Like the N-convex algorithm, this algorithm attempts to find a set of candidates whose centroid is close to . The key difference is that instead of taking unique candidates, we allow candidates to populate the set multiple times. The result is that the weight of each candidate is simply given by its frequency in the list, which we can then index by random selection:
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We have a ‘scrolling wall of icons’ benchmark in our gtk4-demo app, which naturally is good place to test the performance impact of icon rendering changes. When switching it over to GtkSvg, it initially dropped from 60fps to around 40 on my laptop. We’ve since done some optimizations and regained most of the lost fps.
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