def test_sampling_composite_beta_generator():
parameter_space_subset = ParameterSpaceSubset()
parameter_space_subset.generate(box,
n,
sampling=(DrawFrom(random.beta, a=2, b=5),
DrawFrom(random.beta, a=5, b=1)))
plot(0,
box,
parameter_space_subset,
bins,
stats.beta,
a=2,
b=5,
loc=box[0][min],
scale=box[0][max] - box[0][min])
plot(1,
box,
parameter_space_subset,
bins,
stats.beta,
a=5,
b=1,
loc=box[1][min],
scale=box[1][max] - box[1][min])
plt.show()
def __init__(self, a, b):
assert isinstance(a, (list, tuple))
assert isinstance(b, (list, tuple))
assert len(a) == len(b)
CompositeDistribution.__init__(
self,
[DrawFrom(random.beta, a=a_p, b=b_p) for (a_p, b_p) in zip(a, b)])
def test_sampling_composite_log_uniform_and_beta():
parameter_space_subset = ParameterSpaceSubset()
parameter_space_subset.generate(box,
n,
sampling=(LogUniformDistribution(),
DrawFrom(random.beta, a=2, b=5)))
plot(0,
box,
parameter_space_subset,
bins,
stats_loguniform,
loc=box[0][min],
scale=box[0][max] - box[0][min])
plot(1,
box,
parameter_space_subset,
bins,
stats.beta,
a=2,
b=5,
loc=box[1][min],
scale=box[1][max] - box[1][min])
plt.show()