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Add tutorial explaining how to rebuild preprocessed directories #120
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Check out this pull request on See visual diffs & provide feedback on Jupyter Notebooks. Powered by ReviewNB |
I have started reviewing the other PR but will get into this one too this week! |
"source = None # we stick with the OGGM default\n", | ||
"\n", | ||
"# this tasks adds the DEM and defines the local grid\n", | ||
"workflow.execute_entity_task(tasks.define_glacier_region, gdirs,\n", |
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@pat-schmitt
this cell failed for me:
# define the border, we keep the default here
cfg.PARAMS['border'] = cfg.PARAMS['border']
# set the DEM source to use
source = None # we stick with the OGGM default
# this tasks adds the DEM and defines the local grid
workflow.execute_entity_task(tasks.define_glacier_region, gdirs,
source=source);
It does work with SRTM
as source though!
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Besides this cell! everything else works well also the explanation is very clear, as well as the tags to other tutorials for more information .... Great stuff @pat-schmitt ! 😄
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Thanks for the review @bearecinos! Yes, good point. For some of the default DEMs you need to register. This is explained here https://oggm.org/tutorials/master/notebooks/tutorials/dem_sources.html#register-for-online-datasets. I will include this information in the notebook.
Here I add an advanced tutorial that details how to rebuild the preprocessed glacier directories from the ground up. Related to OGGM/oggm#1675.
This tutorial not only guides users through each preprocessing level but also advises on how and where personal data can be integrated. Instead of delving into the specifics of each function, it provides links to related notebooks for further exploration.
An area previously unaddressed in our tutorials is the utilization of different climate datasets. I've included a section on this topic in the current tutorial. However, to maintain its concise and overview nature, this section might be better suited for a separate, dedicated tutorial—possibly within the OGGM shop, where there's already a placeholder for climate data discussions.
I welcome any reviews, especially regarding the appropriateness of the links to other tutorials and whether any relevant tutorials have been overlooked.