minor numpy2 tidy; doc for gaussian_mixture names

CobayaSampler · Dec 16, 2024 · 5c605d3 · 5c605d3
1 parent 7be6a20
commit 5c605d3
Show file tree

Hide file tree

Showing 2 changed files with 17 additions and 4 deletions.
diff --git a/cobaya/samplers/mcmc/mcmc.py b/cobaya/samplers/mcmc/mcmc.py
@@ -703,8 +703,9 @@ def check_convergence_and_learn_proposal(self):
                 self.log.info(" - Average thinned weight: %.3f%s", 1 / acceptance_rate,
                               weights_multi_str)
             else:
-                accpt_multi_str = (" = avg(%r)" % acceptance_rates.tolist()
-                                   if acceptance_rates is not None else "")
+                accpt_multi_str = (
+                    " = avg([%s])" % ", ".join("%.4f" % x for x in acceptance_rates)
+                    if acceptance_rates is not None else "")
                 self.log.info(" - Acceptance rate: %.3f%s", acceptance_rate,
                               accpt_multi_str)
             self.progress.at[self.i_learn, "acceptance_rate"] = acceptance_rate
@@ -813,8 +814,8 @@ def check_convergence_and_learn_proposal(self):
                     self.log.debug(" - normalized std's of bounds = %r", Rminus1_cl)
                     Rminus1_cl = np.max(Rminus1_cl)
                     self.progress.at[self.i_learn, "Rminus1_cl"] = Rminus1_cl
-                    accpt_multi_str = \
-                        " = sum(%r)" % list(Ns) if more_than_one_process() else ""
+                    accpt_multi_str = " = sum(%r)" % Ns.astype(int).tolist() \
+                        if more_than_one_process() else ""
                     self.log.info(
                         " - Convergence of bounds: R-1 = %f after %d accepted steps%s",
                         Rminus1_cl,

diff --git a/docs/likelihood_gaussian_mixture.rst b/docs/likelihood_gaussian_mixture.rst
@@ -42,6 +42,18 @@ A delay (in seconds) in the likelihood evaluation can be specified with the keyw
 
    This module also provides functions to generate random means and covariances – see automatic documentation below.
 
+.. note::
+   If you want to use a Gaussian likelihood with particular input names, you can specify them explicitly, e.g.::
+
+       likelihood:
+          gaussian_mixture:
+            means: [[1.04103e-2, 0.02223, 0.1192]]
+            covs: [[6.8552146e-16, 1.4486860e-12, -1.4105674e-11],
+                   [1.4486860e-12, 2.1344167e-08, -1.1534501e-07],
+                   [-1.4105674e-11, -1.1534501e-07, 1.6977630e-06]]
+            input_params: ['thetastar', 'ombh2', 'omch2']
+            output_params: []
+
 The default option values for this likelihood are
 
 .. literalinclude:: ../cobaya/likelihoods/gaussian_mixture/gaussian_mixture.yaml