/*
* Licensed to the Apache Software Foundation (ASF) under one
* or more contributor license agreements. See the NOTICE file
* distributed with this work for additional information
* regarding copyright ownership. The ASF licenses this file
* to you 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.
*/
package org.apache.tinkerpop.gremlin.algorithm.generator;
import java.util.Random;
/**
* Generates values according to a normal distribution with the configured standard deviation.
*
* @author Matthias Broecheler (me@matthiasb.com)
*/
public class NormalDistribution implements Distribution {
private final double stdDeviation;
private final double mean;
/**
* Constructs a NormalDistribution with the given standard deviation.
* <p/>
* Setting the standard deviation to 0 makes this a constant distribution.
*
* @param stdDeviation Simple deviation of the distribution. Must be non-negative.
*/
public NormalDistribution(final double stdDeviation) {
this(stdDeviation, 0.0);
}
private NormalDistribution(final double stdDeviation, final double mean) {
if (stdDeviation < 0)
throw new IllegalArgumentException("Standard deviation must be non-negative: " + stdDeviation);
if (mean < 0) throw new IllegalArgumentException("Mean must be positive: " + mean);
this.stdDeviation = stdDeviation;
this.mean = mean;
}
@Override
public Distribution initialize(final int invocations, final int expectedTotal) {
double mean = (expectedTotal * 1.0) / invocations; //TODO: account for truncated gaussian distribution
return new NormalDistribution(stdDeviation, mean);
}
@Override
public int nextValue(final Random random) {
if (mean == 0.0) throw new IllegalStateException("Distribution has not been initialized");
return (int) Math.round(random.nextGaussian() * stdDeviation + mean);
}
@Override
public int nextConditionalValue(final Random random, final int otherValue) {
return nextValue(random);
}
@Override
public String toString() {
return "NormalDistribution{" +
"stdDeviation=" + stdDeviation +
", mean=" + mean +
'}';
}
}