def get_metric_bubble_chart_components(
plot_table,
metrics,
ref_group,
global_scales,
selection,
fairness_threshold,
chart_height,
chart_width,
accessibility_mode=False,
concat_chart=False,
):
"""Creates the components necessary to plot the metric chart."""
# COMPUTE SCALED DISPARITIES
for metric in metrics:
plot_table[f"{metric}_disparity_scaled"] = plot_table.apply(
lambda row: transform_ratio(row[f"{metric}_disparity"]), axis=1)
# POSITION SCALES
position_scales = __get_position_scales(metrics, chart_height, chart_width,
concat_chart)
scales = dict(global_scales, **position_scales)
# RULES
horizontal_rules = __draw_metrics_rules(metrics, scales, concat_chart)
vertical_domain_rules = __draw_domain_rules(scales)
# LABELS
x_ticks_labels = __draw_x_ticks_labels(scales, chart_height)
# BUBBLES - CENTERS & AREAS
bubbles = __draw_bubbles(
plot_table,
metrics,
ref_group,
scales,
selection,
)
# THRESHOLD, BANDS & ANNOTATION
if fairness_threshold is not None:
threshold_elements = __get_threshold_elements(
plot_table,
metrics,
fairness_threshold,
ref_group,
scales,
chart_height,
concat_chart,
accessibility_mode,
)
# ASSEMBLE CHART WITH THRESHOLD
main_chart = (horizontal_rules + vertical_domain_rules +
x_ticks_labels + threshold_elements + bubbles)
# ASSEMBLE CHART WITHOUT THRESHOLD
else:
main_chart = horizontal_rules + vertical_domain_rules + x_ticks_labels + bubbles
return main_chart
def __create_disparity_variables(attribute_df, metric, fairness_threshold):
""" Creates scaled disparity, parity test result & disparity explanation tooltip variables. """
# SCALED DISPARITY VALUE
attribute_df[f"{metric}_disparity_scaled"] = attribute_df.apply(
lambda row: transform_ratio(row[f"{metric}_disparity"]), axis=1)
# PARITY RESULT
attribute_df[f"{metric}_parity_result"] = attribute_df.apply(
__get_parity_result_variable,
metric=metric,
fairness_threshold=fairness_threshold,
axis=1,
)