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#! /usr/bin/env python
import openturns as ot
ot.TESTPREAMBLE()
ot.ResourceMap.SetAsUnsignedInteger("RandomMixture-DefaultMaxSize", 4000000)
ot.TTY.ShowColors(False)
# Test fusion of Dirac with no other atoms: should be a unique Dirac(5.8)
d = ot.RandomMixture(
[ot.Dirac(1.0), ot.Dirac(2.0), ot.Dirac(3.0)], [0.5, 0.6, 0.7], 2.0
)
print("d=", d)
# Test fusion of Dirac with other atoms: the Dirac should be merged into
# the constant: 5 + Exponential(lambda=1,gamma=0)
d = ot.RandomMixture([ot.Dirac(1.0), ot.Dirac(2.0), ot.Exponential()], 2.0)
print("d=", d)
# Test flatten RandomMixture atoms: the RandomMixture should have 4 atoms.
d = ot.RandomMixture(
[
ot.Gumbel(),
ot.RandomMixture([ot.Logistic(), ot.WeibullMin()], [0.5, 1.5], 3.0),
ot.Frechet(1.0, 4.0),
],
[2.0, 3.0, 4.0],
2.0,
)
print("d=", d)
# Test merge of Normal atoms:
d = ot.RandomMixture(
[ot.Normal(1.0, 8.0), ot.Logistic(), ot.Normal(2.0, 1.0)], [0.5, 2.5, 3.0], 2.0
)
print("d=", d)
# Test merge of Exponential, Gamma and ChiSquare atoms
d = ot.RandomMixture(
[
ot.Exponential(1.0, 1.0),
ot.Exponential(1.5, -1.0),
ot.Exponential(2.0, 1.0),
ot.Gamma(4.0, 2.0, -1.0),
ot.Gamma(3.0, 1.0, 3.0),
ot.ChiSquare(4.0),
],
[1.0, 1.5, 1.0, 2.0, 2.0, 0.5],
2.0,
)
print("d=", d)
# Test merge of Uniform atoms
d = ot.RandomMixture(
[
ot.Uniform(0.0, 1.0),
ot.Uniform(0.0, 1.0),
ot.Uniform(1.0, 3.0),
ot.Uniform(-1.0, 4.0),
ot.Uniform(2.0, 3.0),
],
[1.0, 1.0, 2.0, 3.0, 4.0],
2.0,
)
print("d=", d)
# Test merge of Bernoulli and Binomial atoms
# Deactivate the fusion of discrete atoms
ot.ResourceMap.SetAsUnsignedInteger("RandomMixture-MaximumSupportSize", 0)
d = ot.RandomMixture(
[
ot.Bernoulli(0.5),
ot.Bernoulli(0.5),
ot.Bernoulli(0.1),
ot.Binomial(4, 0.5),
ot.Binomial(6, 0.5),
ot.Binomial(3, 0.1),
],
[1.0, 1.5, 2.0, 1.0, 4.0, 2.0],
2.0,
)
print("d=", d)
# Test merge of Poisson atoms
# Deactivate the fusion of discrete atoms
ot.ResourceMap.SetAsUnsignedInteger("RandomMixture-MaximumSupportSize", 0)
d = ot.RandomMixture(
[
ot.Poisson(3.0),
ot.Poisson(2.0),
ot.Poisson(6.0),
ot.Poisson(10.0),
ot.Poisson(4.0),
],
[1.0, 2.0, 3.0, 2.0, 1.0],
2.0,
)
print("d=", d)
# Test merge of discrete and continuous atoms
# Deactivate the fusion of discrete atoms
ot.ResourceMap.SetAsUnsignedInteger("RandomMixture-MaximumSupportSize", 0)
# more continuous atoms
d = ot.RandomMixture(
[ot.Logistic(), ot.Binomial(2, 0.5), ot.Uniform()], [1.0, 2.0, 3.0], 2.0
)
print("d=", d)
# more discrete atoms
d = ot.RandomMixture(
[ot.Bernoulli(0.1), ot.Binomial(2, 0.5), ot.Uniform()], [1.0, 2.0, 3.0], 2.0
)
print("d=", d)
# same number of continuous and discrete atoms
d = ot.RandomMixture(
[ot.Logistic(), ot.Bernoulli(0.1), ot.Binomial(2, 0.5), ot.Uniform()],
[1.0, 2.0, 3.0, 4.0],
2.0,
)
print("d=", d)
# Test the fusion of discrete atoms
ot.Log.Show(ot.Log.DBG)
print("\n")
# All the atoms have a too large support
ot.ResourceMap.SetAsUnsignedInteger("RandomMixture-MaximumSupportSize", 1)
d = ot.RandomMixture(
[ot.Binomial(2, 0.1), ot.Binomial(3, 0.5), ot.Poisson(), ot.Geometric()],
[1.0, 2.0, 3.0, 4.0],
2.0,
)
print("d=", d)
print("\n")
# Some atoms have a too large support, no pending aggregated discrete
ot.ResourceMap.SetAsUnsignedInteger("RandomMixture-MaximumSupportSize", 15)
d = ot.RandomMixture(
[ot.Binomial(2, 0.1), ot.Binomial(3, 0.5), ot.Poisson(), ot.Geometric()],
[1.0, 2.0, 3.0, 4.0],
2.0,
)
print("d=", d)
print("\n")
# Some atoms have a too large support, a pending aggregated discrete
ot.ResourceMap.SetAsUnsignedInteger("RandomMixture-MaximumSupportSize", 15)
d = ot.RandomMixture(
[
ot.Binomial(2, 0.1),
ot.Binomial(3, 0.5),
ot.Poisson(),
ot.Binomial(2, 0.1),
ot.Binomial(3, 0.5),
],
[1.0, 2.0, 3.0, 4.0, 5.0],
2.0,
)
print("d=", d)
print("\n")
# All the atoms can be merged
ot.ResourceMap.SetAsUnsignedInteger("RandomMixture-MaximumSupportSize", 100)
d = ot.RandomMixture(
[ot.Bernoulli(0.1), ot.Bernoulli(0.2), ot.Bernoulli(0.3), ot.Bernoulli(0.4)],
[1.0, 2.0, 3.0, 4.0],
2.0,
)
print("d=", d)
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