Python/data_structures/heap/fibonacci_heap.py
2024-11-13 16:36:58 +08:00

444 lines
14 KiB
Python

class Node:
"""A node in the Fibonacci heap.
Each node maintains references to its key, degree (number of children),
marked status, parent, child, and circular linked list references (left/right).
Attributes:
key: The key value stored in the node
degree: Number of children of the node
marked: Boolean indicating if the node is marked
parent: Reference to parent node
child: Reference to one child node
left: Reference to left sibling in circular list
right: Reference to right sibling in circular list
Examples:
>>> node = Node(5)
>>> node.key
5
>>> node.degree
0
>>> node.marked
False
>>> node.left == node
True
>>> node.right == node
True
"""
def __init__(self, key):
self.key = key
self.degree = 0
self.marked = False
self.parent = None
self.child = None
self.left = self
self.right = self
class FibonacciHeap:
"""Implementation of a Fibonacci heap using circular linked lists.
A Fibonacci heap is a collection of trees satisfying the min-heap property.
This implementation uses circular linked lists for both the root list and
child lists of nodes.
Attributes:
min_node: Reference to the node with minimum key
total_nodes: Total number of nodes in the heap
Reference: Introduction to Algorithms (CLRS) Chapter 19
https://en.wikipedia.org/wiki/Fibonacci_heap
Examples:
>>> heap = FibonacciHeap()
>>> heap.is_empty()
True
>>> node = heap.insert(3)
>>> node.key
3
>>> node2 = heap.insert(2)
>>> node2.key
2
>>> heap.find_min()
2
>>> heap.extract_min()
2
>>> heap.find_min()
3
"""
def __init__(self):
self.min_node = None
self.total_nodes = 0
def insert(self, key):
"""Insert a new key into the heap.
Args:
key: The key value to insert
Returns:
Node: The newly created node
Examples:
>>> heap = FibonacciHeap()
>>> node = heap.insert(5)
>>> node.key
5
>>> heap.find_min()
5
>>> node2 = heap.insert(3)
>>> node2.key
3
>>> heap.find_min()
3
"""
new_node = Node(key)
if self.min_node is None:
self.min_node = new_node
else:
self._insert_into_circular_list(self.min_node, new_node)
if new_node.key < self.min_node.key:
self.min_node = new_node
self.total_nodes += 1
return new_node
def _insert_into_circular_list(self, base_node, node_to_insert):
"""Insert node into circular linked list.
Args:
base_node: The reference node in the circular list
node_to_insert: The node to insert into the list
Returns:
Node: The base node
Examples:
>>> heap = FibonacciHeap()
>>> node1 = Node(1)
>>> node2 = Node(2)
>>> result = heap._insert_into_circular_list(node1, node2)
>>> result == node1
True
>>> node1.right == node2
True
>>> node2.left == node1
True
"""
if base_node is None:
return node_to_insert
node_to_insert.right = base_node.right
node_to_insert.left = base_node
base_node.right.left = node_to_insert
base_node.right = node_to_insert
return base_node
def extract_min(self):
"""Remove and return the minimum key from the heap.
This operation removes the node with the minimum key from the heap,
adds all its children to the root list, and consolidates the heap
to maintain the Fibonacci heap properties. This is one of the more
complex operations with amortized time complexity of O(log n).
Returns:
Node: The minimum key value that was removed,
or None if the heap is empty
Example:
>>> heap = FibonacciHeap()
>>> node1 = heap.insert(3)
>>> node2 = heap.insert(1)
>>> node3 = heap.insert(2)
>>> heap.extract_min() # Removes and returns 1
1
>>> heap.extract_min() # Removes and returns 2
2
>>> heap.extract_min() # Removes and returns 3
3
>>> heap.extract_min() # Heap is now empty
Note:
This operation may trigger heap consolidation to maintain
the Fibonacci heap properties after removal of the minimum node.
"""
if self.min_node is None:
return None
min_node = self.min_node
if min_node.child:
current_child = min_node.child
last_child = min_node.child.left
while True:
next_child = current_child.right
self._insert_into_circular_list(self.min_node, current_child)
current_child.parent = None
if current_child == last_child:
break
current_child = next_child
min_node.left.right = min_node.right
min_node.right.left = min_node.left
if min_node == min_node.right:
self.min_node = None
else:
self.min_node = min_node.right
self._consolidate()
self.total_nodes -= 1
return min_node.key
def _consolidate(self):
"""Consolidate the heap after removing the minimum node.
This internal method maintains the Fibonacci heap properties by combining
trees of the same degree until no two roots have the same degree. This
process is key to maintaining the efficiency of the data structure.
The consolidation process works by:
1. Creating a temporary array indexed by tree degree
2. Processing each root node and combining trees of the same degree
3. Reconstructing the root list and finding the new minimum
Time complexity: O(log n) amortized
Note:
This is an internal method called by extract_min and should not be
called directly from outside the class.
