Small add

docs/source/index.rst

@@ -29,6 +29,7 @@ Other examples are provided for specific tasks.
    mcmc_tension
    gaussian_tension
    chains_convergence
+   parameter_reporting
    cosmosis_interface
    utilities
 

docs/source/parameter_reporting.rst

@@ -0,0 +1,7 @@
+tensiometer.parameter_reporting
+==================================
+
+.. currentmodule:: tensiometer.parameter_reporting
+
+.. automodule:: tensiometer.parameter_reporting
+   :members:

tensiometer/parameter_reporting.py

@@ -28,13 +28,28 @@
 # utility functions to get mean and 1d mode:
 
 
-def get_mode1d(chain, param_names):
+def get_mode1d(chain, param_names, settings=None):
     """
+    Utility to compute the peak of the 1d posterior distribution for all
+    parameters (parameter 1d mode).
+    This depends and relies on the precomputed KDE smoothing so one can
+    feed different analysis settings to change that.
+
+    :param chain: :class:`~getdist.mcsamples.MCSamples` the input chain.
+    :param param_names: optional choice of parameter names to
+        restrict the calculation. Default is all parameters.
+    :param settings: optional dictionary with GetDist analysis settings
+        to use for the 1d mode calculation.
+        This will change the analysis settings of the chain globally.
+    :return: an array with the 1d mode.
     """
     # initial check of parameter names:
     if param_names is None:
         param_names = chain.getParamNames().list()
     param_names = gtens._check_param_names(chain, param_names)
+    # KDE settings:
+    if settings is not None:
+        chain.updateSettings(settings=settings, doUpdate=True)
     # get the maximum probability from the precomputed pdf:
     param_mode = []
     for p in param_names:
@@ -57,6 +72,8 @@ def get_mean(chain, param_names):
     #
     return chain.getMeans(_indexes)
 
+###############################################################################
+#