mirror of
https://github.com/TheAlgorithms/Python.git
synced 2024-11-24 13:31:07 +00:00
4700297b3e
* Enable ruff RUF002 rule * Fix --------- Co-authored-by: Christian Clauss <cclauss@me.com>
736 lines
25 KiB
Python
736 lines
25 KiB
Python
"""
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psf/black : true
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ruff : passed
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"""
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from __future__ import annotations
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from collections.abc import Iterator
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class RedBlackTree:
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"""
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A Red-Black tree, which is a self-balancing BST (binary search
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tree).
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This tree has similar performance to AVL trees, but the balancing is
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less strict, so it will perform faster for writing/deleting nodes
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and slower for reading in the average case, though, because they're
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both balanced binary search trees, both will get the same asymptotic
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performance.
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To read more about them, https://en.wikipedia.org/wiki/Red-black_tree
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Unless otherwise specified, all asymptotic runtimes are specified in
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terms of the size of the tree.
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"""
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def __init__(
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self,
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label: int | None = None,
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color: int = 0,
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parent: RedBlackTree | None = None,
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left: RedBlackTree | None = None,
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right: RedBlackTree | None = None,
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) -> None:
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"""Initialize a new Red-Black Tree node with the given values:
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label: The value associated with this node
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color: 0 if black, 1 if red
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parent: The parent to this node
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left: This node's left child
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right: This node's right child
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"""
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self.label = label
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self.parent = parent
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self.left = left
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self.right = right
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self.color = color
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# Here are functions which are specific to red-black trees
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def rotate_left(self) -> RedBlackTree:
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"""Rotate the subtree rooted at this node to the left and
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returns the new root to this subtree.
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Performing one rotation can be done in O(1).
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"""
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parent = self.parent
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right = self.right
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if right is None:
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return self
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self.right = right.left
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if self.right:
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self.right.parent = self
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self.parent = right
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right.left = self
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if parent is not None:
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if parent.left == self:
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parent.left = right
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else:
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parent.right = right
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right.parent = parent
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return right
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def rotate_right(self) -> RedBlackTree:
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"""Rotate the subtree rooted at this node to the right and
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returns the new root to this subtree.
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Performing one rotation can be done in O(1).
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"""
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if self.left is None:
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return self
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parent = self.parent
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left = self.left
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self.left = left.right
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if self.left:
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self.left.parent = self
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self.parent = left
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left.right = self
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if parent is not None:
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if parent.right is self:
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parent.right = left
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else:
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parent.left = left
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left.parent = parent
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return left
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def insert(self, label: int) -> RedBlackTree:
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"""Inserts label into the subtree rooted at self, performs any
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rotations necessary to maintain balance, and then returns the
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new root to this subtree (likely self).
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This is guaranteed to run in O(log(n)) time.
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"""
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if self.label is None:
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# Only possible with an empty tree
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self.label = label
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return self
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if self.label == label:
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return self
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elif self.label > label:
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if self.left:
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self.left.insert(label)
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else:
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self.left = RedBlackTree(label, 1, self)
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self.left._insert_repair()
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elif self.right:
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self.right.insert(label)
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else:
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self.right = RedBlackTree(label, 1, self)
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self.right._insert_repair()
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return self.parent or self
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def _insert_repair(self) -> None:
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"""Repair the coloring from inserting into a tree."""
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if self.parent is None:
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# This node is the root, so it just needs to be black
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self.color = 0
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elif color(self.parent) == 0:
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# If the parent is black, then it just needs to be red
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self.color = 1
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else:
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uncle = self.parent.sibling
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if color(uncle) == 0:
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if self.is_left() and self.parent.is_right():
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self.parent.rotate_right()
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if self.right:
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self.right._insert_repair()
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elif self.is_right() and self.parent.is_left():
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self.parent.rotate_left()
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if self.left:
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self.left._insert_repair()
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elif self.is_left():
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if self.grandparent:
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self.grandparent.rotate_right()
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self.parent.color = 0
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if self.parent.right:
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self.parent.right.color = 1
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else:
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if self.grandparent:
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self.grandparent.rotate_left()
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self.parent.color = 0
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if self.parent.left:
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self.parent.left.color = 1
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else:
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self.parent.color = 0
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if uncle and self.grandparent:
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uncle.color = 0
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self.grandparent.color = 1
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self.grandparent._insert_repair()
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def remove(self, label: int) -> RedBlackTree:
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"""Remove label from this tree."""
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if self.label == label:
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if self.left and self.right:
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# It's easier to balance a node with at most one child,
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# so we replace this node with the greatest one less than
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# it and remove that.
