def __init__(self,
shape=None,
spacing=[1, 1, 1],
label_1='primary',
label_2='secondary',
**kwargs):
super().__init__(**kwargs)
spacing = sp.array(spacing)
shape = sp.array(shape)
# Deal with non-3D shape arguments
shape = sp.pad(shape, [0, 3 - shape.size],
mode='constant',
constant_values=1)
net = Cubic(shape=shape, spacing=[1, 1, 1])
net['throat.' + label_1] = True
net['pore.' + label_1] = True
single_dim = shape == 1
shape[single_dim] = 2
dual = Cubic(shape=shape - 1, spacing=[1, 1, 1])
faces = [['front', 'back'], ['left', 'right'], ['top', 'bottom']]
faces = [faces[i] for i in sp.where(~single_dim)[0]]
faces = sp.array(faces).flatten().tolist()
dual.add_boundaries(faces)
# Add secondary network name as a label
dual['pore.' + label_2] = True
dual['throat.' + label_2] = True
# Shift coordinates prior to stitching
dual['pore.coords'] += 0.5 * (~single_dim)
stitch(net, dual, P_network=net.Ps, P_donor=dual.Ps, len_max=1)
net['throat.interconnect'] = net['throat.stitched']
del net['throat.stitched']
net['pore.coords'] *= spacing
# Clean-up labels
net['pore.surface'] = False
net['throat.surface'] = False
for face in faces:
# Remove face label from secondary network since it's internal now
Ps = net.pores(labels=[face, label_2], mode='intersection')
net['pore.' + face][Ps] = False
Ps = net.pores(labels=[face + '_boundary'])
net['pore.' + face][Ps] = True
Ps = net.pores(face)
net['pore.surface'][Ps] = True
Ts = net.find_neighbor_throats(pores=Ps, mode='intersection')
net['throat.surface'][Ts] = True
net['throat.' + face] = net.tomask(throats=Ts)
[net.pop(item) for item in net.labels() if 'boundary' in item]
# Label non-surface pores and throats as internal
net['pore.internal'] = ~net['pore.surface']
Ts = net.find_neighbor_throats(pores=net['pore.internal'])
net['throat.internal'] = False
net['throat.internal'][Ts] = True
# Transfer all dictionary items from 'net' to 'self'
[self.update({item: net[item]}) for item in net]
del self.workspace[net.name]
def subdivide(network, pores, shape, labels=[]):
r'''
It trim the pores and replace them by cubic networks with the sent shape.
Parameters
----------
network : OpenPNM Network Object
pores : array_like
The first group of pores to be replaced
shape : array_like
The shape of cubic networks in the target locations
Notes
-----
- It works only for cubic networks.
Examples
--------
>>> import OpenPNM
>>> pn = OpenPNM.Network.Cubic(shape=[5,6,5], spacing=0.001)
>>> pn.Np
150
>>> nano_pores = [2,13,14,15]
>>> pn.subdivide(pores=nano_pores, shape=[4,7,3], labels='nano')
>>> pn.Np
482
>>> assert pn.Np == (150+4*(4*7*3)-4)
'''
mro = [item.__name__ for item in network.__class__.__mro__]
if 'Cubic' not in mro:
raise Exception('Subdivide is only supported for Cubic Networks')
from OpenPNM.Network import Cubic
pores = _sp.array(pores, ndmin=1)
# Checks to find boundary pores in the selected pores
try:
b = network.pores('boundary')
if (_sp.in1d(pores, b)).any():
raise Exception('boundary pores cannot be subdivided!')
except KeyError:
pass
# Assigning right shape and division
if _sp.size(shape) != 2 and _sp.size(shape) != 3:
raise Exception('Subdivide not implemented for Networks other than 2D \
and 3D')
elif _sp.size(shape) == 3 and 1 not in shape:
div = _sp.array(shape, ndmin=1)
single_dim = None
else:
single_dim = _sp.where(_sp.array(network._shape) == 1)[0]
if _sp.size(single_dim) == 0:
single_dim = None
if _sp.size(shape) == 3:
div = _sp.array(shape, ndmin=1)
else:
div = _sp.zeros(3, dtype=_sp.int32)
if single_dim is None:
dim = 2
else:
dim = single_dim
div[dim] = 1
div[-_sp.array(div, ndmin=1, dtype=bool)] = _sp.array(shape,
ndmin=1)
# Creating small network and handling labels
network_spacing = network._spacing
new_net_spacing = network_spacing/div
new_net = Cubic(shape=div, spacing=new_net_spacing)
main_labels = ['left', 'right', 'front', 'back', 'top', 'bottom']
if single_dim is not None:
label_groups = _sp.array([['front', 'back'],
['left', 'right'],
['top', 'bottom']])
non_single_labels = label_groups[_sp.array([0, 1, 2]) != single_dim]
for l in main_labels:
new_net['pore.surface_' + l] = False
network['pore.surface_' + l] = False
if single_dim is None:
new_net['pore.surface_' + l][new_net.pores(labels=l)] = True
else:
for ind in [0, 1]:
loc = (non_single_labels[ind] == l)
temp_pores = new_net.pores(non_single_labels[ind][loc])
new_net['pore.surface_' + l][temp_pores] = True
old_coords = _sp.copy(new_net['pore.coords'])
if labels == []:
labels = ['pore.subdivided_' + new_net.name]
for P in pores:
# Shifting the new network to the right location and attaching it to
# the main network
shift = network['pore.coords'][P] - network_spacing/2
new_net['pore.coords'] += shift
Pn = network.find_neighbor_pores(pores=P)
try:
Pn_new_net = network.pores(labels)
except:
Pn_new_net = []
Pn_old_net = Pn[~_sp.in1d(Pn, Pn_new_net)]
Np1 = network.Np
extend(pore_coords=new_net['pore.coords'],
throat_conns=new_net['throat.conns'] + Np1,
labels=labels, network=network)
# Moving the temporary labels to the big network
for l in main_labels:
network['pore.surface_'+l][Np1:] = new_net['pore.surface_'+l]
# Stitching the old pores of the main network to the new extended pores
surf_pores = network.pores('surface_*')
surf_coord = network['pore.coords'][surf_pores]
for neighbor in Pn:
neighbor_coord = network['pore.coords'][neighbor]
dist = [round(_sp.inner(neighbor_coord-x, neighbor_coord-x),
20) for x in surf_coord]
nearest_neighbor = surf_pores[dist == _sp.amin(dist)]
if neighbor in Pn_old_net:
coplanar_labels = network.labels(pores=nearest_neighbor)
new_neighbors = network.pores(coplanar_labels,
mode='intersection')
# This might happen to the edge of the small network
if _sp.size(new_neighbors) == 0:
labels = network.labels(pores=nearest_neighbor,
mode='intersection')
common_label = [l for l in labels if 'surface_' in l]
new_neighbors = network.pores(common_label)
elif neighbor in Pn_new_net:
new_neighbors = nearest_neighbor
connect_pores(network=network, pores1=neighbor,
pores2=new_neighbors, labels=labels)
# Removing temporary labels
for l in main_labels:
network['pore.surface_' + l] = False
new_net['pore.coords'] = _sp.copy(old_coords)
network._label_surfaces()
for l in main_labels:
del network['pore.surface_'+l]
trim(network=network, pores=pores)
