returning to original defaults

openpnm/network/_delaunay.py

@@ -29,7 +29,7 @@ class Delaunay(Network):
         ========== ============================================================
 
     reflect : bool, optional
-        If ``True`` (default) then the base points will be reflected across
+        If ``True`` then the base points will be reflected across
         all the faces of the domain prior to performing the tessellation. This
         feature is best combined with ``trim=True`` to prevent unreasonably long
         connections between points on the surfaces.

openpnm/network/_delaunay_voronoi_dual.py

@@ -30,13 +30,12 @@ class DelaunayVoronoiDual(Network):
         ========== ============================================================
 
     trim : bool, optional
-        If ``True`` (default) then all vertices laying outside the domain will
+        If ``True`` then all vertices laying outside the domain will
         be removed. This is only useful if ``reflect=True``.
     reflect : bool, optional
-        If ``True`` (default) then the base points will be reflected across
+        If ``True`` then the base points will be reflected across
         all the faces of the domain prior to performing the tessellation. This
-        feature is best combined with ``trim=True`` to prevent unreasonably long
-        connections between points on the surfaces.
+        feature is best combined with ``trim=True``.
 
     %(Network.parameters)s
 

openpnm/network/_voronoi.py

@@ -30,10 +30,10 @@ class Voronoi(Network):
         ========== ============================================================
 
     trim : bool, optional
-        If ``True`` (default) then all Voronoi vertices laying outside the domain
+        If ``True`` then all Voronoi vertices laying outside the domain
         will be removed.
     reflect : bool, optional
-        If ``True`` (default) then the base points will be reflected across
+        If ``True`` then the base points will be reflected across
         all the faces of the domain prior to performing the tessellation. This
         feature is best combined with ``trim=True`` to make nice flat faces
         on all sides of the domain.
@@ -57,7 +57,7 @@ class Voronoi(Network):
 
     """
 
-    def __init__(self, shape, points, trim=True, reflect=True, **kwargs):
+    def __init__(self, shape, points, trim=False, reflect=False, **kwargs):
         super().__init__(**kwargs)
         net, vor = voronoi(points=points,
                            shape=shape,

tests/unit/network/DelaunayTest.py

@@ -70,6 +70,16 @@ def test_delaunay_disk_with_2D_points(self):
         assert np.all(tri.coords[:, -1] != pts[:, -1])
         assert np.all(tri.coords[:, -1] == 0.0)
 
+    def test_delaunay_disk_with_prereflected_points(self):
+        np.random.seed(0)
+        rqz = np.random.rand(50, 3)*np.array([1, 2*np.pi, 1])
+        rqz = op._skgraph.generators.tools.reflect_base_points(rqz.T,
+                                                               domain_size=[1, 1])
+        pts = np.vstack(op._skgraph.tools.cyl2cart(*rqz)).T
+        tri = op.network.Delaunay(points=pts, shape=[1, 1], reflect=False, trim=True)
+        assert tri.coords.shape == (50, 3)
+        assert_array_almost_equal(tri.coords, pts[:50, :], decimal=15)
+
     def test_delaunay_disk_with_3D_points(self):
         np.random.seed(0)
         rqz = np.random.rand(50, 3)*np.array([1, 2*np.pi, 1])

tests/unit/network/VoronoiTest.py

@@ -67,7 +67,7 @@ def test_voronoi_cube_num_points(self):
     def test_voronoi_cube_points(self):
         np.random.seed(0)
         pts = np.random.rand(30, 3)
-        net = op.network.Voronoi(points=pts, shape=[1, 1, 1])
+        net = op.network.Voronoi(points=pts, shape=[1, 1, 1], reflect=False)
         assert net.Np > 30
         assert np.all(net.coords[:, -1] != 0.0)
         assert np.all(op.topotools.dimensionality(net) == [True, True, True])