fairlearn.metrics._plotter.plot_metric_frame

fairlearn.metrics._plotter.plot_metric_frame(metric_frame, *, kind='point', metrics=None, conf_intervals=None, subplots=True, plot_ci_labels=False, ci_labels_precision=4, ci_labels_fontsize=8, ci_labels_color='black', ci_labels_ha='center', ci_labels_legend='Conf. Intervals', **kwargs)

Visualization for metrics with and without confidence intervals.

Plots a given metric and its given error (as described by conf_intervals)

This function takes in a fairlearn.metrics.MetricFrame with precomputed metrics and metric errors and a conf_intervals array to interpret the columns of the fairlearn.metrics.MetricFrame.

The items at each index of the given metrics array and given errors or conf_intervals array should correspond to a pair of the same metric and metric error, respectively.

Parameters:

metric_framefairlearn.metrics.MetricFrame

The collection of disaggregated metric values, along with the metric errors.

kindstr, default=”point”

The type of plot to display, e.g., “point”, “bar”, “line”, etc. The supported values are “point” and those listed in pandas.DataFrame.plot()

metricsstr or list of str

The name of the metrics to plot. Should match columns from the given fairlearn.metrics.MetricFrame.

conf_intervalsstr or list of str

The name of the confidence intervals to plot. Should match columns from the given fairlearn.metrics.MetricFrame.

Note:

The return of the error function should be an array of the lower and upper bounds. e.g. [0.59, 0.62]

subplotsbool, default=True

Whether or not to plot metrics on separate subplots

plot_ci_labelsbool, default=False

Whether or not to plot numerical labels for the confidence intervals

ci_labels_precisionint, default=4

The number of digits of precision to show for confidence interval labels

ci_labels_fontsizeint, default=8

The font size to use for confidence interval labels

ci_labels_colorstr, default=”black”

The font color to use for confidence interval labels

ci_labels_hastr, default=”center”

The horizontal alignment modifier to use for confidence interval labels

ci_labels_legendstr, default=”Conf. Intervals”

The label corresponding to the confidence interval bars

**kwargs

Keyword arguments that are passed in to pandas.DataFrame.plot()

Returns:

matplotlib.axes.Axes or numpy.ndarray of them