Function count_steps_without_decrease_robust

dlib/statistics/running_gradient.h:329–369

        typename T
        > 
    size_t count_steps_without_decrease_robust (
        const T& container,
        double probability_of_decrease = 0.51,
        double quantile_discard = 0.10
    )
    {
        // make sure requires clause is not broken
        DLIB_ASSERT(0 <= quantile_discard && quantile_discard <= 1);
        DLIB_ASSERT(0.5 < probability_of_decrease && probability_of_decrease < 1,
            "\t size_t count_steps_without_decrease_robust()"
            << "\n\t probability_of_decrease: "<< probability_of_decrease 
        );

        if (container.size() == 0)
            return 0;

        const auto quantile_thresh = find_upper_quantile(container, quantile_discard); 

        running_gradient g;
        size_t count = 0;
        size_t j = 0;
        for (auto i = container.rbegin(); i != container.rend(); ++i)
        {
            ++j;
            // ignore values that are too large
            if (*i <= quantile_thresh)
                g.add(*i);

            if (g.current_n() > 2)
            {
                // Note that this only looks backwards because we are looping over the
                // container backwards.  So here we are really checking if the gradient isn't
                // decreasing.
                double prob_decreasing = g.probability_gradient_greater_than(0);
                // If we aren't confident things are decreasing.
                if (prob_decreasing < probability_of_decrease)
                    count = j;
            }
        }
        return count;
    }

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