boxcount
¶
A method for measuring the fractal dimension of an image
import matplotlib.pyplot as plt
import numpy as np
import porespy as ps
[01:03:10] 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 their defaults for this function are:
import inspect
inspect.signature(ps.metrics.boxcount)
<Signature (im, bins=10)>
im = ps.generators.sierpinski_foam(dmin=5, n=5, ndim=2)
fig, ax = plt.subplots(1, 1, figsize=[6, 6])
ax.imshow(im, interpolation='none', origin='lower')
ax.axis(False);
im
¶
The image which is to be analzyed. Can be 2D or 3D.
b = ps.metrics.boxcount(im=im)
print(b)
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Results of boxcount generated at Mon Sep 16 01:03:12 2024
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size Array of size (10,)
count [np.int64(6505), np.int64(4095), np.int64(1435), np.int64(552), np.int64(206), np.int64(77), np.int64(24), np.int64(9), np.int64(4), np.int64(1)]
slope Array of size (10,)
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The returned object is like a dataclass with each computed value stored in an attribute. The result can be printed for inspection. The results can also be plotted as follows:
fig, ax = plt.subplots(1, 2, figsize=[12, 6])
ax[0].loglog(b.size, b.count)
ax[0].set_xlabel('box length')
ax[0].set_ylabel('number of partially filled boxes')
ax[1].semilogx(b.size, b.slope)
ax[1].plot([0, 1000], [1.9, 1.9])
ax[1].set_xlabel('box length')
ax[1].set_ylabel('slope')
ax[1].set_ylim([0, 3]);
bins
¶
The box sizes to use. The default is 10. If an integer is given it computes the range of box sizes. If an array is given, these are used directly
b = ps.metrics.boxcount(im=im, bins=20)
fig, ax = plt.subplots(1, 2, figsize=[12, 6])
ax[0].loglog(b.size, b.count)
ax[0].set_xlabel('box length')
ax[0].set_ylabel('number of partially filled boxes')
ax[1].semilogx(b.size, b.slope)
ax[1].plot([0, 1000], [1.9, 1.9])
ax[1].set_xlabel('box length')
ax[1].set_ylabel('slope')
ax[1].set_ylim([0, 3]);