Write "Working with InferenceData" page
See original GitHub issueTell us about it
As part of the documentation revamp described in #1331. We should add a page explaining how to work with InferenceData
and show several common tasks. The guide should cover at least the following topics:
- Stacking dimensions (maybe even reshaping? reshaping is a bit crazy though), fancy chain/draw extraction methods from #1469
- Some grouping/aggregating of data: mean
- Get values and coordinates as arrays
- Slice inferenceData objects
Pending
- modifying, transforming and/or creating a variable within an InferenceData group or groups. See #641 for code examples that can be used for this
- how to combine/merge/extend multiple InferenceData objects
- Coordinate modification. Maybe something like #1461 (includes example code and explanation)
- …
Thoughts on implementation
Feel free to tackle parts of the issue instead of generating the whole section at once.
It is also probably a good idea to add a See also section at the bottom linking to other docs (i.e. pymc3 or pystan docs), blogs and other resources that use inferencedata. For example: https://docs.pymc.io/notebooks/multilevel_modeling.html
Issue Analytics
- State:
- Created 3 years ago
- Comments:19 (14 by maintainers)
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@OriolAbril Hi! I’m sorry for replying so late, I’m alright mentally and physically now so I’m free to get back to contributing!!! Um I think I’ll make a draft PR with very basic changes and whatever I feel might work, and from thereon you can suggest redirections or changes, does that sound good?
Following the documentation system in https://diataxis.fr/ (they just changed the url, but it’s the same content I linked to above), docs are not supposed to be all over the place but should be separate at least into 4 different pages.
InferenceData
docs are actually close to getting there, but we need to also make sure each page is clear on what is explained in them and has links to the other pages in case the info is not in that page but in another one (this last part is a bit of a disaster right now).A very quick summary of diataxis (from its own introduction page):
| Tutorials | How-to guides | Reference | Explanation – | – | – | – | – oriented to | learning | a goal | information | understanding must | allow the newcomer to get started | show how to solve a specific problem | describe the machinery | explain its form | a lesson | a series of steps | dry description | discursive explanation analogy | teaching a small child how to cook | a recipe in a cookery book | a reference encyclopaedia article | an article on culinary social history for
InferenceData
| Working with InferenceData page (in getting started section) | unclear, maybe some page in the user guide secion, maybe links to case studies in pymc/stan/… docs (i.e. radon or rugby examples) | InferenceData schema | XarrayforArviZ |the InferenceData schema is dry and is not a good resource to understand InferenceData: why it’s useful?, why is it needed?, what are it’s main (and super cool) features); but it should not be. It’s goal is to describe InferenceData in an encycopedic-like manner.