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Make use of efficient Julia sparse outer products #4

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jmert opened this issue Dec 8, 2017 · 0 comments · Fixed by #28
Closed

Make use of efficient Julia sparse outer products #4

jmert opened this issue Dec 8, 2017 · 0 comments · Fixed by #28

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@jmert
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jmert commented Dec 8, 2017

Currently I have some non-general code for computing outer products of sparse vectors, but the functionality should really exist in Julia itself. I've opened JuliaLang/julia#24980 to work on this.

If[/when] accepted, the functionality should be copied/backported as a version-limited code block here to support the necessary computations even on julia v0.6.

jmert added a commit that referenced this issue Jul 8, 2020
The feature was added to Julia in time for v1.2 in JuliaLang/julia#24980,
so get rid of the custom `outer()` method here and rewrite `quadprod()`
in terms of just standard matrix methods. Julia v1.2 is the
minimum-supported version at this point, so no need to worry about
backporting the functionality.

In the future, this function may yet still go away since the
implementation is nearly trivial at this point, but that can be a
follow-up PR.
jmert added a commit that referenced this issue Jul 8, 2020
The feature was added to Julia in time for v1.2 in JuliaLang/julia#24980,
so get rid of the custom `outer()` method here and rewrite `quadprod()`
in terms of just standard matrix methods. Julia v1.2 is the
minimum-supported version at this point, so no need to worry about
backporting the functionality.

In the future, this function may yet still go away since the
implementation is nearly trivial at this point, but that can be a
follow-up PR.
@jmert jmert closed this as completed in #28 Jul 8, 2020
jmert added a commit that referenced this issue Jul 8, 2020
The feature was added to Julia in time for v1.2 in JuliaLang/julia#24980,
so get rid of the custom `outer()` method here and rewrite `quadprod()`
in terms of just standard matrix methods. Julia v1.2 is the
minimum-supported version at this point, so no need to worry about
backporting the functionality.

In the future, this function may yet still go away since the
implementation is nearly trivial at this point, but that can be a
follow-up PR.
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