map_to_regions#

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

[1]:
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#

[2]:
im = ps.generators.blobs(shape=[400, 400], porosity=0.6)
ps.imshow(im);
snow_output = ps.networks.snow2(im, voxel_size=1)
try:
    pn, geo = op.io.PoreSpy.import_data(snow_output.network)
except AttributeError:
    pn, geo = op.io.from_porespy(snow_output.network)
../../../_images/examples_networks_reference_map_to_regions_3_5.svg

Plot the pore network#

[3]:
fig, ax = plt.subplots()
op.topotools.plot_connections(pn, c='w', linewidth=2, ax=ax)
op.topotools.plot_coordinates(pn, c='w', s=100, ax=ax)
plt.imshow(snow_output.regions.T, origin='lower')
plt.axis('off');
../../../_images/examples_networks_reference_map_to_regions_5_0.svg

Now assign some values to the network:

[4]:
pn['pore.values'] = np.random.rand(pn.Np)

And now assign these values to the image regions:

[5]:
reg = ps.networks.map_to_regions(regions=snow_output.regions.T, values=pn['pore.values'])
plt.imshow(reg)
[5]:
<matplotlib.image.AxesImage at 0x7f6a94541310>
../../../_images/examples_networks_reference_map_to_regions_9_1.svg