I find myself copy-pasting code to the following in several of my MAR notebooks:
- overwriting the
config dictionary with the MAR environment variables
- getting local parameters and downloading files
- loading model data from those files
It seems unnecessary to expose these to the typical user; for the vast majority of use cases we can replace the many lines of code that do this with a function that takes a config dictionary and outputs a dictionary of xr.Dataset or momgrid instances.
I think this would dramatically lower the barriers for new contributors to MAR. After just two commands of set up,
config = {
"startyr": "1975",
"endyr": "2015",
"dora_id": "odiv-399, odiv-400",
"pathPP": None,
}
models = load_om5_output(config)
users should be able to make a basic plot, e.g.:
models["odiv-399"]["gds"].data.tos.mean("time").plot()
to produce

I find myself copy-pasting code to the following in several of my MAR notebooks:
configdictionary with the MAR environment variablesIt seems unnecessary to expose these to the typical user; for the vast majority of use cases we can replace the many lines of code that do this with a function that takes a config dictionary and outputs a dictionary of
xr.Datasetormomgridinstances.I think this would dramatically lower the barriers for new contributors to MAR. After just two commands of set up,
users should be able to make a basic plot, e.g.:
to produce
