""" Min-heaps. """ __author__ = """ysitu """ # Copyright (C) 2014 ysitu # All rights reserved. # BSD license. from heapq import heappop, heappush from itertools import count import networkx as nx __all__ = ['MinHeap', 'PairingHeap', 'BinaryHeap'] class MinHeap(object): """Base class for min-heaps. A MinHeap stores a collection of key-value pairs ordered by their values. It supports querying the minimum pair, inserting a new pair, decreasing the value in an existing pair and deleting the minimum pair. """ class _Item(object): """Used by subclassess to represent a key-value pair. """ __slots__ = ('key', 'value') def __init__(self, key, value): self.key = key self.value = value def __repr__(self): return repr((self.key, self.value)) def __init__(self): """Initialize a new min-heap. """ self._dict = {} def min(self): """Query the minimum key-value pair. Returns ------- key, value : tuple The key-value pair with the minimum value in the heap. Raises ------ NetworkXError If the heap is empty. """ raise NotImplementedError def pop(self): """Delete the minimum pair in the heap. Returns ------- key, value : tuple The key-value pair with the minimum value in the heap. Raises ------ NetworkXError If the heap is empty. """ raise NotImplementedError def get(self, key, default=None): """Return the value associated with a key. Parameters ---------- key : hashable object The key to be looked up. default : object Default value to return if the key is not present in the heap. Default value: None. Returns ------- value : object. The value associated with the key. """ raise NotImplementedError def insert(self, key, value, allow_increase=False): """Insert a new key-value pair or modify the value in an existing pair. Parameters ---------- key : hashable object The key. value : object comparable with existing values. The value. allow_increase : bool Whether the value is allowed to increase. If False, attempts to increase an existing value have no effect. Default value: False. Returns ------- decreased : bool True if a pair is inserted or the existing value is decreased. """ raise NotImplementedError def __nonzero__(self): """Return whether the heap if empty. """ return bool(self._dict) def __bool__(self): """Return whether the heap if empty. """ return bool(self._dict) def __len__(self): """Return the number of key-value pairs in the heap. """ return len(self._dict) def __contains__(self, key): """Return whether a key exists in the heap. Parameters ---------- key : any hashable object. The key to be looked up. """ return key in self._dict def _inherit_doc(cls): """Decorator for inheriting docstrings from base classes. """ def func(fn): fn.__doc__ = cls.__dict__[fn.__name__].__doc__ return fn return func class PairingHeap(MinHeap): """A pairing heap. """ class _Node(MinHeap._Item): """A node in a pairing heap. A tree in a pairing heap is stored using the left-child, right-sibling representation. """ __slots__ = ('left', 'next', 'prev', 'parent') def __init__(self, key, value): super(PairingHeap._Node, self).__init__(key, value) # The leftmost child. self.left = None # The next sibling. self.next = None # The previous sibling. self.prev = None # The parent. self.parent = None def __init__(self): """Initialize a pairing heap. """ super(PairingHeap, self).__init__() self._root = None @_inherit_doc(MinHeap) def min(self): if self._root is None: raise nx.NetworkXError('heap is empty.') return (self._root.key, self._root.value) @_inherit_doc(MinHeap) def pop(self): if self._root is None: raise nx.NetworkXError('heap is empty.') min_node = self._root self._root = self._merge_children(self._root) del self._dict[min_node.key] return (min_node.key, min_node.value) @_inherit_doc(MinHeap) def get(self, key, default=None): node = self._dict.get(key) return node.value if node is not None else default @_inherit_doc(MinHeap) def insert(self, key, value, allow_increase=False): node = self._dict.get(key) root = self._root if node is not None: if value < node.value: node.value = value if node is not root and value < node.parent.value: self._cut(node) self._root = self._link(root, node) return True elif allow_increase and value > node.value: node.value = value child = self._merge_children(node) # Nonstandard step: Link the merged subtree with the root. See # below for the standard step. if child is not None: self._root = self._link(self._root, child) # Standard step: Perform a decrease followed by a pop as if the # value were the smallest in the heap. Then insert the new # value into the heap. # if node is not root: # self._cut(node) # if child is not None: # root = self._link(root, child) # self._root = self._link(root, node) # else: # self._root = (self._link(node, child) # if child is not None else node) return False else: # Insert a new key. node = self._Node(key, value) self._dict[key] = node self._root = self._link(root, node) if root is not None else node return True def _link(self, root, other): """Link two nodes, making the one with the smaller value the parent of the other. """ if other.value < root.value: root, other = other, root next = root.left other.next = next if next is not None: next.prev = other other.prev = None root.left = other other.parent = root return root def _merge_children(self, root): """Merge the subtrees of the root using the standard two-pass method. The resulting subtree is detached from the root. """ node = root.left root.left = None if node is not None: link = self._link # Pass 1: Merge pairs of consecutive subtrees from left to right. # At the end of the pass, only the prev pointers of the resulting # subtrees have meaningful values. The other pointers will be fixed # in pass 2. prev = None while True: next = node.next if next is None: node.prev = prev break next_next = next.next node = link(node, next) node.prev = prev prev = node if next_next is None: break node = next_next # Pass 2: Successively merge the subtrees produced by pass 1 from # right to left with the rightmost one. prev = node.prev while prev is not None: prev_prev = prev.prev node = link(prev, node) prev = prev_prev # Now node can become the new root. Its has no parent nor siblings. node.prev = None node.next = None node.parent = None return node def _cut(self, node): """Cut a node from its parent. """ prev = node.prev next = node.next if prev is not None: prev.next = next else: node.parent.left = next node.prev = None if next is not None: next.prev = prev node.next = None node.parent = None class BinaryHeap(MinHeap): """A binary heap. """ def __init__(self): """Initialize a binary heap. """ super(BinaryHeap, self).__init__() self._heap = [] self._count = count() @_inherit_doc(MinHeap) def min(self): dict = self._dict if not dict: raise nx.NetworkXError('heap is empty') heap = self._heap pop = heappop # Repeatedly remove stale key-value pairs until a up-to-date one is # met. while True: value, _, key = heap[0] if key in dict and value == dict[key]: break pop(heap) return (key, value) @_inherit_doc(MinHeap) def pop(self): dict = self._dict if not dict: raise nx.NetworkXError('heap is empty') heap = self._heap pop = heappop # Repeatedly remove stale key-value pairs until a up-to-date one is # met. while True: value, _, key = heap[0] pop(heap) if key in dict and value == dict[key]: break del dict[key] return (key, value) @_inherit_doc(MinHeap) def get(self, key, default=None): return self._dict.get(key, default) @_inherit_doc(MinHeap) def insert(self, key, value, allow_increase=False): dict = self._dict if key in dict: old_value = dict[key] if value < old_value or (allow_increase and value > old_value): # Since there is no way to efficiently obtain the location of a # key-value pair in the heap, insert a new pair even if ones # with the same key may already be present. Deem the old ones # as stale and skip them when the minimum pair is queried. dict[key] = value heappush(self._heap, (value, next(self._count), key)) return value < old_value return False else: dict[key] = value heappush(self._heap, (value, next(self._count), key)) return True