Question

摘要：我知道如何在Python中构建二进制树。我知道如何遍历它。我甚至知道如何在该BTree中搜索特定值;但是，我无法弄清楚如何仅遍历二叉树的部分。

目标：我有500万个+数据点。我想查找比所讨论的值所有数据点（例如：所有点数小于40,000）。我的基本逻辑如下：

从树的根开始，然后向下遍历到问题
在问题上，首先，遍历左侧（小于侧）
遍历所有剩余点（左右），直到回到有问题的点

我的代码：

class node:
    def __init__(self, value=None):
        self.value = value
        self.left_child = None
        self.right_child = None

class binary_search_tree:
    def __init__(self):
        self.root = None

    def insert(self, value):
        if self.root is None:
            self.root = node(value)
        else:
            self._insert(value, self.root)

    def _insert(self, value, cur_node):
        if value < cur_node.value:
            if cur_node.left_child is None:
                cur_node.left_child = node(value)
            else:
                self._insert(value, cur_node.left_child)
        elif value > cur_node.value:
            if cur_node.right_child is None:
                cur_node.right_child = node(value)
            else:
                self._insert(value, cur_node.right_child)
        else:
            print('Value already in tree!')

    def print_tree(self):
        if self.root is not None:
            self._print_tree(self.root)

    def _print_tree(self, cur_node):
        if cur_node is not None:
            self._print_tree(cur_node.left_child)
            print(str(cur_node.value))
            self._print_tree(cur_node.right_child)

    def height(self):
        if self.root is not None:
            return self._height(self.root, 0)
        else:
            return 0

    def _height(self, cur_node, cur_height):
        if cur_node is None:
            return cur_height
        left_height = self._height(cur_node.left_child, cur_height+1)
        right_height = self._height(cur_node.right_child, cur_height+1)
        return max(left_height, right_height)

    def print_trav_tree(self):
        return self._print_trav_tree(self.root)

    def _print_trav_tree(self, start):
        #Root -> left -> right
        traversal = ""
        if start:
            traversal += (str(start.value) + "-")
            traversal = self._print_trav_tree(start.left_child)
            traversal = self._print_trav_tree(start.right_child)
        return traversal

    def search(self, value):
        if self.root is not None:
            return self._search(value, self.root)
        else:
            return False

    def _search(self, value, cur_node):
        int_val = 0
        if value == cur_node.value:
            int_val = cur_node.value
        elif value < cur_node.value and cur_node.left_child is not None:
            int_val = self._search(value, cur_node.left_child)
        elif value > cur_node.value and cur_node.right_child is not None:
            int_val = self._search(value, cur_node.right_child)
        else:
            int_val = cur_node.value
            #return -1

        if int_val == -1:
            int_val = cur_node.value

        return int_val


def main():
    tree = binary_search_tree()

    tree.insert(666)
    tree.insert(888)
    tree.insert(88)
    tree.insert(0)
    tree.insert(55)
    tree.insert(143)
    tree.insert(193)
    tree.insert(52)
    tree.insert(21)
    tree.insert(10)

    tree.print_tree()
    print("tree height is: " + str(tree.height()) + "\n")

    print(tree.search(10))
    print(tree.search(777))
    print(tree.search(199))

    jack = tree.print_trav_tree()
    print(jack)

if __name__ == "__main__":
    main()

任何帮助都会很棒！

BTree - 仅遍历树的一部分（Python 3）

0 个答案: