Java tutorial
/* * Copyright (C) 2011 Thomas Akehurst * * 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. */ package com.github.tomakehurst.wiremock.http; import com.fasterxml.jackson.annotation.JsonCreator; import com.fasterxml.jackson.annotation.JsonProperty; import java.util.concurrent.ThreadLocalRandom; /** * Returns log normally distributed values. Takes two parameters, the median (50th percentile) of the lognormal * and the standard deviation of the underlying normal distribution. * * The larger the standard deviation the longer the tails. * * @see <a href="https://www.wolframalpha.com/input/?i=lognormaldistribution%28log%2890%29%2C+0.1%29">lognormal example</a> */ public final class LogNormal implements DelayDistribution { @JsonProperty("median") private final double median; @JsonProperty("sigma") private final double sigma; /** * @param median 50th percentile of the distribution in millis * @param sigma standard deviation of the distribution, a larger value produces a longer tail */ @JsonCreator public LogNormal(@JsonProperty("median") double median, @JsonProperty("sigma") double sigma) { this.median = median; this.sigma = sigma; } @Override public long sampleMillis() { return Math.round(Math.exp(ThreadLocalRandom.current().nextGaussian() * sigma) * median); } }