tabensemb.trainer.Trainer.plot_pdf#

method

Trainer.plot_pdf(feature: str, dist: ~scipy.stats._distn_infrastructure.rv_continuous = <scipy.stats._continuous_distns.norm_gen object>, ax=None, clr: ~typing.Iterable | None = None, imputed: bool = False, figure_kwargs: ~typing.Dict | None = None, plot_kwargs: ~typing.Dict | None = None, select_by_value_kwargs: ~typing.Dict | None = None, savefig_kwargs: ~typing.Dict | None = None, save_show_close: bool = True) Axes[source]#

Plot the probability density function of a feature.

Parameters:
feature

The investigated feature.

dist

The distribution to fit. It should be an instance of scipy.stats.rv_continuous that has fit and pdf methods.

ax

matplotlib.axes.Axes

clr

A seaborn color palette or an Iterable of colors. For example seaborn.color_palette(“deep”).

imputed

Whether the imputed dataset should be considered.

figure_kwargs

Arguments for plt.figure.

plot_kwargs

Arguments for plt.plot

select_by_value_kwargs

Arguments for tabensemb.data.datamodule.DataModule.select_by_value().

savefig_kwargs

Arguments for plt.savefig

save_show_close

Whether to save, show (in the notebook), and close the figure if ax is not given.

Returns:
matplotlib.axes.Axes