/*******************************************************************************
* Copyright 2015 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.sumproduct.sampledfactor;
import com.analog.lyric.dimple.model.variables.Real;
import com.analog.lyric.dimple.solvers.core.parameterizedMessages.NormalParameters;
import com.analog.lyric.dimple.solvers.gibbs.GibbsOptions;
import com.analog.lyric.dimple.solvers.gibbs.GibbsReal;
import com.analog.lyric.dimple.solvers.sumproduct.SumProductNormalEdge;
import com.analog.lyric.util.misc.Internal;
import cern.colt.list.DoubleArrayList;
/**
*
* @since 0.08
* @author Christopher Barber
* @category internal
*/
@Internal
class SumProductSampledNormalEdge extends SumProductNormalEdge
implements ISumProductSampledEdge<NormalParameters>
{
private final GibbsReal _svar;
SumProductSampledNormalEdge(GibbsReal svar)
{
super();
_svar = svar;
setVariableInputUniform();
}
@Override
public void setFactorToVarDirection()
{
_svar.setOption(GibbsOptions.saveAllSamples, true);
setVariableInputUniform();
}
@Override
public void setVarToFactorDirection()
{
_svar.setOption(GibbsOptions.saveAllSamples, false);
Real var = _svar.getModelObject();
if (!var.hasFixedValue()) // Only set the input if there isn't already a fixed value
{
NormalParameters inputMessage = varToFactorMsg;
if (varToFactorMsg.getPrecision() == 0)
{
var.setPrior(null); // If zero precision, then set the input to null to avoid numerical issues
}
else
{
var.setPrior(inputMessage);
}
}
}
@Override
public void setFactorToVarMsgFromSamples()
{
final NormalParameters outputMessage = factorToVarMsg;
// Get the raw sample array to avoid making a copy; this is unsafe, so be careful not to modify it
@SuppressWarnings("null")
DoubleArrayList sampleValues = _svar._getSampleArrayUnsafe();
@SuppressWarnings("null")
int numSamples = sampleValues.size();
// For all sample values, compute the output message
double sum = 0;
double sumsq = 0;
for (int i = 0; i < numSamples; i++)
{
double tmp = sampleValues.get(i);
if (Double.isInfinite(tmp) || Double.isNaN(tmp))
{
outputMessage.setNull();
return;
}
sum += tmp;
sumsq += tmp*tmp;
}
double mean = sum / numSamples;
double variance = (sumsq - sum*mean) / (numSamples - 1);
outputMessage.setMean(mean);
outputMessage.setVariance(variance);
}
private final void setVariableInputUniform()
{
Real var = _svar.getModelObject();
if (!var.hasFixedValue()) // Only set the input if there isn't already a fixed value
{
var.setPrior(null);
}
}
}