/*******************************************************************************
* Copyright 2013 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.solvers.gibbs.customFactors;
import static java.util.Objects.*;
import java.util.HashSet;
import java.util.Set;
import org.eclipse.jdt.annotation.Nullable;
import com.analog.lyric.dimple.factorfunctions.Poisson;
import com.analog.lyric.dimple.factorfunctions.core.FactorFunction;
import com.analog.lyric.dimple.model.core.EdgeState;
import com.analog.lyric.dimple.model.factors.Factor;
import com.analog.lyric.dimple.solvers.core.parameterizedMessages.GammaParameters;
import com.analog.lyric.dimple.solvers.gibbs.GibbsDiscrete;
import com.analog.lyric.dimple.solvers.gibbs.GibbsGammaEdge;
import com.analog.lyric.dimple.solvers.gibbs.GibbsRealFactor;
import com.analog.lyric.dimple.solvers.gibbs.GibbsSolverEdge;
import com.analog.lyric.dimple.solvers.gibbs.GibbsSolverGraph;
import com.analog.lyric.dimple.solvers.gibbs.samplers.conjugate.GammaSampler;
import com.analog.lyric.dimple.solvers.gibbs.samplers.conjugate.IRealConjugateSamplerFactory;
public class CustomPoisson extends GibbsRealFactor implements IRealConjugateFactor
{
private @Nullable GibbsDiscrete _outputVariable;
private int _lambdaParameterEdge;
private int _constantOutputValue;
private boolean _hasConstantOutput;
private static final int NO_PORT = -1;
private static final int OUTPUT_INDEX_FIXED_LAMBDA = 0; // If lambda is in constructor then output is first index (0)
private static final int LAMBDA_PARAMETER_INDEX = 0; // If lambda is not in constructor then lambda is first index (0)
private static final int OUTPUT_INDEX = 1; // If lambda is not in constructor then output is second index (1)
public CustomPoisson(Factor factor, GibbsSolverGraph parent)
{
super(factor, parent);
}
@Override
public @Nullable GibbsSolverEdge<?> createEdge(EdgeState edge)
{
if (edge.getFactorToVariableEdgeNumber() == _lambdaParameterEdge)
{
return new GibbsGammaEdge();
}
return null;
}
@SuppressWarnings("null")
@Override
public void updateEdgeMessage(EdgeState modelEdge, GibbsSolverEdge<?> solverEdge)
{
final int portNum = modelEdge.getFactorToVariableEdgeNumber();
if (portNum == _lambdaParameterEdge)
{
// Port is the probability-parameter input
// Determine sample alpha and beta parameters
GammaParameters outputMsg = (GammaParameters)solverEdge.factorToVarMsg;
// Get the current value of the output count
int outputValue = _hasConstantOutput ? _constantOutputValue : _outputVariable.getCurrentSampleIndex();
outputMsg.setAlphaMinusOne(outputValue);
outputMsg.setBeta(1);
}
else
super.updateEdgeMessage(modelEdge, solverEdge);
}
@Override
public Set<IRealConjugateSamplerFactory> getAvailableRealConjugateSamplers(int portNumber)
{
Set<IRealConjugateSamplerFactory> availableSamplers = new HashSet<IRealConjugateSamplerFactory>();
if (isPortLambdaParameter(portNumber)) // Conjugate sampler if edge is lambda-parameter input
availableSamplers.add(GammaSampler.factory); // Parameter inputs have conjugate Gamma distribution
return availableSamplers;
}
public boolean isPortLambdaParameter(int portNumber)
{
determineConstantsAndEdges(); // Call this here since initialize may not have been called yet
return (portNumber == _lambdaParameterEdge);
}
@Override
public void initialize()
{
super.initialize();
// Determine what parameters are constants or edges, and save the state
determineConstantsAndEdges();
}
private void determineConstantsAndEdges()
{
// Get the factor function and related state
final Factor factor = _model;
FactorFunction factorFunction = factor.getFactorFunction();
Poisson specificFactorFunction = (Poisson)factorFunction;
final int prevLambdaParameterEdge = _lambdaParameterEdge;
// Pre-determine whether or not the parameters are constant; if so save the value; if not save reference to the variable
_lambdaParameterEdge = NO_PORT;
_hasConstantOutput = false;
_constantOutputValue = -1;
_outputVariable = null;
if (specificFactorFunction.hasConstantLambdaParameter()) // Lambda parameter is constructor constant
{
_hasConstantOutput = factor.hasConstantAtIndex(OUTPUT_INDEX_FIXED_LAMBDA);
if (_hasConstantOutput)
{
_constantOutputValue =
requireNonNull(factor.getConstantValueByIndex(OUTPUT_INDEX_FIXED_LAMBDA)).getInt();
}
else
{
int outputEdge = factor.argIndexToSiblingNumber(OUTPUT_INDEX_FIXED_LAMBDA);
_outputVariable = (GibbsDiscrete)getSibling(outputEdge);
}
}
else // Variable or constant lambda parameter
{
if (!factor.hasConstantAtIndex(LAMBDA_PARAMETER_INDEX))
_lambdaParameterEdge = factor.argIndexToSiblingNumber(LAMBDA_PARAMETER_INDEX);
_hasConstantOutput = factor.hasConstantAtIndex(OUTPUT_INDEX);
if (_hasConstantOutput)
{
_constantOutputValue = requireNonNull(factor.getConstantValueByIndex(OUTPUT_INDEX)).getInt();
}
else
{
int outputEdge = factor.argIndexToSiblingNumber(OUTPUT_INDEX);
_outputVariable = (GibbsDiscrete)getSibling(outputEdge);
}
}
if (_lambdaParameterEdge != prevLambdaParameterEdge)
{
removeSiblingEdgeState();
}
}
}