Unexpected ln value for the constant in front of an ExpSquaredKernel

[mar-ses]

Hello, I defined an ExpSquaredKernel like so:

	A_xy_i = 10**(-4.5)
	var_x_i = 18**(-1)
	var_y_i = 18**(-1)

	k_spatial = A_xy_i * kernels.ExpSquaredKernel(metric=[var_x_i, var_y_i], ndim=3, axes=[0,1])

But when I print the values I get this:

In [1]: k_spatial.get_vector()
Out[1]: array([-11.46024521,  -2.89037176,  -2.89037176])

Which doesn't agree with the following:

In [2]: A_xy_i

Out[2]: 3.1622776601683795e-05

In [4]: np.log(A_xy_i)

Out[4]: -10.361632918473205

This happens every time I define a constant in front of the ExpSquaredKernel. I didn't change the vector value either this is immediately after the definition. Is this supposed to happen? What is the actual conversion from the amplitude to the constant vector?

Using 1.0-dev branch.

[dfm]

The parameter for a constant kernel in multiple dimensions is actually value/ndim:

In [1]: np.log(10**(-4.5)/3.)
Out[1]: -11.460245207141314