Local covariance matrix

[Aseman7]

Hello,

Please have a look at Figure 5 of Czekala et al. 2015:

It explains how the addition of local kernel can be so useful in some cases. My question is: how can I add an outlier line (for example, 5202.2 Angestrum) into code?

As the Starfish documentation says, I have to define its kernel by its hyperparameters:

log_amp: The natural logarithm of the amplitude of the kernel mu: The location of the local kernel log_sigma: The natural logarithm of the standard deviation of the kernel

Does it mean that I use the following definition in the SpectrumModel function as:

local_cov = dict(log_amp:?, mu: 5202.2, log_sigma:?)

If yes, please guide me on how to select "log_amp" and "log_sigma". Does "mu" value is correct?

And how to define them in the prior values:

"local_cov:log_amp": st.norm(?), "local_cov:log_sigma": st.norm(?), "local_cov:mu": st.norm (5222.1, 0.1)

Thanks a lot for any help in advance.