PDS/homework_1/matlab/run_test.m

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C1 = [ 
    0.8147    0.1576;
    0.9058    0.9706;
    0.1270    0.9572;
    0.9134    0.4854;
    0.6324    0.8003;
    0.0975    0.1419;
    0.2785    0.4218;
    0.5469    0.9157;
    0.9575    0.7922;
    0.9649    0.9595 ];

Q1 = [
    0.6557    0.7577;
    0.0357    0.7431;
    0.8491    0.3922;
    0.9340    0.6555;
    0.6787    0.1712 ];

C2 = [
    0.7060    0.4456    0.5060    0.6160;
    0.0318    0.6463    0.6991    0.4733;
    0.2769    0.7094    0.8909    0.3517;
    0.0462    0.7547    0.9593    0.8308;
    0.0971    0.2760    0.5472    0.5853;
    0.8235    0.6797    0.1386    0.5497;
    0.6948    0.6551    0.1493    0.9172;
    0.3171    0.1626    0.2575    0.2858;
    0.9502    0.1190    0.8407    0.7572;
    0.0344    0.4984    0.2543    0.7537;
    0.4387    0.9597    0.8143    0.3804;
    0.3816    0.3404    0.2435    0.5678;
    0.7655    0.5853    0.9293    0.0759;
    0.7952    0.2238    0.3500    0.0540;
    0.1869    0.7513    0.1966    0.5308;
    0.4898    0.2551    0.2511    0.7792 ];

Q2 = [
    0.9340    0.3112    0.4505    0.0782;
    0.1299    0.5285    0.0838    0.4427;
    0.5688    0.1656    0.2290    0.1067;
    0.4694    0.6020    0.9133    0.9619;
    0.0119    0.2630    0.1524    0.0046;
    0.3371    0.6541    0.8258    0.7749;
    0.1622    0.6892    0.5383    0.8173;
    0.7943    0.7482    0.9961    0.8687 ];

D1_exp = [
    0.6208    0.9745    0.2371    0.5120    0.1367;
    0.3284    0.8993    0.5811    0.3164    0.8310;
    0.5651    0.2327    0.9169    0.8616    0.9603;
    0.3749    0.9147    0.1132    0.1713    0.3921;
    0.0485    0.5994    0.4621    0.3346    0.6308;
    0.8312    0.6044    0.7922    0.9815    0.5819;
    0.5052    0.4028    0.5714    0.6959    0.4722;
    0.1919    0.5395    0.6045    0.4665    0.7561;
    0.3037    0.9231    0.4144    0.1387    0.6807;
    0.3692    0.9540    0.5790    0.3056    0.8386 ];
  
  
  D2_exp = [
    0.6020    0.7396    0.6583    0.6050    1.0070    0.5542    0.6298    0.6352;
    1.0696    0.6348    0.9353    0.6914    0.8160    0.4475    0.4037    0.9145;
    0.9268    0.8450    0.9376    0.6492    0.9671    0.4360    0.5956    0.7400;
    1.3455    0.9876    1.2953    0.4709    1.2557    0.3402    0.4417    0.7500;
    0.9839    0.5476    0.7517    0.7216    0.7074    0.5605    0.4784    0.9954;
    0.6839    0.7200    0.7305    0.9495    1.0628    0.8718    0.8178    0.9179;
    0.9850    0.7514    0.9585    0.7996    1.2054    0.7784    0.6680    0.8591;
    0.6950    0.4730    0.3103    1.0504    0.4397    0.8967    0.8140    1.2066;
    0.8065    1.2298    0.9722    0.7153    1.3933    0.8141    1.0204    0.6758;
    1.1572    0.3686    0.9031    0.8232    0.7921    0.6656    0.3708    1.0970;
    0.9432    0.9049    1.0320    0.6905    1.1167    0.5094    0.6455    0.6653;
    0.7672    0.3740    0.5277    0.8247    0.6842    0.6945    0.5648    0.9968;
    0.5768    1.1210    0.8403    0.9345    1.1316    0.8292    1.0380    0.8127;
    0.1939    0.8703    0.2684    1.1794    0.8103    1.0683    1.1115    1.1646;
    1.0106    0.2708    0.8184    0.8954    0.7402    0.6982    0.4509    1.0594;
    0.8554    0.5878    0.6834    0.7699    0.9155    0.7161    0.6162    0.9481 ];

% tests
D1 = dist2(C1, Q1);
if norm (D1-pdist2(C1, Q1), 'fro') > 0.01
    disp('Error in dist2(C1, Q1)');
end

D2 = dist2(C2, Q2);
if norm (D2-pdist2(C2, Q2), 'fro') > 0.01
    disp('Error in dist2(C2, Q2)');
end

D2 = dist2(C2, C2);
if norm (D2-pdist2(C2, C2), 'fro') > 0.01
    disp('Error in dist2(C2, C2)');
end
    


%C = rand(10000, 2);  % Corpus
%Q = rand(10000, 2);   % Queries
C = rand(20000, 2);  % Δύο clusters
Q = C;
%Q = rand(10000, 2);  % Queries κοντά στο μέσο
k = 100;             % Number of neighbors
m = 100;             % Max candidates per query
global count;

count =0;
tic; [pi, pd] = recursiveKNN(C, Q, k, m); toc
count
tic; [si, sd] = knnsearch(C, Q, 'k', k); toc

[a,b] = size(si);
all_neighbors = a*b
accuracy = 1 - nnz(si-pi)/all_neighbors
false_neighbors = nnz(sd-pd)