Add evidences to corner plots and fix a few minor bugs

cli_tupak/plot_multiple_posteriors.py

@@ -12,6 +12,8 @@ def setup_command_line_args():
                         help="List of labels to use for each result.")
     parser.add_argument("-p", "--parameters", nargs='+', default=None,
                         help="List of parameters.")
+    parser.add_argument("-e", "--evidences", action='store_true', default=False,
+                        help="Add the evidences to the legend.")
     args, _ = parser.parse_known_args()
 
     return args
@@ -24,4 +26,5 @@ def main():
                for r in args.results]
     tupak.core.result.plot_multiple(results, filename=args.filename,
                                     labels=args.labels,
-                                    parameters=args.parameters)
+                                    parameters=args.parameters,
+                                    evidences=args.evidences)

tupak/core/result.py

@@ -409,7 +409,7 @@ class Result(dict):
 
 
 def plot_multiple(results, filename=None, labels=None, colours=None,
-                  save=True, **kwargs):
+                  save=True, evidences=False, **kwargs):
     """ Generate a corner plot overlaying two sets of results
 
     Parameters
@@ -432,6 +432,9 @@ def plot_multiple(results, filename=None, labels=None, colours=None,
         All other keyword arguments are passed to `result.plot_corner`.
         However, `show_titles` and `truths` are ignored since they would be
         ambiguous on such a plot.
+    evidences: bool, optional
+        Add the log-evidence calculations to the legend. If available, the
+        Bayes factor will be used instead.
 
     Returns
     -------
@@ -460,6 +463,14 @@ def plot_multiple(results, filename=None, labels=None, colours=None,
     if labels is None:
         labels = default_labels
 
+    if evidences:
+        if np.isnan(results[0].log_bayes_factor):
+            template = ' $\mathrm{{ln}}(Z)={:1.3g}$'
+        else:
+            template = ' $\mathrm{{ln}}(B)={:1.3g}$'
+        for i, label in enumerate(labels):
+            labels[i] = label + template.format(results[i].log_bayes_factor)
+
     axes = fig.get_axes()
     ndim = int(np.sqrt(len(axes)))
     axes[ndim-1].legend(lines, labels)

tupak/core/sampler.py

@@ -353,7 +353,7 @@ class Sampler(object):
             for k in kwargs_print:
                 if type(kwargs_print[k]) in (list, np.ndarray):
                     array_repr = np.array(kwargs_print[k])
-                    if array_repr.shape > 10:
+                    if array_repr.size > 10:
                         kwargs_print[k] = ('array_like, shape={}'
                                            .format(array_repr.shape))
             logging.info("Using sampler {} with kwargs {}".format(
@@ -776,7 +776,7 @@ class Emcee(Sampler):
         if 'pos0' in self.kwargs:
             logging.debug("Using given initial positions for walkers")
             pos0 = np.squeeze(self.kwargs['pos0'])
-            if pos0.shape != (self.ndim, self.nwalkers):
+            if pos0.shape != (self.nwalkers, self.ndim):
                 raise ValueError(
                     'Input pos0 should be of shape ndim, nwalkers')
         else: