Nearest-Neighbour-Search-Neural-Networks-Product-Quantization/TEXMEX/Locality Sensitive Hashing/RunPQNNSwithADC.m~

clear all
close all 
clc

kk=[16 64 256 1024 2048];
rat=[1 2 5 10 20 50 100];
mm=[8 16];
%kk=2048;
%mm=[8 16];
nRecall=100;

%%

for ii=1:length(mm)
    for jj=1:length(kk)
        [Performances(jj,ii,:) normCCostADC(jj,ii), ~, ~] = PQNNSwithADC( kk(jj), mm(ii), nRecall, [0 0 0 0 1])
    end
end

%%
for jj=1:length(mm)
figure
for ii=1:length(kk)
    for
    plot(normCCostADC(ii,jj),Performances(ii,jj,:),'-x'), hold on
end
for ii=1:length(kk)
    text(normCCostADC(ii,:)+2e-5,Performances(ii,:,jj),sprintf('k=%d',kk(ii)),'interpreter','latex');
end
h=legend('R@1','R@2','R@5','R@10','R@20','R@50','R@100');
set(h,'Interpreter','latex');
grid on; grid minor;
title('ANNS with ADC - $m=8$','interpreter','latex');
xlabel('Complexity (scaled to Exhaustive NNS)','interpreter','latex');
ylabel('Performances','interpreter','latex');
end

%%
figure
plot(Performances(1,1,:))