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Make use of __binary_op for two tensor binary high-level functions #379

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Markus-Goetz opened this issue Sep 13, 2019 · 2 comments
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enhancement New feature or request good first issue Good for newcomers

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@Markus-Goetz
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Might require issue #167 to be implemented first and potentially #377.

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Make use of the __binary_op for higher-level broadcastable binary operations, such as minimum(), where(), outer(), ... The logic for resplitting DNDarrays should already be present in __binary_op (or should eventually be there). It would be redundant and redundant to have them yet again in each of these high-level calls.

Individual calls might make it necessary to copy some parts of the behaviour. If so, think about how to split up __binary_op so that the code duplication is minimal.

@Markus-Goetz Markus-Goetz added enhancement New feature or request good first issue Good for newcomers high-level functions High-level machine-learning algorithms labels Sep 13, 2019
@ClaudiaComito ClaudiaComito mentioned this issue Sep 1, 2020
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@ClaudiaComito ClaudiaComito removed the high-level functions High-level machine-learning algorithms label Apr 1, 2022
@ClaudiaComito ClaudiaComito added this to the Repo Clean-Up milestone Jul 31, 2023
@ClaudiaComito
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This issue has been partially addressed (#662).

Breaking up __binary_op() in two (separating __binary_checks() ?) would indeed be helpful for many operations, so I'm leaving this issue open.


Reviewed within #1109

@ClaudiaComito ClaudiaComito removed this from the Repo Clean-Up milestone Aug 4, 2023
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Adding logical.isclose #458 , logical.allclose to this list

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