"""
max_degree = int(self.total_nodes**0.5) + 1
degree_table = [None] * max_degree
roots = []
if self.min_node:
current_root = self.min_node
while True:
roots.append(current_root)
if current_root.right == self.min_node:
break
current_root = current_root.right
for current_root in roots:
root_node = current_root
current_degree = root_node.degree
while degree_table[current_degree] is not None:
other_root = degree_table[current_degree]
if root_node.key > other_root.key:
root_node, other_root = other_root, root_node
other_root.left.right = other_root.right
other_root.right.left = other_root.left
if root_node.child is None:
root_node.child = other_root
other_root.right = other_root
other_root.left = other_root
else:
self._insert_into_circular_list(root_node.child, other_root)
other_root.parent = root_node
root_node.degree += 1
other_root.marked = False
degree_table[current_degree] = None
current_degree += 1
degree_table[current_degree] = root_node
self.min_node = None
for degree in range(max_degree):
if degree_table[degree] is not None and (
self.min_node is None or (degree_table[degree].key < self.min_node.key)
):
self.min_node = degree_table[degree]
def decrease_key(self, node, new_key):
"""Decrease the key value of a given node.
This operation updates the key of a node to a new, smaller value and
maintains the min-heap property by potentially cutting the node from
its parent and performing cascading cuts up the tree.
Args:
node: The node whose key should be decreased
new_key: The new key value, must be smaller than the current key
Example:
>>> heap = FibonacciHeap()
>>> node = heap.insert(5)
>>> heap.decrease_key(node, 3)
>>> node.key
3
>>> heap.find_min()
3
>>> heap.decrease_key(node, 1)
>>> node.key
1
>>> heap.find_min()
1
"""
if new_key > node.key:
raise ValueError("New key is greater than current key")
node.key = new_key
parent_node = node.parent
if parent_node is not None and node.key < parent_node.key:
self._cut(node, parent_node)
self._cascading_cut(parent_node)
if node.key < self.min_node.key:
self.min_node = node
def _cut(self, child_node, parent_node):
"""Cut a node from its parent and add it to the root list.
This is a helper method used in decrease_key operations. When a node's key
becomes smaller than its parent's key, it needs to be cut from its parent
and added to the root list to maintain the min-heap property.
Args:
child_node: The node to be cut from its parent
parent_node: The parent node from which to cut
Note:
This is an internal method that maintains heap properties during
decrease_key operations. It should not be called directly from
outside the class.
"""
if child_node.right == child_node:
parent_node.child = None
else:
parent_node.child = child_node.right
child_node.right.left = child_node.left
child_node.left.right = child_node.right
parent_node.degree -= 1
self._insert_into_circular_list(self.min_node, child_node)
child_node.parent = None
child_node.marked = False
def _cascading_cut(self, current_node):
"""Perform cascading cut operation.
Args:
current_node: The node to start cascading cut from
"""
if (parent_node := current_node.parent) is not None:
if not current_node.marked:
current_node.marked = True
else:
self._cut(current_node, parent_node)
self._cascading_cut(parent_node)
def delete(self, node):
"""Delete a node from the heap.
This operation removes a given node from the heap by first decreasing
its key to negative infinity (making it the minimum) and then extracting
the minimum.
Args:
node: The node to be deleted from the heap
Example:
>>> heap = FibonacciHeap()
>>> node1 = heap.insert(3)
>>> node2 = heap.insert(2)
>>> heap.delete(node1)
>>> heap.find_min()
2
>>> heap.total_nodes
1
Note:
This operation has an amortized time complexity of O(log n)
as it combines decrease_key and extract_min operations.
"""
self.decrease_key(node, float("-inf"))
self.extract_min()
def find_min(self):
"""Return the minimum key without removing it from the heap.
This operation provides quick access to the minimum key in the heap
without modifying the heap structure.
Returns:
float | None: The minimum key value, or None if the heap is empty
Example:
>>> heap = FibonacciHeap()
>>> heap.find_min() is None
True
>>> node1 = heap.insert(3)
>>> heap.find_min()
3
"""
return self.min_node.key if self.min_node else None
def is_empty(self):
"""Check if heap is empty.
Returns:
bool: True if heap is empty, False otherwise
Examples:
>>> heap = FibonacciHeap()
>>> heap.is_empty()
True
>>> node = heap.insert(1)
>>> heap.is_empty()
False
"""
return self.min_node is None
def merge(self, other_heap):
"""Merge another Fibonacci heap into this one.
This operation combines two Fibonacci heaps by concatenating their
root lists and updating the minimum pointer if necessary. The other
heap is effectively consumed in this process.
Args:
other_heap: Another FibonacciHeap instance to merge into this one
Example:
>>> heap1 = FibonacciHeap()
>>> node1 = heap1.insert(3)
>>> heap2 = FibonacciHeap()
>>> node2 = heap2.insert(2)
>>> heap1.merge(heap2)
>>> heap1.find_min()
2
>>> heap1.total_nodes
2
"""
if other_heap.min_node is None:
return
if self.min_node is None:
self.min_node = other_heap.min_node
else:
self.min_node.right.left = other_heap.min_node.left
other_heap.min_node.left.right = self.min_node.right
self.min_node.right = other_heap.min_node
other_heap.min_node.left = self.min_node
if other_heap.min_node.key < self.min_node.key:
self.min_node = other_heap.min_node
self.total_nodes += other_heap.total_nodes
if __name__ == "__main__":
import doctest
doctest.testmod()