openturns / otmixmod Goto Github PK

import otmixmod 

def otmixmod_GetValidCovarianceModels():
    listOfValidModels = [
        "Gaussian_p_L_I",
        "Gaussian_p_Lk_I",
        "Gaussian_p_L_B",
        "Gaussian_p_Lk_B",
        "Gaussian_p_L_Bk",
        "Gaussian_p_Lk_Bk",
        "Gaussian_p_L_C",
        "Gaussian_p_Lk_C",
        "Gaussian_p_L_D_Ak_D",
        "Gaussian_p_Lk_D_Ak_D",
        "Gaussian_p_L_Dk_A_Dk",
        "Gaussian_p_Lk_Dk_A_Dk",
        "Gaussian_p_L_Ck",
        "Gaussian_p_Lk_Ck",
        "Gaussian_pk_L_I",
        "Gaussian_pk_Lk_I",
        "Gaussian_pk_L_B",
        "Gaussian_pk_Lk_B",
        "Gaussian_pk_L_Bk",
        "Gaussian_pk_Lk_Bk",
        "Gaussian_pk_L_C",
        "Gaussian_pk_Lk_C",
        "Gaussian_pk_L_D_Ak_D",
        "Gaussian_pk_Lk_D_Ak_D",
        "Gaussian_pk_L_Dk_A_Dk",
        "Gaussian_pk_Lk_Dk_A_Dk",
        "Gaussian_pk_L_Ck",
        "Gaussian_pk_Lk_Ck"
    ]
    return listOfValidModels


# %%
listOfValidModels = otmixmod_GetValidCovarianceModels()
numberOfClasses = 2
for covarianceModel in listOfValidModels:
    factory = otmixmod.MixtureFactory(numberOfClasses, covarianceModel)
    print(f"Build with covariance model = {covarianceModel}")
    mixture, labels, logLikelihood = factory.buildAsMixture(sample)

# %%
import openturns as ot
import otmixmod

# %%
print(ot.__version__)
print(otmixmod.__version__)

# %%
ot.RandomGenerator.SetSeed(0)


# %%
def generateData(sampleSize):
    # Gaussian 1
    mu1 = ot.Point([-2.0, 2.0])
    sigma1 = ot.Point(2, 1.0)
    correlation1 = ot.CorrelationMatrix(2)
    correlation1[0, 1] = 0.2
    gaussian1 = ot.Normal(mu1, sigma1, correlation1)

    # Gaussian 2
    mu2 = ot.Point([2.0, -2.0])
    sigma2 = ot.Point(2, 0.5)
    correlation2 = ot.CorrelationMatrix(2)
    correlation2[0, 1] = -0.5
    gaussian2 = ot.Normal(mu2, sigma2, correlation2)

    # Mixture
    w1 = 1.0 / 3.0
    w2 = 1.0 - w1
    mixture = ot.Mixture([gaussian1, gaussian2], [w1, w2])
    #
    sample = mixture.getSample(sampleSize)
    return mixture, sample


# %%
sampleSize = 200
mixture, sample = generateData(sampleSize)
print("True mixture:")
print(mixture)

# %%
listOfValidModels = [
        "Gaussian_p_L_I"
        "Gaussian_p_Lk_I"
    ]
numberOfClasses = 2

# %%
for covarianceModel in listOfValidModels:
    factory = otmixmod.MixtureFactory(numberOfClasses, covarianceModel)
    print(f"Build with covariance model = {covarianceModel}")
    mixture, labels, logLikelihood = factory.buildAsMixture(sample)
    print(mixture)