If no seed is given when initialising the Midas object, then no seed is passed to Midas.train_model() and so the variable train_rng is left unassigned (line 748) and this creates an error on line on 759 when a value for train_rng is expected.
I suspect this same issue will arise in other areas where if self.seed is not None: is used without a corresponding else statement (e.g. line 1184 in Midas.over_impute()).
I suspect this can be fixed by simply adding an else statement which generates a random seed and uses this to assign a value to train_rng
If no seed is given when initialising the Midas object, then no seed is passed to Midas.train_model() and so the variable
train_rng
is left unassigned (line 748) and this creates an error on line on 759 when a value fortrain_rng
is expected.I suspect this same issue will arise in other areas where
if self.seed is not None:
is used without a correspondingelse
statement (e.g. line 1184 in Midas.over_impute()).I suspect this can be fixed by simply adding an
else
statement which generates a random seed and uses this to assign a value totrain_rng
Interpreter settings: Python 3.9
numpy~=1.22.1 pandas~=1.3.5
scipy==1.8.0 matplotlib~=3.5.1 scikit-learn~=1.0.1 tensorflow==2.8.0 keras~=2.6.0 graphviz~=0.19 MIDASpy~=1.2.1 statsmodels~=0.13.2