Draws a beeswarm plot for one feature's attribution values across many samples/predictions – the global "how does the model behave overall" view (hc_information_visualization.md SS5), complementing AttributionBarChart's single-prediction "why this one" view.
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#include <attribution_beeswarm.hpp>
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| static void | Draw (const char *title, const std::vector< Attribution > &attributions_across_samples, int64_t feature_index) |
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Draws a beeswarm plot for one feature's attribution values across many samples/predictions – the global "how does the model behave overall" view (hc_information_visualization.md SS5), complementing AttributionBarChart's single-prediction "why this one" view.
- Note
- ImPlot has no native beeswarm primitive – the jitter/collision-avoidance layout is computed by plot_data.hpp's ToBeeswarmPoints (unit-tested); this draw call only plots already-jittered points. Colors by the attribution value's own sign/magnitude (DivergingColormap) rather than the original feature value, since Attribution does not carry the input feature value alongside its attribution – a real limitation relative to a canonical SHAP beeswarm's color encoding, not an oversight.
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Deliberately not unit-tested – see AttributionBarChart's note.
◆ Draw()
| static void pulsatrix::AttributionBeeswarmView::Draw |
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const char * |
title, |
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const std::vector< Attribution > & |
attributions_across_samples, |
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int64_t |
feature_index |
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) |
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static |
- Parameters
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| title | ImPlot plot title/id. |
| attributions_across_samples | One Attribution per sample/prediction. |
| feature_index | Which feature (element position) to plot. |
The documentation for this class was generated from the following file:
1.9.8