Comments (2)
Alternatively, we can use the datasets packaged with ArviZ to showcase the plots in a quickstart. From there, we can link to individual notebooks in an examples
folder for Turing, CmdStan, and Soss. This way we can avoid some of the compatibility clashes that sometimes arise between these packages.
I'll write the examples so that I can use Literate.jl to turn them into either notebooks or markdown, but this will still be done locally and periodically updated instead of using CI.
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Closing in favor of building the docs on Azure (#48), which can handle long builds.
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Related Issues (20)
- Better reproducibility wrapping Python ArviZ HOT 4
- ArviZ fails to load when scipy.fft is imported HOT 3
- Add required_groups argument to convert_to_inference_data
- Removing MonteCarloMeasurements support HOT 2
- Removing bokeh plotting backend
- Documenting InferenceData usage HOT 1
- Quickstart page build failing HOT 1
- Cannot load package HOT 8
- Separating InferenceData and Dataset into their own package HOT 12
- Supporting more MCMCChains variable names
- Move InferenceData examples to own repo HOT 1
- Using MultiDocumenter HOT 1
- Converting directly from StanSample
- Moving converters to other packages HOT 2
- Installing ArviZ.jl in a new environment results in arviz version error (0.13.0 or greater but found version 0.12.1) HOT 3
- Precompilation failed HOT 2
- Move converters to extensions
- Adding docs page on package structure
- Docs build broken on Julia v1.10 HOT 1
- `from_cmdstan` HOT 7
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