Boundaries

Simple boundaries for an optimisation can be created using RectangularBoundaries. More complex types can be made using LogPDFBoundaries or a custom implementation of the Boundaries interface.

Overview:

• Boundaries
• LogPDFBoundaries
• RectangularBoundaries

class pints.Boundaries

Abstract class representing boundaries on a parameter space.

check(parameters)

Returns True if and only if the given point in parameter space is within the boundaries.

Parameters:parameters – A point in parameter space

n_parameters()

Returns the dimension of the parameter space these boundaries are defined on.

sample(n=1)

Returns n random samples from within the boundaries, for example to use as starting points for an optimisation.

The returned value is a NumPy array with shape (n, d) where n is the requested number of samples, and d is the dimension of the parameter space these boundaries are defined on.

Note that implementing :meth:`sample()` is optional, so some boundary types may not support it.

Parameters:n (int) – The number of points to sample

class pints.LogPDFBoundaries(log_pdf, threshold=-inf)

Uses a pints.LogPDF (e.g. a LogPrior) as boundaries), accepting log-likelihoods above a given threshold as within bounds.

For a pints.LogPrior based on pints.Boundaries, see pints.UniformLogPrior.

Extends pints.Boundaries.

Parameters:

• log_pdf – A pints.LogPdf to use.
• threshold – A threshold to determine whether a given log-prior value counts as within bounds. Anything _above_ the threshold counts as within bounds.

check(parameters)

See pints.Boundaries.check().

n_parameters()

See pints.Boundaries.n_parameters().

sample(n=1)

See pints.Boundaries.sample().

Note: This method is implemented only when the error measure is based on a pints.LogPrior that supports sampling.

class pints.RectangularBoundaries(lower, upper)

Represents a set of lower and upper boundaries for model parameters.

A point x is considered within the boundaries if (and only if) lower <= x < upper.

Extends pints.Boundaries.

Parameters:

• lower – A 1d array of lower boundaries.
• upper – The corresponding upper boundaries

check(parameters)

See pints.Boundaries.check().

lower()

Returns the lower boundaries for all parameters (as a read-only NumPy array).

n_parameters()

See pints.Boundaries.n_parameters().

range()

Returns the size of the parameter space (i.e. upper - lower).

sample(n=1)

See pints.Boundaries.sample().

upper()

Returns the upper boundary for all parameters (as a read-only NumPy array).