pore_size_distribution

pore_size_distribution(im, bins=10, log=True, voxel_size=1)[source]

Calculate a pore-size distribution based on the image produced by the porosimetry or local_thickness functions.

Parameters
  • im (ND-array) – The array of containing the sizes of the largest sphere that overlaps each voxel. Obtained from either porosimetry or local_thickness.

  • bins (scalar or array_like) – Either an array of bin sizes to use, or the number of bins that should be automatically generated that span the data range.

  • log (boolean) – If True (default) the size data is converted to log (base-10) values before processing. This can help to plot wide size distributions or to better visualize the in the small size region. Note that you should not anti-log the radii values in the retunred tuple, since the binning is performed on the logged radii values.

  • voxel_size (scalar) – The size of a voxel side in preferred units. The default is 1, so the user can apply the scaling to the returned results after the fact.

Returns

result – A named-tuple containing the following attributes which can be accessed by name:

R or logR

Radius, equivalent to bin_centers

pdf

Probability density function

cdf

Cumulative density function

satn

Phase saturation in differential form. For the cumulative saturation, just use cfd which is already normalized to 1.

bin_centers

The center point of each bin

bin_edges

Locations of bin divisions, including 1 more value than the number of bins

bin_widths

Useful for passing to the width argument of matplotlib.pyplot.bar

Return type

named_tuple

Notes

(1) To ensure the returned values represent actual sizes you can manually scale the input image by the voxel size first (im *= voxel_size)

plt.bar(psd.R, psd.satn, width=psd.bin_widths, edgecolor=’k’)

Examples

Click here to view online example.