[ot-users] Stored process of function results in Monte Carlo simulation

Luiz augusto da silva Florêncio luiz.engh at gmail.com
Mon Oct 9 16:41:47 CEST 2017


Hi all,

I am a new user of OpenTurns and I have two questions about how I can
handle  the results of a Python function in a Monte Carlo simulation
algorithm:

1) I would like to skip the stored process of a specific values calculated
from my OpenTurns Python Function or store a Null/None value in the
outputRandomVector. For example, if I have the script:

 class modelePYTHON(OpenTURNSPythonFunction):

    def __init__(self):
        OpenTURNSPythonFunction.__init__(self,4,1)
    def _exec(self,x):
        E = x[0]
        F = x[1]
        L = x[2]
        I = x[3]
        uy = (F*L*L*L)/(3*E*I)
        if uy <= 15.0:
            return[uy]
        else:
            # Here I face my problem
            return[None()]

deviation = NumericalMathFunction(modelePYTHON())

that possibility does not work, so how can I solve my problem?

2) Is it possible to transfrom the outputRandomVectors in a list of its
sample valuesand modify their values according to the propreties of list
from Python? ( delete a value, add new ones)

Thanks for your time,
Luiz Augusto.

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