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/*******************************************************************************
* Copyright (c) 2010-2020 Haifeng Li. All rights reserved.
*
* Smile is free software: you can redistribute it and/or modify
* it under the terms of the GNU Lesser General Public License as
* published by the Free Software Foundation, either version 3 of
* the License, or (at your option) any later version.
*
* Smile is distributed in the hope that it will be useful,
* but WITHOUT ANY WARRANTY; without even the implied warranty of
* MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
* GNU Lesser General Public License for more details.
*
* You should have received a copy of the GNU Lesser General Public License
* along with Smile. If not, see .
******************************************************************************/
package smile.math.distance;
import java.util.Arrays;
/**
* Manhattan distance, also known as L1 distance or L1
* norm, is the sum of the (absolute) differences of their coordinates. Use
* getInstance() to get the standard unweighted Manhattan distance. Or create
* an instance with a specified weight vector. For float or double arrays,
* missing values (i.e. NaN) are also handled.
*
* @see SparseManhattanDistance
*
* @author Haifeng Li
*/
public class ManhattanDistance implements Metric {
private static final long serialVersionUID = 1L;
/**
* The weights used in weighted distance.
*/
private double[] weight = null;
/**
* Constructor.
*/
public ManhattanDistance() {
}
/**
* Constructor.
*
* @param weight the weight vector.
*/
public ManhattanDistance(double[] weight) {
for (int i = 0; i < weight.length; i++) {
if (weight[i] < 0) {
throw new IllegalArgumentException(String.format("Weight has to be nonnegative: %f", weight[i]));
}
}
this.weight = weight;
}
@Override
public String toString() {
if (weight != null) {
return String.format("Weighted Manhattan Distance(%s)", Arrays.toString(weight));
} else {
return "Manhattan Distance";
}
}
/**
* Manhattan distance between two arrays of type integer.
*/
public double d(int[] x, int[] y) {
if (x.length != y.length)
throw new IllegalArgumentException(String.format("Arrays have different length: x[%d], y[%d]", x.length, y.length));
double dist = 0.0;
if (weight == null) {
for (int i = 0; i < x.length; i++) {
dist += Math.abs(x[i] - y[i]);
}
} else {
if (x.length != weight.length)
throw new IllegalArgumentException(String.format("Input vectors and weight vector have different length: %d, %d", x.length, weight.length));
for (int i = 0; i < x.length; i++) {
dist += weight[i] * Math.abs(x[i] - y[i]);
}
}
return dist;
}
/**
* Manhattan distance between two arrays of type float.
* NaN will be treated as missing values and will be excluded from the
* calculation. Let m be the number non-missing values, and n be the
* number of all values. The returned distance is n * d / m,
* where d is the distance between non-missing values.
*/
public double d(float[] x, float[] y) {
if (x.length != y.length)
throw new IllegalArgumentException(String.format("Arrays have different length: x[%d], y[%d]", x.length, y.length));
int n = x.length;
int m = 0;
double dist = 0.0;
if (weight == null) {
for (int i = 0; i < n; i++) {
if (!Float.isNaN(x[i]) && !Float.isNaN(y[i])) {
m++;
dist += Math.abs(x[i] - y[i]);
}
}
} else {
if (x.length != weight.length)
throw new IllegalArgumentException(String.format("Input vectors and weight vector have different length: %d, %d", x.length, weight.length));
for (int i = 0; i < n; i++) {
if (!Float.isNaN(x[i]) && !Float.isNaN(y[i])) {
m++;
dist += weight[i] * Math.abs(x[i] - y[i]);
}
}
}
dist = n * dist / m;
return dist;
}
/**
* Manhattan distance between two arrays of type double.
* NaN will be treated as missing values and will be excluded from the
* calculation. Let m be the number non-missing values, and n be the
* number of all values. The returned distance is n * d / m,
* where d is the distance between non-missing values.
*/
@Override
public double d(double[] x, double[] y) {
if (x.length != y.length)
throw new IllegalArgumentException(String.format("Arrays have different length: x[%d], y[%d]", x.length, y.length));
int n = x.length;
int m = 0;
double dist = 0.0;
if (weight == null) {
for (int i = 0; i < n; i++) {
if (!Double.isNaN(x[i]) && !Double.isNaN(y[i])) {
m++;
dist += Math.abs(x[i] - y[i]);
}
}
} else {
if (x.length != weight.length)
throw new IllegalArgumentException(String.format("Input vectors and weight vector have different length: %d, %d", x.length, weight.length));
for (int i = 0; i < n; i++) {
if (!Double.isNaN(x[i]) && !Double.isNaN(y[i])) {
m++;
dist += weight[i] * Math.abs(x[i] - y[i]);
}
}
}
dist = n * dist / m;
return dist;
}
}
