map_to_regions#

Maps pore values from a network onto the image from which it was extracted

import numpy as np
import porespy as ps
import openpnm as op
import matplotlib.pyplot as plt

ws = op.Workspace()
ws.settings['loglevel'] = 50
np.random.seed(10)
ps.visualization.set_mpl_style()

Create image and extract network#

im = ps.generators.blobs(shape=[400, 400], porosity=0.6)
ps.imshow(im);
snow_output = ps.networks.snow2(im, voxel_size=1)
pn = op.io.network_from_porespy(snow_output.network)
../../../_images/5b96ad897297cc4f2b8d6e41c2c985dac53d4927a49831e2f16230e5a9f10ec7.png

Plot the pore network#

fig, ax = plt.subplots()
op.visualization.plot_connections(pn, c='w', linewidth=2, ax=ax)
op.visualization.plot_coordinates(pn, c='w', s=100, ax=ax)
plt.imshow(snow_output.regions.T, origin='lower')
plt.axis('off');
../../../_images/c84680a0530ac2f3f18ea26c3ddc53af8deb4e0901432d98fd2e48dca54a1a9c.png

Now assign some values to the network:

pn['pore.values'] = np.random.rand(pn.Np)

And now assign these values to the image regions:

reg = ps.networks.map_to_regions(regions=snow_output.regions.T, values=pn['pore.values'])
plt.imshow(reg, origin='lower');
../../../_images/72993b26d6f99b152be7bb9b6f8db00f366c459d32495543a63a45b49fc4df6a.png