xray

Visualize a 3D image as a 2D image in the style of an xray radiograph, with the brightness corresponding inversely to the amount of material the xray passed through.

import porespy as ps
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

Create a test image of fibers since the orientation is useful for visualization:

im = ps.generators.cylinders(shape=[200, 200, 200], r=6, porosity=0.7)
fig, ax = plt.subplots(1, 3, figsize=[8, 12])
ax[0].imshow(im[50, :, :])
ax[0].axis(False)
ax[1].imshow(im[:, 50, :])
ax[1].axis(False)
ax[2].imshow(im[:, :, 50])
ax[2].axis(False);

axis

The default behavior is the view the sample as though the xrays passed along the x-axis, but this is adjustable:

fig, ax = plt.subplots(1, 3, figsize=[8, 12])

im1 = ps.visualization.xray(im)
ax[0].imshow(im1, cmap=plt.cm.plasma)
ax[0].axis(False)

im2 = ps.visualization.xray(im, axis=1)
ax[1].imshow(im2, cmap=plt.cm.nipy_spectral)
ax[1].axis(False)

im2 = ps.visualization.xray(im, axis=2)
ax[2].imshow(im2, cmap=plt.cm.bone)
ax[2].axis(False);