Hi,
I also hit a limitation of BOOST_CHECK_CLOSE. In testing my code to check the accuracy of the algorithm for the standard normalized normal distribution, of zero mean and unit variance, it always failed, giving an infinite percent accuracy. Changing the distribution to mean of one and variance of one resulted in the test passing. Clearly the incorrect result of a failed test was due to a division by zero, and thus BOOST_CHECK_CLOSE clearly can not compare a double with 0.0, and that strikes me as a significant limitation. It is true that for my purposes, simply shifting the distribution to the right by one meets my needs, I can imagine cases in which that is not viable. Is there another macro that is specialized for the case when the expected outcome, for a double, of a given calculation is zero?
BOOST_CHECK_CLOSE can't work, because it evaluates a difference between the two values in percent. But no one can answer how many percent difference are between 0 and 1 (I think infinite is a good guess, though). What you are searching is BOOST_CHECK_SMALL which checks, whether a number is smaller than a certain threshold. Greetings, Oswin