Rosenbrock function¶
- class pints.toy.RosenbrockError[source]¶
Error measure based on the rosenbrock function [1].
\[f(x,y) = (1 - x)^2 + 100(y - x^2)^2\]Extends
pints.ErrorMeasure
.References
- evaluateS1(x)¶
Evaluates this error measure, and returns the result plus the partial derivatives of the result with respect to the parameters.
The returned data has the shape
(e, e')
wheree
is a scalar value ande'
is a sequence of lengthn_parameters
.This is an optional method that is not always implemented.
- class pints.toy.RosenbrockLogPDF[source]¶
Unnormalised LogPDF based on the Rosenbrock function [2] with an addition of 1 on the denominator to avoid a discontinuity:
\[f(x,y) = -log[1 + (1 - x)^2 + 100(y - x^2)^2 ]\]Extends
pints.toy.ToyLogPDF
.References
[2] - distance(samples)[source]¶
Calculates a measure of normed distance of samples from exact mean and covariance matrix assuming uniform prior with bounds given by
suggested_bounds()
.
- sample(n_samples)¶
Generates independent samples from the underlying distribution.