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value = self.left.get_max()
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if value is not None:
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self.label = value
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self.left.remove(value)
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else:
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# This node has at most one non-None child, so we don't
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# need to replace
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child = self.left or self.right
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if self.color == 1:
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# This node is red, and its child is black
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# The only way this happens to a node with one child
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# is if both children are None leaves.
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# We can just remove this node and call it a day.
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if self.parent:
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if self.is_left():
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self.parent.left = None
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else:
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self.parent.right = None
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# The node is black
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elif child is None:
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# This node and its child are black
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if self.parent is None:
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# The tree is now empty
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return RedBlackTree(None)
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else:
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self._remove_repair()
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if self.is_left():
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self.parent.left = None
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else:
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self.parent.right = None
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self.parent = None
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else:
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# This node is black and its child is red
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# Move the child node here and make it black
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self.label = child.label
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self.left = child.left
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self.right = child.right
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if self.left:
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self.left.parent = self
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if self.right:
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self.right.parent = self
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elif self.label is not None and self.label > label:
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if self.left:
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self.left.remove(label)
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elif self.right:
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self.right.remove(label)
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return self.parent or self
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def _remove_repair(self) -> None:
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"""Repair the coloring of the tree that may have been messed up."""
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if (
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self.parent is None
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or self.sibling is None
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or self.parent.sibling is None
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or self.grandparent is None
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):
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return
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if color(self.sibling) == 1:
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self.sibling.color = 0
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self.parent.color = 1
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if self.is_left():
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self.parent.rotate_left()
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else:
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self.parent.rotate_right()
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if (
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color(self.parent) == 0
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and color(self.sibling) == 0
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and color(self.sibling.left) == 0
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and color(self.sibling.right) == 0
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):
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self.sibling.color = 1
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self.parent._remove_repair()
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return
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if (
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color(self.parent) == 1
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and color(self.sibling) == 0
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and color(self.sibling.left) == 0
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and color(self.sibling.right) == 0
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):
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self.sibling.color = 1
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self.parent.color = 0
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return
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if (
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self.is_left()
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and color(self.sibling) == 0
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and color(self.sibling.right) == 0
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and color(self.sibling.left) == 1
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):
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self.sibling.rotate_right()
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self.sibling.color = 0
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if self.sibling.right:
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self.sibling.right.color = 1
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if (
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self.is_right()
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and color(self.sibling) == 0
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and color(self.sibling.right) == 1
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and color(self.sibling.left) == 0
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):
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self.sibling.rotate_left()
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self.sibling.color = 0
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if self.sibling.left:
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self.sibling.left.color = 1
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if (
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self.is_left()
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and color(self.sibling) == 0
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and color(self.sibling.right) == 1
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):
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self.parent.rotate_left()
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self.grandparent.color = self.parent.color
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self.parent.color = 0
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self.parent.sibling.color = 0
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if (
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self.is_right()
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and color(self.sibling) == 0
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and color(self.sibling.left) == 1
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):
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self.parent.rotate_right()
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self.grandparent.color = self.parent.color
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self.parent.color = 0
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self.parent.sibling.color = 0
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def check_color_properties(self) -> bool:
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"""Check the coloring of the tree, and return True iff the tree
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is colored in a way which matches these five properties:
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(wording stolen from wikipedia article)
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1. Each node is either red or black.
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2. The root node is black.
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3. All leaves are black.
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4. If a node is red, then both its children are black.
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5. Every path from any node to all of its descendent NIL nodes
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has the same number of black nodes.
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This function runs in O(n) time, because properties 4 and 5 take
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that long to check.
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"""
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# I assume property 1 to hold because there is nothing that can
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# make the color be anything other than 0 or 1.
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# Property 2
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if self.color:
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# The root was red
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print("Property 2")
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return False
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# Property 3 does not need to be checked, because None is assumed
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# to be black and is all the leaves.
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# Property 4
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if not self.check_coloring():
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print("Property 4")
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return False
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# Property 5
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if self.black_height() is None:
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print("Property 5")
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return False
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# All properties were met
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return True
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def check_coloring(self) -> bool:
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"""A helper function to recursively check Property 4 of a
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Red-Black Tree. See check_color_properties for more info.
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"""
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if self.color == 1 and 1 in (color(self.left), color(self.right)):
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return False
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if self.left and not self.left.check_coloring():
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return False
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if self.right and not self.right.check_coloring():
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return False
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return True
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def black_height(self) -> int | None:
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"""Returns the number of black nodes from this node to the
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leaves of the tree, or None if there isn't one such value (the
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tree is color incorrectly).
