Add support for crs on holoviews datashader operations

Datashader is very useful when working with geospatial data and holoviews now offers datashader operations. One major issue is that these operations do not currently handle a crs, which makes it difficult to work with them. The main obstacle here is that a) there is no geoviews RGB type, which could be used to hold the output of datashade and b) that projecting on every datashader plot update is very inefficient. I’d therefore suggest a temporary approach to make this work is to offer an operation that projects any Element type to a new crs and secondly to add a crs-aware RGB type to geoviews.

[AlexHilson]

Thanks a lot for the above information, it’s really helpful.

When I use regrid with the matplotlib backend the above code works as I’d expect. But with the bokeh backend I get DataError: None of the available storage backends were able to support the supplied data format.

i.e. given the setup:

# <iris 'Cube' of air_temperature / (K) (latitude: 1200; longitude: 1600)>
kdims = ['longitude', 'latitude']
vdims = ['air_temperature']
ds = gv.Dataset(cube, kdims=kdims, vdims=vdims)
gv_img = ds.to(gv.Image, kdims)
hv_img = ds.to(hv.Image, kdims)

These will plot:

hv.notebook_extension('bokeh')
regrid(hv_img)

hv.notebook_extension('matplotlib')
regrid(gv_img)

But this throws the exception:

hv.notebook_extension('bokeh')
regrid(gv_img)

My understanding is that I can only add gf.coastline when using gv.Image, so this means that when using datashader I need to choose between an interactive bokeh plot and one with coastlines.

Does this seem correct? If there’s anything I can do to help that’d be great, I’d love to have interactive + geospatially aware datashader plots.

[philippjfr]

This has now been implemented, datashader operations will now respect the coordinate reference system of the inputs. Should make things a lot more intuitive, we should however add a guide on working with Datashader and GeoViews.