Voronoi diagram: Difference between revisions
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Note that for large numbers of points, using a KDTree will be much faster thanks to lookups in log(N) time rather than N comparisons at every coordinate. The code below has running time O(X*Y*log(N)), whereas the code above has running time O(X*Y*N). For 1000 points, the code below is 250x faster than the above. |
Note that for large numbers of points, using a KDTree will be much faster thanks to lookups in log(N) time rather than N comparisons at every coordinate. The code below has running time O(X*Y*log(N)), whereas the code above has running time O(X*Y*N). For 1000 points, the code below is 250x faster than the above. |
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Alternative metrics can be supported by using a [https://scikit-learn.org/stable/modules/generated/sklearn.neighbors.KDTree.html#sklearn.neighbors.KDTree.query scikit-learn KDTree ]. |
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