pairs_posterior

bayesflow.diagnostics.pairs_posterior(estimates: dict[str, ndarray] | ndarray, targets: dict[str, ndarray] | ndarray = None, priors: dict[str, ndarray] | ndarray = None, dataset_id: int = None, variable_keys: Sequence[str] = None, variable_names: Sequence[str] = None, height: int = 3, post_color: str | tuple = '#132a70', prior_color: str | tuple = 'gray', alpha=0.9, label_fontsize: int = 14, tick_fontsize: int = 12, legend_fontsize: int = 14, **kwargs) → PairGrid

Generates a bivariate pair plot given posterior draws and optional prior or prior draws.

Parameters:

estimatesnp.ndarray of shape (n_post_draws, n_params)

The posterior draws obtained for a SINGLE observed data set.

targetsnp.ndarray of shape (n_params,) or None, optional, default: None

Optional true parameter values that have generated the observed dataset.

priorsnp.ndarray of shape (n_prior_draws, n_params) or None, optional (default: None)

Optional prior samples obtained from the prior.

dataset_id: Optional ID of the dataset for whose posterior the pairs plot shall be generated.

Should only be specified if estimates contains posterior draws from multiple datasets.

variable_keyslist or None, optional, default: None

Select keys from the dictionary provided in samples. By default, select all keys.

variable_nameslist or None, optional, default: None

The parameter names for nice plot titles. Inferred if None

heightfloat, optional, default: 3

The height of the pairplot

label_fontsizeint, optional, default: 14

The font size of the x and y-label texts (parameter names)

tick_fontsizeint, optional, default: 12

The font size of the axis ticklabels

legend_fontsizeint, optional, default: 16

The font size of the legend text

post_colorstr, optional, default: ‘#132a70’

The color for the posterior histograms and KDEs

priors_colorstr, optional, default: gray

The color for the optional prior histograms and KDEs

post_alphafloat in [0, 1], optional, default: 0.9

The opacity of the posterior plots

prior_alphafloat in [0, 1], optional, default: 0.7

The opacity of the prior plots

**kwargsdict, optional, default: {}

Further optional keyword arguments propagated to _pairs_samples

Returns:

fplt.Figure - the figure instance for optional saving

Raises:

AssertionError

If the shape of posterior_draws is not 2-dimensional.