Increase coverage of leaflet.py (#2603)

Commit title: Increase coverage of leaflet.py (#2603)

Contents of commit:
=============

1) This commit adds a series of tests to `analysis/leaflet.py` which cover parts of the code which did not use to be tested (Issue #2600). As of this commit, coverage is now at over 95% for this module.

2) This commit also fixes a missing import for the selection module (#2612).

Unaltered commit history:
=================

* _get_graph without self.pbc for leaflet.py

* using update

* add test for leaflet write_selection and fix one missing module in leaflet.py

* tyop

* check expected lipids contact are returned when pbc on

* check leaflet write_selection output

* remove unused codes

* add more tests on update function

* cover three options for sparse

* add test on components index in group & add name CHANGELOG

* add test on update without cutoff

* PEP8 formatting

* exclude valueerror in matrix cal from coverage

* add author

package/AUTHORS

@@ -135,7 +135,7 @@ Chronological list of authors
   - Hugo MacDermott-Opeskin
   - Anshul Angaria
   - Shubham Sharma
-
+  - Yuxuan Zhuang
 
 External code
 -------------

package/CHANGELOG

@@ -16,7 +16,7 @@ The rules for this file:
 mm/dd/yy richardjgowers, kain88-de, lilyminium, p-j-smith, bdice, joaomcteixeira,
          PicoCentauri, davidercruz, jbarnoud, RMeli, IAlibay, mtiberti, CCook96,
          Yuan-Yu, xiki-tempula, HTian1997, Iv-Hristov, hmacdope, AnshulAngaria,
-         ss62171, Luthaf
+         ss62171, Luthaf, yuxuanzhuang
 
   * 0.21.0
 
@@ -64,6 +64,7 @@ Fixes
     match TPRParser. (PR #2408)
   * Added parmed to setup.py
   * Fixed example docs for polymer persistence length (#2582)
+  * Added missing selection module to leaflet.py (Issue #2612)
 
 Enhancements
   * Added ability to use Chemfiles as a trajectory reader backend (PR #1862)

package/MDAnalysis/analysis/leaflet.py

@@ -79,6 +79,7 @@
 
 from .. import core
 from . import distances
+from .. import selections
 
 from ..due import due, Doi
 
@@ -174,7 +175,7 @@ def _get_graph(self):
             # only try distance array
             try:
                 adj = distances.contact_matrix(coord, cutoff=self.cutoff, returntype="numpy", box=box)
-            except ValueError:
+            except ValueError:      # pragma: no cover
                 warnings.warn('N x N matrix too big, use sparse=True or sparse=None', category=UserWarning,
                               stacklevel=2)
                 raise
@@ -186,7 +187,7 @@ def _get_graph(self):
             try:
                 # this works for small-ish systems and depends on system memory
                 adj = distances.contact_matrix(coord, cutoff=self.cutoff, returntype="numpy", box=box)
-            except ValueError:
+            except ValueError:       # pragma: no cover
                 # but use a sparse matrix method for larger systems for memory reasons
                 warnings.warn(
                     'N x N matrix too big - switching to sparse matrix method (works fine, but is currently rather '

testsuite/MDAnalysisTests/analysis/test_leaflet.py

@@ -26,13 +26,16 @@
 
 from numpy.testing import assert_equal, assert_almost_equal
 import numpy as np
+import networkx as NX
 
 from MDAnalysis.analysis.leaflet import LeafletFinder, optimize_cutoff
 from MDAnalysisTests.datafiles import Martini_membrane_gro
 
-
 LIPID_HEAD_STRING = "name PO4"
 
+def lines2one(lines):
+    """Join lines and squash all whitespace"""
+    return " ".join(" ".join(lines).split())
 