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"""
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if self is None or self.left is None or self.right is None:
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# If we're already at a leaf, there is no path
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return 1
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left = RedBlackTree.black_height(self.left)
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right = RedBlackTree.black_height(self.right)
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if left is None or right is None:
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# There are issues with coloring below children nodes
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return None
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if left != right:
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# The two children have unequal depths
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return None
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# Return the black depth of children, plus one if this node is
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# black
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return left + (1 - self.color)
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# Here are functions which are general to all binary search trees
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def __contains__(self, label: int) -> bool:
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"""Search through the tree for label, returning True iff it is
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found somewhere in the tree.
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Guaranteed to run in O(log(n)) time.
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"""
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return self.search(label) is not None
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def search(self, label: int) -> RedBlackTree | None:
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"""Search through the tree for label, returning its node if
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it's found, and None otherwise.
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This method is guaranteed to run in O(log(n)) time.
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"""
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if self.label == label:
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return self
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elif self.label is not None and label > self.label:
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if self.right is None:
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return None
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else:
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return self.right.search(label)
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elif self.left is None:
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return None
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else:
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return self.left.search(label)
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def floor(self, label: int) -> int | None:
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"""Returns the largest element in this tree which is at most label.
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This method is guaranteed to run in O(log(n)) time."""
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if self.label == label:
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return self.label
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elif self.label is not None and self.label > label:
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if self.left:
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return self.left.floor(label)
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else:
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return None
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else:
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if self.right:
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attempt = self.right.floor(label)
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if attempt is not None:
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return attempt
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return self.label
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def ceil(self, label: int) -> int | None:
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"""Returns the smallest element in this tree which is at least label.
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This method is guaranteed to run in O(log(n)) time.
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"""
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if self.label == label:
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return self.label
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elif self.label is not None and self.label < label:
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if self.right:
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return self.right.ceil(label)
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else:
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return None
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else:
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if self.left:
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attempt = self.left.ceil(label)
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if attempt is not None:
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return attempt
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return self.label
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def get_max(self) -> int | None:
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"""Returns the largest element in this tree.
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This method is guaranteed to run in O(log(n)) time.
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"""
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if self.right:
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# Go as far right as possible
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return self.right.get_max()
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else:
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return self.label
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def get_min(self) -> int | None:
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"""Returns the smallest element in this tree.
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This method is guaranteed to run in O(log(n)) time.
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"""
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if self.left:
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# Go as far left as possible
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return self.left.get_min()
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else:
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return self.label
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@property
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def grandparent(self) -> RedBlackTree | None:
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"""Get the current node's grandparent, or None if it doesn't exist."""
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if self.parent is None:
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return None
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else:
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return self.parent.parent
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@property
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def sibling(self) -> RedBlackTree | None:
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"""Get the current node's sibling, or None if it doesn't exist."""
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if self.parent is None:
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return None
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elif self.parent.left is self:
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return self.parent.right
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else:
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return self.parent.left
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def is_left(self) -> bool:
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"""Returns true iff this node is the left child of its parent."""
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if self.parent is None:
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return False
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return self.parent.left is self
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def is_right(self) -> bool:
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"""Returns true iff this node is the right child of its parent."""
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if self.parent is None:
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return False
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return self.parent.right is self
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def __bool__(self) -> bool:
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return True
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def __len__(self) -> int:
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"""
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Return the number of nodes in this tree.
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"""
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ln = 1
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if self.left:
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ln += len(self.left)
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if self.right:
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ln += len(self.right)
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return ln
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|
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def preorder_traverse(self) -> Iterator[int | None]:
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yield self.label
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if self.left:
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yield from self.left.preorder_traverse()
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if self.right:
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yield from self.right.preorder_traverse()
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def inorder_traverse(self) -> Iterator[int | None]:
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if self.left:
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yield from self.left.inorder_traverse()
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yield self.label
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if self.right:
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yield from self.right.inorder_traverse()
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|
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def postorder_traverse(self) -> Iterator[int | None]:
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if self.left:
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yield from self.left.postorder_traverse()
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if self.right:
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yield from self.right.postorder_traverse()
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yield self.label
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|
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def __repr__(self) -> str:
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from pprint import pformat
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if self.left is None and self.right is None:
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return f"'{self.label} {(self.color and 'red') or 'blk'}'"
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return pformat(
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{
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f"{self.label} {(self.color and 'red') or 'blk'}": (
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self.left,
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self.right,
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)
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},
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indent=1,
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)
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|
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def __eq__(self, other: object) -> bool:
|
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"""Test if two trees are equal."""
|
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if not isinstance(other, RedBlackTree):
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return NotImplemented
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if self.label == other.label:
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return self.left == other.left and self.right == other.right
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else:
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return False
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|
|
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def color(node: RedBlackTree | None) -> int:
|
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"""Returns the color of a node, allowing for None leaves."""
|
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if node is None:
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return 0
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else:
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return node.color
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|
|
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"""
|
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Code for testing the various
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functions of the red-black tree.
