键盘输入两个稀疏矩阵，求相加，减，乘，及任一矩阵的转置结果，C++

以下是 C++ 代码实现：

#include <iostream>
using namespace std;

const int MAX_SIZE = 100;

// 稀疏矩阵结构体
struct SparseMatrix {
    int m, n, num;  // 矩阵的行数、列数、非零元素个数
    int data[MAX_SIZE][3];  // 矩阵中每个非零元素的行、列、值
};

// 读入稀疏矩阵
void readSparseMatrix(SparseMatrix& matrix) {
    cin >> matrix.m >> matrix.n >> matrix.num;
    for (int i = 0; i < matrix.num; i++) {
        cin >> matrix.data[i][0] >> matrix.data[i][1] >> matrix.data[i][2];
    }
}

// 打印稀疏矩阵
void printSparseMatrix(SparseMatrix matrix) {
    for (int i = 0; i < matrix.num; i++) {
        cout << matrix.data[i][0] << " " << matrix.data[i][1] << " " << matrix.data[i][2] << endl;
    }
}

// 稀疏矩阵相加
SparseMatrix addSparseMatrix(SparseMatrix matrix1, SparseMatrix matrix2) {
    SparseMatrix result;
    result.m = matrix1.m;
    result.n = matrix1.n;
    result.num = 0;
    int i = 0, j = 0;
    while (i < matrix1.num && j < matrix2.num) {
        if (matrix1.data[i][0] < matrix2.data[j][0] || (matrix1.data[i][0] == matrix2.data[j][0] && matrix1.data[i][1] < matrix2.data[j][1])) {
            result.data[result.num][0] = matrix1.data[i][0];
            result.data[result.num][1] = matrix1.data[i][1];
            result.data[result.num][2] = matrix1.data[i][2];
            i++;
        } else if (matrix1.data[i][0] > matrix2.data[j][0] || (matrix1.data[i][0] == matrix2.data[j][0] && matrix1.data[i][1] > matrix2.data[j][1])) {
            result.data[result.num][0] = matrix2.data[j][0];
            result.data[result.num][1] = matrix2.data[j][1];
            result.data[result.num][2] = matrix2.data[j][2];
            j++;
        } else {
            result.data[result.num][0] = matrix1.data[i][0];
            result.data[result.num][1] = matrix1.data[i][1];
            result.data[result.num][2] = matrix1.data[i][2] + matrix2.data[j][2];
            i++;
            j++;
        }
        result.num++;
    }
    while (i < matrix1.num) {
        result.data[result.num][0] = matrix1.data[i][0];
        result.data[result.num][1] = matrix1.data[i][1];
        result.data[result.num][2] = matrix1.data[i][2];
        i++;
        result.num++;
    }
    while (j < matrix2.num) {
        result.data[result.num][0] = matrix2.data[j][0];
        result.data[result.num][1] = matrix2.data[j][1];
        result.data[result.num][2] = matrix2.data[j][2];
        j++;
        result.num++;
    }
    return result;
}

// 稀疏矩阵相减
SparseMatrix subSparseMatrix(SparseMatrix matrix1, SparseMatrix matrix2) {
    SparseMatrix result;
    result.m = matrix1.m;
    result.n = matrix1.n;
    result.num = 0;
    int i = 0, j = 0;
    while (i < matrix1.num && j < matrix2.num) {
        if (matrix1.data[i][0] < matrix2.data[j][0] || (matrix1.data[i][0] == matrix2.data[j][0] && matrix1.data[i][1] < matrix2.data[j][1])) {
            result.data[result.num][0] = matrix1.data[i][0];
            result.data[result.num][1] = matrix1.data[i][1];
            result.data[result.num][2] = matrix1.data[i][2];
            i++;
        } else if (matrix1.data[i][0] > matrix2.data[j][0] || (matrix1.data[i][0] == matrix2.data[j][0] && matrix1.data[i][1] > matrix2.data[j][1])) {
            result.data[result.num][0] = matrix2.data[j][0];
            result.data[result.num][1] = matrix2.data[j][1];
            result.data[result.num][2] = -1 * matrix2.data[j][2];
            j++;
        } else {
            result.data[result.num][0] = matrix1.data[i][0];
            result.data[result.num][1] = matrix1.data[i][1];
            result.data[result.num][2] = matrix1.data[i][2] - matrix2.data[j][2];
            i++;
            j++;
        }
        result.num++;
    }
    while (i < matrix1.num) {
        result.data[result.num][0] = matrix1.data[i][0];
        result.data[result.num][1] = matrix1.data[i][1];
        result.data[result.num][2] = matrix1.data[i][2];
        i++;
        result.num++;
    }
    while (j < matrix2.num) {
        result.data[result.num][0] = matrix2.data[j][0];
        result.data[result.num][1] = matrix2.data[j][1];
        result.data[result.num][2] = -1 * matrix2.data[j][2];
        j++;
        result.num++;
    }
    return result;
}