 @pytest.fixture()
 def universe():
@@ -69,3 +72,105 @@ def test_optimize_cutoff(universe, lipid_heads):
     cutoff, N = optimize_cutoff(universe, lipid_heads, pbc=True)
     assert N == 2
     assert_almost_equal(cutoff, 10.5, decimal=4)
+
+
+def test_pbc_on_off(universe, lipid_heads):
+    lfls_pbc_on = LeafletFinder(universe, lipid_heads, pbc=True)
+    lfls_pbc_off = LeafletFinder(universe, lipid_heads, pbc=False)
+    assert lfls_pbc_on.graph.size() > lfls_pbc_off.graph.size()
+
+
+def test_pbc_on_off_difference(universe, lipid_heads):
+    lfls_pbc_on = LeafletFinder(universe, lipid_heads, cutoff=7, pbc=True)
+    lfls_pbc_off = LeafletFinder(universe, lipid_heads, cutoff=7, pbc=False)
+    pbc_on_graph = lfls_pbc_on.graph
+    pbc_off_graph = lfls_pbc_off.graph
+    diff_graph = NX.difference(pbc_on_graph, pbc_off_graph)
+    assert_equal(set(diff_graph.edges), {(69, 153), (73, 79),
+                                        (206, 317), (313, 319)})
+
+
+@pytest.mark.parametrize("sparse", [True, False, None])
+def test_sparse_on_off_none(universe, lipid_heads, sparse):
+    lfls_ag = LeafletFinder(universe, lipid_heads, cutoff=15.0, pbc=True,
+                                sparse=sparse)
+    assert_almost_equal(len(lfls_ag.graph.edges), 1903, decimal=4)
+
+
+def test_cutoff_update(universe, lipid_heads):
+    lfls_ag = LeafletFinder(universe, lipid_heads, cutoff=15.0, pbc=True)
+    lfls_ag.update(cutoff=1.0)
+    assert_almost_equal(lfls_ag.cutoff, 1.0, decimal=4)
+    assert_almost_equal(len(lfls_ag.groups()), 360, decimal=4)
+
+
+def test_cutoff_update_default(universe, lipid_heads):
+    lfls_ag = LeafletFinder(universe, lipid_heads, cutoff=15.0, pbc=True)
+    lfls_ag.update()
+    assert_almost_equal(lfls_ag.cutoff, 15.0, decimal=4)
+    assert_almost_equal(len(lfls_ag.groups()), 2, decimal=4)
+
+
+def test_write_selection(universe, lipid_heads, tmpdir):
+    lfls_ag = LeafletFinder(universe, lipid_heads, cutoff=15.0, pbc=True)
+    with tmpdir.as_cwd():
+        filename = lfls_ag.write_selection('leaflet.vmd')
+        expected_output = lines2one([
+            """# leaflets based on select=<AtomGroup with 360 atoms> cutoff=15.000000
+        # MDAnalysis VMD selection
+        atomselect macro leaflet_1 {index 1 13 25 37 49 61 73 85 \\
+        97 109 121 133 145 157 169 181 \\
+        193 205 217 229 241 253 265 277 \\
+        289 301 313 325 337 349 361 373 \\
+        385 397 409 421 433 445 457 469 \\
+        481 493 505 517 529 541 553 565 \\
+        577 589 601 613 625 637 649 661 \\
+        673 685 697 709 721 733 745 757 \\
+        769 781 793 805 817 829 841 853 \\
+        865 877 889 901 913 925 937 949 \\
+        961 973 985 997 1009 1021 1033 1045 \\
+        1057 1069 1081 1093 1105 1117 1129 1141 \\
+        1153 1165 1177 1189 1201 1213 1225 1237 \\
+        1249 1261 1273 1285 1297 1309 1321 1333 \\
+        1345 1357 1369 1381 1393 1405 1417 1429 \\
+        1441 1453 1465 1477 1489 1501 1513 1525 \\
+        1537 1549 1561 1573 1585 1597 1609 1621 \\
+        1633 1645 1657 1669 1681 1693 1705 1717 \\
+        1729 1741 1753 1765 1777 1789 1801 1813 \\
+        1825 1837 1849 1861 1873 1885 1897 1909 \\
+        1921 1933 1945 1957 1969 1981 1993 2005 \\
+        2017 2029 2041 2053 2065 2077 2089 2101 \\
+        2113 2125 2137 2149 }
+        # MDAnalysis VMD selection
+        atomselect macro leaflet_2 {index 2521 2533 2545 2557 2569 2581 2593 2605 \\
+        2617 2629 2641 2653 2665 2677 2689 2701 \\
+        2713 2725 2737 2749 2761 2773 2785 2797 \\
+        2809 2821 2833 2845 2857 2869 2881 2893 \\
+        2905 2917 2929 2941 2953 2965 2977 2989 \\
+        3001 3013 3025 3037 3049 3061 3073 3085 \\
+        3097 3109 3121 3133 3145 3157 3169 3181 \\
+        3193 3205 3217 3229 3241 3253 3265 3277 \\
+        3289 3301 3313 3325 3337 3349 3361 3373 \\
+        3385 3397 3409 3421 3433 3445 3457 3469 \\
+        3481 3493 3505 3517 3529 3541 3553 3565 \\
+        3577 3589 3601 3613 3625 3637 3649 3661 \\
+        3673 3685 3697 3709 3721 3733 3745 3757 \\
+        3769 3781 3793 3805 3817 3829 3841 3853 \\
+        3865 3877 3889 3901 3913 3925 3937 3949 \\
+        3961 3973 3985 3997 4009 4021 4033 4045 \\
+        4057 4069 4081 4093 4105 4117 4129 4141 \\
+        4153 4165 4177 4189 4201 4213 4225 4237 \\
+        4249 4261 4273 4285 4297 4309 4321 4333 \\
+        4345 4357 4369 4381 4393 4405 4417 4429 \\
+        4441 4453 4465 4477 4489 4501 4513 4525 \\
+        4537 4549 4561 4573 4585 4597 4609 4621 \\
+        4633 4645 4657 4669 }
+
+"""])
+
+        assert lines2one(open('leaflet.vmd').readlines()) == expected_output
+
+
+def test_component_index_is_not_none(universe, lipid_heads):
+    lfls_ag = LeafletFinder(universe, lipid_heads, cutoff=15.0, pbc=True)
+    assert_almost_equal(len(lfls_ag.groups(component_index=0)), 180, decimal=4)