Bug report

Bug summary

Thescatter documentation says:

vmin andvmax are ignored if you pass anorm instance.

However, it seems that this is not the case. Is the documentation correct of the behaviour?

Code for reproduction

importnumpyasnpimportmatplotlib.pyplotaspltimportmatplotlibcmap=matplotlib.cm.viridis_rnorm=matplotlib.colors.BoundaryNorm([1,3,6,8],cmap.N,clip=True)values=np.arange(10)# only specifying a normplt.scatter(values,values,c=values,norm=norm)# also specifying vmin/vmax. Should those be ignored?plt.scatter(values,values,c=values,norm=norm,vmin=6,vmax=10)

Actual outcome

# only specifying a normplt.scatter(values, values, c=values, norm=norm)

# also specifying vmin/vmax. Should those be ignored?plt.scatter(values, values, c=values, norm=norm, vmin=6, vmax=10)

So the vmin/vmax have clearly "altered" the BoundaryNorm applied on the data.

According to the documentation, this should not happen.
Specifically for a BoundaryNorm (with specified bounds), it seems strange let the plotting change those bounds.

Matplotlib version

• Operating system: Ubuntu 16.04
• Matplotlib version: 3.1.0
• Matplotlib backend (print(matplotlib.get_backend())): notebook inline backend
• Python version: 3.7
• Installed from conda-forge