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clear;
rand('state', 123456);
more off; # for Octave
n = 10;
A = rand(n, n);
K = A'*A;
for ii=1:n
for jj=1:n
fprintf("matrix_set(K, n, %i, %i, %.16f);\n", ii-1, jj-1, K(ii, jj));
end
end
[P, Sigma] = eig(K);
eigenvalues = diag(Sigma);
ratios = eigenvalues ./ eigenvalues(end, end);
cutoff = 1e-2;
realP = fliplr(P(:, ratios > cutoff));
realSigma = flipud(eigenvalues(ratios > cutoff));
r = sum(ratios > cutoff);
assert(r == size(realP, 2));
fprintf('\n');
for ii=1:n
for jj=1:r
fprintf("mu_assert(fabs(fabs(matrix_get(P, r, %i, %i)) -\nfabs(%.16f)) < eps,\n\"Incorrect P at %i, %i\");\n", ii-1, jj-1, realP(ii, jj), ii-1, jj-1);
end
end
fprintf('\n');
for jj=1:r
fprintf("mu_assert(fabs(Sigma[%i] - %.16f) < eps,\n\"Incorrect Sigma at %i\");\n", jj-1, realSigma(jj), jj-1);
end
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