# evaluate sampler¶

This is a dummy sampler that just evaluates the likelihood at a reference point. You can use it to test your likelihoods (take a look too at the model wrapper for a similar but more interactive tool).

To use it, simply make the sampler block:

sampler:
evaluate:
# Optional: override parameter values
override:
# param: value


The posterior will be evaluated at a point sampled from the reference pdf (which may be a fixed value) or from the prior if there is no reference. Values passed through evaluate:override will take precedence. For example:

params:
a:
prior:
min: -1
max:  1
ref: 0.5
b:
prior:
min: -1
max:  1
ref:
dist: norm
loc: 0
scale: 0.1
c:
prior:
min: -1
max:  1
d:
prior:
min: -1
max:  1
ref: 0.4

sampler:
evaluate:
override:
d: 0.2


In this case, the posterior will be evaluated for each parameter at:

a: Exactly at $$0.5$$.

b: Sampled from the reference pdf: a Gaussian centred at $$0$$ with standard deviation $$0.1$$.

c: From the prior, since there is no reference pdf: sampled uniformly in the interval $$[-1, 1]$$.

d: From the override, which takes precedence above all else.

Note

If using this sampler cobaya appears to be stuck, this normally means that it cannot sample a point with finite posterior value. Check that your prior/likelihood definitions leave room for some finite posterior density, e.g. don’t define an external prior that imposes that $$x>2$$ if the range allowed for $$x$$ is just $$[0,1]$$.

## Evaluate sampler class¶

Synopsis

Dummy “sampler”: simply evaluates the likelihood.

Author