dynode.utils.vis_utils.plot_prior_distributions

dynode.utils.vis_utils.plot_prior_distributions(priors: dict[str, Any], matplotlib_style: list[str] | str = ['seaborn-v0_8-colorblind'], num_samples=5000, hist_kwargs={'bins': 50, 'density': True}, median_line_kwargs={'label': 'prior median', 'linestyle': 'dotted', 'linewidth': 3}) → Figure

Visualize prior distributions by sampling from them and plotting the results.

Parameters

priorsdict[str, Any]

Dictionary with string keys and distribution objects as values. Each key with a distribution object will be included in the plot.

matplotlib_stylelist[str] | str, optional

Matplotlib style to use for plotting; default is [“seaborn-v0_8-colorblind”].

num_samplesint, optional

Number of times to sample each distribution; default is 5000.

hist_kwargsdict[str: Any]

Additional kwargs passed to plt.hist(); default is {“bins”: 50}.

Returns

plt.Figure

Matplotlib figure containing all distribution keys found within priors.