def test_mixed_2(histogram):
conditions = (
HistogramCondition(histogram["xs"], histogram["densities"]),
IntervalCondition(p=0.4, max=1),
IntervalCondition(p=0.45, max=1.2),
IntervalCondition(p=0.48, max=1.3),
IntervalCondition(p=0.5, max=2),
IntervalCondition(p=0.7, max=2.2),
IntervalCondition(p=0.9, max=2.3),
)
dist = LogisticMixture.from_conditions(conditions,
num_components=3,
verbose=True)
assert dist.pdf1(-5) == pytest.approx(0, abs=0.1)
assert dist.pdf1(6) == pytest.approx(0, abs=0.1)
my_cache = {}
my_cache[conditions] = 3
conditions_2 = (
HistogramCondition(histogram["xs"], histogram["densities"]),
IntervalCondition(p=0.4, max=1),
IntervalCondition(p=0.45, max=1.2),
IntervalCondition(p=0.48, max=1.3),
IntervalCondition(p=0.5, max=2),
IntervalCondition(p=0.7, max=2.2),
IntervalCondition(p=0.9, max=2.3),
)
assert hash(conditions) == hash(conditions_2)
assert my_cache[conditions_2] == 3
def test_mixture_from_histogram(histogram):
conditions = [HistogramCondition(histogram["xs"], histogram["densities"])]
mixture = LogisticMixture.from_conditions(conditions,
num_components=3,
verbose=True)
for (x, density) in zip(histogram["xs"], histogram["densities"]):
assert mixture.pdf1(x) == pytest.approx(density, abs=0.2)
def test_mixture_from_percentile():
for value in [0.01, 0.1, 1, 3]:
conditions = [IntervalCondition(p=0.5, max=value)]
dist = LogisticMixture.from_conditions(conditions,
num_components=1,
verbose=True)
loc = dist.components[0].loc
assert loc == pytest.approx(value, rel=0.1), loc
def test_mixture_from_percentile():
for value in [0.01, 0.1, 1, 3]:
conditions = [IntervalCondition(p=0.5, max=value)]
dist = LogisticMixture.from_conditions(conditions,
{"num_components": 1},
verbose=True,
scale=Scale(0, 3))
loc = dist.components[0].base_dist.true_loc
assert loc == pytest.approx(value, rel=0.1), loc
def test_mixture_from_histogram(histogram):
conditions = [HistogramCondition(histogram["xs"], histogram["densities"])]
mixture = LogisticMixture.from_conditions(
conditions,
{"num_components": 3},
Scale(min(histogram["xs"]), max(histogram["xs"])),
)
for (x, density) in zip(histogram["xs"], histogram["densities"]):
assert mixture.pdf(x) == pytest.approx(density, abs=0.2)
def test_weights_mixture():
conditions = [
IntervalCondition(p=0.4, max=1, weight=0.01),
IntervalCondition(p=0.5, max=2, weight=100),
IntervalCondition(p=0.8, max=2.2, weight=0.01),
IntervalCondition(p=0.9, max=2.3, weight=0.01),
]
dist = LogisticMixture.from_conditions(conditions,
num_components=1,
verbose=True)
assert dist.components[0].loc == pytest.approx(2, rel=0.1)
def test_mixture_from_percentiles():
conditions = [
IntervalCondition(p=0.1, max=1),
IntervalCondition(p=0.5, max=2),
IntervalCondition(p=0.6, max=3),
]
dist = LogisticMixture.from_conditions(conditions,
num_components=3,
verbose=True)
for condition in conditions:
assert dist.cdf(condition.max) == pytest.approx(condition.p, rel=0.1)
def test_weights_mixture():
conditions = [
IntervalCondition(p=0.4, max=1, weight=0.01),
IntervalCondition(p=0.5, max=2, weight=100),
IntervalCondition(p=0.8, max=2.2, weight=0.01),
IntervalCondition(p=0.9, max=2.3, weight=0.01),
]
dist = LogisticMixture.from_conditions(conditions, {"num_components": 1},
verbose=True,
scale=Scale(0, 3))
assert dist.components[0].base_dist.true_loc == pytest.approx(2, rel=0.1)
def test_mixture_from_percentiles():
conditions = [
IntervalCondition(p=0.1, max=1),
IntervalCondition(p=0.5, max=2),
IntervalCondition(p=0.6, max=3),
]
dist = LogisticMixture.from_conditions(conditions, {"num_components": 4},
verbose=False,
scale=Scale(0, 3))
for condition in conditions:
assert dist.cdf(condition.max) == pytest.approx(condition.p, rel=0.1)
def test_percentile_roundtrip():
conditions = [
IntervalCondition(p=0.01, max=0.61081324517545),
IntervalCondition(p=0.1, max=0.8613634657212543),
IntervalCondition(p=0.25, max=1),
IntervalCondition(p=0.5, max=1.5),
IntervalCondition(p=0.75, max=2),
IntervalCondition(p=0.9, max=2.1386364698410034),
IntervalCondition(p=0.99, max=2.3891870975494385),
]
mixture = LogisticMixture.from_conditions(conditions,
num_components=3,
verbose=True)
recovered_conditions = mixture.percentiles(
percentiles=[condition.p for condition in conditions])
for (condition, recovered_condition) in zip(conditions,
recovered_conditions):
assert recovered_condition.max == pytest.approx(condition.max, rel=0.1)
