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Description
File: https://nbviewer.jupyter.org/github/pymc-devs/pymc-examples/blob/main/examples/case_studies/log-gaussian-cox-process.ipynb
Reviewers: @ckrapu
Context
Known changes needed
Changes listed in this section should all be done at some point in order to get this
notebook to a "Best Practices" state. However, these are probably not enough!
Make sure to thoroughly review the notebook and search for other updates.
General updates
- use numpy Generator. See also https://numpy.org/doc/stable/reference/random/index.html?highlight=random%20sampling%20numpy%20random#quick-start
Changes for discussion
Changes listed in this section are up for discussion, these are ideas on how to improve
the notebook but may not have a clear implementation, or fix some know issue only partially.
ArviZ related
- Use xarray and
from_pymc3_predictions
to filter nans and slice/reduceintensity_samples
Notes
Exotic dependencies
None
Computing requirements
Model takes roughly 5 mins to sample.
Metadata
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Type
Projects
Status
Best practices (v3)