Benchmark multi-model/multi-view models.

Note

This page is a reference documentation. It only explains the function signature, and not how to use it. Please refer to the gallery for the big picture.

mmbench.plotting.plot_bar(key, rsa, ax=None, figsize=(5, 2), dpi=300, fontsize=16, fontsize_star=25, fontweight='bold', line_width=2.5, marker_size=0.1, title=None, palette='Spectral', report_t=False, do_pairwise_stars=False, do_one_sample_stars=True, yname='model fit (r)')[source]¶

Display results with bar plots.

Parameters

key : str

the analysis identifier.

rsa : dict of dict

the sampling data with the analysis identifiers as first key and experimental conditions as second key.

ax : matplotlib.axes.Axes, default None

the axes used to display the plot.

figsize : (float, float), default (5, 2)

width, height in inches.

dpi : float, default 300

the resolution of the figure in dots-per-inch.

fontsize : int or str, default 16

size in points or relative size, e.g., ‘smaller’, ‘x-large’.

fontsize_star : int or str, default 25

size in points or relative size, e.g., ‘smaller’, ‘x-large’ used to display pairwise statistics.

fontweight : str, default ‘bold’

the font weight, e.g. ‘normal’, ‘bold’, ‘heavy’, ‘light’, ‘ultrabold’ or ‘ultralight’.

line_width : int, default 2.5

the bar plot line width.

marker_size : int, default .1

the sampling scatter plot marker size.

title : str, default None

the title displayed on the figure.

palette : palette name, list, or dict

colors to use for the different levels of the hue variable. Should be something that can be interpreted by color_palette(), or a dictionary mapping hue levels to matplotlib colors.

report_t : bool, default False

optionally, generate a report with pairwise statistics.

do_pairwise_stars : bool, default False

optionally, display pairwise statistics.

do_one_sample_stars : bool, default True

optionally, display sampling statistics.

yname : str, default ‘model fit (r)’

optionally, name of the metric on y-axis.

Returns

pairwise_stat_df : pandas.DataFrame or None

the generated pairwise statistics.