After implementing the naive solution ( #15 ), we should implement a faster solution in case our dataset grows larger. Here are various links that should lead us to a log(n) solution using the KD data structure, with the last link being a nearly parallel example of what we need.
http://stackoverflow.com/questions/10818546/finding-index-of-nearest-point-in-numpy-arrays-of-x-and-y-coordinates <----- Theory of the Problem
http://www.geeksforgeeks.org/k-dimensional-tree/ <----- Theory of the Data Structure
https://github.com/ubilabs/kd-tree-javascript <----- Data Structure Implementation
http://ubilabs.github.io/kd-tree-javascript/examples/map/ <----- Practical Example
After implementing the naive solution ( #15 ), we should implement a faster solution in case our dataset grows larger. Here are various links that should lead us to a log(n) solution using the KD data structure, with the last link being a nearly parallel example of what we need.
http://stackoverflow.com/questions/10818546/finding-index-of-nearest-point-in-numpy-arrays-of-x-and-y-coordinates <----- Theory of the Problem
http://www.geeksforgeeks.org/k-dimensional-tree/ <----- Theory of the Data Structure
https://github.com/ubilabs/kd-tree-javascript <----- Data Structure Implementation
http://ubilabs.github.io/kd-tree-javascript/examples/map/ <----- Practical Example