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/*
* 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.matrix;
/**
* A ProximityMatrix provides a pseudo-metric of proximities
* between points. As a matrix, proximity matrices are symmetric, contain
* only non-negative values and have 0.0 values on the diagonal.
*
* Implementation Note: Proximity matrices are implemented as a
* wrapper around a triangular matrix of primitive double values
* without the diagonal values.
*
* @author Bob Carpenter
* @version 3.0
* @since LingPipe2.0
*/
public class ProximityMatrix extends AbstractMatrix {
private final double[][] mValues;
private final int mSize;
ProximityMatrix(double[][] values, boolean ignoreMe) {
mValues = values;
mSize = values.length;
}
/**
* Construct a square proximity matrix of the specified
* dimensionality, with all values initially zero.
*
* @param numDimensions Number of dimensions.
*/
public ProximityMatrix(int numDimensions) {
this(zeroValues(numDimensions),true);
}
/**
* Returns the number of columns for this matrix. The number
* of rows is the same as the number of columns.
*
* @return The number of columns for this matrix.
*/
@Override
public int numColumns() {
return mSize;
}
/**
* Returns the number of rows for this matrix. The number
* of rows is the same as the number of columns.
*
* @return The number of rows for this matrix.
*/
@Override
public int numRows() {
return mSize;
}
/**
* Sets the value for the specified row and column to the
* specified non-negative value as well as swapping row for column
* for symmetry. Thus setValue(i,j,x) sets the value
* for row i and column j to
* x as well as setting the value for row
* j and column i to x.
*
* @param row Matrix row.
* @param column Matrix column.
* @param value Value to set for row and column and reverse.
* @throws IllegalArgumentException If the row and column are the
* same or if the value is negative or not a number.
* @throws IndexOutOfBoundsException If the row or column are less
* than 0 or greater than the dimensionality of this proximity
* matrix.
*/
@Override
public void setValue(int row, int column, double value) {
if (row == column) {
if (value == 0.0) return;
String msg = "Cannot set non-zero diagonal on a proximity matrix."
+ " Found row=" + row
+ " column=" + column
+ " value=" + value;
throw new IllegalArgumentException(msg);
}
if (value < 0.0 || Double.isNaN(value)) {
String msg = "Proximity matrix values must be >= 0.0"
+ " Found=" + value;
throw new IllegalArgumentException(msg);
}
if (row < column) {
mValues[column-1][row] = value;
} else {
mValues[row-1][column] = value;
}
}
/**
* Returns the value in this proximity matrix for the specified
* row and column.
*
* @param row Specified row.
* @param column Specified column.
* @return Value for the specified row and column.
* @throws IndexOutOfBoundsException If the row or column are
* negative or greater than or equal to the dimensionality of this
* matrix.
*/
@Override
public double value(int row, int column) {
if (row == column) {
if (row > mSize) {
String msg = "Index out of bounds row=column=" + row;
throw new IndexOutOfBoundsException(msg);
}
return 0.0;
}
return (row < column)
? mValues[column-1][row]
: mValues[row-1][column];
}
private static double[][] zeroValues(int numDimensions) {
if (numDimensions < 1) {
String msg = "Require positive number of dimensions."
+ " Found numDimensions=" + numDimensions;
throw new IllegalArgumentException(msg);
}
double[][] values = new double[numDimensions-1][];
for (int i = 0; i < values.length; ++i) {
values[i] = new double[i + 1];
for (int j = 0; j < values[i].length; ++j)
values[i][j] = 0.0;
}
return values;
}
}