Closed Beauprel closed 1 year ago
It works with gdfmap
sp.gdfmap(df, 'OBJECTID',projection = ccrs.LambertConformal(), features = {'ocean': {'color':'#a2bdeb'}, 'borders':{'scale':'50m'}}, plot_kw = {'legend_kwds':{'orientation': 'vertical'}, 'edgecolor': 'black'}, cmap='prec_div', frame=False, levels=5 )
Actually, it works with the proper colormap filename of something_div_disc
. But I think the whole idea of creating a colormap based on the number of levels (from the IPCC files) is bad. Instead I think we should get the colormap and divide it after - like we go in gdfmap
.
Est-ce que les couleurs restent les mêmes avec les splits et correspondent +/- à celles de l'IPCC?
After discussion, removing the IPCC discrete colormap files and implementing the way of dividing colormaps used in gdfmap
and scattermap
will fix this issue.
I verified that dividing the colormaps in n colors, no matter the data, produces the same n colors.
Closing as this is fixed by PR https://github.com/Ouranosinc/spirograph/pull/87
Using levels should divide the colormap - even when the cmap is passed explicitely
cmap=None
(guessed)levels
is passed inplot_kw