Java tutorial
/* * Copyright 2015-2016 Red Hat, Inc. and/or its affiliates * and other contributors as indicated by the @author tags. * * 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 org.hawkular.datamining.forecast; import java.util.HashMap; import java.util.Map; import java.util.concurrent.ConcurrentHashMap; import org.apache.commons.math3.distribution.NormalDistribution; /** * @author Pavol Loffay */ public class PredictionIntervalMultipliers { private static final Map<Integer, Double> cashedMultipliers; static { Map<Integer, Double> multipliers = new HashMap<>(); multipliers.put(50, 0.67); multipliers.put(85, 1.44); multipliers.put(95, 1.96); cashedMultipliers = new ConcurrentHashMap<>(multipliers); } private PredictionIntervalMultipliers() { } public static double multiplier(int percentage) { if (percentage < 0 || percentage > 100) { throw new IllegalArgumentException(); } Double multiplier = cashedMultipliers.get(percentage); if (multiplier == null) { NormalDistribution normalDistribution = new NormalDistribution(0, 1); multiplier = normalDistribution.inverseCumulativeProbability(0.5 + (percentage * 0.01) / 2); cashedMultipliers.put(percentage, multiplier); } return multiplier; } }