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Currently random functions work returning a float
dim1: A,B,C~~| var[dim1] = RANDOM UNIFORM(1,3) ~~|
returns a length 3 vector with different random numbers, however this is translated in PySD as:
@(["dim1"], _subscript_dict) def var(): return np.random.uniform(1, 3)
which will produce a unique random value and repeat it to generate a vector.
This should be done as:
@(["dim1"], _subscript_dict) def var(): return xr.DataArray(np.random.uniform(1, 3, size=(3,)), {"dim1": ["A", "B", "C"]}, ["dim1"])
I am working on it for a future release.
The text was updated successfully, but these errors were encountered:
enekomartinmartinez
Successfully merging a pull request may close this issue.
Currently random functions work returning a float
returns a length 3 vector with different random numbers, however this is translated in PySD as:
which will produce a unique random value and repeat it to generate a vector.
This should be done as:
I am working on it for a future release.
The text was updated successfully, but these errors were encountered: