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A collection of image analysis algorithms for X-ray tomographic images

Project description

What is PoreSpy?

PoreSpy is a collection of algorithms used to extract information from 3D images of porous materials typically obtained from X-ray tomography. The package is still in early alpha stage and is subject to major changes in API.

Examples

One typical use of PoreSpy is to product a chord length distribution which gives an indication of the sizes of the void spaces in the materials {ref Torquato’s book}. This can be accomplished failry easily with PoreSpy using:

# Generate a test image of a sphere pack:
import scipy as sp
import scipy.image as spim
im = sp.rand(40, 40, 40) < 0.997
im = spim.distance_transform_bf(im) >= 4

# Import porespy and use it:
import porespy
a = porespy.cld(im)
cx = a.xdir(spacing=5, trim_edges=True)
cim = a.get_chords(direction='x', spacing=5, trim_edges=True)

# Visualize with Matplotlib
import matplotlib as plt
plt.subplot(2, 2, 1)
plt.imshow(im[:, :, 7])
plt.subplot(2, 2, 3)
plt.imshow(im[:, :, 7]*1.0 - cim[:, :, 7]*0.5)
plt.subplot(2, 2, 2)
plt.plot(cx)
plt.subplot(2, 2, 4)
plt.plot(sp.log10(cx))

Project details


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