Adds function to generate multiple-result corner plots

Closes #110

tupak/core/result.py

@@ -4,6 +4,7 @@ import numpy as np
 import deepdish
 import pandas as pd
 import corner
+import matplotlib
 
 
 def result_file_name(outdir, label):
@@ -320,3 +321,69 @@ class Result(dict):
                 elif typeA in [np.ndarray]:
                     return np.all(A == B)
         return False
+
+
+def plot_multiple(results, filename=None, labels=None, colours=None,
+                  save=True, **kwargs):
+    """ Generate a corner plot overlaying two sets of results
+
+    Parameters
+    ----------
+    results: list
+        A list of `tupak.core.result.Result` objects containing the samples to
+        plot.
+    filename: str
+        File name to save the figure to. If None (default), a filename is
+        constructed from the outdir of the first element of results and then
+        the labels for all the result files.
+    labels: list
+        List of strings to use when generating a legend. If None (default), the
+        `label` attribute of each result in `results` is used.
+    colours: list
+        The colours for each result. If None, default styles are applied.
+    save: bool
+        If true, save the figure
+    kwargs: dict
+        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.
+
+    Returns
+    -------
+    fig:
+        A matplotlib figure instance
+
+    """
+
+    kwargs['show_titles'] = False
+    kwargs['truths'] = None
+
+    fig = results[0].plot_corner(save=False, **kwargs)
+    default_filename = '{}/{}'.format(results[0].outdir, results[0].label)
+    lines = []
+    default_labels = []
+    for i, result in enumerate(results):
+        if colours:
+            c = colours[i]
+        else:
+            c = 'C{}'.format(i)
+        fig = result.plot_corner(fig=fig, save=False, color=c, **kwargs)
+        default_filename += '_{}'.format(result.label)
+        lines.append(matplotlib.lines.Line2D([0], [0], color=c))
+        default_labels.append(result.label)
+
+    if labels is None:
+        labels = default_labels
+
+    axes = fig.get_axes()
+    ndim = int(np.sqrt(len(axes)))
+    axes[ndim-1].legend(lines, labels)
+
+    if filename is None:
+        filename = default_filename
+
+    if save:
+        fig.savefig(filename)
+    return fig
+
+