JuliaDataCubes / JuliaDataCubes/YAXArrays.jl
make interface for aggregate_diskarray and interpolate_diskarray from DiskArrayEngine
Nobody has claimed this yet.
- Dominant language
- Julia
- Stars
- 132
- Forks
- 25
- PR merge metrics
- No merged PRs in 30d
Description
We want to have a high level interface for aggregate_diskarray and interpolate_diskarray from DiskArrayEngine.
- monthly mean example:
aggregate_diskarray(a, mean, :time => yearmonth) - make a nicer name than aggregate_diskarray
- quarter degree to one degree: `aggregate_diskarray(a, mean, :lon=>4, :lat => 4)
- one grid to another: aggregate_diskarray(a, mean, target_grid)
Similar for interpolate_diskarrays
- interpolate_diskarrays(a, target_dims=DimTuple, method=Nearest())
These functions should use the diskarrayEngine functions for the data and recompute the dimensions to then wrap everything into a new YAXArray or maybe even make it work for AbstractDimArray.
rebuild(a, data=aggdata, dims=aggdims)
Contributor guide
No contributing guide indexed for this repository
First steps
- Read the whole issue, then the project's contributing guide.
- Comment on the issue to say you are picking it up — it saves two people doing the same work.
- Fork the repository and make your change on a branch.
- Open a pull request that references the issue number.
Research direction
Start by reading the DiskArrayEngine functions aggregate_diskarray and interpolate_diskarrays, then inspect how rebuild wraps data and dimensions. Define the high-level aggregation and interpolation interface, including dimension recomputation and wrapping in a YAXArray or AbstractDimArray; done means the monthly, spatial, grid, and target-dimension examples work.
Written by the indexing model from the issue text.
Assessment
- Tech stack
- julia
- Domain
- data
- Issue type
- Feature
- Difficulty
- 5/5
- Estimated time
- Over a week
- Activity status
- Quiet
- Clarity
- Mostly clear
- Newbie friendliness
- 38/100