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Remove obsolete write_netcdf option from ncl diagnostic scripts #2387

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merged 1 commit into from Oct 28, 2021

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zklaus
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@zklaus zklaus commented Oct 28, 2021

Description

This addresses the write_netcdf part of #2005 for NCL diagnostics.


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New or updated recipe/diagnostic


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Looks good!

@zklaus zklaus merged commit d8847a2 into main Oct 28, 2021
@zklaus zklaus deleted the remove-write_netcdf-ncl branch October 28, 2021 11:26
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zklaus commented Oct 28, 2021

Cheers, @axel-lauer

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For me it crashed again for a new reason:
2021-10-28 11:31:58,651 [5412] INFO esmvaltool.diag_scripts.shared._base,550 Creating /work/bd1083/b380216/output/recipe_flato13ipcc_20211028_100738/plots/fig09-14/fig09-14
Traceback (most recent call last):
File "/mnt/lustre02/work/bd1083/b380216/CORE202102/ESMValTool/esmvaltool/diag_scripts/ipcc_ar5/ch09_fig09_14.py", line 407, in
main(cfg)
File "/mnt/lustre02/work/bd1083/b380216/CORE202102/ESMValTool/esmvaltool/diag_scripts/ipcc_ar5/ch09_fig09_14.py", line 396, in main
plot_path = produce_plots(config, data)
File "/mnt/lustre02/work/bd1083/b380216/CORE202102/ESMValTool/esmvaltool/diag_scripts/ipcc_ar5/ch09_fig09_14.py", line 351, in produce_plots
lines, labels = plot_zonal_mean_errors_ensemble(
File "/mnt/lustre02/work/bd1083/b380216/CORE202102/ESMValTool/esmvaltool/diag_scripts/ipcc_ar5/ch09_fig09_14.py", line 259, in plot_zonal_mean_errors_ensemble
cube_list = multi_model_merge(zonal_mean_errors)
File "/mnt/lustre02/work/bd1083/b380216/CORE202102/ESMValTool/esmvaltool/diag_scripts/ipcc_ar5/ch09_fig09_14.py", line 177, in multi_model_merge
equalise_attributes(cube_list)
File "/work/bd0854/b380216/anaconda3/envs/esmvaltool202106/lib/python3.9/site-packages/iris/experimental/equalise_cubes.py", line 30, in equalise_attributes
raise Exception(emsg)
Exception: The function "iris.experimental.equalise_cubes.equalise_attributes" has been moved.
Please replace "iris.experimental.equalise_cubes.equalise_attributes()" with "iris.util.equalise_attributes()".

I had that before fixed in my local version but I think I forgot to mention it on github in connection with the new release, only write it in PR #2156 so far.
It should be easy to fix with changing:
from iris.experimental.equalise_cubes import equalise_attributes
against
from iris.util import equalise_attributes
Unfortunately when I tried to fix it this way still using the old core that didn't work, but this could be caused by different reasons (issues with data sets) as assumed by @zklaus
Since I'm not sure I can finish PR #2156 soon, should we open a new PR just for that one line or should I include/ continue to check it in the context of PR #2156?

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zklaus commented Oct 28, 2021

I also think #2156 will take some more time. If you would be so kind to open a PR for this change, that would be appreciated.

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3 participants