have
* a size greater or equal than MINIMUM_SIZE.
*/
private void internalSetPlanes(final List<Plane> planes) {
if (planes.size() < MINIMUM_SIZE) {
throw new IllegalArgumentException();
}
this.planes = planes;
}
/**
* Computes the residual between a dual quadric and a 3D plane.
*
* @param dq a dual quadric.
* @param plane a 3D plane.
* @return residual.
*/
protected double residual(final DualQuadric dq, final Plane plane) {
dq.normalize();
try {
if (testDualQ == null) {
testDualQ = dq.asMatrix();
} else {
dq.asMatrix(testDualQ);
}
if (testPlane == null) {
testPlane = new Matrix(Plane.PLANE_NUMBER_PARAMS, 1);
}
plane.normalize();
testPlane.setElementAt(0, 0, plane.getA());
testPlane.setElementAt(1, 0, plane.getB());
testPlane.setElementAt(2, 0, plane.getC());
testPlane.setElementAt(3, 0, plane.getD());
final var locusMatrix = testPlane.transposeAndReturnNew();
locusMatrix.multiply(testDualQ);
locusMatrix.multiply(testPlane);
return Math.abs(locusMatrix.getElementAt(0, 0));
} catch (final AlgebraException e) {
return Double.MAX_VALUE;
}
}
}