Hbond excl fix

package/CHANGELOG

@@ -26,6 +26,9 @@ Fixes
     array warnings (PR #3139, backports PRs #2845 and #2834)
   * Fixed several issues with NSGrid and triclinic boxes not finding some pairs.
     (Issues #2229 #2345 #2919, PR #2937).
+  * Removed deprecation warning from numpy in hbond_autocorrel
+    (Issue #2987 PR #3242)
+  * Fixed bug in exclusion matrix of hbond_autocorrel (PR #3242)
 
 Changes
   * Maximum pinned versions in setup.py removed for python 3.6+ (PR #3139)

package/MDAnalysis/analysis/hbonds/hbond_autocorrel.py

@@ -115,7 +115,7 @@
 
 
 The keyword **exclusions** allows a tuple of array addresses to be provided,
-(Hidx, Aidx),these pairs of hydrogen-acceptor are then not permitted to be
+(Hidx, Aidx), these pairs of hydrogen-acceptor are then not permitted to be
 counted as part of the analysis.  This could be used to exclude the
 consideration of hydrogen bonds within the same functional group, or to perform
 analysis on strictly intermolecular hydrogen bonding.
@@ -215,6 +215,7 @@
 
 from MDAnalysis.lib.log import ProgressBar
 from MDAnalysis.lib.distances import capped_distance, calc_angles, calc_bonds
+from MDAnalysis.lib._cutil import _in2d
 from MDAnalysis.core.groups import requires
 
 from MDAnalysis.due import due, Doi
@@ -320,11 +321,13 @@ def __init__(self, universe,
             raise ValueError("Donors and Hydrogen groups must be identical "
                              "length.  Try using `find_hydrogen_donors`.")
 
-        self.exclusions = exclusions
-        if self.exclusions:
-            if not len(self.exclusions[0]) == len(self.exclusions[1]):
+        if exclusions is not None:
+            if len(exclusions[0]) != len(exclusions[1]):
                 raise ValueError(
                     "'exclusion' must be two arrays of identical length")
+            self.exclusions = np.column_stack((exclusions[0], exclusions[1])).astype(np.intp)
+        else:
+            self.exclusions = None
 
         self.bond_type = bond_type
         if self.bond_type not in ['continuous', 'intermittent']:
@@ -427,11 +430,10 @@ def _single_run(self, start, stop):
         box = self.u.dimensions if self.pbc else None
 
         # 2d array of all distances
-        pair, d = capped_distance(self.h.positions, self.a.positions, max_cutoff=self.d_crit, box=box)
-        if self.exclusions:
-            # set to above dist crit to exclude
-            exclude = np.column_stack((self.exclusions[0], self.exclusions[1]))
-            pair = np.delete(pair, np.where(pair==exclude), 0)
+        pair = capped_distance(self.h.positions, self.a.positions, max_cutoff=self.d_crit, box=box,
+                               return_distances=False)
+        if self.exclusions is not None:
+            pair = pair[~ _in2d(pair, self.exclusions)]
 
         hidx, aidx = np.transpose(pair)