| // 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.spaceroots.mantissa.random; |
| |
| /** This class compute basic statistics on a scalar sample. |
| * @version $Id$ |
| * @author L. Maisonobe |
| */ |
| public class ScalarSampleStatistics { |
| |
| /** Number of sample points. */ |
| private int n; |
| |
| /** Minimal value in the sample. */ |
| private double min; |
| |
| /** Maximal value in the sample. */ |
| private double max; |
| |
| /** Sum of the sample values. */ |
| private double sum; |
| |
| /** Sum of the squares of the sample values. */ |
| private double sum2; |
| |
| /** Simple constructor. |
| * Build a new empty instance |
| */ |
| public ScalarSampleStatistics() { |
| n = 0; |
| min = Double.NaN; |
| max = min; |
| sum = 0; |
| sum2 = 0; |
| } |
| |
| /** Add one point to the instance. |
| * @param x value of the sample point |
| */ |
| public void add(double x) { |
| |
| if (n++ == 0) { |
| min = x; |
| max = x; |
| sum = x; |
| sum2 = x * x; |
| } else { |
| |
| if (x < min) { |
| min = x; |
| } else if (x > max) { |
| max = x; |
| } |
| |
| sum += x; |
| sum2 += x * x; |
| |
| } |
| |
| } |
| |
| /** Add all points of an array to the instance. |
| * @param points array of points |
| */ |
| public void add(double[] points) { |
| for (int i = 0; i < points.length; ++i) { |
| add(points[i]); |
| } |
| } |
| |
| /** Add all the points of another sample to the instance. |
| * @param s sample to add |
| */ |
| public void add(ScalarSampleStatistics s) { |
| |
| if (s.n == 0) { |
| // nothing to add |
| return; |
| } |
| |
| if (n == 0) { |
| n = s.n; |
| min = s.min; |
| max = s.max; |
| sum = s.sum; |
| sum2 = s.sum2; |
| } else { |
| |
| n += s.n; |
| |
| if (s.min < min) { |
| min = s.min; |
| } else if (s.max > max) { |
| max = s.max; |
| } |
| |
| sum += s.sum; |
| sum2 += s.sum2; |
| |
| } |
| |
| } |
| |
| /** Get the number of points in the sample. |
| * @return number of points in the sample |
| */ |
| public int size() { |
| return n; |
| } |
| |
| /** Get the minimal value in the sample. |
| * @return minimal value in the sample |
| */ |
| public double getMin() { |
| return min; |
| } |
| |
| /** Get the maximal value in the sample. |
| * @return maximal value in the sample |
| */ |
| public double getMax() { |
| return max; |
| } |
| |
| /** Get the mean value of the sample. |
| * @return mean value of the sample |
| */ |
| public double getMean() { |
| return (n == 0) ? 0 : (sum / n); |
| } |
| |
| /** Get the standard deviation of the underlying probability law. |
| * This method estimate the standard deviation considering that the |
| * data available are only a <em>sample</em> of all possible |
| * values. This value is often called the sample standard deviation |
| * (as opposed to the population standard deviation). |
| * @return standard deviation of the underlying probability law |
| */ |
| public double getStandardDeviation() { |
| if (n < 2) { |
| return 0; |
| } |
| return Math.sqrt((n * sum2 - sum * sum) / (n * (n - 1))); |
| } |
| |
| } |