graph.rst

Graphs

The code is a Python package containing classes and functions for estimating integrals using various sampling algorithms. The Integral class in the package caches samples and evaluates the integral given a hyperparameter psi. It takes two callable arguments: data_given_theta, which is the joint probability of the observed data viewed as a function of parameter, and theta_given_psi, which is the conditional probability of parameters theta given hyperparameter psi. The method parameter specifies the type of sampling algorithm to use, and the options parameter is a dictionary of options for the sampling algorithm.

The package contains several sampling algorithms implemented as functions, including metropolis and langevin. metropolis is a Metropolis sampler, which takes as arguments a function that calculates the unnormalized density or log unnormalized probability, the number of samples to draw, the initial point, the scale of the proposal distribution, and a boolean indicating whether to assume log-probability. langevin is a Metropolis-adjusted Langevin (MALA) sampler, which takes as arguments a function that calculates the unnormalized density or log unnormalized probability, the number of samples to draw, the initial point, the gradient of the log unnormalized probability, the standard deviation of the proposal distribution, and a boolean indicating whether to assume log-probability.

Summary

.. autosummary::
   graph.cmaes
   graph.Integral
   graph.korali
   graph.metropolis
   graph.tmcmc

Functions

.. autoclass:: graph.Integral
               :special-members: __call__

.. autofunction:: graph.cmaes

.. autofunction:: graph.korali

.. autofunction:: graph.metropolis

.. autofunction:: graph.tmcmc