Timeline for Spatial 1 to 1 join by proximity in sf and R?
Current License: CC BY-SA 4.0
8 events
| when toggle format | what | by | license | comment | |
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| Sep 23, 2019 at 15:17 | answer | added | Michael Dorman | timeline score: 4 | |
| Aug 24, 2019 at 4:36 | comment | added | Kenji | MatchingR. I'll have a look at that! Thank you. | |
| Aug 23, 2019 at 20:57 | comment | added | Spacedman |
I've just tried playing with the Gale-Shapley functions from the matchingR package using a negative distance matrix as the utility and am getting interesting and feasible results - any use?
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| Aug 23, 2019 at 11:02 | comment | added | Kenji | I know that the points represent one of the buildings in the same 100x100m grid cell. Your solution of iterating and removing would not lead to long distances if I restricted the matches to the same cell. Do you think that this would be feasible on datasets with over 20000 points and polygons? | |
| Aug 23, 2019 at 10:57 | comment | added | Spacedman | You could loop over the data, matching the nearest point/poly pair then removing them from the data for the next iteration. But you might end up with a final point/poly a long distance away. If that's okay then fine. But to find the set of pairings that minimises the total inter-pair distance sounds a bit like a travelling salesperson problem in complexity terms... | |
| Aug 23, 2019 at 10:52 | history | edited | Kenji | CC BY-SA 4.0 |
deleted 1 character in body
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| Aug 23, 2019 at 10:19 | history | edited | TomazicM | CC BY-SA 4.0 |
Title edit.
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| Aug 23, 2019 at 9:48 | history | asked | Kenji | CC BY-SA 4.0 |