Skip to content

Mention removal of ArviZ-delegated plotting and stats in release notes #4432

New issue

Have a question about this project? Sign up for a free GitHub account to open an issue and contact its maintainers and the community.

By clicking “Sign up for GitHub”, you agree to our terms of service and privacy statement. We’ll occasionally send you account related emails.

Already on GitHub? Sign in to your account

Merged
merged 2 commits into from
Jan 22, 2021
Merged
Changes from 1 commit
Commits
File filter

Filter by extension

Filter by extension

Conversations
Failed to load comments.
Loading
Jump to
Jump to file
Failed to load files.
Loading
Diff view
Diff view
1 change: 1 addition & 0 deletions RELEASE-NOTES.md
Original file line number Diff line number Diff line change
Expand Up @@ -14,6 +14,7 @@ This release breaks some APIs w.r.t. `3.10.0`. It also brings some dreadfully aw
- In `sample_prior_predictive` the `vars` kwarg was removed in favor of `var_names` (see [#4327](https://github.com/pymc-devs/pymc3/pull/4327)).
- Removed `theanof.set_theano_config` because it illegally changed Theano's internal state (see [#4329](https://github.com/pymc-devs/pymc3/pull/4329)).
- We now depend on `Theano-PyMC` version `1.1.0` exactly (see [#4405](https://github.com/pymc-devs/pymc3/pull/4405)). Major refactorings were done in `Theano-PyMC` 1.1.0. If you implement custom `Op`s or interact with Theano in any way yourself, make sure to read the [Theano-PyMC 1.1.0 release notes](https://github.com/pymc-devs/Theano-PyMC/releases/tag/rel-1.1.0).
- Many plotting and diagnostic functions that were just aliasing ArviZ functions were removed (see [4397](https://github.com/pymc-devs/pymc3/pull/4397/files#)). This includes `pm.summary`, `pm.traceplot`, `pm.ess` and many more!
Copy link
Member

Choose a reason for hiding this comment

The reason will be displayed to describe this comment to others. Learn more.

I would move this as the second (or even first) point because it's probably the most important one.


### New Features
- Option to set `check_bounds=False` when instantiating `pymc3.Model()`. This turns off bounds checks that ensure that input parameters of distributions are valid. For correctly specified models, this is unneccessary as all parameters get automatically transformed so that all values are valid. Turning this off should lead to faster sampling (see [#4377](https://github.com/pymc-devs/pymc3/pull/4377)).
Expand Down