Merge pull request PMEAL#2774 from PMEAL/enhancing_generators

# Enhanced Voronoi generators to accept a `relaxation` argument #enh
# Fixed labeling bug in `FaceCenteredCubic` for face-to-face throats #bug
# Add `pore_labels` and `throat_labels` argments to `plot_tutorial` so apply custom labels #enh

openpnm/network/_delaunay_voronoi_dual.py

@@ -36,6 +36,9 @@ class DelaunayVoronoiDual(Network):
         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``.
+    relaxation : int
+        The number of time to iteratively relax the base points by moving them to
+        the centroid of their respective Voronoi hulls. The default it 0.
 
     %(Network.parameters)s
 
@@ -51,12 +54,21 @@ class DelaunayVoronoiDual(Network):
 
     """
 
-    def __init__(self, shape, points, trim=True, reflect=True, **kwargs):
+    def __init__(
+        self,
+        shape,
+        points,
+        trim=True,
+        reflect=True,
+        relaxation=0,
+        **kwargs
+    ):
         super().__init__(**kwargs)
         net, vor, tri = voronoi_delaunay_dual(shape=shape,
                                               points=points,
                                               trim=trim,
                                               reflect=reflect,
+                                              relaxation=relaxation,
                                               node_prefix='pore',
                                               edge_prefix='throat')
         self.update(net)

openpnm/network/_fcc.py

@@ -50,20 +50,19 @@ def __init__(self, shape, mode='sc', spacing=1, **kwargs):
         net = fcc(shape=shape, spacing=spacing,
                   node_prefix='pore', edge_prefix='throat')
         self.update(net)
-        # Deal with labels
-        Ts = self.find_neighbor_throats(pores=self.pores('corner'),
-                                        mode='xnor')
-        self['throat.corner_to_corner'] = False
-        self['throat.corner_to_corner'][Ts] = True
-        Ts = self.find_neighbor_throats(pores=self.pores('face'))
-        self['throat.corner_to_face'] = False
-        self['throat.corner_to_face'][Ts] = True
+        # Add labels
+        Ts1 = np.all(self['pore.corner'][self.conns], axis=1)
+        self['throat.corner_to_corner'] = Ts1
+        Ts2 = np.all(self['pore.face'][self.conns], axis=1)
+        self['throat.face_to_face'] = Ts2
+        self['throat.corner_to_face'] = ~(Ts1 + Ts2)
 
-        # Finally scale network to specified spacing
         topotools.label_faces(self)
-        Ps = self.pores(['left', 'right', 'top', 'bottom', 'front', 'back'])
+        Ps = self.pores(['xmin', 'xmax', 'ymin', 'ymax', 'zmin', 'zmax'])
         Ps = self.to_mask(pores=Ps)
         self['pore.surface'] = Ps
+
+        # Finally scale network to specified spacing
         self['pore.coords'] *= np.array(spacing)
 
     def add_boundary_pores(self, labels, spacing):

openpnm/network/_voronoi.py

@@ -38,6 +38,9 @@ class Voronoi(Network):
         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.
+    relaxation : int
+        The number of time to iteratively relax the base points by moving them to
+        the centroid of their respective Voronoi hulls. The default it 0.
 
     %(Network.parameters)s
 
@@ -58,12 +61,21 @@ class Voronoi(Network):
 
     """
 
-    def __init__(self, shape, points, trim=True, reflect=True, **kwargs):
+    def __init__(
+        self,
+        shape,
+        points,
+        trim=True,
+        reflect=True,
+        relaxation=0,
+        **kwargs
+    ):
         super().__init__(**kwargs)
         net, vor = voronoi(points=points,
                            shape=shape,
                            trim=trim,
                            reflect=reflect,
+                           relaxation=relaxation,
                            node_prefix='pore',
                            edge_prefix='throat')
         self.update(net)

openpnm/visualization/_plottools.py

@@ -208,7 +208,9 @@ def plot_coordinates(network,
         well as throat connections from ``plot_connections``.
     size_by : str or array_like
         An ndarray of pore values (e.g. alg['pore.concentration']). These
-        values are normalized by scaled by ``markersize``.
+        values are normalized by scaled by ``markersize``.  Note that this controls
+        the marker *area*, so if you want the markers to be proportional to diameter
+        you should do `size_by=net['pore.diameter']**2`.
     color_by : str or array_like
         An ndarray of pore values (e.g. alg['pore.concentration']).
     cmap : str or cmap object
@@ -469,6 +471,8 @@ def plot_networkx(network,
 
 
 def plot_tutorial(network,
+                  pore_labels=None,
+                  throat_labels=None,
                   font_size=12,
                   line_width=2,
                   node_color='b',
@@ -482,6 +486,12 @@ def plot_tutorial(network,
     network : Network
         The network to plot, should be 2D, since the z-coordinate will be
         ignored.
+    pore_labels : array_like
+        A list of values to use for labeling the pores. If not provided then pore
+        index is used.
+    throat_labels : array_like
+        A list of values to use for labeling the throat. If not provided then throat
+        index is used.
     font_size : int
         Size of font to use for labels.
     line_width : int
@@ -504,8 +514,15 @@ def plot_tutorial(network,
 
     G = network_to_networkx(network=network)
     pos = {i: network['pore.coords'][i, 0:2] for i in network.Ps}
-    labels = {i: i for i in network.Ps}
-    edge_labels = {tuple(network['throat.conns'][i, :]): i for i in network.Ts}
+    if pore_labels is None:
+        labels = {i: i for i in network.Ps}
+    else:
+        labels = {i: pore_labels[i] for i in network.Ps}
+    if throat_labels is None:
+        edge_labels = {tuple(network['throat.conns'][i, :]): i for i in network.Ts}
+    else:
+        edge_labels = {tuple(network['throat.conns'][i, :]): throat_labels[i]
+                       for i in network.Ts}
 
     gplot = nx.draw_networkx_nodes(G, pos,
                                    node_size=node_size,

tests/unit/network/BravaisTest.py

@@ -17,7 +17,8 @@ def test_generation_fcc(self):
         assert fcc.num_pores('pore.corner') == 27
         assert fcc.num_pores('pore.face') == 36
         assert fcc.num_throats('throat.corner_to_corner') == 54
-        assert fcc.num_throats('throat.corner_to_face') == 240
+        assert fcc.num_throats('throat.face_to_face') == 96
+        assert fcc.num_throats('throat.corner_to_face') == 144
 
     def test_fcc_add_boundary_pores(self):
         fcc = op.network.FaceCenteredCubic(shape=[3, 3, 3])