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data_structures/heap/fibonacci_heap.py

@@ -1,444 +1,361 @@
-from __future__ import annotations
+"""
+Fibonacci Heap
+A more efficient priority queue implementation that provides amortized time bounds
+that are better than those of the binary and binomial heaps.
+reference: https://en.wikipedia.org/wiki/Fibonacci_heap
+
+Operations supported:
+- Insert: O(1) amortized
+- Find minimum: O(1)
+- Delete minimum: O(log n) amortized
+- Decrease key: O(1) amortized
+- Merge: O(1)
+"""
 
 
 class Node:
-    """A node in the Fibonacci heap.
+    """
+    A node in a Fibonacci heap.
 
-    Each node maintains references to its key, degree (number of children),
-    marked status, parent, child, and circular linked list references (left/right).
+    Args:
+        val: The value stored in the node.
 
     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
+        val: The value stored in the node.
+        parent: Reference to parent node.
+        child: Reference to one child node.
+        left: Reference to left sibling.
+        right: Reference to right sibling.
+        degree: Number of children.
+        mark: Boolean indicating if node has lost a child.
     """
 
-    def __init__(self, key: float | None) -> None:
-        self.key = key or None
-        self.degree = 0
-        self.marked = False
-        self.parent = Node(None)
-        self.child = Node(None)
+    def __init__(self, val):
+        self.val = val
+        self.parent = None
+        self.child = None
         self.left = self
         self.right = self
+        self.degree = 0
+        self.mark = False
+
+    def add_sibling(self, node):
+        """
+        Adds a node as a sibling to the current node.
+
+        Args:
+            node: The node to add as a sibling.
+        """
+        node.left = self
+        node.right = self.right
+        self.right.left = node
+        self.right = node
+
+    def add_child(self, node):
+        """
+        Adds a node as a child of the current node.
+
+        Args:
+            node: The node to add as a child.
+        """
+        node.parent = self
+        if not self.child:
+            self.child = node
+        else:
+            self.child.add_sibling(node)
+        self.degree += 1
+
+    def remove(self):
+        """Removes this node from its sibling list."""
+        self.left.right = self.right
+        self.right.left = self.left
 
 
 class FibonacciHeap:
-    """Implementation of a Fibonacci heap using circular linked lists.
+    """
+    A Fibonacci heap implementation providing
+    amortized efficient priority queue operations.
 
-    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.
+    This implementation provides the following time complexities:
+        - Insert: O(1) amortized
+        - Find minimum: O(1)
+        - Delete minimum: O(log n) amortized
+        - Decrease key: O(1) amortized
+        - Merge: O(1)
 
-    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
+    Example:
+    >>> heap = FibonacciHeap()
+    >>> node1 = heap.insert(3)
+    >>> node2 = heap.insert(2)
+    >>> node3 = heap.insert(15)
+    >>> heap.peek()
+    2
+    >>> heap.delete_min()
+    2
+    >>> heap.peek()
+    3
+    >>> other_heap = FibonacciHeap()
+    >>> node4 = other_heap.insert(1)
+    >>> heap.merge_heaps(other_heap)
+    >>> heap.peek()
+    1
     """
 
-    def __init__(self) -> None:
-        self.min_node = Node(None)
-        self.total_nodes = 0
+    def __init__(self):
+        """Initializes an empty Fibonacci heap."""
+        self.min_node = None
+        self.size = 0
 
-    def insert(self, key: float | None) -> Node:
-        """Insert a new key into the heap.
-
-        Args:
-            key: The key value to insert
+    def is_empty(self):
+        """
+        Checks if the heap is empty.
 
         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
+            bool: True if heap is empty, False otherwise.
         """
-        new_node = Node(key)
-        if self.min_node is None:
-            self.min_node = new_node
+        return self.min_node is None
+
+    def insert(self, val):
+        """
+        Inserts a new value into the heap.
+
+        Args:
+            val: Value to insert.
+
+        Returns:
+            Node: The newly created node.
+        """
+        node = Node(val)
+        if not self.min_node:
+            self.min_node = 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
+            self.min_node.add_sibling(node)
+            if node.val < self.min_node.val:
+                self.min_node = node
+        self.size += 1
+        return node
 
-    @staticmethod
-    def _insert_into_circular_list(base_node: Node, node_to_insert: Node) -> Node:
-        """Insert node into circular linked list.
+    def peek(self):
+        """
+        Returns the minimum value without removing it.
+
+        Returns:
+            The minimum value in the heap.
+
+        Raises:
+            IndexError: If the heap is empty.
+        """
+        if not self.min_node:
+            raise IndexError("Heap is empty")
+        return self.min_node.val
+
+    def merge_heaps(self, other):
+        """
+        Merges another Fibonacci heap into this one.
 
