java进行矩阵运算

搜索了下java的矩阵运算工具，网上有很多。这篇博文总结的特别好，https://www.cnblogs.com/jpfss/p/11533902.html，大家可以拿去。

我试用了下ujmp包，觉得还是挺好用的，网上的资料不多。特分享在这里。

依赖pom

<dependency>
            <groupId>org.ujmp</groupId>
            <artifactId>ujmp-core</artifactId>
            <version>0.3.0</version>
        </dependency>

 

试用代码

public class MatrixTest {
    public static void main(String[] args) {
        DenseDoubleMatrix2D zeros = DenseMatrix.Factory.zeros(2, 2);
        DenseDoubleMatrix2D ones = DenseMatrix.Factory.zeros(2, 2);
        zeros.setAsDouble(2, 0, 0);
        zeros.setAsDouble(5, 0, 1);
        zeros.setAsDouble(-3, 1, 0);
        zeros.setAsDouble(-7, 1, 1);

        ones.setAsDouble(2, 0, 0);
        ones.setAsDouble(1, 0, 1);
        ones.setAsDouble(3, 1, 0);
        ones.setAsDouble(4, 1, 1);

        System.out.println("当前矩阵：");
        System.out.println(zeros);
        Matrix transpose = zeros.transpose();
        System.out.println("矩阵的转置：");
        System.out.println(transpose);
        Matrix inv = zeros.inv();
        System.out.println("矩阵的逆：");
        System.out.println(inv);
        System.out.println("矩阵的维数：");
        System.out.println(zeros.getDimensionCount());
        System.out.println("矩阵的秩：");
        System.out.println(zeros.rank());

        Matrix plus = zeros.plus(ones);
        System.out.println("矩阵求和：");
        System.out.println(plus);

        Matrix minus = zeros.minus(ones);
        System.out.println("矩阵求差：");
        System.out.println(minus);

        Matrix mtimes = zeros.mtimes(ones);
        System.out.println("矩阵求积：");
        System.out.println(mtimes);

        //矩阵和数值的四则运算
        Matrix plus1 = zeros.plus(2);
        Matrix minus1 = zeros.minus(2);
        Matrix times = zeros.times(2);
        Matrix divide = zeros.divide(2);
        System.out.println("矩阵数值运算：");
        System.out.println(times);

        double det = zeros.det();
        System.out.println("矩阵行列式：");
        System.out.println(det);

        Matrix[] eig = zeros.eig();
        System.out.println("矩阵特征值：");
        for (Matrix matrix : eig) {
            System.out.println(matrix);
        }

        double valueSum = zeros.getValueSum();
        long rowCount = zeros.getRowCount();
        long valueCount = zeros.getValueCount();
        long valueCount1 = zeros.getValueCount();
        System.out.println("所有元素求和：" + valueSum);
        ValueType valueType = zeros.getValueType();
        System.out.println("所有元素类型：" + valueType);


        Matrix randMatrix = Matrix.Factory.rand(4, 4);
        System.out.println("随机矩阵：");
        System.out.println(randMatrix);
        Matrix matrix = randMatrix.subMatrix(Ret.LINK, 1, 1, 2, 2);
        System.out.println("随机子矩阵：");
        System.out.println(matrix);

        Matrix matrix1 = randMatrix.selectRows(Ret.LINK, 1, 2);
        System.out.println("选取行：");
        System.out.println(matrix1);
        Matrix matrix2 = randMatrix.selectColumns(Ret.LINK, 2, 3);
        System.out.println("选取列：");
        System.out.println(matrix2);

        Matrix eq = zeros.eq(Ret.LINK, ones);
        //相等的话在相应的位置设置为true否则为false
        System.out.println("矩阵是否相等：");
        System.out.println(eq);
        System.out.println(ones);
        //对行排序?
        //有三种返回型，Ret.LINK Ret.ORIG, Ret.NEW 计算时间new > orig > link
        Matrix sortrows = ones.sortrows(Ret.LINK, 0, true);
        System.out.println("对行排序:");
        System.out.println(sortrows);

    }

    /**
     * 常用构造方法
     */
    public static void test() {
        long m = 5;
        long n = 5;
        /**
         * 制造一个空矩阵
         */
        DefaultDenseMatrixFactory factory = Matrix.Factory;
        Matrix emptyMatrix = factory.emptyMatrix();
        /**
         * 制造一个m*n随机矩阵
         */
        Matrix randMatrix = factory.rand(m, n);
        /**
         * 制造一个m*n零矩阵
         */
        Matrix zeroMatrix = factory.zeros(m, n);
        /**
         * 制造一个m*n对角线为1其余元素为0的矩阵
         */
        Matrix eyeMatrix = factory.eye(m, n);
        /**
         * 制造一个m*n全部元素为1的矩阵
         */
        Matrix oneMatrix = factory.ones(m, n);


    }
}