issue_comments: 57849594
This data as json
| html_url | issue_url | id | node_id | user | created_at | updated_at | author_association | body | reactions | performed_via_github_app | issue |
|---|---|---|---|---|---|---|---|---|---|---|---|
| https://github.com/pydata/xarray/issues/214#issuecomment-57849594 | https://api.github.com/repos/pydata/xarray/issues/214 | 57849594 | MDEyOklzc3VlQ29tbWVudDU3ODQ5NTk0 | 1217238 | 2014-10-03T20:03:53Z | 2014-10-03T20:03:53Z | MEMBER | @WeatherGod You are totally correct. The last dataset on which I have needed to do this was an unprojected grid with a constant increment of 0.5 degrees between points, so finding nearest neighbors was easy. If you have a lot of points to select at, finding nearest neighbor points could be done efficiently with a tree, e.g., |
{
"total_count": 0,
"+1": 0,
"-1": 0,
"laugh": 0,
"hooray": 0,
"confused": 0,
"heart": 0,
"rocket": 0,
"eyes": 0
} |
40395257 |