ffa_fnc_kmean_clustering2

/*
    File: ffa_fnc_kmean_clustering2.sqf
    Author: ArseniyK

    Description:
    Feature clustering array by the method of k-means
    Функция кластеризации массива методом k-means

    Parameter(s):
    _this select 0: array (Array) [[x,y,z],[x1,y1,z1],[x2,y2,z2],[x3,y3,z3],[x4,y4,z4],[x5,y5,z5],[x6,y6,z6],[x7,y7,z7],[x8,y8,z8]...]
    _this select 1: the number of clusters (Number)

    Returns:
    Array - format [[[x,y,z],[x1,y1,z1],[x2,y2,z2]],[[x3,y3,z3],[x4,y4,z4],[x5,y5,z5]],[[x6,y6,z6],[x7,y7,z7],[x8,y8,z8]]...]
*/
private ["_means","_xx","_y","_k","_points","_centers","_new_centers","_clusters","_point","_dist","_cluster_index","_dist1", "_kmeanspp"];
KK_fnc_isEqual = {
    switch (_this select 0) do
    {
        case (_this select 1) : {true};
        default {false};
    };
};
_means = {
    _xx = 0;
    _y = 0;
    {
        _xx = _xx + (_x select 0);
        _y = _y + (_x select 1);
    }foreach _this;
    _xx = _xx / (count _this);
    _y = _y / (count _this);
    [floor _xx, floor _y];
};

_k = _this select 0;
_points = _this select 1;
_centers = [];
_new_centers = [];
_clusters = [];
_clusters_2 = [];

for "_i" from 0 to _k - 1 do{
    _clusters set [_i, []];
};

_kmeanspp = {
    private ["_sum", "_k", "_points", "_centers", "_rnd", "_dist_s"];
    _k = _this select 0;
    _points = _this select 1;
    _centers = [];
    _centers set [0, _points select (floor (random (count _points)))];
    _sum = 0;

    for "_i" from 0 to _k-2 do {
        _center = _centers select (_i);
        _sum = 0;
        {

            _dist_s = (_x distance _center)^2;
            _sum = _sum + _dist_s;
        } foreach _points;
        _rnd = (random 1)*_sum;
        _sum = 0;
        {
            _dist_s = (_x distance _center)^2;
            _sum = _sum + _dist_s;
            if (_sum > _rnd) exitWith {_centers set [_i+1, _x];};
        } foreach _points;

    };
    _centers
};

private ["_sum", "_k", "_points", "_centers", "_rnd", "_dist_s"];
_k = _this select 0;
_points = _this select 1;
_new_centers = [_k, _points] call _kmeanspp;
//while {([_new_centers, _centers] call BIS_fnc_areEqual)} do //убрал
for "_i" from 0 to 1 step 0 do //добавил
{
    _centers = []+_new_centers;
    {
        _point = _x;
        _dist = _point distance (_centers select 0);
        _cluster_index = 0;

        {
            _dist1 = _x distance _point;
            if (_dist1 <= _dist) then {_dist = _dist1; _cluster_index = _foreachindex;}
        } foreach _centers;

        _cluster = _clusters select _cluster_index;
        _cluster set [count _cluster, _x];
        _clusters set [_cluster_index, _cluster];
    } foreach _points;

    _new_centers = [];
    _clusters_2 = []+_clusters;
//  player sideChat str(_centers);
    {
        if (count _x > 0) then {
            _new_centers set [count _new_centers, _x call _means];
            _clusters set [count _clusters, []];
        }
    }foreach _clusters_2;

    if !([_new_centers, _centers] call KK_fnc_isEqual) exitwith {};//добавил
};
_clusters_2