Explain naming convention in sample_stats
See original GitHub issueThe section on sample stats group in InferenceData scheme is missing a description of the naming convention and what does every variable represents.
The bullet points should be extended with variables still missing and all explanations added/improved. After this is done, it may be interesting to have something like SUPPORTED_GROUPS
for sample stats variables.
Issue Analytics
- State:
- Created 4 years ago
- Comments:5 (5 by maintainers)
Top Results From Across the Web
Designing a Naming Convention - Boston University
Researchers often use structured guidelines known as file naming conventions to describe the content and date of the file. These conventions help you...
Read more >Naming convention (programming) - Wikipedia
In computer programming, a naming convention is a set of rules for choosing the character sequence to be used for identifiers which denote...
Read more >What is the naming convention for Landsat Collections Level ...
The Landsat Collection 1 Level-1 product identifier includes the Collection processing levels, processing date, collection number, and collection tier ...
Read more >A guide to common variable naming conventions
The standard naming conventions used in modern software development are as follows: Pascal case; camel case; snake case; kebab case. Pascal case.
Read more >Variable naming convention - IBM
Variables are tokens within the command statements that are to be replaced with actual values immediately before the statement is run.
Read more >
Top Related Medium Post
No results found
Top Related StackOverflow Question
No results found
Troubleshoot Live Code
Lightrun enables developers to add logs, metrics and snapshots to live code - no restarts or redeploys required.
Start Free
Top Related Reddit Thread
No results found
Top Related Hackernoon Post
No results found
Top Related Tweet
No results found
Top Related Dev.to Post
No results found
Top Related Hashnode Post
No results found
This is a good start! Good work, thanks
There are some things to be noted before starting: different libraries, different samplers and schema specification style.
First is to use ArviZ names, most will be the same, but some will differ (e.g.
model_logp -> lp
) it is currently not explained anywhere so you’ll have to readio_pymc3
andio_pystan
to check the name used in ArviZ and that the name convention is coherent (maybe some less used quantities keep different names depending on the original inference library).Then, ArviZ also has to account for the multiple samplers available (if you check the end of the page you linked you’ll see that Metropolis has some different sample_stats).
And finally, the schema specification should ideally be clear and concise, thus, I think we should only describe the variable, not explain how is is used/why is it useful (which should be explained in the educational material).
Thanks for the help!