mean_zscore()

std::vector< double > MayaFlux::Kinesis::Discrete::mean_zscore	(	std::span< const double >	data,
		size_t	n_windows,
		uint32_t	hop_size,
		uint32_t	window_size,
		bool	sample_variance = true
	)

Mean z-score per window.

Returns the mean of ((x - mean) / std_dev) over each window. Returns 0 when std_dev is zero.

Parameters

sample_variance

If true, uses sample variance (N-1)

Definition at line 590 of file Analysis.cpp.

{
    std::vector<double> out(n_windows);
    std::vector<size_t> idx(n_windows);
    std::iota(idx.begin(), idx.end(), 0);
 
    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;
            }
            double s = 0.0;
            for (double v : w)
                s += v;
            const double m = s / static_cast<double>(w.size());
            double sq = 0.0;
            for (double v : w) {
                const double d = v - m;
                sq += d * d;
            }
            const double div = sample_variance
                ? static_cast<double>(w.size() - 1)
                : static_cast<double>(w.size());
            const double sd = std::sqrt(sq / div);
            if (sd <= 0.0) {
                out[i] = 0.0;
                return;
            }
            double zs = 0.0;
            for (double v : w)
                zs += (v - m) / sd;
            out[i] = zs / static_cast<double>(w.size());
        });
 
    return out;
}

References mean_zscore().

Referenced by mean_zscore().

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