norm ignored when (when clipping) for coloring scatter plots; normalizer is modified #75
Description
when passing a norm to scatter / pcolor, the norm is ignored for coloring but also its vmin/vmax values are modified
import numpy as np
import ultraplot as uplt
import matplotlib.pyplot as plt
x = np.arange(10)
y = x**2
c = y
cmap = uplt.Colormap("viridis")
norm = uplt.Norm("linear", 0, 10)
fig, ax = uplt.subplots()
ax.scatter(x, y, c=c, cmap=cmap, norm=norm)
print(norm.vmin, norm.vmax)
fig, ax = plt.subplots()
norm = uplt.Norm("linear", 0, 10)
ax.scatter(x, y, c=c, cmap=cmap, norm=norm)>>> 0.0 81.0
ultraplot result
matplotlib result
See also the discussion on the proplot github: proplot-dev/proplot#400
A workaround is to pass vmin, vmax directly.
norm not correctly applying colors I can live with but the modification of the norm object is unexpected thus dangerous