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Description
Using a large dataset ( > 500 ) and removing nodes at random will cause the KDTree to not be segmented correctly. This will cause nodes to not be found correctly.
- Create a set of random 2d points
- Find the single nearest point within a random 2d point.
- Remove the single nearest point.
- Repeat from step 2 until you have no more points.
Expected outcome. We are able to remove all records from the tree.
Actual: There are records left, as the tree has made some nodes "unreachable" by not placing them correctly due to the remove
function.
Let me know if you want a proof of bug.
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