def test_scipy_integer_dist_interval_bug(self):
"""Scipy does not return the correct answer for integer distributions."""
dim = Integer('yolo', 'randint', -3, 6)
assert dim.interval() == (-3, 6)
assert dim.interval(1.0) == (-3, 6)
assert dim.interval(0.9999) == (-3, 6)
dim = Integer('yolo2', 'randint', -2, 4, loc=8)
assert dim.interval() == (6, 12)
def _sample_int_point(
self,
dimension: Integer,
below_points: numpy.ndarray | Sequence[numpy.ndarray],
above_points: numpy.ndarray | Sequence[numpy.ndarray],
):
"""Sample one value for integer dimension based on the observed good and bad points"""
low, high = dimension.interval()
assert isinstance(low, int)
assert isinstance(high, int)
choices = range(low, high + 1)
below_points = numpy.array(below_points).astype(int) - low
above_points = numpy.array(above_points).astype(int) - low
sampler_below = CategoricalSampler(self, below_points, choices)
candidate_points = sampler_below.sample(self.n_ei_candidates)
sampler_above = CategoricalSampler(self, above_points, choices)
lik_below = sampler_below.get_loglikelis(candidate_points)
lik_above = sampler_above.get_loglikelis(candidate_points)
new_point: numpy.ndarray = compute_max_ei_point(
candidate_points, lik_below, lik_above
)
new_point = new_point + low
return new_point
def test_simple_instance(self, seed):
"""Test Integer.__init__."""
dim = Integer('yolo', 'uniform', -3, 6)
samples = dim.sample(seed=seed)
assert len(samples) == 1
assert samples[0] == -2
assert dim.interval() == (-3, 3)
assert dim.interval(0.5) == (-2, 2)
assert 1.0 in dim
assert str(dim) == "Integer(name=yolo, prior={uniform: (-3, 6), {}}, "\
"shape=(), default value=None)"
assert dim.name == 'yolo'
assert dim.type == 'integer'
assert dim.shape == ()
def discrete_grid(dim: Integer, num: int):
"""Build discretized real grid"""
grid = real_grid(dim, num)
_, b = dim.interval()
discrete_grid = [int(numpy.round(grid[0]))]
for v in grid[1:]:
int_v = int(numpy.round(v))
if int_v <= discrete_grid[-1]:
int_v = discrete_grid[-1] + 1
if int_v > b:
log.warning(f"Cannot list {num} discrete values for {dim.name}. "
"Will use {len(discrete_grid)} points instead.")
break
discrete_grid.append(int_v)
return discrete_grid
def test_interval_with_infs(self):
"""Regression test: Interval handles correctly extreme bounds."""
dim = Integer('yolo', 'poisson', 5)
# XXX: Complete this on both end of interval when scipy bug is fixed
assert dim.interval()[1] == np.inf
def test_inclusive_intervals(self):
"""Test that discretized bounds are valid"""
dim = Integer("yolo", "uniform", -3, 5.5)
assert dim.interval() == (-3, 3)
