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Currently methods like heatmap don't allow for custom Normalize objects to be fed into the matplotlib drawing process (i.e. when calling pcolormesh you can provide a norm argument) and only allow for custom Colormaps.
This makes it hard to have e.g. logarithmically scaled color in the plots without directly scaling the actual data, which messes up the colorbar values etc. because of the way matplotlib separates normalization of data and after that color assignment to the normalized values using color maps. Is it possible to open up method arguments to allow to pass in those custom Normalize objects?
The text was updated successfully, but these errors were encountered:
Currently methods like
heatmap
don't allow for customNormalize
objects to be fed into the matplotlib drawing process (i.e. when callingpcolormesh
you can provide anorm
argument) and only allow for custom Colormaps.This makes it hard to have e.g. logarithmically scaled color in the plots without directly scaling the actual data, which messes up the colorbar values etc. because of the way matplotlib separates normalization of data and after that color assignment to the normalized values using color maps. Is it possible to open up method arguments to allow to pass in those custom Normalize objects?
The text was updated successfully, but these errors were encountered: