apply_chords_3D

Adds chords to the void space in all three principle directions. The chords are seprated by 1 voxel plus the provided spacing. Chords in the X, Y and Z directions are labelled 1, 2 and 3 resepctively.

import numpy as np
import porespy as ps
import scipy.ndimage as spim
import matplotlib.pyplot as plt
ps.visualization.set_mpl_style()

/opt/hostedtoolcache/Python/3.8.16/x64/lib/python3.8/site-packages/openpnm/algorithms/_invasion_percolation.py:358: NumbaDeprecationWarning: The 'nopython' keyword argument was not supplied to the 'numba.jit' decorator. The implicit default value for this argument is currently False, but it will be changed to True in Numba 0.59.0. See https://numba.readthedocs.io/en/stable/reference/deprecation.html#deprecation-of-object-mode-fall-back-behaviour-when-using-jit for details.
  def _find_trapped_pores(inv_seq, indices, indptr, outlets):  # pragma: no cover

import inspect
print(inspect.signature(ps.filters.apply_chords_3D))

(im, spacing=0, trim_edges=True)

im

The function takes a boolean image with True values indicating the void space, or phase of interest.

im = ps.generators.blobs(shape=[50, 50, 50])
chords = ps.filters.apply_chords_3D(im)

fig, ax = plt.subplots(1, 2, figsize=[12, 6])
ax[0].imshow(chords[20, ...] + ~im[20, ...]*4)
ax[0].axis(False)
ax[1].imshow(chords[22, ...] + ~im[22, ...]*4)
ax[1].axis(False);

The chords in each direction are given different integer values so they can isolated by thresholding.

fig, ax = plt.subplots(1, 1, figsize=[6, 6])
ax.imshow(chords[20, ...] ==2)
ax.axis(False);

spacing

By default the chords are drown with a spacing of 1 voxel between each orientation to provide the maximum number of chords. This can be adjusted to create few chords if the image is very large if needed.

c1 = ps.filters.apply_chords_3D(im, spacing=1)
c3 = ps.filters.apply_chords_3D(im, spacing=3)

fig, ax = plt.subplots(1, 2, figsize=[12, 6])
ax[0].imshow(c1[20, ...] + ~im[20, ...]*4)
ax[0].axis(False)
ax[1].imshow(c3[30, ...] + ~im[30, ...]*4)
ax[1].axis(False);

trim_edges

c1 = ps.filters.apply_chords_3D(im, trim_edges=False)
c2 = ps.filters.apply_chords_3D(im, trim_edges=True)

fig, ax = plt.subplots(1, 2, figsize=[12, 6])
ax[0].imshow(c1[20, ...] + ~im[20, ...]*4)
ax[0].axis(False)
ax[0].set_title('trim_edges = False')
ax[1].imshow(c2[20, ...] + ~im[20, ...]*4)
ax[1].axis(False)
ax[1].set_title('trim_edges = True');