Classes

Top level classes.

`kSFS`([X, mutation_types, file, n])	Primary class for working with SFS data to infer demography \(\eta(t)\equiv 2N(t)\), or with \(k\)-SFS data to infer demography and mutation spectrum history \(\boldsymbol\mu(t)\).
`eta`(change_points, y)	Demographic history \(\eta(t)\).
`mu`(change_points, Z, mutation_types)	Mutation spectrum history (MuSH) \(\boldsymbol\mu(t)\).

Submodules

Submodules that the main classes rely on, and may be of interest to some users

`optimization`	Optimization algorithms.
`histories`	History objects for representing demography \(\eta(t)\) and MuSH \(\boldsymbol\mu(t)\).
`loss_functions`	Loss functions for measuring goodness of fit.
`utils`	Utility functions.
`composition`	Functions for compositional data analysis.