/*******************************************************************************
* 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.model.repeated;
import com.analog.lyric.dimple.exceptions.DimpleException;
import com.analog.lyric.dimple.solvers.core.parameterizedMessages.NormalParameters;
public class DoubleArrayDataSink extends GenericDataSink<double[]>
{
public double [][] getArray()
{
double [][] retval = new double[_data.size()][];
int i = 0;
for (double [] data : _data)
{
retval[i] = data;
i++;
}
return retval;
}
// This is a hack to support backward compatibility with using double-arrays to represent
// beliefs represented as Gaussian parameters. For beliefs of this type, a new class of
// data sink should be created that explicitly supports this representation (as in the
// multivariate case). Then this hack can be removed at some point, and getNext from
// the base class can be used directly.
@Override
public double[] getNext()
{
if (_data.size() <= 0)
throw new DimpleException("Data sink is empty.");
Object value = _data.pollFirst();
if (value instanceof NormalParameters)
{
NormalParameters belief = (NormalParameters)value;
return new double[] {belief.getMean(), belief.getStandardDeviation()};
}
else
return (double[])value;
}
}