/* Copyright (C) 2002 Univ. of Massachusetts Amherst, Computer Science Dept.
This file is part of "MALLET" (MAchine Learning for LanguagE Toolkit).
http://www.cs.umass.edu/~mccallum/mallet
This software is provided under the terms of the Common Public License,
version 1.0, as published by http://www.opensource.org. For further
information, see the file `LICENSE' included with this distribution. */
/**
@author Andrew McCallum <a href="mailto:mccallum@cs.umass.edu">mccallum@cs.umass.edu</a>
*/
package cc.mallet.pipe;
import cc.mallet.types.Alphabet;
import cc.mallet.types.AugmentableFeatureVector;
import cc.mallet.types.Instance;
/** Given an AugmentableFeatureVector, set those values greater than
or equal to 1 to log(value)+1. This is useful when multiple
counts should not be treated as independent evidence. */
public class AugmentableFeatureVectorLogScale extends Pipe
{
public AugmentableFeatureVectorLogScale ()
{
super ((Alphabet)null, null);
}
public Instance pipe (Instance carrier)
{
AugmentableFeatureVector afv = (AugmentableFeatureVector)carrier.getData();
double v;
for (int i = afv.numLocations() - 1; i >= 0; i--) {
v = afv.valueAtLocation (i);
if (v >= 1)
afv.setValueAtLocation (i, Math.log(v)+1);
}
return carrier;
}
}