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This is the original Lingpipe:
http://alias-i.com/lingpipe/web/download.html
There were not made any changes to the source code.
/*
* LingPipe v. 4.1.0
* Copyright (C) 2003-2011 Alias-i
*
* This program is licensed under the Alias-i Royalty Free License
* Version 1 WITHOUT ANY WARRANTY, without even the implied warranty of
* MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the Alias-i
* Royalty Free License Version 1 for more details.
*
* You should have received a copy of the Alias-i Royalty Free License
* Version 1 along with this program; if not, visit
* http://alias-i.com/lingpipe/licenses/lingpipe-license-1.txt or contact
* Alias-i, Inc. at 181 North 11th Street, Suite 401, Brooklyn, NY 11211,
* +1 (718) 290-9170.
*/
package com.aliasi.stats;
import java.util.Arrays;
import java.util.HashMap;
import java.util.Map;
/**
* A MultivariateConstant provides a multinomial
* distribution with constant probabilities and labels. A range
* of constructors allow a constant multivariate to be constructed
* from integer counts, floating point probability ratios, with
* an optional set of labels.
*
* @author Bob Carpenter
* @version 3.8
* @since LingPipe2.0
*/
public class MultivariateConstant extends MultivariateDistribution {
final String[] mLabels;
final double[] mEstimates;
final Map mLabelToIndex;
/**
* Construct a uniform constant multinomial distribution with the
* specified number of outcomes. The outcomes will be labeled
* as defined in {@link MultivariateDistribution}.
*
* @param numOutcomes Number of outcomes.
* @throws IllegalArgumentException If the number of outcomes is
* less than one.
*/
public MultivariateConstant(int numOutcomes) {
this(allOnes(numOutcomes));
}
/**
* Construct a constant multinomial distribution with
* probabilities proportional to the specified counts. The
* outcomes will be labeled as defined in {@link
* MultivariateDistribution}.
*
* @param counts Counts for each outcome.
* @throws IllegalArgumentException If any of the counts are less
* than zero.
*/
public MultivariateConstant(long[] counts) {
this(toDouble(counts));
}
/**
* Construct a constant multinomial distribution with
* probabilities proportional to the specified ratios. The
* outcomes will be labeled as defined in {@link
* MultivariateDistribution}.
*
* @param probabilityRatios Probability ratios of outcomes.
* @throws IllegalArgumentException If any of the ratios are less
* than zero.
*/
public MultivariateConstant(double[] probabilityRatios) {
this(probabilityRatios,null,null);
}
/**
* Construct a uniform constant multinomial distribution with the
* specified labels. Indices are asisgned to labels in order, and
* the labels must not be duplicated.
*
* @param labels Labels of outcomes in order of their indices.
* @throws IllegalArgumentException If any of the labels are
* duplicated.
*/
public MultivariateConstant(String[] labels) {
this(allOnes(labels.length),labels);
}
/**
* Construct a constant multinomial distribution with the
* specified labels and probabilities proportional to the
* specified counts. All counts must be non-negative and there
* must be the same number of labels as counts with no ducplicate
* labels.
*
* @param counts Counts for outcomes.
* @param labels Labels of outcomes.
* @throws IllegalArgumentException If any count is negative,
* if there are not the same number of counts and labels, or
* if there are duplicate labels.
*/
public MultivariateConstant(long[] counts,
String[] labels) {
this(toDouble(counts),labels);
}
/**
* Construct a constant multinomial distribution with the
* specified labels and probabilities proportional to the
* specified counts. All counts must be non-negative and there.
*
* @param probabilityRatios Counts for outcomes.
* @param labels Labels of outcomes.
* @throws IllegalArgumentException If any count is negative or if
* there are not the same number of counts and labels.
*/
public MultivariateConstant(double[] probabilityRatios,
String[] labels) {
this(probabilityRatios, labels.clone(), new HashMap());
validateEqualLengths(probabilityRatios,labels);
for (int i = 0; i < labels.length; ++i) {
if (mLabelToIndex.put(labels[i],Long.valueOf(i)) != null) {
String msg = "Duplicate labels=" + labels[i];
throw new IllegalArgumentException(msg);
}
}
}
private MultivariateConstant(double[] probabilityRatios,
String[] labels,
Map labelToIndex) {
if (probabilityRatios.length < 1) {
String msg = "Require at least one count or probability ratio.";
throw new IllegalArgumentException(msg);
}
mLabels = labels;
mLabelToIndex = labelToIndex;
validateRatios(probabilityRatios);
double z = 0;
for (int i = 0; i < probabilityRatios.length; ++i)
z += probabilityRatios[i];
mEstimates = new double[probabilityRatios.length];
for (int i = 0; i < probabilityRatios.length; ++i)
mEstimates[i] = probabilityRatios[i] / z;
}
@Override
public int numDimensions() {
return mEstimates.length;
}
@Override
public long outcome(String outcomeLabel) {
if (mLabels == null) return super.outcome(outcomeLabel);
Long result = mLabelToIndex.get(outcomeLabel);
if (result == null) {
String msg="Unknown outcome label=" + outcomeLabel;
throw new IllegalArgumentException(msg);
}
return result.longValue();
}
@Override
public String label(long outcome) {
if (mLabels == null) return super.label(outcome);
checkOutcome(outcome);
return mLabels[(int)outcome];
}
@Override
public double probability(long outcome) {
return outcomeOutOfRange(outcome)
? 0.0
: mEstimates[(int)outcome];
}
private void validateEqualLengths(double[] probabilityRatios, String[] labels) {
if (probabilityRatios.length != labels.length) {
String msg = "Require same number of ratios and labels."
+ " Found #ratios=" + probabilityRatios.length
+ " # labels=" + labels.length;
throw new IllegalArgumentException(msg);
}
}
private void validateRatios(double[] probabilityRatios) {
for (int i = 0; i < probabilityRatios.length; ++i) {
if (probabilityRatios[i] < 0) {
String msg = "All probability ratios must be >= 0."
+ " Found probabilityRatios[" + i + "]="
+ probabilityRatios[i];
throw new IllegalArgumentException(msg);
}
}
}
static double[] toDouble(long[] counts) {
double[] result = new double[counts.length];
for (int i = 0; i < counts.length; ++i) {
if (counts[i] < 0l) {
String msg = "All counts must be positive."
+ " Found counts[" + i + "]=" + counts[i];
throw new IllegalArgumentException(msg);
}
result[i] = counts[i];
}
return result;
}
static double[] allOnes(int length) {
if (length < 0) {
String msg="Number of outcomes must be positive."
+ "Found number of outcomes=" + length;
throw new IllegalArgumentException(msg);
}
double[] result = new double[length];
Arrays.fill(result,1.0);
return result;
}
static String[] numberedLabels(int length) {
String[] labels = new String[length];
for (int i = 0; i < length; ++i)
labels[i] = Integer.toString(i);
return labels;
}
}
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