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Clarify or check Estimator input shapes #37
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The intended usage pattern for The main reason for not adding a validation/reshaping method is that it seems to me to fall into a kind of no-man's land in between the convenience of the |
Then it sounds like dropping Are Datasets going to still be the preferred inputs for vectorized calls (e.g., neurostuff/NiMARE#211)? |
Oh, but note also that there's an |
It's probably worth doing a bit of profiling to see how much overhead the |
I was trying to run one of the Estimators using
weighted_least_squares
without initializing a Dataset and was getting confusing errors fromnumpy.einsum
before I realized that inputs need to be 2D no matter what. We can coerce 1D inputs to 2D with a newEstimator._validate_inputs()
method, or we can just update the docstrings to clarify requirements.BTW, based on variable convention, I think it's reasonable to assume that
X
must be 2D, but it's not obvious thaty
,v
, etc. should be 2D as well, and indeed, there's an obvious error about shape ifX
is 1D, but no shape check fory
,v
, etc.To replicate:
Results in:
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