Is it possible to define a parametric probabilistic model

Persalys usage
1

Hi to the Persalys team,

I wonder if there is a way to define parametrics data in the probabilistic model window ?

Indeed, when I create a variable with the associated probabilistic law (normal for example), I can only define law characteristics with “numbers” (numericals values).

I would like to define this law characteristics by anothers parameters.

For example, define a normal variable “X” with parameters :

  • mean “Xmean”

  • standard deviation “Xstd”

This model definition make it possible to define the law charateristics in an input file for example. Or to define law characteristics with a more complexe formulation [Xmean = (a + b) **c]

Besides, the parameters “Xmean” and “Xstd” could be define by anothers probabilistics law. For example :

  • “Xmean” has a mean “Xmeanmean” and standard deviation “Xmeanstd”

  • “Xstd” has a mean “Xstdmean” and standard deviation “Xstdstd”

(Data given with bootstrap approach for example)

Thanks you

Laurent

2

Hello,

Unfortunately it is not possible to do that, as it was in Phimecasoft I imagined you think. I think the only possibility is to do the math before or try directly in the Python model to create the final X random realization.

Regards,
Antoine

3

Hi Antoine,

Ok, thanks you.
Yes, this is a way to define variables in PhimecaSoft… Variables I would like to transpose in Persalys.

Indeed, a solution I found is to generate a random realization with a fortran code just before to create my input program (coupling model) with a fortran code too. This sequence is driven by a shell code in an upper level. Persalys generate the others variables.

I tried to make a python model but I found it difficult to write the python code and to make the link with my coupling program… for now !

Laurent