java稀疏矩阵相乘

稀疏矩阵相乘是一个比较复杂的操作，需要将两个稀疏矩阵转换成三元组的形式，然后再进行相乘操作。下面是Java实现稀疏矩阵相乘的步骤：

1. 定义一个SparseMatrix类，包含三个属性：行数、列数和一个三元组数组。
2. 定义一个SparseMatrix类的构造函数，用于初始化三元组数组。
3. 定义一个transpose()方法，用于将稀疏矩阵转置。
4. 定义一个multiply()方法，用于实现稀疏矩阵相乘。

下面是Java代码实现稀疏矩阵相乘的示例：

class SparseMatrix {
    int rows;
    int cols;
    int[][] data;

    public SparseMatrix(int[][] matrix) {
        rows = matrix.length;
        cols = matrix[0].length;
        int count = 0;
        for (int i = 0; i < rows; i++) {
            for (int j = 0; j < cols; j++) {
                if (matrix[i][j] != 0) {
                    count++;
                }
            }
        }
        data = new int[count][3];
        int index = 0;
        for (int i = 0; i < rows; i++) {
            for (int j = 0; j < cols; j++) {
                if (matrix[i][j] != 0) {
                    data[index][0] = i;
                    data[index][1] = j;
                    data[index][2] = matrix[i][j];
                    index++;
                }
            }
        }
    }

    public SparseMatrix transpose() {
        SparseMatrix transposed = new SparseMatrix(new int[cols][rows]);
        transposed.rows = cols;
        transposed.cols = rows;
        transposed.data = new int[data.length][3];
        for (int i = 0; i < data.length; i++) {
            transposed.data[i][0] = data[i][1];
            transposed.data[i][1] = data[i][0];
            transposed.data[i][2] = data[i][2];
        }
        Arrays.sort(transposed.data, new Comparator<int[]>() {
            @Override
            public int compare(int[] o1, int[] o2) {
                if (o1[0] == o2[0]) {
                    return o1[1] - o2[1];
                } else {
                    return o1[0] - o2[0];
                }
            }
        });
        return transposed;
    }

    public SparseMatrix multiply(SparseMatrix other) {
        if (cols != other.rows) {
            throw new IllegalArgumentException("Invalid matrix dimensions");
        }
        SparseMatrix transposed = other.transpose();
        SparseMatrix result = new SparseMatrix(new int[rows][other.cols]);
        for (int i = 0; i < data.length; i++) {
            int row = data[i][0];
            int col = data[i][1];
            int value = data[i][2];
            for (int j = 0; j < transposed.data.length; j++) {
                int row2 = transposed.data[j][0];
                int col2 = transposed.data[j][1];
                int value2 = transposed.data[j][2];
                if (col == row2) {
                    result.data[row][col2] += value * value2;
                }
            }
        }
        return result;
    }
}