def main():
tree = BST()
N = 11
_set = set([random.randint(1, N * N) for _ in range(N)])
for x in _set:
tree.insert(x, "")
print "original tree"
tree.pretty_print()
inorder = [node.key for node in tree.inorder_nodes()]
preorder = [node.key for node in tree.preorder_nodes()]
# now build a new tree from these traversals
root = binary_tree_from_traversals(preorder, inorder)
new_tree = BST()
new_tree.root = root
print "reconstructed tree"
new_tree.pretty_print()
# verify the correctness
for orig_node, cloned_node in zip(tree.levelorder_nodes(),
new_tree.levelorder_nodes()):
assert orig_node is not cloned_node
assert orig_node.key == cloned_node.key
def main():
N = 22
arr = sorted([random.randint(1, N * N) for _ in range(N)])
print arr
root = balanced_bst_from_sorted_array(arr, 0, len(arr) - 1)
tree = BST()
tree.root = root
tree.pretty_print()
inorder = [node.key for node in tree.inorder_nodes()]
assert arr == inorder
def main():
tree = BST()
N = 11
_set = set([random.randint(1, N * N) for _ in range(N)])
# _set = [50, 6, 33, 20, 35, 36]
for x in _set:
tree.insert(x, "")
# just set the root to 0 so the full tree is not BST
tree.root.key = 0
tree.pretty_print()
print "largest bst with nodes: %d" % largest_bst(tree.root)
def main():
tree = BST()
N = 6
_set = set([random.randint(1, N * N) for _ in range(N)])
for x in _set:
tree.insert(x, "")
tree.pretty_print()
mirror_image(tree.root)
print ""
print "after inverting"
print ""
tree.pretty_print()
def main():
tree = BST()
N = 10
_set = set([random.randint(1, N * N) for _ in range(N)])
for x in _set:
tree.insert(x, "")
tree.pretty_print()
postorder = [node.key for node in tree.postorder_nodes()]
print postorder
postorder_iterator = PostorderIterator(tree.root)
idx = 0
while postorder_iterator.has_next():
postorder_iterator.next() is postorder[idx]
idx += 1
