size_to_satn
¶
Converts values of invasion size into a saturation map
import numpy as np
import porespy as ps
import matplotlib.pyplot as plt
from edt import edt
ps.visualization.set_mpl_style()
[01:03:26] ERROR PARDISO solver not installed, run `pip install pypardiso`. Otherwise, _workspace.py:56 simulations will be slow. Apple M chips not supported.
The arguments and default values for this function are:
import inspect
inspect.signature(ps.filters.size_to_satn)
<Signature (size, im=None, bins=None, mode='drainage')>
Generate an image containing invasion sizes using the porosimetry
function:
np.random.seed(0)
im = ps.generators.blobs([200, 200], porosity=0.5)
inv = ps.filters.porosimetry(im)
size
¶
The sizes are produced by porosimetry
for instance:
satn = ps.filters.size_to_satn(size=inv)
fig, ax = plt.subplots(1, 2, figsize=[12, 6])
ax[0].imshow(inv/im, origin='lower', interpolation='none')
ax[0].set_title('Invasion map by size')
ax[0].axis(False)
ax[1].imshow(satn/im, origin='lower', interpolation='none')
ax[1].set_title('Invasion map by saturation')
ax[1].axis(False);
The saturation map makes it very easy to obtain a desired fluid configuration just by applying a threhold:
fig, ax = plt.subplots(1, 2, figsize=[12, 6])
s = 0.3
ax[0].imshow((satn < s)*(satn > 0)/im, origin='lower', interpolation='none')
ax[0].set_title(f'saturation = {s}')
ax[0].axis(False)
s = 0.6
ax[1].imshow((satn < s)*(satn > 0)/im, origin='lower', interpolation='none')
ax[1].set_title(f'saturation = {s}')
ax[1].axis(False);
im
¶
The boolean image can be optionally passed into so that uninvaded regions can be differentiated from solid (if both are labelled 0).
fig, ax = plt.subplots(1, 2, figsize=[12, 6])
satn = ps.filters.size_to_satn(size=inv)
ax[0].imshow(satn, origin='lower', interpolation='none')
ax[0].set_title('Invasion map by size')
ax[0].axis(False)
satn = ps.filters.size_to_satn(size=inv, im=im)
ax[1].imshow(satn, origin='lower', interpolation='none')
ax[1].set_title('Invasion map by saturation')
ax[1].axis(False);
The different between the two images above is that when im
is not supplied, then uninvaded regions are given a lable of 0, matching solid. When im
is supplied, the uninvaded regions are labelled -1.
bins
¶
The number of sequence values to when converting sizes. The default is 25.
fig, ax = plt.subplots(1, 2, figsize=[12, 6])
bins = 5
seq = ps.filters.size_to_satn(size=inv, bins=bins)
ax[0].imshow(seq, origin='lower', interpolation='none')
ax[0].set_title(f'bins = {bins}')
ax[0].axis(False)
bins = 25
seq = ps.filters.size_to_satn(size=inv, bins=bins)
ax[1].imshow(seq, origin='lower', interpolation='none')
ax[1].set_title(f'bins = {bins}')
ax[1].axis(False);