def setUp(self):
count_trials = 1000
keys = np.cumsum(np.random.random_integers(1, 10000, count_trials))
vals = range(count_trials)
self.indata = zip(keys, vals)
self.keyfunc = lambda x: x[0]
self.valfunc = lambda x: x[1]
self.heap = SlidingMaxHeap(value=self.valfunc)
def setUp(self): count_trials = 1000 keys = np.cumsum(np.random.random_integers(1, 10000, count_trials)) vals = range(count_trials) self.indata = zip(keys, vals) self.keyfunc = lambda x: x[0] self.valfunc = lambda x: x[1] self.heap = SlidingMaxHeap(value = self.valfunc)
def sliding_max(iterable, window_len, valfunc):
heap = SlidingMaxHeap(value=valfunc)
for i, item in enumerate(iterable):
heap.append(item)
heap.drop_while(lambda x: len(heap._heap) > window_len)
yield heap.root
class TestHeapMonotonic(unittest.TestCase):
def setUp(self):
count_trials = 1000
keys = np.cumsum(np.random.random_integers(1, 10000, count_trials))
vals = range(count_trials)
self.indata = zip(keys, vals)
self.keyfunc = lambda x: x[0]
self.valfunc = lambda x: x[1]
self.heap = SlidingMaxHeap(value=self.valfunc)
def test1(self):
"""Insert monotonic time series, and then delete all elements."""
for item in self.indata:
self.heap.append(item)
self.assertEqual(item, self.heap.root)
self.assertTrue(self.heap.is_heap())
self.assertTrue(all_distinct(self.heap.history))
for item in self.indata:
self.assertTrue(self.heap.is_heap())
self.assertTrue(all_distinct(self.heap.history))
self.heap._drop_oldest()
def test2(self):
"""Maintain fixed window history of a monotonic time series."""
for i, item in enumerate(self.indata):
self.heap.append(item)
if i > 100:
self.heap._drop_oldest()
self.assertEqual(item, self.heap.root)
self.assertTrue(self.heap.is_heap())
def sliding_max(iterable, window_len, valfunc): heap = SlidingMaxHeap(value = valfunc) for i, item in enumerate(iterable): heap.append(item) heap.drop_while(lambda x: len(heap._heap) > window_len) yield heap.root
class TestHeapMonotonic(unittest.TestCase): def setUp(self): count_trials = 1000 keys = np.cumsum(np.random.random_integers(1, 10000, count_trials)) vals = range(count_trials) self.indata = zip(keys, vals) self.keyfunc = lambda x: x[0] self.valfunc = lambda x: x[1] self.heap = SlidingMaxHeap(value = self.valfunc) def test1(self): """Insert monotonic time series, and then delete all elements.""" for item in self.indata: self.heap.append(item) self.assertEqual(item, self.heap.root) self.assertTrue(self.heap.is_heap()) self.assertTrue(all_distinct(self.heap.history)) for item in self.indata: self.assertTrue(self.heap.is_heap()) self.assertTrue(all_distinct(self.heap.history)) self.heap._drop_oldest() def test2(self): """Maintain fixed window history of a monotonic time series.""" for i, item in enumerate(self.indata): self.heap.append(item) if i > 100: self.heap._drop_oldest() self.assertEqual(item, self.heap.root) self.assertTrue(self.heap.is_heap())
