ParameterDriver.java
/* Copyright 2002-2017 CS Systèmes d'Information
* Licensed to CS Systèmes d'Information (CS) under one or more
* contributor license agreements. See the NOTICE file distributed with
* this work for additional information regarding copyright ownership.
* CS 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.orekit.utils;
import java.util.ArrayList;
import java.util.List;
import org.hipparchus.util.FastMath;
import org.hipparchus.util.Precision;
import org.orekit.errors.OrekitException;
import org.orekit.errors.OrekitMessages;
import org.orekit.time.AbsoluteDate;
/** Class allowing to drive the value of a parameter.
* <p>
* This class is typically used as a bridge between an estimation
* algorithm (typically orbit determination or optimizer) and an
* internal parameter in a physical model that needs to be tuned,
* or a bridge between a finite differences algorithm and an
* internal parameter in a physical model that needs to be slightly
* offset. The physical model will expose to the algorithm a
* set of instances of this class so the algorithm can call the
* {@link #setValue(double)} method to update the
* parameter value. Each time the value is set, the physical model
* will be notified as it will register a {@link ParameterObserver
* ParameterObserver} for this purpose.
* </p>
* <p>
* This design has two major goals. First, it allows an external
* algorithm to drive internal parameters almost anonymously, as it only
* needs to get a list of instances of this class, without knowing
* what they really drive. Second, it allows the physical model to
* not expose directly setters methods for its parameters. In order
* to be able to modify the parameter value, the algorithm
* <em>must</em> retrieve a parameter driver.
* </p>
* @see ParameterObserver
* @author Luc Maisonobe
* @since 8.0
*/
public class ParameterDriver {
/** Name of the parameter. */
private String name;
/** Reference value. */
private final double referenceValue;
/** Scaling factor. */
private final double scale;
/** Minimum value. */
private final double minValue;
/** Maximum value. */
private final double maxValue;
/** Reference date.
* @since 9.0
*/
private AbsoluteDate referenceDate;
/** Current value. */
private double value;
/** Selection status.
* <p>
* Selection is used for estimated parameters in orbit determination,
* or to compute the Jacobian matrix in partial derivatives computation.
* </p>
*/
private boolean selected;
/** Observers observing this driver. */
private final List<ParameterObserver> observers;
/** Simple constructor.
* <p>
* At construction, the parameter is configured as <em>not</em> selected,
* the reference date is set to {@code null} and the value is set to the
* {@code referenceValue}.
* </p>
* @param name name of the parameter
* @param referenceValue reference value of the parameter
* @param scale scaling factor to convert the parameters value to
* non-dimensional (typically set to the expected standard deviation of the
* parameter), it must be non-zero
* @param minValue minimum value
* @param maxValue maximum value
* @exception OrekitException if scale is too close to zero
*/
public ParameterDriver(final String name, final double referenceValue,
final double scale, final double minValue,
final double maxValue)
throws OrekitException {
if (FastMath.abs(scale) <= Precision.SAFE_MIN) {
throw new OrekitException(OrekitMessages.TOO_SMALL_SCALE_FOR_PARAMETER,
name, scale);
}
this.name = name;
this.referenceValue = referenceValue;
this.scale = scale;
this.minValue = minValue;
this.maxValue = maxValue;
this.referenceDate = null;
this.value = referenceValue;
this.selected = false;
this.observers = new ArrayList<ParameterObserver>();
}
/** Add an observer for this driver.
* <p>
* The observer {@link ParameterObserver#valueChanged(double, ParameterDriver)
* valueChanged} method is called once automatically when the
* observer is added, and then called at each value change.
* </p>
* @param observer observer to add
* @exception OrekitException if the observer triggers one
* while being updated
*/
public void addObserver(final ParameterObserver observer)
throws OrekitException {
observers.add(observer);
observer.valueChanged(getValue(), this);
}
/** Change the name of this parameter driver.
* @param name new name
*/
public void setName(final String name) {
final String previousName = this.name;
this.name = name;
for (final ParameterObserver observer : observers) {
observer.nameChanged(previousName, this);
}
}
/** Get name.
* @return name
*/
public String getName() {
return name;
}
/** Get reference parameter value.
* @return reference parameter value
*/
public double getReferenceValue() {
return referenceValue;
}
/** Get minimum parameter value.
* @return minimum parameter value
*/
public double getMinValue() {
return minValue;
}
/** Get maximum parameter value.
* @return maximum parameter value
*/
public double getMaxValue() {
return maxValue;
}
/** Get scale.
* @return scale
*/
public double getScale() {
return scale;
}
/** Get normalized value.
* <p>
* The normalized value is a non-dimensional value
* suitable for use as part of a vector in an optimization
* process. It is computed as {@code (current - reference)/scale}.
* </p>
* @return normalized value
*/
public double getNormalizedValue() {
return (value - referenceValue) / scale;
}
/** Set normalized value.
* <p>
* The normalized value is a non-dimensional value
* suitable for use as part of a vector in an optimization
* process. It is computed as {@code (current - reference)/scale}.
* </p>
* @param normalized value
* @exception OrekitException if an observer throws one
*/
public void setNormalizedValue(final double normalized) throws OrekitException {
setValue(referenceValue + scale * normalized);
}
/** Get current reference date.
* @return current reference date (null if it was never set)
* @since 9.0
*/
public AbsoluteDate getReferenceDate() {
return referenceDate;
}
/** Set reference date.
* @param newReferenceDate new reference date
* @since 9.0
*/
public void setReferenceDate(final AbsoluteDate newReferenceDate) {
final AbsoluteDate previousReferenceDate = getReferenceDate();
referenceDate = newReferenceDate;
for (final ParameterObserver observer : observers) {
observer.referenceDateChanged(previousReferenceDate, this);
}
}
/** Get current parameter value.
* @return current parameter value
*/
public double getValue() {
return value;
}
/** Set parameter value.
* <p>
* If {@code newValue} is below {@link #getMinValue()}, it will
* be silently to {@link #getMinValue()}. If {@code newValue} is
* above {@link #getMaxValue()}, it will be silently to {@link
* #getMaxValue()}.
* </p>
* @param newValue new value
* @exception OrekitException if an observer throws one
*/
public void setValue(final double newValue) throws OrekitException {
final double previousValue = getValue();
value = FastMath.max(minValue, FastMath.min(maxValue, newValue));
for (final ParameterObserver observer : observers) {
observer.valueChanged(previousValue, this);
}
}
/** Configure a parameter selection status.
* <p>
* Selection is used for estimated parameters in orbit determination,
* or to compute the Jacobian matrix in partial derivatives computation.
* </p>
* @param selected if true the parameter is selected,
* otherwise it will be fixed
*/
public void setSelected(final boolean selected) {
final boolean previousSelection = isSelected();
this.selected = selected;
for (final ParameterObserver observer : observers) {
observer.selectionChanged(previousSelection, this);
}
}
/** Check if parameter is selected.
* <p>
* Selection is used for estimated parameters in orbit determination,
* or to compute the Jacobian matrix in partial derivatives computation.
* </p>
* @return true if parameter is selected, false if it is not
*/
public boolean isSelected() {
return selected;
}
/** Get a text representation of the parameter.
* @return text representation of the parameter, in the form name = value.
*/
public String toString() {
return name + " = " + value;
}
}