def plot_metric_bubble_chart(
disparity_df,
metrics_list,
attribute,
fairness_threshold=1.25,
chart_height=None,
chart_width=Metric_Chart.full_width,
accessibility_mode=False,
):
"""Draws bubble chart to visualize the values of the selected metrics for a given attribute.
:param disparity_df: a dataframe generated by the Aequitas Bias class
:type disparity_df: pandas.core.frame.DataFrame
:param metrics_list: a list of the metrics of interest
:type metrics_list: list
:param attribute: an attribute to plot
:type attribute: str
:param fairness_threshold: a value for the maximum allowed disparity, defaults to 1.25
:type fairness_threshold: float, optional
:param chart_height: a value (in pixels) for the height of the chart
:type chart_height: int, optional
:param chart_width: a value (in pixels) for the width of the chart
:type chart_width: int, optional
:param accessibility_mode: a switch for the display of more accessible visual elements, defaults to False
:type accessibility_mode: bool, optional
:return: the full metrics chart
:rtype: Altair chart object
"""
(
plot_table,
metrics,
ref_group,
global_scales,
chart_height,
chart_width,
selection,
) = Initializer.prepare_bubble_chart(
disparity_df,
metrics_list,
attribute,
fairness_threshold,
chart_height,
chart_width,
Metric_Chart,
accessibility_mode,
)
# GET MAIN CHART COMPONENTS
main_chart = get_metric_bubble_chart_components(
plot_table,
metrics,
ref_group,
global_scales,
selection,
fairness_threshold,
chart_height,
chart_width,
accessibility_mode,
)
# ADD LEGEND
legend = draw_legend(global_scales, selection, chart_width)
full_chart = main_chart + legend
# FINALIZE CHART
metric_chart = (
full_chart.configure_view(strokeWidth=0)
.configure_axisLeft(
labelFontSize=Metric_Axis.label_font_size,
labelColor=Metric_Axis.label_color,
labelFont=FONT,
)
.properties(
height=chart_height,
width=chart_width,
title=f"Absolute values by {attribute.title()}",
padding=Metric_Chart.full_chart_padding,
)
.configure_title(
align="center",
baseline="middle",
font=FONT,
fontWeight=Chart_Title.font_weight,
fontSize=Chart_Title.font_size,
color=Chart_Title.font_color,
)
.resolve_scale(y="independent", size="independent")
)
return metric_chart
def plot_concatenated_bubble_charts(
disparity_df,
metrics_list,
attribute,
fairness_threshold=1.25,
chart_height=None,
chart_width=Sizes.Concat_Chart.full_width,
accessibility_mode=False,
):
"""Draws a concatenation of the disparity bubble chart and the metric values bubble chart,
of the selected metrics for a given attribute.
:param disparity_df: a dataframe generated by the Aequitas Bias class
:type disparity_df: pandas.core.frame.DataFrame
:param metrics_list: a list of the metrics of interest
:type metrics_list: list
:param attribute: an attribute to plot
:type attribute: str
:param fairness_threshold: a value for the maximum allowed disparity, defaults to 1.25
:type fairness_threshold: float, optional
:param chart_height: a value (in pixels) for the height of the chart
:type chart_height: int, optional
:param chart_width: a value (in pixels) for the width of the chart
:type chart_width: int, optional
:param accessibility_mode: a switch for the display of more accessible visual elements, defaults to False
:type accessibility_mode: bool, optional
:return: the full disparities chart
:rtype: Altair chart object
"""
(
plot_table,
metrics,
ref_group,
global_scales,
chart_height,
chart_width,
selection,
) = Initializer.prepare_bubble_chart(
disparity_df,
metrics_list,
attribute,
fairness_threshold,
chart_height,
chart_width,
Sizes.Disparity_Chart,
accessibility_mode,
)
chart_sizes = __get_chart_sizes(chart_width)
# TITLES
disparity_title = draw_chart_title("DISPARITIES",
chart_sizes["disparity_chart_width"])
metric_title = draw_chart_title("METRICS",
chart_sizes["metric_chart_width"])
# DISPARITY CHART
disparity_chart = ((get_disparity_bubble_chart_components(
plot_table,
metrics,
ref_group,
global_scales,
selection,
fairness_threshold,
chart_height,
chart_sizes["disparity_chart_width"],
accessibility_mode,
concat_chart=True,
) + disparity_title).resolve_scale(
y="independent", size="independent").properties(
height=chart_height, width=chart_sizes["disparity_chart_width"]))
# METRIC CHART
metric_chart = (
(get_metric_bubble_chart_components(
plot_table,
metrics,
ref_group,
global_scales,
selection,
fairness_threshold,
chart_height,
chart_sizes["metric_chart_width"],
accessibility_mode,
concat_chart=True,
) + metric_title +
draw_legend(global_scales, selection,
chart_sizes["metric_chart_width"])).resolve_scale(
y="independent").properties(
height=chart_height,
width=chart_sizes["metric_chart_width"]))
full_chart = (alt.hconcat(
disparity_chart, metric_chart, bounds="flush",
spacing=20).configure_view(strokeWidth=0).configure_axisLeft(
labelFontSize=Metric_Axis.label_font_size,
labelColor=Metric_Axis.label_color,
labelFont=FONT,
))
return full_chart