pybop.plot.distribution#

Functions#

distribution(parameters[, posterior, title, ...])

Plot the posterior on top of the prior distribution for a Bayesian optimisation result.

Module Contents#

pybop.plot.distribution.distribution(parameters: pybop.parameters.parameter.Parameters, posterior: pybop.parameters.parameter.Parameters | None = None, title: str = 'Prior and Posterior Distributions', n_samples: int = 100, transformed: bool = False, show: bool = True, backend: str = None, figures=None, axes=None)[source]#

Plot the posterior on top of the prior distribution for a Bayesian optimisation result.

Parameters:

  • parameters (pybop.Parameters) – The prior distribution of the parameters.

  • posterior (pybop.Parameters, optional) – The posterior distribution of the parameters (default: None).

  • title (str, optional) – The title of the figure (default: “Prior and Posterior Distributions”).

  • n_samples (int, optional) – The number of samples to use for plotting the distributions (default: 100).

  • transformed (bool, optional) – If True, the transformed distributions are plotted (default: False).

  • show (bool, optional) – If True, the figure is shown upon creation (default: True).

  • backend (str or pybop.plot.backends.PlotBackend, optional) – Select a plotting backend. If None, the current default backend is used.

  • figures (figure object, optional) – Figure for plotting. If not provided a new figure is created. Can be a single figure or one figure per parameter.

  • axes (axis, optional) – The axes to be used for plotting. One axis per parameter is expected. plotly: axes expected to be of the form list of tuple(row, col)

Returns:

  • fig (if show is False; plotly.graph_objs.Figure or matplotlib.figure.Figure) – The figure object for the distribution plot. Returns a list of figures if multiple figures are provided for plotting.

  • None (if show is True)