porespy.metrics.rev_tortuosity#

porespy.metrics.rev_tortuosity(im, n=100, axis=None, slices=None, dask_on=False)#

Calculates the tortuosity for a range of subdomain sizes suitable for an REV plot

Parameters:

im (ndarray) – The binary image to analyze with True indicating the phase of interest
n (int, default = 1000) – The number of random blocks to analyze. If slices are provided this is ignored.
slices (list) – A list of slice objects into the image which define the subdomains. If not provided then n random blocks are used.
axis (int) – The axis along which to simulate the diffusion. If None then all axes are considered.

Returns:

df – A pandas data frame with the properties for each block on a given row

Attribute	Description
eps_orig	The original porosity of the subdomain tested
eps_perc	The porosity of the subdomain after filling non-percolating paths (e.g. blind and closed pores). This is the domain on which the calculation of tortuosity is performed.
g	The calculated diffusive conductance for the subdomain tested
tau	The calculated tortuosity for the tested subdomain
volume	The total volume of each cubic subdomain tested
length	The length of one side of the subdomain tested
axis	The axis for which the above properties were calculated
time	The elapsed time required to perform the calculations
slice	The coordinates for the subdomain tested in the original image

Return type:

DataFrame

Notes

If both block_sizes and slices are left empty, the default mode of block generation is gridding the image.