Sparsearray稀疏数组原理及实例详解

public class SparseArray {
  public static void main(String[] args) {
    // 创建原始二维数组（0 表示无子，1 表示黑子 2 表示 白子）
    int chessArr1[][] = new int[11][11];
    chessArr1[1][2] = 1;
    chessArr1[3][3] = 2;
    chessArr1[5][1] = 2;
    // 使用 for 循环遍原始二维数组
    System.out.println("-------------------------------------------原始二维数组---------------------------------");
    for (int row[] : chessArr1) {
      for (int data : row) {
        System.out.printf("%d\t", data);
      }
      System.out.println();
    }
    // 将二维数组转换为洗漱数组
    // 获取原始二维数组非零数目
    int sum = 0;
    for (int i = 0; i < chessArr1.length; i++) {
      for (int j = 0; j < chessArr1.length; j++) {
        if (chessArr1[i][j] != 0) {
          sum++;
        }
      }
    }
    System.out.println("sum = " + sum);

    // 创建稀疏数组
    int sparseArr[][] = new int[sum + 1][3];
    // 为稀疏数组赋值
    sparseArr[0][0] = chessArr1.length;
    sparseArr[0][1] = chessArr1.length;
    sparseArr[0][2] = sum;
    // 便利原始二维数组，进行存放
    int n = 0;
    for (int i = 0; i < chessArr1.length; i++) {
      for (int j = 0; j < chessArr1.length; j++) {
        if (chessArr1[i][j] != 0) {
          n++;
          sparseArr[n][0] = i;
          sparseArr[n][1] = j;
          sparseArr[n][2] = chessArr1[i][j];
        }
      }
    }
    // 遍历稀疏数组
    System.out.println("-------------------------------------------稀疏数组---------------------------------");
    for (int i = 0; i < sparseArr.length; i++) {
      System.out.printf("%d\t%d\t%d\t\n", sparseArr[i][0], sparseArr[i][1], sparseArr[i][2]);
    }
    // 将稀疏数组还原为原始二维数组
    int chessArr2[][] = new int[sparseArr[0][0]][sparseArr[0][1]];
    for (int i = 1; i < sparseArr.length; i++) {
      chessArr2[chessArr2[i][0]][chessArr2[i][1]] = chessArr2[i][2];
    }
    System.out.println("-------------------------------------------恢复后的二维数组---------------------------------");
    for (int row[] : chessArr1) {
      for (int data : row) {
        System.out.printf("%d\t", data);
      }
      System.out.println();
    }

  }
}

-------------------------------------------原始二维数组-------------------------------
0  0  0  0  0  0  0  0  0  0  0 
0  0  1  0  0  0  0  0  0  0  0 
0  0  0  0  0  0  0  0  0  0  0 
0  0  0  2  0  0  0  0  0  0  0 
0  0  0  0  0  0  0  0  0  0  0 
0  2  0  0  0  0  0  0  0  0  0 
0  0  0  0  0  0  0  0  0  0  0 
0  0  0  0  0  0  0  0  0  0  0 
0  0  0  0  0  0  0  0  0  0  0 
0  0  0  0  0  0  0  0  0  0  0 
0  0  0  0  0  0  0  0  0  0  0 
sum = 3
-------------------------------------------稀疏数组---------------------------------
11 11 3 
1  2  1 
3  3  2 
5  1  2 
-------------------------------------------恢复后的二维数组---------------------------
0  0  0  0  0  0  0  0  0  0  0 
0  0  1  0  0  0  0  0  0  0  0 
0  0  0  0  0  0  0  0  0  0  0 
0  0  0  2  0  0  0  0  0  0  0 
0  0  0  0  0  0  0  0  0  0  0 
0  2  0  0  0  0  0  0  0  0  0 
0  0  0  0  0  0  0  0  0  0  0 
0  0  0  0  0  0  0  0  0  0  0 
0  0  0  0  0  0  0  0  0  0  0 
0  0  0  0  0  0  0  0  0  0  0 
0  0  0  0  0  0  0  0  0  0  0