exactPotts {bayesImageS}

Calculate the distribution of the Potts model using a brute force algorithm.

Description

Warning: this algorithm is O(k^n) and therefore will not scale for k^n > 2^{31} - 1

Usage

exactPotts(neighbors, blocks, k, beta)

Arguments

neighbors

A matrix of all neighbours in the lattice, one row per pixel.

blocks

A list of pixel indices, dividing the lattice into independent blocks.

k

The number of unique labels.

beta

The inverse temperature parameter of the Potts model.

Value

A list containing the following elements:

expectation

The exact mean of the sufficient statistic.

variance

The exact variance of the sufficient statistic.

exp_PL

Pseudo-likelihood (PL) approximation of the expectation of S(z).

var_PL

PL approx. of the variance of the sufficient statistic.