// 稀疏矩阵相乘
SparseMatrix mulSparseMatrix(SparseMatrix matrix1, SparseMatrix matrix2) {
    SparseMatrix result;
    result.m = matrix1.m;
    result.n = matrix2.n;
    result.num = 0;
    int row[MAX_SIZE][MAX_SIZE] = {0};  // 存储 matrix1 中每一行非零元素的列号
    int col[MAX_SIZE][MAX_SIZE] = {0};  // 存储 matrix2 中每一列非零元素的行号
    for (int i = 0; i < matrix1.num; i++) {
        row[matrix1.data[i][0]][matrix1.data[i][1]] = matrix1.data[i][2];
    }
    for (int i = 0; i < matrix2.num; i++) {
        col[matrix2.data[i][1]][matrix2.data[i][0]] = matrix2.data[i][2];
    }
    for (int i = 0; i < matrix1.m; i++) {
        for (int j = 0; j < matrix2.n; j++) {
            int sum = 0;
            for (int k = 0; k < matrix1.n; k++) {
                sum += row[i][k] * col[j][k];
            }
            if (sum != 0) {
                result.data[result.num][0] = i;
                result.data[result.num][1] = j;
                result.data[result.num][2] = sum;
                result.num++;
            }
        }
    }
    return result;
}

// 稀疏矩阵转置
SparseMatrix transposeSparseMatrix(SparseMatrix matrix) {
    SparseMatrix result;
    result.m = matrix.n;
    result.n = matrix.m;
    result.num = matrix.num;
    int count[MAX_SIZE] = {0};  // 存储每一列的非零元素个数
    int pos[MAX_SIZE + 1] = {0};  // 存储每一列第一个非零元素的位置
    for (int i = 0; i < matrix.num; i++) {
        count[matrix.data[i][1]]++;
    }
    pos[0] = 0;
    for (int i = 1; i <= matrix.n; i++) {
        pos[i] = pos[i - 1] + count[i - 1];
    }
    for (int i = 0; i < matrix.num; i++) {
        int col = matrix.data[i][1];
        result.data[pos[col]][0] = matrix.data[i][1];
        result.data[pos[col]][1] = matrix.data[i][0];
        result.data[pos[col]][2] = matrix.data[i][2];
        pos[col]++;
    }
    return result;
}

int main() {
    SparseMatrix matrix1, matrix2;
    readSparseMatrix(matrix1);
    readSparseMatrix(matrix2);

    SparseMatrix result = addSparseMatrix(matrix1, matrix2);
    cout << "Add:" << endl;
    printSparseMatrix(result);

    result = subSparseMatrix(matrix1, matrix2);
    cout << "Subtract:" << endl;
    printSparseMatrix(result);

    result = mulSparseMatrix(matrix1, matrix2);
    cout << "Multiply:" << endl;
    printSparseMatrix(result);

    result = transposeSparseMatrix(matrix1);
    cout << "Transpose:" << endl;
    printSparseMatrix(result);

    return 0;
}

输入格式为：

m1 n1 num1
r1 c1 v1
r2 c2 v2
...
m2 n2 num2
r1 c1 v1
r2 c2 v2
...

其中 `m1` 为矩阵 1 的行数，`n1` 为矩阵 1 的列数，`num1` 为矩阵 1 中非零元素的个数，后面 `num1` 行分别表示矩阵 1 中每个非零元素的行、列、值。`m2`、`n2`、`num2`、矩阵 2 类似。