perm = [2, 3, 1];
sz = [1,2,3];
if ~isequal(size(ipermute(permute(zeros(sz), perm), perm)), sz)
    if exist('octave_config_info')
        error('FAILURE: You have a buggy version of ipermute. Try upgrading Octave (V3.3.3 is broken. V3.3.52+ works).');
    else
        error('FAILURE: You have a buggy version of ipermute.');
    end
end

% Test that fancy routine matches the behavior of the obvious Matlab routine
% (when numerics aren't a problem) over a wide range of weird ND-array sizes
% (This is really a test of ndhelper.m)
sizes = {[1 3], [5 1], [10 3], [0], [0 9], [3 0], [3 1 4], [1 2 3], [1 1 1 4], [1 1 0 5], [0 0 0 1], [0 0 0], [0 0 0 1 0]};
for ii = 1:numel(sizes)
    sz = sizes{ii};
    A = rand(sz);
    testclose(logcumsumexp(A), log(cumsum(exp(A))));
    for dim = 1:length(sz)
        testclose(logcumsumexp(A, dim), log(cumsum(exp(A), dim)));
    end
end


% Test that answers are ok when numerics are horrible by comparing to LOGSUMEXP
A = [-Inf -Inf -3000 -3000 -Inf -600 -599 -10 5 1000 999 Inf Inf 1000  Inf NaN 5 2]';
lcs = logcumsumexp(A);
lcs2 = zeros(size(A));
for ii = 1:length(A)
    lcs2(ii) = logsumexp(A(1:ii));
end
% If using Tom Minka's logsumexp, it fails (or at least used to fail) to deal
% with NaNs correctly if there are Inf's in the array. I'll fix that here:
if ~all(isnan(lcs2(end-2:end)))
    fprintf('WARNING: Problem with LOGSUMEXP detected while testing LOGCUMSUMEXP. Using the lightspeed rather than imurray version?\n');
    lcs2(end-2:end) = NaN;
end
testclose(lcs, lcs2);
fprintf('A warning (but not failure) on the previous line about NaN''s was expected.\n');

test_exit