Typechecks

[JCSyng]

Thank you for this wonderful package and your efforts!

For future users, would it be possible to add type-checks and more verbose error statements to the fit func of the MERF class when the input type deviates from the expected input type? This led to a bit of reverse engineering to figure out why the underlying linear alg was failing when, for example, inputting a NUMPY array in place of an expected pandas series.

(Also happy to contribute...when I have the time).

Thanks!

[resdntalien]

@JCSyng Sounds great! Yeah, this is definitely still more "lab code". And I was thinking of refactoring that entire section to take in a validation set as well -- since that seems to be the best way to determine how many MERF iterations to run. Also, adding divergence checks.

[resdntalien]

Where exactly were you having the issue @JCSyng? I have some time now, and I want to make sure that this code works for both numpy and pandas inputs.

[DrewDevereux]

I have hit (and worked around) this issue. The x, y and z inputs can be ndarrays, but the cluster parameter must be a pandas.Series. If you pass an ndarray, you get the error "AttributeError: 'numpy.ndarray' object has no attribute 'nunique'"; and if you pass a pandas.DataFrame, you get "AttributeError: 'DataFrame' object has no attribute 'value_counts'".