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 程式師世界 >> 編程語言 >> JAVA編程 >> 關於JAVA >> Jakarta-Common-Math使用筆記

Jakarta-Common-Math使用筆記

編輯:關於JAVA

apache的math組件,盡管不常用,我今天也整理出來。

下載地址: http://commons.apache.org/math/

示例代碼:

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(); // 算術平均值
     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(); // 百分位數
     GeometricMean geoMean = new GeometricMean(); // 幾何平均數,n個正數的連乘積的n次算術根叫做這n個數的幾何平均數
     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));
     // 就是標准方差
     System.out.println("StandardDeviation: "
         + StandardDeviation.evaluate(values));
   }
}

幾個主要功能類:

A.RandomData類:

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類,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]);
   }
}

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