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Add a subsection detailing what to do if you use dask + Iris for parallel file load and encounter merge conflicts when you try and merge the cubes.
For example:
files = glob.glob(iris.sample_data_path('GloSea4', '*.pp')) cb = db.from_sequence(files).map(iris.load_cube) dmc = delayed(lambda cubes: iris.cube.CubeList(cubes).merge_cube())(cb) dmc.compute() MergeError Traceback (most recent call last) ... MergeError: failed to merge into a single cube. Coordinates in cube.aux_coords (scalar) differ: realization. Coordinates in cube.aux_coords (non-scalar) differ: forecast_period.
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Add a subsection detailing what to do if you use dask + Iris for parallel file load and encounter merge conflicts when you try and merge the cubes.
For example:
The text was updated successfully, but these errors were encountered: