def a_star(G: Graph, start: int, stop: int):
H = G.H
open = BinaryHeap()
for succ in G.get_succesors(start):
open.add([G[start][succ] + H[succ][stop], start, succ])
closed = Map(start, len(G))
while True:
f, u, x = open.get()
g = f - H[x][stop]
if g < closed[x][0]:
closed[x] = (round(g, 2), u)
for ng in G.get_succesors(x):
if ng not in closed:
open.add((closed[x][0] + G[x][ng] + H[ng][stop], x, ng))
if x == stop:
return closed.reconstruct_path(start, stop)
class TestBinaryHeap(unittest.TestCase):
def setUp(self):
self.heap = BinaryHeap()
self.replayMemory = ReplayMemory(10, 32, 4, 84, 84)
def test_Add(self):
totalNo = 10
for i in range(totalNo):
state = np.zeros((84, 84), dtype=np.int)
state.fill(i)
td = i
addedIndex = self.replayMemory.add(0, 0, state, 0)
self.heap.add(addedIndex, td)
for i in range(totalNo):
topItem = self.heap.getTop()
self.assertEqual(totalNo - i - 1, topItem[0])
self.heap.remove(0)
def make_tree(freq_table):
"""
Constructs and returns the Huffman tree from the given frequency table.
"""
trees = BinaryHeap()
trees.add(TreeLeaf(None), 1)
for (symbol, freq) in freq_table.items():
trees.add(TreeLeaf(symbol), freq)
while len(trees) > 1:
right, rfreq = trees.pop_min()
left, lfreq = trees.pop_min()
trees.add(TreeBranch(left, right), lfreq + rfreq)
tree, _ = trees.pop_min()
return tree
print("\nBinomialHeap")
test(BinomialHeap, lst)
print("\nBinaryHeap")
test(BinaryHeap,lst)
print("\nQueue")
test(Queue,lst)
print('\n')
brh = BinaryHeap()
brh_time = timer()
for dst, u, v in lst:
brh.add([dst, u, v])
brh_time = timer() - brh_time
blh = BinomialHeap()
blh_time = timer()
for dst, u, v in lst:
blh.add([dst, u, v])
blh_time = timer() - blh_time
sq = Queue()
q_time = timer()
for dst, u, v in lst:
sq.add([dst, u, v])
q_time = timer()-q_time
print(f"Binary Heap: {brh_time}\nBinomial Heap: {blh_time}\n" +
