Can we access the component distributions in a mixture model?

If I have a mixture model with a Gaussian (for the central tendency) and a Uniform (for the outliers), is there some way I can look at the samples of the component distributions? Since they are distributions, they don’t have names…
If I make the mixture model “by hand” (as in @junpenglao’s schizophrenic reaction time example), I can “look into” the components of a mixture model, but the built in pm.MixtureModel doesn’t seem to support this in any way.

By sample you mean posterior samples? In that case it is not possible as in a marginalized mixture model they are blend together.

Thanks. I see. In your schizophrenia example you make a mixture model “by hand,” and I think in there you can “look into” the mixture components and the mixing weights, because they are all normal PyMC3 entities, but in the MixtureModel the are just .dist objects.