Class problem_definition

x.__init__(...) initializes x; see help(type(x)) for signature

Overrides: object.__init__

(inherited documentation)

Compute the log of the probability density at x.

Parameters:

• x - a parameter vector

Returns: float

The log of the probability that the model assigns to parameters x.

Raises:

• NotGoodPosition - This exception is used to indicate that the position x is not valid. This is equivalent to returning an extremely negative logp.

Overrides: mcmc.problem_definition.logp

(inherited documentation)

Only define this if you can compute the actual probability density for the data given model & parameters, not just something proportional to it! To do this function, you need to be able to do the full multidimensional integral over the probability distribution!

NOTE that x is an indexer! NOTE that this is not the full logp function: it doesn't contain the prior!

This is called on each candidate position vector. Generally, it is used to restrict the possible solution space by folding position vectors that escape outside the solution space back into the solution space. It can also allow for symmetries in equations.

Formally, it defines a convex region. All vectors outside the region are mapped into the region, and the mapping must be continuous at the boundary. (More precisely, logp(fixer(x)) must be continuous everywhere that logp(x) is continuous, including the boundary.) For instance, mapping x[0] into abs(x[0]) defines a convex region (the positive half-space), and the mapping is continuous near x[0]=0.

Additionally, it may re-normalize parameters at will subject to the restriction that logp(fixer(x))==logp(x). For instance, it can implement a constraint that sum(x)==0 by mapping x into x - average(x), so long as the value of logp() is unaffected by that substitution. Other folds can sometimes lead to problems.

Parameters:

• x - a parameter vector

Returns: numpy.ndarray

a (possibly modified) parameter vector.

Raises:

• NotGoodPosition - This exception is used to indicate that the position x is not valid. Fixer has the option of either mapping invalid parameter vectors into valid ones or raising this exception.

Overrides: mcmc.problem_definition.fixer

(inherited documentation)