def teardown_class(self):
mgr = op.Workspace()
mgr.clear()
def teardown_class(self):
ws = op.Workspace()
ws.clear()
import numpy as np
import openpnm as op
import openpnm.models.geometry as gm
from openpnm.algorithms import MixedInvasionPercolation as mp
import matplotlib.pyplot as plt
plt.close('all')
ws = op.Workspace()
ws.loglevel = 50
class MixedPercolationTest:
def setup_class(self, Np=5):
ws.clear()
# Create Topological Network object
self.net = op.network.Cubic([Np, Np, 1], spacing=1)
self.geo = op.geometry.GenericGeometry(network=self.net,
pores=self.net.pores(),
throats=self.net.throats())
self.geo['pore.diameter'] = 0.5
self.geo['throat.diameter'] = 0.25
self.geo.add_model(propname='throat.length',
model=gm.throat_length.spheres_and_cylinders)
self.geo.add_model(propname='throat.volume',
model=gm.throat_volume.cylinder,
throat_diameter='throat.diameter',
throat_length='throat.length')
self.geo.add_model(propname='pore.volume',
model=gm.pore_volume.sphere,
pore_diameter='pore.diameter')
self.phase = op.phases.Air(network=self.net)
import scipy as sp
import numpy as np
import openpnm as op
import matplotlib.pyplot as plt
mgr = op.Workspace()
class IPTest:
def setup_class(self):
self.net = op.network.Cubic(shape=[10, 10, 10], spacing=0.0005)
self.geo = op.geometry.StickAndBall(
network=self.net, pores=self.net.Ps, throats=self.net.Ts
)
self.water = op.phases.Water(network=self.net)
self.air = op.phases.Air(network=self.net)
self.phys = op.physics.GenericPhysics(
network=self.net, phase=self.water, geometry=self.geo
)
mod = op.models.physics.capillary_pressure.washburn
self.phys.add_model(propname="throat.entry_pressure", model=mod)
def test_set_inlets_overwrite(self):
alg = op.algorithms.InvasionPercolation(network=self.net)
alg.setup(phase=self.water)
alg.set_inlets(pores=self.net.pores("top"))
assert np.sum(alg["pore.invasion_sequence"] == 0) == 100
alg.set_inlets(pores=self.net.pores("bottom"))
assert np.sum(alg["pore.invasion_sequence"] == 0) == 200
import openpnm as op
import numpy as np
from openpnm.algorithms import MixedInvasionPercolation as mp
import matplotlib.pyplot as plt
import openpnm.models.geometry as gm
plt.close('all')
wrk = op.Workspace()
wrk.loglevel = 50
class MixedPercolationTest:
def setup_class(self, Np=5):
wrk.clear()
# Create Topological Network object
self.net = op.network.Cubic([Np, Np, 1], spacing=1)
self.geo = op.geometry.GenericGeometry(network=self.net,
pores=self.net.pores(),
throats=self.net.throats())
self.geo['pore.diameter'] = 0.5
self.geo['throat.diameter'] = 0.25
self.geo.add_model(propname='throat.endpoints',
model=gm.throat_endpoints.spherical_pores)
self.geo.add_model(propname='throat.length',
model=gm.throat_length.piecewise)
self.geo.add_model(propname='throat.volume',
model=gm.throat_volume.cylinder,
throat_diameter='throat.diameter',
throat_length='throat.length')
self.geo.add_model(propname='pore.volume',
model=gm.pore_volume.sphere,
def regions_to_network(im, dt=None, voxel_size=1):
r"""
Analyzes an image that has been partitioned into pore regions and extracts
the pore and throat geometry as well as network connectivity.
Parameters
----------
im : ND-array
An image of the pore space partitioned into individual pore regions.
Note that this image must have zeros indicating the solid phase.
dt : ND-array
The distance transform of the pore space. If not given it will be
calculated, but it can save time to provide one if available.
voxel_size : scalar
The resolution of the image, expressed as the length of one side of a
voxel, so the volume of a voxel would be **voxel_size**-cubed. The
default is 1, which is useful when overlaying the PNM on the original
image since the scale of the image is alway 1 unit lenth per voxel.
Returns
-------
A dictionary containing all the pore and throat size data, as well as the
network topological information. The dictionary names use the OpenPNM
convention (i.e. 'pore.coords', 'throat.conns') so it may be converted
directly to an OpenPNM network object using the ``update`` command.
