Skip to content
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

Use compact traceplot by default #3502

Merged
merged 2 commits into from May 31, 2019

Conversation

Projects
None yet
5 participants
@ColCarroll
Copy link
Member

commented May 30, 2019

Fixes #3489 .

This is backwards compatible, and will effect anyone running arviz master, returning to its previous behavior.

image

@twiecki twiecki merged commit 3fa26cf into pymc-devs:master May 31, 2019

2 checks passed

continuous-integration/travis-ci/pr The Travis CI build passed
Details
coverage/coveralls Coverage decreased (-0.03%) to 89.581%
Details
@twiecki

This comment has been minimized.

Copy link
Member

commented May 31, 2019

Thanks!

@junpenglao

This comment has been minimized.

Copy link
Member

commented May 31, 2019

Can we make a 3.71 release...?

@fonnesbeck

This comment has been minimized.

Copy link
Member

commented May 31, 2019

I'm not a huge fan of compact, TBH. You can't really see anything most of the time, which obviates the utility of the time series plots. Large numbers of variables (or large multivariates) should be displayed with plot_forest, as that's what it was designed for.

For example, I'd never want a new user to see a plot like the one above. It would be easy to mistake that for a failed MCMC run where there was no mixing, since the histograms look like point masses and the traces look like horizontal lines.

@ColCarroll

This comment has been minimized.

Copy link
Member Author

commented May 31, 2019

Any thoughts on something like pm.plot(trace), and just putting Best Practice Best Plots in there? I think @aloctavodia was thinking of doing something like this. Instructions for reading and interpreting could go in the docstring.

@twiecki

This comment has been minimized.

Copy link
Member

commented May 31, 2019

@fonnesbeck

This comment has been minimized.

Copy link
Member

commented May 31, 2019

Yes, I agree. I suppose we need to agree what best practices are. Maybe we can start a shared doc.

@aloctavodia

This comment has been minimized.

Copy link
Member

commented Jun 4, 2019

We asked a small grant to numfocus to write a educational material. We are at a lag phase at the moment, but I guess this project will start taking momentum in about a couple of weeks. Basically the idea is to create an online e-book with best practices (and a little bit of theory) of Exploratory analysis of Bayesian Models. Also we have been discussing the idea of adding "cheat sheets" or something like that as ArviZ's functions.

Sign up for free to join this conversation on GitHub. Already have an account? Sign in to comment
You can’t perform that action at this time.