Comments (10)
Have you a status here @paul-buerkner ?
from posteriordb.
Oh, for some reasons, I overlooked I was assigned for it. Sorry, I didn't take any further look at this.
Do you have a proposal for how to do it already? Otherwise, I will think about it a little bit more today.
from posteriordb.
Not really. I think this defines a little how we would access/filter in the databases so maybe have ashort discussion on it. I could also do the work, but the API need some thinking.
from posteriordb.
I agree. Let's think of this a little bit more and then have a discussion to make some decisions about this, maybe thursday or friday?
from posteriordb.
from posteriordb.
Sounds good.
from posteriordb.
Summary of discussion:
We implement the filter function based on the dplyr filter function, essentially using the same framework. The API will be:
pos <- pdb_filter_posterior(.pdb, ...)
ms <- pdb_filter_models(.pdb, ...)
ds <- pdb_filter_data(.pdb, ...)
Here ... is filtering syntax according to the dplyr filter function:
https://dplyr.tidyverse.org/reference/filter.html
This would mean that we would implement this as three steps:
- create a pdb_posteriors_df() function to create a posterior/model/data tibble for all elements in the posterior database. Here we expand all keyterms.
- Use dplyr::filter() to select from the tibble.
- Return posteriors as read posterior objects.
from posteriordb.
Lovely, I am very happy with this interface. One minor comment. You use posterior
in singular and models
in plural. Does your plan to have singular/plural aliases still apply or shall we settle for just one of them?
from posteriordb.
Good point. I think using both would be reasonable (using alias).
from posteriordb.
I'm not familiar with dplyr syntax, can you show me how these queries should be written?
-
Find all posteriors where the model was added by Måns.
My attempt
ms <- pdb_filter_models(.pdb, added_by == "Mans Magnusson") posteriors <- ??
-
Find all posteriors where the model has keyword
bda3_example
. -
Same as 2. but only find posteriors that have a gold standard.
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Related Issues (20)
- Example problems from astrophysics HOT 5
- Transferring to stan-dev HOT 1
- Updating Stan Models to be more performant HOT 3
- Convert golden samples to arviz IData HOT 3
- Add model code dependency structure
- Document data variables separately
- Handling of posterior licenses HOT 11
- Include explicit stan version in reference posterior computations
- install instructions for R package HOT 4
- Add eight schools with flat prior
- Add the occupancy model (population biology)
- Better examples needed HOT 5
- How to get the log probabilities of MCMC samples
- dogs-dogs not constrained properly in Stan HOT 1
- PyMC3 eight school example HOT 5
- Missing reference posteriors HOT 2
- Make a new release? HOT 3
- Change Stan syntax to new syntax HOT 6
- Proposal: Add `data-used` to posterior `.json` files where relevant
- Discussion: Correctness Checking Between PPLs
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