org.simmetrics.metrics.EuclideanDistance.java Source code

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Here is the source code for org.simmetrics.metrics.EuclideanDistance.java

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/*
 * #%L
 * Simmetrics Core
 * %%
 * Copyright (C) 2014 - 2016 Simmetrics Authors
 * %%
 * 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.
 * #L%
 */

package org.simmetrics.metrics;

import static org.simmetrics.metrics.Math.union;
import static java.lang.Math.sqrt;

import org.simmetrics.MultisetDistance;
import org.simmetrics.MultisetMetric;

import com.google.common.collect.Multiset;

/**
 * Calculates the Euclidean distance and similarity over two multisets.
 * <p>
 * <code>
 * similarity(a,b) = 1 - distance(a,b) / (a + b)
 * <br>
 * distance(a,b) = a - b  
 * </code>
 * <p>
 * This class is immutable and thread-safe.
 * 
 * @see <a href="https://en.wikipedia.org/wiki/Euclidean_distance">Wikipedia - Euclidean Distance</a>
 * @param <T>
 *            type of the token
 * 
 */
public final class EuclideanDistance<T> implements MultisetMetric<T>, MultisetDistance<T> {

    @Override
    public float compare(Multiset<T> a, Multiset<T> b) {

        if (a.isEmpty() && b.isEmpty()) {
            return 1.0f;
        }

        float maxDistance = (float) sqrt((a.size() * a.size()) + (b.size() * b.size()));
        return 1.0f - distance(a, b) / maxDistance;
    }

    @Override
    public float distance(Multiset<T> a, Multiset<T> b) {

        float distance = 0.0f;

        for (T token : union(a, b).elementSet()) {
            float frequencyInA = a.count(token);
            float frequencyInB = b.count(token);

            distance += ((frequencyInA - frequencyInB) * (frequencyInA - frequencyInB));
        }

        return (float) sqrt(distance);
    }

    @Override
    public String toString() {
        return "EuclideanDistance";
    }

}