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TonioF
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TonioF
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Looks good! Just a few minor comments, mostly typos.
| if resolution is None: | ||
| if crs is not None and crs.is_geographic: | ||
| resolution = 10 / CONVERSION_FACTOR_DEG_METER | ||
| else: | ||
| resolution = 10 |
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You have almost exactly the same code in get_native_res. You could simplify this by adapting get_native_res
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get_native_res goes from degree to meter, is crs is geographic. res_native = resolution * CONVERSION_FACTOR_DEG_METER Then after that, the nearest equal or coarser Sentinel-2 spatial resolution is selected.
The part above goes from degree to meter to degree, if crs is geographic. resolution = 10 / CONVERSION_FACTOR_DEG_METER Here, no further selection should be done.
Programmatically it would be possible, but logically it think it would complicate things.
xarray_eopf/amodes/sentinel2.py
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| crs = pyproj.CRS.from_wkt(ds.spatial_ref.attrs["crs_wkt"]) | ||
| if bbox is None: | ||
| res, ds = next(iter(datasets.items())) | ||
| crs_data = pyproj.CRS.from_wkt(ds.spatial_ref.attrs["crs_wkt"]) |
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The name 'source_crs' would have made it a lot clearer to me what is happening here.
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I will change crs_data to source_crs
Co-authored-by: Tonio Fincke <tonio.fincke@brockmann-consult.de>
Co-authored-by: Tonio Fincke <tonio.fincke@brockmann-consult.de>
Co-authored-by: Tonio Fincke <tonio.fincke@brockmann-consult.de>
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crsresolutionandbbox.