def test_naive_nbest(self):
data = [random.randrange(2000) for _ in xrange(1000)]
heap = self.makeHeap()
for item in data:
heap.push(item)
if len(heap) > 10:
heap.popmin()
assert list(heap.iterpop()) == self.sorted(data)[-10:]
def test_heapsort(self):
# Exercise everything with repeated heapsort checks
for trial in xrange(100):
size = random.randrange(50)
data = [random.randrange(25) for _ in xrange(size)]
if trial & 1: # Half of the time, use heapify
heap = self.makeHeap(data)
else: # The rest of the time, use heappush
heap = self.makeHeap()
for item in data:
heap.push(item)
heap_sorted = [heap.popmin() for _ in xrange(size)]
assert heap_sorted == self.sorted(data)
def test_push_pop(self):
# push 256 random numbers and pop them off, verifying all's OK.
heap = self.makeHeap()
data = []
self.assert_heap_invariant(heap)
for _ in xrange(256):
item = random.random()
data.append(item)
heap.push(item)
self.assert_heap_invariant(heap)
results = []
while heap:
item = heap.popmin()
self.assert_heap_invariant(heap)
results.append(item)
assert self.sorted(data) == results
# check that the invariant holds for a sorted array
self.assert_heap_invariant(results)
py.test.raises(TypeError, heap.push)
py.test.raises(TypeError, heap.push, None, None)
py.test.raises(TypeError, heap.popmin, None)