mode()

MAYAFLUX_API std::vector< double > MayaFlux::Kinesis::Discrete::mode	(	std::span< const double >	data,
		size_t	n_windows,
		uint32_t	hop_size,
		uint32_t	window_size
	)

Mode per window via tolerance-bucketed frequency count.

Buckets values at tolerance 1e-10 and returns the mean of the most frequent bucket.

Definition at line 559 of file Analysis.cpp.

{
    std::vector<double> out(n_windows);
    std::vector<size_t> idx(n_windows);
    std::iota(idx.begin(), idx.end(), 0);
 
    constexpr double tol = 1e-10;
 
    Parallel::for_each(Parallel::par_unseq, idx.begin(), idx.end(),
        [&](size_t i) {
            const size_t start = i * hop_size;
            auto w = data.subspan(start, std::min<size_t>(window_size, data.size() - start));
            if (w.empty()) {
                out[i] = 0.0;
                return;
            }
            std::map<int64_t, std::pair<double, size_t>> freq;
            for (double v : w) {
                const auto bucket = static_cast<int64_t>(std::round(v / tol));
                auto& [sum_v, cnt] = freq[bucket];
                sum_v = (sum_v * static_cast<double>(cnt) + v) / static_cast<double>(cnt + 1);
                ++cnt;
            }
            const auto it = std::ranges::max_element(freq,
                [](const auto& a, const auto& b) { return a.second.second < b.second.second; });
            out[i] = it->second.first;
        });
 
    return out;
}

References a, b, and mode().

Referenced by MayaFlux::Yantra::StatisticalAnalyzer< InputType, OutputType >::compute_statistical_values(), and mode().

Here is the call graph for this function:

Here is the caller graph for this function: