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Add weight_predictions function #2147
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I think this is a fantastic idea. I always found
`pm.sample_posterior_predictive_w` awkward.
One check that I think we need is something ensuring all models have
identical observed data.
…On Sat, 29 Oct 2022, 15:04 Osvaldo A Martin, ***@***.***> wrote:
This function will take a list of idatas with posterior_predictive groups
and a list of model weights (computed using az.compare or something else)
and it will return a new inference data with a posterior_predictive group
composed of weighted samples from the input idatas.
@zaxtax <https://github.com/zaxtax> maybe we can focus on this and forgot
about pm.sample_posterior_predictive_w
- Follows official
<https://github.com/arviz-devs/arviz/blob/main/CONTRIBUTING.md#pull-request-checklist>
PR format
- Includes a sample plot to visually illustrate the changes (only for
plot-related functions)
- New features are properly documented (with an example if
appropriate)?
- Includes new or updated tests to cover the new feature
- Code style correct (follows pylint and black guidelines)
- Changes are listed in changelog
<https://github.com/arviz-devs/arviz/blob/main/CHANGELOG.md#v0xx-unreleased>
------------------------------
You can view, comment on, or merge this pull request online at:
#2147
Commit Summary
- b9a599b
<b9a599b>
add weight_predictions
File Changes
(1 file <https://github.com/arviz-devs/arviz/pull/2147/files>)
- *M* arviz/stats/stats.py
<https://github.com/arviz-devs/arviz/pull/2147/files#diff-f1da0a2c4f56d6fa32279f759e04b4b1057a1266dc36f94d22347e5111a03bdc>
(24)
Patch Links:
- https://github.com/arviz-devs/arviz/pull/2147.patch
- https://github.com/arviz-devs/arviz/pull/2147.diff
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Should we just remove sample_posterior_predictive_w or throw an error
pointing people to this function?
…On Sat, 29 Oct 2022, 16:16 Rob Zinkov, ***@***.***> wrote:
I think this is a fantastic idea. I always found
`pm.sample_posterior_predictive_w` awkward.
One check that I think we need is something ensuring all models have
identical observed data.
On Sat, 29 Oct 2022, 15:04 Osvaldo A Martin, ***@***.***>
wrote:
> This function will take a list of idatas with posterior_predictive
> groups and a list of model weights (computed using az.compare or
> something else) and it will return a new inference data with a
> posterior_predictive group composed of weighted samples from the input
> idatas.
>
> @zaxtax <https://github.com/zaxtax> maybe we can focus on this and
> forgot about pm.sample_posterior_predictive_w
>
> - Follows official
> <https://github.com/arviz-devs/arviz/blob/main/CONTRIBUTING.md#pull-request-checklist>
> PR format
> - Includes a sample plot to visually illustrate the changes (only for
> plot-related functions)
> - New features are properly documented (with an example if
> appropriate)?
> - Includes new or updated tests to cover the new feature
> - Code style correct (follows pylint and black guidelines)
> - Changes are listed in changelog
> <https://github.com/arviz-devs/arviz/blob/main/CHANGELOG.md#v0xx-unreleased>
>
> ------------------------------
> You can view, comment on, or merge this pull request online at:
>
> #2147
> Commit Summary
>
> - b9a599b
> <b9a599b>
> add weight_predictions
>
> File Changes
>
> (1 file <https://github.com/arviz-devs/arviz/pull/2147/files>)
>
> - *M* arviz/stats/stats.py
> <https://github.com/arviz-devs/arviz/pull/2147/files#diff-f1da0a2c4f56d6fa32279f759e04b4b1057a1266dc36f94d22347e5111a03bdc>
> (24)
>
> Patch Links:
>
> - https://github.com/arviz-devs/arviz/pull/2147.patch
> - https://github.com/arviz-devs/arviz/pull/2147.diff
>
> —
> Reply to this email directly, view it on GitHub
> <#2147>, or unsubscribe
> <https://github.com/notifications/unsubscribe-auth/AAACCUKXHQGE7MRCB3ZLM2DWFUOFVANCNFSM6AAAAAARRZAIRA>
> .
> You are receiving this because you were mentioned.Message ID:
> ***@***.***>
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glad you like it. yeah we are assuming a few things here, we should add some check. We may want to deprecate |
Codecov Report
@@ Coverage Diff @@
## main #2147 +/- ##
==========================================
- Coverage 90.70% 90.67% -0.03%
==========================================
Files 120 120
Lines 12647 12667 +20
==========================================
+ Hits 11471 11486 +15
- Misses 1176 1181 +5
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Couple of comments
ready for review or merge, depending on how benevolent you are feeling today |
|
Hi @oussamadhaoui, did you check that also for the future, it is usually the best idea to open a new issue ticket instead of adding comments to merged PRs. Check this guide |
This function will take a list of idatas with
posterior_predictive
groups and a list of model weights (computed usingaz.compare
or something else) and it will return a new inference data with aposterior_predictive
group composed of weighted samples from the input idatas.@zaxtax maybe we can focus on this and forgot about
pm.sample_posterior_predictive_w
📚 Documentation preview 📚: https://arviz--2147.org.readthedocs.build/en/2147/