/******************************************************************************* * Copyright 2012 Analog Devices, Inc. * * 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.analog.lyric.dimple.model.variables; import org.eclipse.jdt.annotation.Nullable; import com.analog.lyric.collect.Supers; import com.analog.lyric.dimple.exceptions.DimpleException; import com.analog.lyric.dimple.factorfunctions.Normal; import com.analog.lyric.dimple.factorfunctions.core.FactorFunction; import com.analog.lyric.dimple.factorfunctions.core.IUnaryFactorFunction; import com.analog.lyric.dimple.factorfunctions.core.UnaryJointRealFactorFunction; import com.analog.lyric.dimple.model.domains.RealJointDomain; import com.analog.lyric.dimple.solvers.core.parameterizedMessages.MultivariateNormalParameters; @SuppressWarnings("deprecation") public class RealJoint extends VariableBase { // Constructors... public RealJoint(int size) { this(RealJointDomain.create(size)); } public RealJoint(RealJointDomain domain) { this(domain, "RealJoint"); } /** * @deprecated as of release 0.08 use {@link #RealJoint(RealJointDomain)} instead. */ @Deprecated public RealJoint(RealJointDomain domain, String modelerClassName) { super(domain, modelerClassName); } protected RealJoint(RealJoint that) { super(that); } @Override public RealJoint clone() { return new RealJoint(this); } @Override public RealJointDomain getDomain() { return (RealJointDomain)super.getDomain(); } public RealJointDomain getRealDomain() { return getDomain(); } public double[] getValue() { return (double[])requireSolver("getValue").getValue(); } public @Nullable MultivariateNormalParameters getBelief() { return (MultivariateNormalParameters)getBeliefObject(); } /*-------------------- * Deprecated methods */ /** * @deprecated use {@link #getPriorFunction()} instead */ @Deprecated public @Nullable Object getInput() { return getInputObject(); } /** * @deprecated use {@link #getPriorValue()} instead */ // Fix the variable to a specific value @Deprecated public final double[] getFixedValue() { Object tmp = getFixedValueObject(); if (tmp == null) throw new DimpleException("Fixed Value is not set"); else return (double[])tmp; } /** * @deprecated instead use {@link #setPrior(Object)} */ @Deprecated public void setFixedValue(double[] fixedValue) { // Verify that the fixed value is in the domain of the variable if (!getDomain().inDomain(fixedValue)) throw new DimpleException("Attempt to set fixed value outside of variable domain."); setFixedValueObject(fixedValue); } // FIXME - replace and deprecate public void setInput(@Nullable FactorFunction[] input) { setInputObject(input); } /** * @deprecated instead {@link #setPrior(Object)} to {@link MultivariateNormalParameters} instance. */ @Deprecated public void setInput(double [] means, double [][] covar) { setInputObject(new MultivariateNormalParameters(means,covar)); } /** * @deprecated instead use {@link #setPrior(Object)} */ @Deprecated public void setInput(@Nullable MultivariateNormalParameters msg) { setInputObject(msg); } @Deprecated @Override public void setInputObject(@Nullable Object value) { if (value instanceof Object[]) { final Object[] inputArray = (Object[])value; final int n = getDomain().getDimensions(); if (inputArray.length != n) throw new DimpleException("Number of Inputs must equal the variable dimension"); Normal[] normals = Supers.narrowArrayOf(Normal.class, inputArray); if (normals != null) { double[] mean = new double[n]; double[] variance = new double[n]; for (int i = 0; i < n; i++) { mean[i] = normals[i].getMean(); variance[i] = normals[i].getVariance(); } value = new MultivariateNormalParameters(mean, variance); } else { IUnaryFactorFunction[] functions = Supers.narrowArrayOf(IUnaryFactorFunction.class, inputArray); if (functions != null) { value = new UnaryJointRealFactorFunction(functions); } } } super.setInputObject(value); } }