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Have a list of basic operations that are guaranteed to be supported for all MatrixBase #105
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Yes, I strongly approve of having a clearly documented API that is consistent between the various MatrixBase classes! Thanks for pointing this out, Marc. Part of the task here seems like a question of where to enumerate this. In the docstrings of the MatrixBase class? Somewhere else? |
Yes, please! With a consistent API across subtypes. At the moment, |
Marc and I talked a couple days ago about some indexing issues where the capabilities of DenseMatrix greatly exceeded that of other matrix types because the underlying numpy arrays have a lot of features. It seems like this will be the case for many operations. |
To my mind, it's okay if one subtype has a fuller API than the others. I only mentioned |
I think we should distinguish between a fuller API and an inconsistent API. Fuller is fine but inconsistent is not. Does that seem reasonable? And like the title of this issue is saying, we should also identify the minimal API. Just wanted to summarize. I don't think this is disagreeing with any of the above posts. =) |
Going through old issues and found this one. This issue will be solved by #286. |
A cleanup would probably help us identify low-hanging fruits.
For instance, should we define
__matmul__
for all the classes? Should we define the more basic__mul__
and__rmul__
?I would also like to standardize all our
__repr__
methods so that a user knows quickly that these objects are coming from the same package.The text was updated successfully, but these errors were encountered: