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When I try to use the ConditionalModel class, I get TypeError: __init__() missing 2 required positional arguments: 'features' and 'samplespace' from the call super(ConditionalModel, self).__init__() in ConditonalModel.__init__().
If I comment out the call to super, then the fit function fails because model is not defined. Not sure if these things are directly related, or if this is a separate issue.
The text was updated successfully, but these errors were encountered:
Update: I just realized there is an examples_scipy directory that shows the conditional examples are broken. I had only looked through the notebooks when I created the issue. Is there a current effort to get the conditional versions fixed or will it likely be a while?
Thanks for opening this issue, it does look like something has broke here in the process of refactoring since the super call here is not passing over the needed arguments. The features seems easy enough to forward on but I'm not as sure about the samplespace otherwise I'd have opened a PR to fix this
I think this is probably related to #5.
When I try to use the
ConditionalModel
class, I getTypeError: __init__() missing 2 required positional arguments: 'features' and 'samplespace'
from the callsuper(ConditionalModel, self).__init__()
inConditonalModel.__init__()
.Is this due to a current round of refactoring? Should it be necessary to pass feature functions and sample space in to
ConditionalModel
? It looks like it wasn't always necessary (e.g. this old python 2 example https://github.com/stefanv/scipy3/blob/master/scipy/maxentropy/examples/conditionalexample2.py).If I comment out the call to
super
, then thefit
function fails becausemodel
is not defined. Not sure if these things are directly related, or if this is a separate issue.The text was updated successfully, but these errors were encountered: