def test_plot_mixture_data(self):
mixt1 = Mixture(0.6, Distribution("B", 2, 18, 0.5), 0.4,
Distribution("NB", 10, 10, 0.5))
mixt_histo1 = Simulate(mixt1, 200)
if DISABLE_PLOT == False:
mixt1.plot()
mixt_histo1.plot()
def test_plot_mixture_data(self):
mixt1 = Mixture(0.6, Distribution("B", 2, 18, 0.5), 0.4,
Distribution("NB", 10, 10, 0.5))
mixt_histo1 = Simulate(mixt1, 200)
if DISABLE_PLOT == False:
mixt1.plot()
mixt_histo1.plot()
def get_mixture(self):
"""create a mixture data"""
d1 = Uniform(0, 10)
d2 = Uniform(10, 20)
d3 = Uniform(20, 30)
m = Mixture(0.1, d1, 0.2, d2, 0.7, d3)
return m
def test_constructor_from_dists_failure(self):
d1 = Binomial(0, 12, 0.1)
d2 = Binomial(0, 12, 0.5)
try:
_mixt = Mixture(0.1, d1, d2)
assert False
except TypeError:
assert True
def build_data(self):
d1 = Binomial(0, 12, 0.1)
d2 = Binomial(0, 12, 0.5)
d3 = Binomial(0, 12, 0.8)
mixt = Mixture(0.1, d1, 0.2, d2, 0.7, d3)
assert mixt.nb_component == 3
return mixt
def test_constructor_from_model(self):
from openalea.stat_tool.compound import Compound
from openalea.stat_tool.mixture import Mixture
from openalea.stat_tool.convolution import Convolution
from openalea.stat_tool.distribution import Binomial
Renewal(Compound(Binomial(0,10,0.5), Binomial(0,10,0.3)),
Type="Equilibrium", ObservationTime=20)
Renewal(Mixture(0.1, Binomial(0,10,0.5), 0.9, Binomial(0,10,0.3)),
Type="Equilibrium", ObservationTime=20)
Renewal(Compound(Binomial(0,10,0.5), Binomial(0,10,0.3)),
Type="Equilibrium", ObservationTime=20)
def test_merge(self):
mixt1 = Mixture(0.6, Distribution("B", 2, 18, 0.5),
0.4, Distribution("NB", 10, 10, 0.5))
mixt_histo1 = Simulate(mixt1, 200)
histo10 = mixt_histo1.extract_component(1)
histo11 = mixt_histo1.extract_component(2)
histo12 = Merge(histo10, histo11)
assert histo12
Plot(histo12)
def test_simulate_mixture():
m = Mixture("data/mixture1.mixt")
s1 = Simulate(m, 1000)
assert s1
def mixt(self):
d1 = Uniform(0, 10)
d2 = Uniform(10, 20)
d3 = Uniform(20, 30)
m = Mixture(0.1, d1, 0.2, d2, 0.7, d3)
return m
def mixt_data(self):
d1 = Binomial(0, 10, 0.5)
d2 = NegativeBinomial(0, 1, 0.1)
mixt = Mixture(0.1, d1, 0.4, d2)
mixt_data = mixt.simulate(self.N)
return mixt_data
def test2():
"""finite mixture of discrete distributions"""
mixt1 = Mixture("data//mixture1.mixt")
mixt1 = Mixture(0.6, Distribution("B", 2, 18, 0.5), 0.4,
Distribution("NB", 10, 10, 0.5))
mixt_histo1 = Simulate(mixt1, 200)
Plot(mixt_histo1)
# extraction of histograms/frequency distributions corresponding
# to a given mixture component
# (i.e. elementary distributions which are combined by mixture)
histo10 = ExtractHistogram(mixt_histo1, "Component", 1)
histo11 = ExtractHistogram(mixt_histo1, "Component", 2)
_histo12 = Merge(histo10, histo11)
_histo13 = ExtractHistogram(mixt_histo1, "Weight")
# estimation
mixt2 = Estimate(mixt_histo1,
"MIXTURE",
"B",
"NB",
MinInfBound=0,
InfBoundStatus="Fixed",
DistInfBoundStatus="Fixed")
_mixt_histo2 = ExtractData(mixt2)
_histo14 = ExtractHistogram(ExtractData(mixt2), "Component", 1)
_histo15 = ToHistogram(ExtractDistribution(mixt2, "Component", 1))
# estimation and selection of the number of components
meri1 = Histogram(get_shared_data("meri1.his"))
meri2 = Histogram(get_shared_data("meri2.his"))
meri3 = Histogram(get_shared_data("meri3.his"))
meri4 = Histogram(get_shared_data("meri4.his"))
meri5 = Histogram(get_shared_data("meri5.his"))
#mixt3 = Estimate(meri1, "MIXTURE", Distribution("B", 6, 7, 0.5), "B")
mixt3 = Estimate(meri1, "MIXTURE", "B", "B")
Plot(mixt3)
# NbComponent="Fixed" (default) / "Estimated"
# Penalty="AIC"/ "AICc" / "BIC" / "BICc" (default), option
# valide if NbComponent="Estimated"
meri = Merge(meri1, meri2, meri3, meri4, meri5)
mixt2 = Estimate(meri,
"MIXTURE",
"B",
"B",
"B",
"B",
NbComponent="Estimated",
Penalty="BIC")
Display(mixt2, Detail=2)
dist_mixt = ExtractDistribution(mixt2, "Mixture")
Plot(dist_mixt)