"""
print('_' * 60)
print('Extracting pore and throat information from image')
from skimage.morphology import disk, square, ball, cube
if im.ndim == 2:
cube = square
ball = disk
# if ~sp.any(im == 0):
# raise Exception('The received image has no solid phase (0\'s)')
if dt is None:
dt = spim.distance_transform_edt(im > 0)
dt = spim.gaussian_filter(input=dt, sigma=0.5)
# Get 'slices' into im for each pore region
slices = spim.find_objects(im)
# Initialize arrays
Ps = sp.arange(1, sp.amax(im) + 1)
Np = sp.size(Ps)
p_coords = sp.zeros((Np, im.ndim), dtype=float)
p_volume = sp.zeros((Np, ), dtype=float)
p_dia_local = sp.zeros((Np, ), dtype=float)
p_dia_global = sp.zeros((Np, ), dtype=float)
p_label = sp.zeros((Np, ), dtype=int)
p_area_surf = sp.zeros((Np, ), dtype=int)
t_conns = []
t_dia_inscribed = []
t_area = []
t_perimeter = []
t_coords = []
dt_shape = sp.array(dt.shape)
# Start extracting size information for pores and throats
for i in tqdm(Ps):
pore = i - 1
if slices[pore] is None:
continue
s = extend_slice(slices[pore], im.shape)
sub_im = im[s]
sub_dt = dt[s]
pore_im = sub_im == i
padded_mask = sp.pad(pore_im, pad_width=1, mode='constant')
pore_dt = spim.distance_transform_edt(padded_mask)
s_offset = sp.array([i.start for i in s])
p_label[pore] = i
p_coords[pore, :] = spim.center_of_mass(pore_im) + s_offset
p_volume[pore] = sp.sum(pore_im)
p_dia_local[pore] = 2 * sp.amax(pore_dt)
p_dia_global[pore] = 2 * sp.amax(sub_dt)
p_area_surf[pore] = sp.sum(pore_dt == 1)
im_w_throats = spim.binary_dilation(input=pore_im, structure=ball(1))
im_w_throats = im_w_throats * sub_im
Pn = sp.unique(im_w_throats)[1:] - 1
for j in Pn:
if j > pore:
t_conns.append([pore, j])
vx = sp.where(im_w_throats == (j + 1))
t_dia_inscribed.append(2 * sp.amax(sub_dt[vx]))
t_perimeter.append(sp.sum(sub_dt[vx] < 2))
t_area.append(sp.size(vx[0]))
t_inds = tuple([i + j for i, j in zip(vx, s_offset)])
temp = sp.where(dt[t_inds] == sp.amax(dt[t_inds]))[0][0]
if im.ndim == 2:
t_coords.append(tuple((t_inds[0][temp], t_inds[1][temp])))
else:
t_coords.append(
tuple((t_inds[0][temp], t_inds[1][temp],
t_inds[2][temp])))
# Clean up values
Nt = len(t_dia_inscribed) # Get number of throats
if im.ndim == 2: # If 2D, add 0's in 3rd dimension
p_coords = sp.vstack((p_coords.T, sp.zeros((Np, )))).T
t_coords = sp.vstack((sp.array(t_coords).T, sp.zeros((Nt, )))).T
net = {}
net['pore.all'] = sp.ones((Np, ), dtype=bool)
net['throat.all'] = sp.ones((Nt, ), dtype=bool)
net['pore.coords'] = sp.copy(p_coords) * voxel_size
net['pore.centroid'] = sp.copy(p_coords) * voxel_size
net['throat.centroid'] = sp.array(t_coords) * voxel_size
net['throat.conns'] = sp.array(t_conns)
net['pore.label'] = sp.array(p_label)
net['pore.volume'] = sp.copy(p_volume) * (voxel_size**3)
net['throat.volume'] = sp.zeros((Nt, ), dtype=float)
net['pore.diameter'] = sp.copy(p_dia_local) * voxel_size
net['pore.inscribed_diameter'] = sp.copy(p_dia_local) * voxel_size
net['pore.equivalent_diameter'] = 2 * (
(3 / 4 * net['pore.volume'] / sp.pi)**(1 / 3))
net['pore.extended_diameter'] = sp.copy(p_dia_global) * voxel_size
net['pore.surface_area'] = sp.copy(p_area_surf) * (voxel_size)**2
net['throat.diameter'] = sp.array(t_dia_inscribed) * voxel_size
net['throat.inscribed_diameter'] = sp.array(t_dia_inscribed) * voxel_size
net['throat.area'] = sp.array(t_area) * (voxel_size**2)
