fix: integrate field coords and object arrays for changing field shapes #34
Add this suggestion to a batch that can be applied as a single commit.
This suggestion is invalid because no changes were made to the code.
Suggestions cannot be applied while the pull request is closed.
Suggestions cannot be applied while viewing a subset of changes.
Only one suggestion per line can be applied in a batch.
Add this suggestion to a batch that can be applied as a single commit.
Applying suggestions on deleted lines is not supported.
You must change the existing code in this line in order to create a valid suggestion.
Outdated suggestions cannot be applied.
This suggestion has been applied or marked resolved.
Suggestions cannot be applied from pending reviews.
Suggestions cannot be applied on multi-line comments.
Suggestions cannot be applied while the pull request is queued to merge.
Suggestion cannot be applied right now. Please check back later.
fixes #31, fixes #32, fixes #33
Proposed Changes
System
andComponent
predict functions handle the special{{ var }}_coords
variables -- which are the field coordinates returned by a model associated with the{{ var }}
field quantity.Component.call_model
as numpy object arrays, where each element is the field quantity itself for a given input sample. This allows variable shapes/sizes for field quantities between inputs to be stored in the same data structure.Compression
now handles interpolation to/from grids where field coordinates and values are passed as object arrays. This assumes 1d object arrays, and will only loop over the first axis when interpolating.[ list ]
in yaml for scalars, which will get converted to tuples internally as long as the length of the list is exactly equal to 2.YamlLoader
will now fail if it can't find the specified yaml file. It will try to load from a path; if this fails, then it will try to load from a stream directly.