def test_stats_2_int() -> None:
s = SampleStatistics()
s.put(-1)
s.put(1)
assert s.mean() == 0.0
assert s.variance() == 2.0
assert s.deviation() == sqrt(2.0)
def test_stats_3_int() -> None:
s = SampleStatistics()
s.put(89)
s.put(90)
s.put(91)
assert s.mean() == 90.0
assert s.variance() == 1.0
assert s.deviation() == 1.0
def test_stats_2_float() -> None:
s = SampleStatistics()
s.put(1.0)
s.put(2.0)
assert s.mean() == 1.5
assert s.variance() == 0.5
assert s.deviation() == sqrt(0.5)
def test_stats_3_float_mean_small() -> None:
# found by hypothesis
s = SampleStatistics()
s.put(-9.020465019382587e+92)
s.put(-9.020465019382587e+92)
s.put(-9.020465019382587e+92)
assert s.sum / s.samples < s.min
assert s.mean() == s.min
def test_stats_floats(samples: Sequence[float]) -> None:
s = SampleStatistics()
for sample in samples:
s.put(sample)
assert s.mean() >= s.min
assert s.mean() <= s.max
assert s.variance() >= 0.
if s.min < s.max:
assert s.deviation() <= s.max - s.min
def test_stats_3_float_deviation_small() -> None:
# found by hypothesis
s = SampleStatistics()
s.put(1.5765166949677225e-06)
s.put(1.5765166949677225e-06)
s.put(1.5765166949677225e-06)
assert s.max == s.min
assert (s.sum_of_squares - s.sum * s.sum / 3) / 2 > 0
def test_stats_3_float_deviation_big() -> None:
# found by hypothesis
s = SampleStatistics()
s.put(688338275.2675972)
s.put(688338275.2675972)
s.put(688338275.2675972)
assert s.max == s.min
assert (s.sum_of_squares - s.sum * s.sum / 3) / 2 > 0
def bron_kerbosch_timed(graph: Graph, clique_count: int,
func_indices: List[int],
samples: int) -> List[SampleStatistics]:
first = None
times = [SampleStatistics() for _ in range(len(FUNCS))]
for sample in range(1 if samples == 1 else 0, samples + 1):
for func_index in func_indices:
func = FUNCS[func_index]
func_name = FUNC_NAMES[func_index]
if sample == 0:
reporter = SimpleReporter()
begin = time.perf_counter()
try:
func(graph, reporter)
except RecursionError:
print(f"{func_name} recursed out!")
secs = time.perf_counter() - begin
if secs >= 3.0:
print(f" {func_name:<8}: {secs:6.3f}s")
current = sorted(sorted(clique) for clique in reporter.cliques)
if first is None:
if len(current) != clique_count:
print(
f"{func_name}: expected {clique_count}, obtained {len(current)} cliques!"
)
if graph.order < 100 and not are_maximal(current):
print(f" {func_name} not maximal")
first = current
elif first != current:
print(f"{func_name}: " +
f"expected {len(first)} cliques, " +
f"obtained {len(current)} different cliques!")
else:
counter = CountingReporter()
begin = time.perf_counter()
try:
func(graph, counter)
except RecursionError:
print(f"{func_name} recursed out!")
secs = time.perf_counter() - begin
if counter.cliques != clique_count:
print(
f"{func_name}: expected {clique_count}, obtained {counter.cliques} cliques!"
)
times[func_index].put(secs)
return times
def test_stats_0_i32() -> None:
s = SampleStatistics()
assert isnan(s.mean())
assert isnan(s.variance())
assert isnan(s.deviation())
def test_stats_9_int() -> None:
s = SampleStatistics()
s.put(2)
s.put(4)
s.put(4)
s.put(4)
s.put(5)
s.put(5)
s.put(5)
s.put(7)
s.put(9)
assert s.mean() == 5.0
assert s.variance() == 4.0
assert s.deviation() == 2.0
def test_stats_1_int() -> None:
s = SampleStatistics()
s.put(-1)
assert s.mean() == -1.0
assert isnan(s.variance())
assert isnan(s.deviation())