view tests/GAPgentest.m @ 18:a8ff9a881d2f

GAP test almost working. For some data the results are not the same because of representation error, so the test doesn't fully work for now. But the results seem to be accurate.

% Run GAP and save parameters and solutions as reference test data
% to check if other algorithms are correct

numA = 10;
numY = 100;

sizesA{1} = [50 100];
sizesA{2} = [20 25];
sizesA{3} = [10 120];
sizesA{4} = [15 100];
sizesA{5} = [70 100];
sizesA{6} = [80 100];
sizesA{7} = [90 100];
sizesA{8} = [99 100];
sizesA{9} = [100 100];
sizesA{10} = [250 400];
for i = 1:numA sizesA{i} = fliplr(sizesA{i}); end

sigmamin = [0.00001 0.01 0.2 0.3 0.4 0.0001 0.1 0.001 0.1 0.1];

for i = 1:numA
    sz = sizesA{i};
    cellA{i} = randn(sz);
    m = round((0.2 + 0.6*rand)*sz(2));
    cellM{i} = randn(m,sz(2));
    cellY{i} = randn(m, numY);
    cellXinit{i} = zeros(sz(2), numY);
    for j = 1:numY
        cellEps{i}(j) = rand / 100; % restrict from 0 to 1% of measurements
    end
end
opt_num_iteration = 1000;
opt_greedy_level = 0.9;
opt_stopping_coefficient_size = 1e-4;
opt_l2solver = 'pseudoinverse';

%load GAPtestdata
tic
for i = 1:numA
    for j = 1:numY
        gapparams.num_iteration = opt_num_iteration;
        gapparams.greedy_level = opt_greedy_level;
        gapparams.stopping_coefficient_size = opt_stopping_coefficient_size;
        gapparams.l2solver = opt_l2solver;
        gapparams.noise_level = cellEps{i}(j);
        
        cellXr{i}(:,j) = GAP(cellY{i}(:,j), cellM{i}, cellM{i}', cellA{i}, cellA{i}', gapparams, cellXinit{i}(:,j));
    end
end
toc

save GAPtestdata