run_tropomi.py.md

@@ -11,8 +11,18 @@ This line creates the object TROPOMI:
 There are 6 methods available:
 
 * `read_nc`, selects the filepaths.
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 * `process_data`, computes averages and the number of valid observations. If `monthly_avg=True` it performs monthly averages (data is split per month). If `monthly_avg=False` the data is averaged all together. Choose the first option if you are interested in averages per month and from `start_date` and `end_date` there are 1,2...12 months of data. If `save=True` the averaged data (obs, lat, lon) is saved in a netCDF file. If `apply_qa=True`, the quality assurance flags set in the satellite_config.yaml file are applied. If `geospatial_crop` settings are specified, it applies geospatial crop to the data. Default parameters are `monthly_avg=False`, `months=[0]`, `save=False`, `apply_qa=True` and `geospatial_crop: NDArray | None = None`.
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 * `process_lazy_data`, is very similar to `process_data`, but without averaging. Produces daily netCDF files of unprocessed data (no averaging techniques are applied). QA can also be implemented by setting `apply_qa=True`, as well as `geospatial_crop`. Default parameters are `monthly_avg=False`, `months=[0]`, `save=False`, `apply_qa=True` and `geospatial_crop: NDArray | None = None`.
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 * `yearly_average`, computes the yearly average from the averages of the single months. It runs only if `monthly_avg=True`.
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 * `plot_2D_observations`, generates the 2D plot of average observations. If `monthly_avg=True`, in the variable `months` you need to specify for which months you want to see results. If `monthly_avg=False`, set `months=[0]`. If `monthly_avg=True` and you called `yearly_average` set `months=None`.
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 * `plot_2D_num_obs`, plots the valid observations. The variable `months` follows the same rules of the one in `plot_2D_observations`.
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