pairs_samples#

bayesflow.diagnostics.pairs_samples(samples: dict[str, ndarray] | ndarray = None, variable_keys: Sequence[str] = None, variable_names: Sequence[str] = None, height: float = 2.5, color: str | tuple = '#132a70', alpha: float = 0.9, label_fontsize: int = 14, tick_fontsize: int = 12, **kwargs) → PairGrid[source]#

A more flexible pair plot function for multiple distributions based upon collected samples.

Parameters:

samplesdict[str, Tensor], default: None: Sample draws from any dataset
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: 2.5: The height of the pair plot
colorstr, optional, default‘#8f2727’: The color of the plot
alphafloat in [0, 1], optional, default: 0.9: The opacity of the plot
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
**kwargsdict, optional: Additional keyword arguments passed to the sns.PairGrid constructor