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"""
|
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|
|
|
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def test_rotations() -> bool:
|
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"""Test that the rotate_left and rotate_right functions work."""
|
|
# Make a tree to test on
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tree = RedBlackTree(0)
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tree.left = RedBlackTree(-10, parent=tree)
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tree.right = RedBlackTree(10, parent=tree)
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tree.left.left = RedBlackTree(-20, parent=tree.left)
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tree.left.right = RedBlackTree(-5, parent=tree.left)
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tree.right.left = RedBlackTree(5, parent=tree.right)
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tree.right.right = RedBlackTree(20, parent=tree.right)
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# Make the right rotation
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|
left_rot = RedBlackTree(10)
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|
left_rot.left = RedBlackTree(0, parent=left_rot)
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|
left_rot.left.left = RedBlackTree(-10, parent=left_rot.left)
|
|
left_rot.left.right = RedBlackTree(5, parent=left_rot.left)
|
|
left_rot.left.left.left = RedBlackTree(-20, parent=left_rot.left.left)
|
|
left_rot.left.left.right = RedBlackTree(-5, parent=left_rot.left.left)
|
|
left_rot.right = RedBlackTree(20, parent=left_rot)
|
|
tree = tree.rotate_left()
|
|
if tree != left_rot:
|
|
return False
|
|
tree = tree.rotate_right()
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|
tree = tree.rotate_right()
|
|
# Make the left rotation
|
|
right_rot = RedBlackTree(-10)
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|
right_rot.left = RedBlackTree(-20, parent=right_rot)
|
|
right_rot.right = RedBlackTree(0, parent=right_rot)
|
|
right_rot.right.left = RedBlackTree(-5, parent=right_rot.right)
|
|
right_rot.right.right = RedBlackTree(10, parent=right_rot.right)
|
|
right_rot.right.right.left = RedBlackTree(5, parent=right_rot.right.right)
|
|
right_rot.right.right.right = RedBlackTree(20, parent=right_rot.right.right)
|
|
if tree != right_rot:
|
|
return False
|
|
return True
|
|
|
|
|
|
def test_insertion_speed() -> bool:
|
|
"""Test that the tree balances inserts to O(log(n)) by doing a lot
|
|
of them.
|
|
"""
|
|
tree = RedBlackTree(-1)
|
|
for i in range(300000):
|
|
tree = tree.insert(i)
|
|
return True
|
|
|
|
|
|
def test_insert() -> bool:
|
|
"""Test the insert() method of the tree correctly balances, colors,
|
|
and inserts.
|
|
"""
|
|
tree = RedBlackTree(0)
|
|
tree.insert(8)
|
|
tree.insert(-8)
|
|
tree.insert(4)
|
|
tree.insert(12)
|
|
tree.insert(10)
|
|
tree.insert(11)
|
|
ans = RedBlackTree(0, 0)
|
|
ans.left = RedBlackTree(-8, 0, ans)
|
|
ans.right = RedBlackTree(8, 1, ans)
|
|
ans.right.left = RedBlackTree(4, 0, ans.right)
|
|
ans.right.right = RedBlackTree(11, 0, ans.right)
|
|
ans.right.right.left = RedBlackTree(10, 1, ans.right.right)
|
|
ans.right.right.right = RedBlackTree(12, 1, ans.right.right)
|
|
return tree == ans
|
|
|
|
|
|
def test_insert_and_search() -> bool:
|
|
"""Tests searching through the tree for values."""
|
|
tree = RedBlackTree(0)
|
|
tree.insert(8)
|
|
tree.insert(-8)
|
|
tree.insert(4)
|
|
tree.insert(12)
|
|
tree.insert(10)
|
|
tree.insert(11)
|
|
if 5 in tree or -6 in tree or -10 in tree or 13 in tree:
|
|
# Found something not in there
|
|
return False
|
|
if not (11 in tree and 12 in tree and -8 in tree and 0 in tree):
|
|
# Didn't find something in there
|
|
return False
|
|
return True
|
|
|
|
|
|
def test_insert_delete() -> bool:
|
|
"""Test the insert() and delete() method of the tree, verifying the
|
|
insertion and removal of elements, and the balancing of the tree.
