Hello,

I am trying to understand if alpha is truly equivalent to WhiteKernel by looking at gpr.py. 

I can see that that the two are the same when fit() is called, i.e. self.L_ and self.alpha_ are the same whether alpha or WhiteKernel is used. 

In predict(), however, y_var = self.kernel_.diag(X) produces a different result depending on whether alpha or WhiteKernel is used. Is this correct? Indeed, if I run http://scikit-learn.org/stable/auto_examples/gaussian_process/plot_gpr_noisy.html the grey areas are completely different depending on which one I use, although the red and black curves are exactly the same.