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Visualization methods

Methods for visualizing evaluations results:

Radar Plot

evaluate.visualization.radar_plot

< >

( data model_names invert_range = [] config = None fig = None )

Parameters

  • data (List[dict]) — the results (list of metric + value pairs). E.g. data = [{“accuracy”: 0.9, “precision”:0.8},{“accuracy”: 0.7, “precision”:0.6}]
  • names (List[dict]) — model names. E.g. names = [“model1”, “model 2”, …]
  • invert_range (List[dict], optional) — the metrics to invert (in cases when smaller is better, e.g. speed) E.g. invert_range=[“latency_in_seconds”]
  • config (dict, optional) — a specification of the formatting configurations, namely:

    • rad_ln_args (dict, default {"visible": True}): The visibility of the radial (circle) lines.

    • outer_ring (dict, default {"visible": True}): The visibility of the outer ring.

    • angle_ln_args (dict, default {"visible": True}): The visibility of the angle lines.

    • rgrid_tick_lbls_args (dict, default {"fontsize": 12}): The font size of the tick labels on the scales.

    • theta_tick_lbls (dict, default {"fontsize": 12}): The font size of the variable labels on the plot.

    • theta_tick_lbls_pad (int, default 3): The padding of the variable labels on the plot.

    • theta_tick_lbls_brk_lng_wrds (bool, default True ): Whether long words in the label are broken up or not.

    • theta_tick_lbls_txt_wrap (int, default 15): Text wrap for tick labels

    • incl_endpoint (bool, default False): Include value endpoints on calse

    • marker (str, default "o"): the shape of the marker used in the radar plot.

    • markersize (int, default 3): the shape of the marker used in the radar plot.

    • legend_loc (str, default "upper right"): the location of the legend in the radar plot. Must be one of: ‘upper left’, ‘upper right’, ‘lower left’, ‘lower right’.

    • bbox_to_anchor (tuple, default (2, 1): anchor for the legend.

  • fig (matplotlib.figure.Figure, optional) — figure used to plot the radar plot.

Create a complex radar chart with different scales for each variable Source: https://towardsdatascience.com/how-to-create-and-visualize-complex-radar-charts-f7764d0f3652