porespy.beta

Functions

df_to_tortuosity(im, df)	Compute the tortuosity of a network populated with diffusive conductance values
fibers_1D(shape, r, n[, overlap])	Generates randomly located fibers which are all oriented in z-direction
fibers_2D(shape, r[, n, porosity])	Generates randomly located fibers which are randomly oriented in the x-y plane
flux(c, axis[, k])	Computes the layer-by-layer diffusive flux in a given direction.
get_block_sizes(im[, block_size_range])	Finds all viable block sizes between lower and upper limits
gyroid(shape[, method, skew, phi])	Generate a boolean image of a triply periodic minimal surface (TPMS).
local_diff(vals, im[, strel])	Computes the difference pixel and the average of it's neighbors.
polydisperse_cylinders(shape, porosity, dist[, ...])	Generates overlapping cylinders with radii from the given size distribution
pts_to_voronoi(im[, r, centroids, borders])	Compute a Voronoi tessellation from seed points via watershed.
rev_tortuosity(im[, block_sizes, use_dask])	Generates the data for creating an REV plot based on tortuosity.
tau_from_cmap(c, im, axis)	Computes the tortuosity factor from a concentration field.
tile(im, n[, mode])	Tile a TPMS image to create a larger domain.
tortuosity_bt(im[, block_size, method, use_dask])	Computes the tortuosity of an image in all directions
vor_to_im(vor, im[, centroids])	Render a 2-D Voronoi tessellation onto a boolean image.