Dealing with NA-Values when plotting rasters with folium in python

Question

I have some tiffs that I'd like to plot interactively in python using folium (or any other package, but I don't know of any). My problem is, that I have many na-values in the raster. At the moment I read in the raster with rasterio, read the data into a 2d-numpy-array, and then I write it back out as .png. Finally I use folium with:

rasterlayer = folium.FeatureGroup(name = "raster")
rasterlayer.add_child(folium.raster_layers.ImageOverlay(
 image=ndvi,
 bounds=[[bottom, left], [top, right]],
 interactive=True,
 cross_origin=False,
 zindex=1,
 colormap=matplotlib.pyplt.cm.Greens
 ))
m.add_child(rasterlayer)
m.add_child(folium.LayerControl())
m

But I get all the NA-Values printed in some colour. And I didn't find any solution to that problem. I had a look here:

https://stackoverflow.com/questions/50689068/display-raster-data-in-folium-handling-no-data-values

but also did not really help. I also did set all NA-values in the "numpy"-array to 0, but this also was not the solution. The NA-Values always got plotted. Is there some, relatively easy way, to omit the plotting of na values. And more general: What is a good way of plotting raster with folium? It seems that in R it's so easy with packages like mapview or tmap and in python it feels way more complicated...

Answer 1

I couldn't find a solution that worked apart from building my own colormap. This function will make the lowest 100 values in the scale transparent

 def cmap(cm, scale=9999):
 from matplotlib.colors import ListedColormap
 ncm = np.zeros((scale, 4))
 pcm = ListedColormap(ncm)
 ncm = np.vstack((pcm(np.linspace(0, 1, 100)), cm(np.linspace(0, 1, 2000)))
 )
 return ListedColormap(ncm)
 cmap(matplotlip.colormap.viridis)

Worked off this document https://matplotlib.org/3.1.0/tutorials/colors/colormap-manipulation.html