metrics

Collection of functions for extracting quantitative information from images

This submodule contains functions for determining key metrics about an image. Typically these are applied to an image after applying a filter, but a few functions can be applied directly to the binary image.

metrics.boxcount(im[, bins])	Calculates the fractal dimension of an image using the tiled box counting method [1]_
metrics.chord_counts(im)	Find the length of each chord in the supplied image
metrics.chord_length_distribution(im[, ...])	Determines the distribution of chord lengths in an image containing chords.
metrics.find_h(saturation[, position, srange])	Given a saturation profile, compute the height between given bounds
metrics.lineal_path_distribution(im[, bins, ...])	Determines the probability that a point lies within a certain distance of the opposite phase along a specified direction
metrics.mesh_surface_area([mesh, verts, faces])	Calculate the surface area of a meshed region
metrics.mesh_volume(region[, voxel_size])	Compute the volume of a single region by meshing it
metrics.pc_curve(im, pc[, seq])	Produces a Pc-Snwp curve given a map of meniscus radii or capillary pressures at which each voxel was invaded
metrics.phase_fraction(im[, normed])	Calculate the fraction of each phase in an image
metrics.pore_size_distribution(im[, bins, ...])	Calculate a pore-size distribution based on the image produced by the porosimetry or local_thickness functions.
metrics.porosity(im)	Calculates the porosity of an image assuming 1's are void space and 0's are solid phase.
metrics.porosity_profile(im[, axis])	Computes the porosity profile along the specified axis
metrics.prop_to_image(regionprops, shape, prop)	Create an image with each region colored according the specified prop, as obtained by regionprops_3d.
metrics.props_to_DataFrame(regionprops)	Create a pandas DataFrame containing all the scalar metrics for each region, such as volume, sphericity, and so on, calculated by regionprops_3D.
metrics.radial_density_distribution(dt[, ...])	Computes radial density function by analyzing the histogram of voxel values in the distance transform.
metrics.region_interface_areas(regions, areas)	Calculate the interfacial area between all pairs of adjecent regions
metrics.region_surface_areas(regions[, ...])	Extract the surface area of each region in a labeled image.
metrics.region_volumes(regions[, mode, ...])	Compute volume of each labelled region in an image
metrics.regionprops_3D(im)	Calculates various metrics for each labeled region in a 3D image.
metrics.representative_elementary_volume(im)	Calculates the porosity of an image as a function subdomain size.
metrics.satn_profile(satn[, s, im, axis, ...])	Computes a saturation profile from an image of fluid invasion
metrics.two_point_correlation(im[, ...])	Calculate the two-point correlation function using Fourier transforms