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Unfortunately the "compute Covariance" does not work.... it returns all NaN... I had to input the diagonal covariance by hand.
RavenRunningRaven does not work as well because the output of the inner is not interpreted as an HistorySet but as pointSet (no matter what I do in the outer dataobject). I had to use the GenericCode interface for the inner
The node if does not have the simply silently "skips" the reduction (Without informing the user)
If the is inputted and == 0 (optimal rank should be computed atuomatically) the reduction is skipped because this line "if self._subspace is None and self._truncationRank:" is evaluated as False (since if "self._truncationRank is 0.0 and it is False)...It should be modified to "if self._subspace is None and self._truncationRank is not None"
If the is set to > 1 the code just crashes after the first evaluation.
It would be nice to have the possibility to provide the values as CSV (or RAVEN data object) and maybe also to associate a pivot parameter to them (so the underlying model can be run in parallel (e.g. the inner RAVEN that runs relap5 for each experiement). Now I am forced to have the inner to run in serial to keep the right order of values (mapping with the values in )
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The text was updated successfully, but these errors were encountered: