如何用十字链表实现矩阵加法,你能给我写一个代码吗
时间: 2024-01-27 19:06:25 浏览: 33
当然可以,这是一个用十字链表实现矩阵加法的示例代码:
```python
class MatrixNode:
def __init__(self, row, col, value):
self.row = row
self.col = col
self.value = value
self.right = None
self.down = None
class CrossMatrix:
def __init__(self, rows, cols):
self.rows = rows
self.cols = cols
self.row_heads = [MatrixNode(i, -1, None) for i in range(rows)]
self.col_heads = [MatrixNode(-1, i, None) for i in range(cols)]
self.head = MatrixNode(-1, -1, None)
self.head.right = self.col_heads[0]
self.head.down = self.row_heads[0]
def insert(self, row, col, value):
node = MatrixNode(row, col, value)
row_head = self.row_heads[row]
col_head = self.col_heads[col]
current_node = row_head
while current_node.right and current_node.right.col < col:
current_node = current_node.right
node.right = current_node.right
current_node.right = node
current_node = col_head
while current_node.down and current_node.down.row < row:
current_node = current_node.down
node.down = current_node.down
current_node.down = node
def add(self, other):
if self.rows != other.rows or self.cols != other.cols:
raise ValueError("Matrices must have the same size")
result = CrossMatrix(self.rows, self.cols)
for i in range(self.rows):
current_node1 = self.row_heads[i].right
current_node2 = other.row_heads[i].right
while current_node1 or current_node2:
if current_node1 and (not current_node2 or current_node1.col < current_node2.col):
result.insert(i, current_node1.col, current_node1.value)
current_node1 = current_node1.right
elif current_node2 and (not current_node1 or current_node2.col < current_node1.col):
result.insert(i, current_node2.col, current_node2.value)
current_node2 = current_node2.right
else:
result.insert(i, current_node1.col, current_node1.value + current_node2.value)
current_node1 = current_node1.right
current_node2 = current_node2.right
return result
```
这里定义了两个类:`MatrixNode`和`CrossMatrix`。`MatrixNode`表示矩阵中的一个节点,包括行、列、值以及右边和下面的节点。`CrossMatrix`表示一个十字链表形式的矩阵,包括行数、列数、行头节点数组、列头节点数组和头节点。这个类提供了插入、加法等方法。
在`add`方法中,我们通过遍历两个矩阵的每一行并按列顺序合并它们,然后将结果插入到新的矩阵中。