def test_mixture_1(self):
distributions = ["B", "NB", "NB", "NB"]
h = Histogram(get_shared_data( "peup2.his"))
m1 = h.estimate_mixture(distributions, NbComponent="Estimated")
assert m1
types = []
for d in distributions:
temp = distribution_identifier_type[d]
types.append(temp)
c = h.mixture_estimation2(types, 0, True, True,
likelihood_penalty_type['AIC'])
assert str(c)==str(m1)
def test_mixture(self):
h = Histogram(get_shared_data("meri2.his"))
mixt = h.estimate_mixture(["B", "NB"])
assert ExtractHistogram(mixt, "Weight") == \
mixt.extract_weight()
assert ExtractHistogram(mixt, "Mixture") == \
mixt.extract_mixture()
assert ExtractHistogram(mixt, "Component", 1) == \
mixt.extract_component(1)
assert ExtractHistogram(mixt, "Component", 2) == \
mixt.extract_component(2)
try:
ExtractHistogram(mixt, "Component", 3)
assert False
except: # Bas distrubition index
assert True
def test_mixture_2(self):
h = Histogram(get_shared_data( "peup2.his"))
m2 = h.estimate_mixture([Binomial(0, 10, 0.5), "NB"])
assert m2
def test_histo_extract_data(self):
h = Histogram(get_shared_data("meri2.his"))
mixt = h.estimate_mixture(["B", "NB"])
assert ExtractData(mixt)
assert mixt.extract_data() == ExtractData(mixt)
def get_mixture_2(self):
"""create another mixture data"""
h = Histogram(get_shared_data("meri2.his"))
m = h.estimate_mixture("B", "NB")
return m
def get_mixture_2(self):
"""create another mixture data"""
h = Histogram(get_shared_data("meri2.his"))
m = h.estimate_mixture("B", "NB")
return m
