kliff.uq.mcmc

kliff.uq.mcmc.logprior_uniform(x, bounds)[source]

Logarithm of the non-normalized joint uniform prior.

This is the default prior distribution.

Parameters:

  • x (ndarray) – (ndim,) Parameter values to evaluate.

  • bounds (ndarray) – (ndim, 2,) An array containing the boundaries of the uniform prior. The first column of the array contains the lower bounds and the second column contains the upper bounds.

Return type:

float

Returns:

Logarithm of the non-normalized joint uniform prior evaluated at parameter x.

kliff.uq.mcmc.get_T0(loss)[source]

Compute the natural temperature.

The minimum loss is the loss value at the optimal parameters.

Parameters:

loss (Loss) – Loss function class from Loss.

Return type:

float

Returns:

Value of the natural temperature.

class kliff.uq.mcmc.MCMC(loss: Loss, nwalkers: int | None = None, logprior_fn: Callable | None = None, logprior_args: tuple | None = None, sampler: str | None = 'ptemcee', **kwargs)[source]

MCMC sampler class for Bayesian uncertainty quantification.

This is a wrapper over PtemceeSampler and EmceeSampler. Currently, only these 2 samplers implemented.

Parameters:

  • loss – Loss function class from Loss.

  • nwalkers – Number of walkers to simulate. The minimum number of walkers is twice

  • value. (the number of parameters. It defaults to this minimum)

  • logprior_fn – A function that evaluate logarithm of the prior distribution. The prior doesn’t need to be normalized. It defaults to a uniform prior over a finite range.

  • logprior_args – Additional positional arguments of the logprior_fn. If the default logprior_fn is used, then the boundaries of the uniform prior can be specified here.

  • sampler – An argument that specifies the MCMC sampler to use. The value can be one of the strings "ptemcee" (the default value) or "emcee", or a sampler class instance. If "ptemcee" or "emcee" is given, a respective internal sampler class will be uses.

  • **kwargs – Additional keyword arguments for ptemcee.Sampler or emcee.EnsembleSampler.

builtin_samplers = ['ptemcee', 'emcee']
exception kliff.uq.mcmc.MCMCError(msg)[source]