M-H algorithm with custom distribution with scipy

Questions v5
3

Hi ! Thanks a lot for your time.
Ok I get it, I think. However, is there a way to automatically get the function that returns the likelihood of the data for a given sigma value with scipy.stats ?
For example, one of my dist_func is gausshyper, is there a way to have density from dist_func variable, and where to include it, as a logp(x) in custom ? Because I guess replacing rvs by pdf is not as simple ?

More specifically, where does x parameter come from ?

rvs(a, b, c, z, loc=0, scale=1, size=1, random_state=None) Random variates.
pdf(x, a, b, c, z, loc=0, scale=1) Probability density function.

Thanks also for the pm.Metropolis : >

  step = pm.Metropolis()
  trace = pm.sample(step=step,
      draws=2000,
      tune=5000,
      chains=2,
      cores=1,
      target_accept=0.9,
      return_inferencedata=True,
      init="adapt_full",
  )