label_phases
¶
Version 2 of PoreSpy included the ability to perform network extractions on images that contain multiple phases, as outlined by Khan et al. The regions_to_network
function includes the ability to label each pore with the phase to which it belongs, but does nothing else. The label_phases
function then analyzes the network output by regions_to_network
to create the labels that can be used within OpenPNM.
import porespy as ps
import openpnm as op
import matplotlib.pyplot as plt
import numpy as np
from edt import edt
import scipy.ndimage as spim
[01:05:48] ERROR PARDISO solver not installed, run `pip install pypardiso`. Otherwise, _workspace.py:56 simulations will be slow. Apple M chips not supported.
np.random.seed(13)
im = ps.generators.overlapping_spheres([100, 100], r=7, porosity=0.7)
snow = ps.filters.snow_partitioning_n(im=im.astype(int) + 1)
ps.imshow(snow.regions, origin='lower', interpolation='none');
network
¶
The dictionary returned from the regions_to_network
function must be supplied:
net = ps.networks.regions_to_network(regions=snow.regions, phases=snow.im)
net = ps.networks.label_phases(network=net)
for item in net.keys():
print(item)
throat.conns
pore.coords
pore.all
throat.all
pore.region_label
pore.phase
throat.phases
pore.region_volume
pore.equivalent_diameter
pore.local_peak
pore.global_peak
pore.geometric_centroid
throat.global_peak
pore.inscribed_diameter
pore.extended_diameter
throat.inscribed_diameter
throat.total_length
throat.direct_length
throat.perimeter
pore.volume
pore.surface_area
throat.cross_sectional_area
throat.equivalent_diameter
pore.void
throat.void_void
throat.void_solid
pore.solid
throat.solid_void
throat.solid_solid
In the above print-out we can see that several labels have been added to the list, such as 'throat.void_void'
which is True
for all throats which connect a void pore to another void pore, and so forth.
alias
¶
We can override the default names of 'solid'
and 'void'
by providing a dict
which maps the phase number to our desired name as follows:
net = ps.networks.regions_to_network(regions=snow.regions, phases=snow.im)
net = ps.networks.label_phases(network=net, alias={1: 'void', 2: 'grain'})
for item in net.keys():
print(item)
throat.conns
pore.coords
pore.all
throat.all
pore.region_label
pore.phase
throat.phases
pore.region_volume
pore.equivalent_diameter
pore.local_peak
pore.global_peak
pore.geometric_centroid
throat.global_peak
pore.inscribed_diameter
pore.extended_diameter
throat.inscribed_diameter
throat.total_length
throat.direct_length
throat.perimeter
pore.volume
pore.surface_area
throat.cross_sectional_area
throat.equivalent_diameter
pore.void
throat.void_void
throat.void_grain
pore.grain
throat.grain_void
throat.grain_grain
Now we can see that 'solid'
and 'void'
have been replaced by 'void'
and 'grain'
.