Allow multiple reference groups

This allows to track the contact differences to several states over time. This is for example needed to implement a q1-q2 analysis.
MDAnalysis · Mar 28, 2016 · 1082927 · 1082927
1 parent 76bf3af
commit 1082927
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Showing 2 changed files with 7 additions and 4 deletions.
diff --git a/package/MDAnalysis/analysis/contacts.py b/package/MDAnalysis/analysis/contacts.py
@@ -172,6 +172,7 @@
 import MDAnalysis.lib.distances
 from MDAnalysis.lib.util import openany
 from MDAnalysis.analysis.distances import distance_array
+from MDAnalysis.core.AtomGroup import AtomGroup
 from .base import AnalysisBase
 
 logger = logging.getLogger("MDAnalysis.analysis.contacts")
@@ -342,14 +343,14 @@ def __init__(self, u, selection, refgroup, method="cutoff", radius=4.5,
         self.r0 = []
         self.initial_contacts = []
 
-        if isinstance(refgroup[0], mda.AtomGroup.AtomGroup):
+        if isinstance(refgroup[0], AtomGroup):
             refA, refB = refgroup
             self.r0.append(distance_array(refA.positions, refB.positions))
-            self.initial_contacts.append(contact_matrix(self.r0, radius))
+            self.initial_contacts.append(contact_matrix(self.r0[-1], radius))
         else:
             for refA, refB in refgroup:
                 self.r0.append(distance_array(refA.positions, refB.positions))
-                self.initial_contacts.append(contact_matrix(self.r0, radius))
+                self.initial_contacts.append(contact_matrix(self.r0[-1], radius))
 
         self.fraction_kwargs = kwargs
         self.timeseries = []
@@ -366,6 +367,8 @@ def _single_frame(self):
             r0 = r0[initial_contacts]
             y[i] = self.fraction_contacts(r, r0, **self.fraction_kwargs)
 
+        if len(y) == 1:
+            y = y[0]
         self.timeseries.append((self._ts.frame, y))
 
     def save(self, outfile):

diff --git a/testsuite/MDAnalysisTests/analysis/test_contacts.py b/testsuite/MDAnalysisTests/analysis/test_contacts.py
@@ -199,5 +199,5 @@ def test_villin_unfolded():
                                                   method="soft_cut")
         q.run()
 
-        results = zip(*soft_cut(f, u, sel, sel)) [1]
+        results = zip(*soft_cut(f, u, sel, sel))[1]
         assert_almost_equal(zip(*q.timeseries)[1], results)