Jakarta-Common-Math使用笔记

apache的math组件，尽管不常用，我今天也整理出来。

下载地址： http://commons.apache.org/math/

示例代码：

package  demo;

import  org.apache.commons.math.stat.descriptive.moment.GeometricMean;
import  org.apache.commons.math.stat.descriptive.moment.Kurtosis;
import  org.apache.commons.math.stat.descriptive.moment.Mean;
import  org.apache.commons.math.stat.descriptive.moment.Skewness;
import  org.apache.commons.math.stat.descriptive.moment.StandardDeviation;
import  org.apache.commons.math.stat.descriptive.moment.Variance;
import  org.apache.commons.math.stat.descriptive.rank.Max;
import  org.apache.commons.math.stat.descriptive.rank.Min;
import  org.apache.commons.math.stat.descriptive.rank.Percentile;
import  org.apache.commons.math.stat.descriptive.summary.Product;
import  org.apache.commons.math.stat.descriptive.summary.Sum;
import  org.apache.commons.math.stat.descriptive.summary.SumOfSquares;

public   class  TestMathUserage  ... {
    
    public static void main(String[] args) ...{
        
        double[] values = new double[] ...{ 0.33, 1.33, 0.27333, 0.3, 0.501,
                0.444, 0.44, 0.34496, 0.33, 0.3, 0.292, 0.667 };
        /**//*
         * System.out.println( "min: " + StatUtils.min( values ) );
         * System.out.println( "max: " + StatUtils.max( values ) );
         * System.out.println( "mean: " + StatUtils.mean( values ) ); // Returns
         * the arithmetic mean of the entries in the input array, or Double.NaN
         * if the array is empty System.out.println( "product: " +
         * StatUtils.product( values ) ); //Returns the product of the entries
         * in the input array, or Double.NaN if the array is empty.
         * System.out.println( "sum: " + StatUtils.sum( values ) ); //Returns
         * the sum of the values in the input array, or Double.NaN if the array
         * is empty. System.out.println( "variance: " + StatUtils.variance(
         * values ) ); // Returns the variance of the entries in the input
         * array, or Double.NaN if the array is empty.
         */

        Min min = new Min();
        Max max = new Max();
        Mean mean = new Mean(); // 算术平均值
        Product product = new Product();
        Sum sum = new Sum();
        Variance variance = new Variance();
        System.out.println("min: " + min.evaluate(values));
        System.out.println("max: " + max.evaluate(values));
        System.out.println("mean: " + mean.evaluate(values));
        System.out.println("product: " + product.evaluate(values));
        System.out.println("sum: " + sum.evaluate(values));
        System.out.println("variance: " + variance.evaluate(values));

        Percentile percentile = new Percentile(); // 百分位数
        GeometricMean geoMean = new GeometricMean(); // 几何平均数,n个正数的连乘积的n次算术根叫做这n个数的几何平均数
        Skewness skewness = new Skewness(); // Skewness();
        Kurtosis kurtosis = new Kurtosis(); // Kurtosis,峰度
        SumOfSquares sumOfSquares = new SumOfSquares(); // 平方和
        StandardDeviation StandardDeviation = new StandardDeviation();
        System.out.println("80 percentile value: "
                + percentile.evaluate(values, 80.0));
        System.out.println("geometric mean: " + geoMean.evaluate(values));
        System.out.println("skewness: " + skewness.evaluate(values));
        System.out.println("kurtosis: " + kurtosis.evaluate(values));
        System.out.println("sumOfSquares: " + sumOfSquares.evaluate(values));
        // 就是标准方差
        System.out.println("StandardDeviation: "
                + StandardDeviation.evaluate(values));
    }
}

几个主要功能类：

A.RandomData类：

package  demo;

import  org.apache.commons.math.random.RandomData;
import  org.apache.commons.math.random.RandomDataImpl;

public   class  MathDemo  ... {

    public static void main(String[] args) ...{
        
        RandomData randomData = new RandomDataImpl(); 
        for (int i = 0; i < 10; i++) ...{
            long value = randomData.nextLong(1, 100);
            System.out.println(value);
        }

        System.out.println("＝＝＝＝＝＝＝＝＝＝＝＝＝＝＝");
        
        for (int i = 0; i < 10; i++) ...{
            randomData = new RandomDataImpl(); 
            long value = randomData.nextLong(1, 100);
            System.out.println(value);
        }
    }
}

B.RealMatrix类，求解方程

2x + 3y - 2z = 1
-x + 7y + 6x = -2
4x - 3y - 5z = 1

package  demo;

import  java.io.IOException;

import  org.apache.commons.math.linear.RealMatrix;
import  org.apache.commons.math.linear.RealMatrixImpl;

public   class  MathDemo  ... {

    public static void main(String[] args) throws IOException ...{

        double[][] coefficientsData = ...{...{2, 3, -2}, ...{-1, 7, 6}, ...{4, -3, -5}};
        RealMatrix coefficients = new RealMatrixImpl(coefficientsData);

        double[] constants = ...{1, -2, 1};
        double[] solution = coefficients.solve(constants);
        
        System.out.println(solution[0]);
        System.out.println(solution[1]);
        System.out.println(solution[2]);
    }
}