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import openturns as ot
import otfmi
import os

# Define probabilistic model.
E = ot.Beta(0.93, 3.2, 2.8e7, 4.8e7)
Fparam = ot.LogNormalMuSigma(3.0e4, 9000.0, 15000.0)
F = ot.ParametrizedDistribution(Fparam)
L = ot.Uniform(250.0, 260.0)
I = ot.Beta(2.5, 4.0, 310.0, 450.0)

# Create the Spearman correlation matrix of the input random vector
RS = ot.CorrelationMatrix(4)
RS[2,3] = -0.2

# Evaluate the correlation matrix of the Normal copula from RS
R = ot.NormalCopula.GetCorrelationFromSpearmanCorrelation(RS)

# Create the Normal copula parametrized by R
mycopula = ot.NormalCopula(R)

# Create the input probability distribution of dimension 4
inputDistribution = ot.ComposedDistribution([E, F, L, I], mycopula)

# Give a description of each component of the input distribution
inputDistribution.setDescription( ("E", "F", "L", "I") )

# Create the input random vector
inputRandomVector = ot.RandomVector(inputDistribution)

# FMU model
path = os.path.dirname(os.path.abspath(__file__))
path_fmu = os.path.join(path,"deviationpoutre-win64.fmu")

model_fmu = otfmi.FMUFunction(path_fmu, inputs_fmu=["E", "F", "L", "I"], outputs_fmu="y")

# One single point
X = inputDistribution.getMean()
print(X)
Y = model_fmu(X)
print(Y)

# Simple Monte-Carlo sampling
size = 10
sampleX = inputRandomVector.getSample(size)
print(sampleX)
sampleY = model_fmu(sampleX)
print(sampleY)

TypeError: InvalidArgumentException : Output value for OpenTURNSFMUFunction._exec_sample() method is not a 2d-sequence object

([array([15.76007131])], [array([12.98466089])], [array([18.23594914])], [array([7.42586189])], [array([12.31297981])], [array([13.38886067])], [array([24.85640079])], [array([12.18491227])], [array([9.01482853])], [array([13.38254173])])

        output = pool.run(list_kwargs, final=self.__final)
        dataOutput = [x[0] for x in output]
        return dataOutput