def test_build_binary_tree(self):
array = [-10, 9, 20, None, None, 15, 7]
root = build_binary_tree(array)
in_order_array = []
in_order(root, in_order_array)
array.remove(None)
self.assertEqual(self.list_equal([-10, 9, 20, 15, 7], in_order_array),
True)
def test_build_binary_tree02(self):
array = [5, 4, 8, 11, None, 13, 4, 7, 2, None, None, None, 1]
root = build_binary_tree(array)
in_order_array = []
in_order(root, in_order_array)
array.remove(None)
self.assertEqual(
self.list_equal([5, 4, 11, 7, 2, 8, 13, 4, 1], in_order_array),
True)
def random_binary_tree(max_tree_val, max_tree_size):
tree_values = [
random.randint(0, max_tree_val) for i in range(max_tree_size)
]
pytree = None
for val in tree_values:
pytree = tree_insert(pytree, val)
py_pre = pre_order(pytree)
py_in = in_order(pytree)
py_post = post_order(pytree)
return (tree_values, py_pre, py_in, py_post)
rithm to create a binary search tree with minimal height.
"""
from binary_tree import BinaryNode, in_order, pre_order, post_order
def minimal_tree(arr):
if not arr:
return None
return do_minimal_tree(arr, 0, len(arr) - 1)
def do_minimal_tree(arr, low, high):
if low > high:
return None
mid = (low + high) // 2
node = BinaryNode(arr[mid])
node.left = do_minimal_tree(arr, low, mid - 1)
node.right = do_minimal_tree(arr, mid + 1, high)
return node
if __name__ == '__main__':
tree = minimal_tree([1, 2, 3, 4, 5, 6, 7, 8, 9, 10])
in_order(tree, lambda n: print(n.value))
print('')
pre_order(tree, lambda n: print(n.value))
print('')
post_order(tree, lambda n: print(n.value))
from binary_tree import Node, in_order
def helper(start, end):
if start >= end:
return [None] if start > end else [Node(start)]
res = []
for i in range(start, end):
left = helper(start, i)
right = helper(i + 1, end)
for j in left:
for k in right:
node = Node(i)
node.left = j
node.right = k
res.append(node)
return res
def generate_tree(n):
return helper(1, n + 1)
if __name__ == '__main__':
print('leetcode 95')
for r in generate_tree(3):
print(in_order(r))