allow for N-d output

[basnijholt]

(original issue on GitLab)

opened by Jorn Hoofwijk (@Jorn) at 2018-07-08T16:33:53.401Z

currently supports $R^N \mapsto R$, but we want support for $R^N \mapsto R^M$

should be easy

[basnijholt]

originally posted by Jorn Hoofwijk (@Jorn) at 2018-07-13T08:30:34.936Z on GitLab

Added support in: https://gitlab.kwant-project.org/qt/adaptive/compare/f7fd43ad232da2d371e8e01427a7b1d373ed0938...83362f0ed88b7ef4e472a97e7c4df87fa8b8d56b

However, we accept a tuple as output and also the loss is computed to take all output dimensions into account, yet plotting is not supported, so this issue can be closed as soon as we have some kind of interface to plot the output (i.e. pass a parameter with the index of the dimension you want to plot.

sneak preview: LearnerND_2d_to_2d.py
(I run this from a terminal, I don't think it runs from a jupyter notebook)

[basnijholt]

originally posted by Bas Nijholt (@basnijholt) at 2018-07-18T17:15:26.603Z on GitLab

So this can be closed?

Do we have a test for the vectorized output?

[basnijholt]

originally posted by Bas Nijholt (@basnijholt) at 2018-12-07T19:16:52.673Z on GitLab

This has been implemented for quite a while now.