         Args:
-            base_node: The reference node in the circular list
-            node_to_insert: The node to insert into the list
+            other: Another FibonacciHeap instance to merge with this one.
+        """
+        if not other.min_node:
+            return
+        if not self.min_node:
+            self.min_node = other.min_node
+        else:
+            # Merge root lists
+            self.min_node.right.left = other.min_node.left
+            other.min_node.left.right = self.min_node.right
+            self.min_node.right = other.min_node
+            other.min_node.left = self.min_node
+
+            if other.min_node.val < self.min_node.val:
+                self.min_node = other.min_node
+
+        self.size += other.size
+
+    def __link_trees(self, node1, node2):
+        """
+        Links two trees of same degree.
+
+        Args:
+            node1: First tree's root node.
+            node2: Second tree's root node.
+        """
+        node1.remove()
+        if node2.child:
+            node2.child.add_sibling(node1)
+        else:
+            node2.child = node1
+        node1.parent = node2
+        node2.degree += 1
+        node1.mark = False
+
+    def delete_min(self):
+        """
+        Removes and returns the minimum value from the heap.
 
         Returns:
-            Node: The base node
+            The minimum value that was removed.
 
-        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
+        Raises:
+            IndexError: If the heap is empty.
         """
-        if base_node.key is None:
-            return node_to_insert
+        if not self.min_node:
+            raise IndexError("Heap is empty")
 
-        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
+        min_val = self.min_node.val
 
-    def extract_min(self) -> float | None:
-        """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 Node(None).key
-
-        min_node = self.min_node
-
-        if min_node.child:
-            current_child = min_node.child
-            last_child = min_node.child.left
+        # Add all children to root list
+        if self.min_node.child:
+            curr = self.min_node.child
             while True:
-                next_child = current_child.right
-                self._insert_into_circular_list(self.min_node, current_child)
-                current_child.parent.key = None
-                if current_child == last_child:
+                next_node = curr.right
+                curr.parent = None
+                curr.mark = False
+                self.min_node.add_sibling(curr)
+                if curr.right == self.min_node.child:
                     break
-                current_child = next_child
+                curr = next_node
 
-        min_node.left.right = min_node.right
-        min_node.right.left = min_node.left
-
-        if min_node == min_node.right:
-            self.min_node.key = None
+        # Remove minimum node
+        if self.min_node.right == self.min_node:
+            self.min_node = None
         else:
-            self.min_node = min_node.right
-            self._consolidate()
+            self.min_node.remove()
+            self.min_node = self.min_node.right
+            self.__consolidate()
 
-        self.total_nodes -= 1
-        return min_node.key
+        self.size -= 1
+        return min_val
 
-    def _consolidate(self) -> None:
-        """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.
+    def __consolidate(self):
         """
-        max_degree = int(self.total_nodes**0.5) + 1
-        degree_table = [Node(None)] * max_degree
+        Consolidates the trees in the heap after a delete_min operation.
 
+        This is an internal method that maintains the heap's structure.
+        """
+        max_degree = int(self.size**0.5) + 1
+        degree_table = [None] * max_degree
+
+        # Collect all roots
         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
+        curr = self.min_node
+        while True:
+            roots.append(curr)
+            curr = curr.right
+            if curr == self.min_node:
+                break
 
-        for current_root in roots:
-            root_node = current_root
-            current_degree = root_node.degree
+        # Consolidate trees
+        for root in roots:
+            degree = root.degree
+            while degree_table[degree]:
+                other = degree_table[degree]
+                if root.val > other.val:
+                    root, other = other, root
+                self.__link_trees(other, root)
+                degree_table[degree] = None
+                degree += 1
+            degree_table[degree] = root
 
-            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.key 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] = Node(None)
-                current_degree += 1
-
-            degree_table[current_degree] = root_node
-
-        self.min_node.key = None
+        # Find new minimum
+        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] < self.min_node.key)
-            ):
-                self.min_node = degree_table[degree]
+            if degree_table[degree]:
+                if not self.min_node:
+                    self.min_node = degree_table[degree]
+                    self.min_node.left = self.min_node
+                    self.min_node.right = self.min_node
+                else:
+                    self.min_node.add_sibling(degree_table[degree])
+                    if degree_table[degree].val < self.min_node.val:
+                        self.min_node = degree_table[degree]
 
-    def decrease_key(self, node: Node, new_key: float | None) -> None:
-        """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.
+    def decrease_key(self, node, new_val):
+        """
+        Decreases the value of a node.
 
         Args:
-            node: The node whose key should be decreased
-            new_key: The new key value, must be smaller than the current key
+            node: The node whose value should be decreased.
+            new_val: The new value for the node.
 
-        Example:
-            >>> heap = FibonacciHeap()
-            >>> node1 = 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
+        Raises:
+            ValueError: If new value is greater than current value.
         """
-        if new_key > node.key:
-            raise ValueError("New key is greater than current key")
+        if new_val > node.val:
+            raise ValueError("New value is greater than current value")
 
-        node.key = new_key
-        parent_node = node.parent
+        node.val = new_val
+        parent = node.parent
 
-        if parent_node.key is not None and node.key < parent_node.key:
-            self._cut(node, parent_node)
-            self._cascading_cut(parent_node)
+        if parent and node.val < parent.val:
+            self.__cut(node, parent)
+            self.__cascading_cut(parent)
 
-        if node.key < self.min_node.key:
+        if node.val < self.min_node.val:
             self.min_node = node
 
-    def _cut(self, child_node: Node, parent_node: Node) -> None:
-        """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.
+    def __cut(self, node, parent):
+        """
+        Cuts a node from its parent.
 
         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 = Node(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 = Node(None)
-        child_node.marked = False
-
-    def _cascading_cut(self, current_node: Node) -> None:
-        """Perform cascading cut operation.
+            node: Node to be cut.
+            parent: Parent of the node to be cut.
+        """ """
+        Performs cascading cut operation.
 
         Args:
-            current_node: The node to start cascading cut from
+            node: Starting node for cascading cut.
         """
-        if (parent_node := current_node.parent) is not None:
-            if not current_node.marked:
-                current_node.marked = True
+
+        parent.degree -= 1
+        if parent.child == node:
+            parent.child = node.right if node.right != node else None
+        node.remove()
+        node.left = node
+        node.right = node
+        node.parent = None
+        node.mark = False
+        self.min_node.add_sibling(node)
+
+    def __cascading_cut(self, node):
+        """
+        Performs cascading cut operation.
+
+        Args:
+            node: Starting node for cascading cut.
+        """
+
+        if parent := node.parent:
+            if not node.mark:
+                node.mark = True
             else:
-                self._cut(current_node, parent_node)
-                self._cascading_cut(parent_node)
+                self.__cut(node, parent)
+                self.__cascading_cut(parent)
 
-    def delete(self, node: Node) -> None:
-        """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.
+    def __str__(self):
         """
-        self.decrease_key(node, float("-inf"))
-        self.extract_min()
-
-    def find_min(self) -> float | None:
-        """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 a string representation of the heap.
 
         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
+            str: A string showing the heap structure.
         """
-        return self.min_node.key if self.min_node else Node(None).key
+        if not self.min_node:
+            return "Empty heap"
 
-    def is_empty(self) -> bool:
-        """Check if heap is empty.
+        def print_tree(node, level=0):
+            result = []
+            curr = node
+            while True:
+                result.append("-" * level + str(curr.val))
+                if curr.child:
+                    result.extend(print_tree(curr.child, level + 1))
+                curr = curr.right
+                if curr == node:
+                    break
+            return result
 
-        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.key is None
-
-    def merge(self, other_heap: FibonacciHeap) -> None:
-        """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.key is None:
-            return
-        if self.min_node.key 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
+        return "\n".join(print_tree(self.min_node))
 
 
 if __name__ == "__main__":