Scipy.spatial.distance.cdist with "euclidean" can give you a matrix of distance between all points to all others. With the output, maybe call a output >= 1, which will give you a bool numpy …

Given a 2D array arr [] and value K, where each list in arr [] represents a point on Cartesian coordinates, the task is to group the given points if the distance between them is less than or …

If you would like to find the distance between centers (or means) of the groups, you need the within-group data. Let us simplify the problem to perhaps an unrealistic level: imagine the …

If the distance between POINTS [i] and POINTS [j] is less than or equal to ‘K’: Group them together as unionn (i,j, ’GROUPS’ SIZES). Declare a variable ‘ANS’ to store the number of …

If you compute a matrix where the [x] [y] place is the distance between the point x and the point y. Then, iterate over it so that if the distance is less than the threshold, mark the place with a 1, …

You can speed up your exact construction as follows: Insert all records (distance_X_Y, X, Y) into a priority queue. Then, repeatedly, pop the smallest distance, check whether the two points …

Suppose you the distance threshold is d d, i.e., you want two elements at distance ≤ d ≤ d to be in the same group. Then you can divide up space into cubes of side length 2d 2 d, and store …

Sometimes, while working with Python lists, we can have a problem in which we need to perform the grouping of all the coordinates which occur adjacent on a matrix, i.e horizontally and …

If the number of points was low, I could find the distance of each points using the least square method. In other words, I could calculate the eucleadian distance of each point from all points …

Hi all, I am looking to group points with the following rules. if the distance is between the points is == to .5 to .6 group the points to a maximum of 3 points per group. then find the average point …