net['throat.perimeter'] = sp.array(t_perimeter) * voxel_size
net['throat.equivalent_diameter'] = ((sp.array(t_area) *
(voxel_size**2))**(0.5))
P12 = net['throat.conns']
PT1 = (sp.sqrt(
sp.sum(((p_coords[P12[:, 0]] - t_coords) * voxel_size)**2, axis=1)))
PT2 = (sp.sqrt(
sp.sum(((p_coords[P12[:, 1]] - t_coords) * voxel_size)**2, axis=1)))
net['throat.total_length'] = PT1 + PT2
PT1 = PT1 - p_dia_local[P12[:, 0]] / 2 * voxel_size
PT2 = PT2 - p_dia_local[P12[:, 1]] / 2 * voxel_size
net['throat.length'] = PT1 + PT2
dist = (p_coords[P12[:, 0]] - p_coords[P12[:, 1]]) * voxel_size
net['throat.direct_length'] = sp.sqrt(sp.sum(dist**2, axis=1))
# Make a dummy openpnm network to get the conduit lengths
pn = op.network.GenericNetwork()
pn.update(net)
pn.add_model(propname='throat.endpoints',
model=op_gm.throat_endpoints.spherical_pores,
pore_diameter='pore.inscribed_diameter',
throat_diameter='throat.inscribed_diameter')
pn.add_model(propname='throat.conduit_lengths',
model=op_gm.throat_length.conduit_lengths)
pn.add_model(propname='pore.area', model=op_gm.pore_area.sphere)
net['throat.endpoints.head'] = pn['throat.endpoints.head']
net['throat.endpoints.tail'] = pn['throat.endpoints.tail']
net['throat.conduit_lengths.pore1'] = pn['throat.conduit_lengths.pore1']
net['throat.conduit_lengths.pore2'] = pn['throat.conduit_lengths.pore2']
net['throat.conduit_lengths.throat'] = pn['throat.conduit_lengths.throat']
net['pore.area'] = pn['pore.area']
prj = pn.project
prj.clear()
wrk = op.Workspace()
wrk.close_project(prj)
return net
To visualize the throat data (like diameters or molar flow rates) we need to set up the following filters in Paraview. First, use the Shrink filter and set it up to 1. Then, the cell data needs to be transposed to the data point with CellDatatoPointdata filter. Then extract the surface with the filter ExtractSurface. Finally, the data may be plotted as tube by using the Tube filter. As previously for the pore data, either the Tube radius or color can be linked to throat data.
Throat data plotted with tubes radius proportional to throat diameter and tubes color linked to the throat mole rate:
'''
import scipy as sp
import openpnm as op
import numpy as np
import matplotlib.pyplot as plt
np.random.seed(10)
op.Workspace().settings['loglevel'] = 50
Nx = 11
Ny = 11
Nz = 11
spacing = 1e-4
pn = op.network.Cubic(shape=[11, 11, 11], spacing=[spacing, spacing, spacing])
#regular network
geo = op.geometry.StickAndBall(network=pn, pores=pn.Ps, throats=pn.Ts)
#geo.show_hist(['pore.diameter', 'throat.diameter', 'throat.length'])
#trim the network (1 in x, 4 in y, 7 in z)
#op.topotools.trim(network=pn, pores=[1, 4, 7])
print(pn['pore.coords'][pn.pores('all')])
f = np.savetxt("node.dat", (pn['pore.coords'][pn.pores('all')]))
def setup_class(self):
self.ws = op.Workspace()
def setup_class(self):
ws = op.Workspace()
ws.clear()
self.net = op.network.Cubic(shape=[10, 10, 10])
def setup_class(self):
self.ws = op.Workspace()
self.ws.clear()
self.proj = self.ws.new_project()
self.net = op.network.Cubic(shape=[2, 2, 2], project=self.proj)
def setup_class(self):
ws = op.Workspace()
ws.clear()
def setup_class(self):
ws = op.Workspace()
ws.settings['local_data'] = True
def setup_class(self):
self.ws = op.Workspace()
self.ws.clear()
self.net = op.network.Cubic(shape=[5, 5, 5])
self.phase = op.phases.Air(network=self.net)