JuliaDataCubes / JuliaDataCubes/YAXArrays.jl
Chunking changed for function over time axis
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Description
The following function seems to destroy the chunking of my data when it is used on a larger dataset.
It keeps the chunking, when it is applied on a small testset.
function cube_eemd(xout, xin)
# libeemd segfaults when using Float32 data
ind = .!ismissing.(xin)
ts = Float64.(collect(xin[ind]))
xout[ind] .= ceemdan(ts, 3)[:, end]
xout[.!ind] .=missing
end
function eemdfilter(cube)
indims = InDims("Time")
outdims = OutDims("Time")
efcube = mapCube(cube_eemd, cube, indims=indims, outdims=outdims, max_cache=1e8)
newcube = mapCube(copyto!, efcube, indims=InDims("Lon", "Lat"), outdims=OutDims("Lon", "Lat"), max_cache=1e8)
return newcube
end
This was reported as https://github.com/esa-esdl/ESDL.jl/issues/127.
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Research direction
Start by reproducing the larger-dataset case in the eemdfilter function, focusing on the two mapCube calls and the cube_eemd callback. Compare chunking before and after applying the function, and use the small test set as a baseline. Done means the function preserves chunking for larger datasets as well as small ones.
Written by the indexing model from the issue text.
Assessment
- Tech stack
- julia
- Domain
- data
- Issue type
- Bug
- Difficulty
- 4/5
- Estimated time
- 3-5 days
- Activity status
- Stale
- Clarity
- Needs clarification
- Newbie friendliness
- 35/100