Load no-time vars as numpy arrays in to_windowed_arrays#2752
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erikvansebille wants to merge 4 commits into
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Load no-time vars as numpy arrays in to_windowed_arrays#2752erikvansebille wants to merge 4 commits into
erikvansebille wants to merge 4 commits into
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To show which fields are WindowedArrays, which are Dask and which are NumPy
erikvansebille
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Jul 15, 2026
| | V_wind | Field | 1 | XLinear(...) | | ||
| | UV_wind | VectorField | 1 | XLinear_Velocity(...) | | ||
| | constant_field | Field | 2 | XConstantField(...) | | ||
| | Name | Type | Grid number | Interp method / value | Backend | |
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@VeckoTheGecko, what do you think of the name of this extra column? Is "Backend" indeed the best term to use?
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I think 'Parcels backend' would be better as to not conflate with xarrays use of the word
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Description
This PR fixes #2751, by calling a
.compute()on variables that have amockTdimension (i.e. no time), thereby speeding up thefieldset.to_windowed_arrays()method.It also loads
lonandlatexplicitly, which are not dimensions but variables in a curvilinear grid.Finally, it adds information about rhetorical backend (Numpy, Dask or WindowedArray) to each field in
fieldset.describe()Checklist
mainfor normal development,v3-supportfor v3 support)AI Disclosure
None