class MovingMedian:
def __init__(self, window_size=-1):
self.window_size = window_size
self.median = 0
self.iter = 0
self.history = deque() if window_size > 0 else None
self.lower = IndexedHeap()
self.upper = IndexedHeap()
def update(self, v):
if not self.upper.size():
self.upper.push((v, 0))
if self.window_size > 0:
self.history.append((v, 0))
self.median = v
return
self.iter += 1
if self.window_size > 0 and len(self.history) == self.window_size:
oldest, i = self.history.popleft()
if self.lower.has((-oldest, i)):
self.lower.decrease((-oldest, i), (float('-inf'),) * 2)
self.lower.pop()
elif self.upper.has((oldest, i)):
self.upper.decrease((oldest, i), (float('-inf'),) * 2)
self.upper.pop()
else:
raise Exception('oldest value not found {}'.format(oldest))
if v > self.upper.peek()[0]:
self.upper.push((v, self.iter))
if self.window_size > 0:
self.history.append((v, self.iter))
else:
self.lower.push((-v, self.iter))
if self.window_size > 0:
self.history.append((v, self.iter))
if self.upper.size() - self.lower.size() > 1:
item = self.upper.pop()
self.lower.push((-item[0], item[1]))
if self.lower.size() - self.upper.size() > 1:
item = self.lower.pop()
self.upper.push((-item[0], item[1]))
if self.upper.size() > self.lower.size():
self.median = self.upper.peek()[0]
elif self.lower.size() > self.upper.size():
self.median = -self.lower.peek()[0]
else:
self.median = (-self.lower.peek()[0] + self.upper.peek()[0]) / 2.0
def minimum_spanning_tree(self, root=0):
"""
Implementacion del algoritmo de Prim.
Da por sentado que esta instancia de Digrafo es un Grafo. Es decir, que
una arista esta representada por dos aristas dirigidas del mismo peso.
Inicia el algoritmo desde el vertice raiz "root", por defecto = 0.
:return Digraph: arbol de tendido minimo dirigido
"""
# Setup
visited = [False] * self.V()
# edge_to = {dstVertex: Edge(srcVertex, dstVertex, weight)}
edge_to = {}
# heap inicializado con vertice raiz del arbol
heap = IndexedHeap()
heap._push(root, 0)
# Execution
while heap:
v = heap.pop()
visited[v] = True
for e in self.adj_e(v):
if not visited[e.dst]:
new_priority = e.weight
if e.dst in heap:
if new_priority < heap[e.dst]:
edge_to[e.dst] = e
heap._decreaseKey(e.dst, new_priority)
else:
edge_to[e.dst] = e
heap._push(e.dst, new_priority)
# Return
tree = Digraph(self.V())
for edge in edge_to.values():
tree.add_edge(edge.src, edge.dst, edge.weight)
return tree