|
|
"""
|
|
tree = RedBlackTree(0)
|
|
tree = tree.insert(-12)
|
|
tree = tree.insert(8)
|
|
tree = tree.insert(-8)
|
|
tree = tree.insert(15)
|
|
tree = tree.insert(4)
|
|
tree = tree.insert(12)
|
|
tree = tree.insert(10)
|
|
tree = tree.insert(9)
|
|
tree = tree.insert(11)
|
|
tree = tree.remove(15)
|
|
tree = tree.remove(-12)
|
|
tree = tree.remove(9)
|
|
if not tree.check_color_properties():
|
|
return False
|
|
if list(tree.inorder_traverse()) != [-8, 0, 4, 8, 10, 11, 12]:
|
|
return False
|
|
return True
|
|
|
|
|
|
def test_floor_ceil() -> bool:
|
|
"""Tests the floor and ceiling functions in the tree."""
|
|
tree = RedBlackTree(0)
|
|
tree.insert(-16)
|
|
tree.insert(16)
|
|
tree.insert(8)
|
|
tree.insert(24)
|
|
tree.insert(20)
|
|
tree.insert(22)
|
|
tuples = [(-20, None, -16), (-10, -16, 0), (8, 8, 8), (50, 24, None)]
|
|
for val, floor, ceil in tuples:
|
|
if tree.floor(val) != floor or tree.ceil(val) != ceil:
|
|
return False
|
|
return True
|
|
|
|
|
|
def test_min_max() -> bool:
|
|
"""Tests the min and max functions in the tree."""
|
|
tree = RedBlackTree(0)
|
|
tree.insert(-16)
|
|
tree.insert(16)
|
|
tree.insert(8)
|
|
tree.insert(24)
|
|
tree.insert(20)
|
|
tree.insert(22)
|
|
if tree.get_max() != 22 or tree.get_min() != -16:
|
|
return False
|
|
return True
|
|
|
|
|
|
def test_tree_traversal() -> bool:
|
|
"""Tests the three different tree traversal functions."""
|
|
tree = RedBlackTree(0)
|
|
tree = tree.insert(-16)
|
|
tree.insert(16)
|
|
tree.insert(8)
|
|
tree.insert(24)
|
|
tree.insert(20)
|
|
tree.insert(22)
|
|
if list(tree.inorder_traverse()) != [-16, 0, 8, 16, 20, 22, 24]:
|
|
return False
|
|
if list(tree.preorder_traverse()) != [0, -16, 16, 8, 22, 20, 24]:
|
|
return False
|
|
if list(tree.postorder_traverse()) != [-16, 8, 20, 24, 22, 16, 0]:
|
|
return False
|
|
return True
|
|
|
|
|
|
def test_tree_chaining() -> bool:
|
|
"""Tests the three different tree chaining functions."""
|
|
tree = RedBlackTree(0)
|
|
tree = tree.insert(-16).insert(16).insert(8).insert(24).insert(20).insert(22)
|
|
if list(tree.inorder_traverse()) != [-16, 0, 8, 16, 20, 22, 24]:
|
|
return False
|
|
if list(tree.preorder_traverse()) != [0, -16, 16, 8, 22, 20, 24]:
|
|
return False
|
|
if list(tree.postorder_traverse()) != [-16, 8, 20, 24, 22, 16, 0]:
|
|
return False
|
|
return True
|
|
|
|
|
|
def print_results(msg: str, passes: bool) -> None:
|
|
print(str(msg), "works!" if passes else "doesn't work :(")
|
|
|
|
|
|
def pytests() -> None:
|
|
assert test_rotations()
|
|
assert test_insert()
|
|
assert test_insert_and_search()
|
|
assert test_insert_delete()
|
|
assert test_floor_ceil()
|
|
assert test_tree_traversal()
|
|
assert test_tree_chaining()
|
|
|
|
|
|
def main() -> None:
|
|
"""
|
|
>>> pytests()
|
|
"""
|
|
print_results("Rotating right and left", test_rotations())
|
|
print_results("Inserting", test_insert())
|
|
print_results("Searching", test_insert_and_search())
|
|
print_results("Deleting", test_insert_delete())
|
|
print_results("Floor and ceil", test_floor_ceil())
|
|
print_results("Tree traversal", test_tree_traversal())
|
|
print_results("Tree traversal", test_tree_chaining())
|
|
print("Testing tree balancing...")
|
|
print("This should only be a few seconds.")
|
|
test_insertion_speed()
|
|
print("Done!")
|
|
|
|
|
|
if __name__ == "__main__":
|
|
main()
|