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. 2018 Sep 10;51(Pt 5):1378–1386. doi: 10.1107/S1600576718011032

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© V. Lutz-Bueno et al. 2018

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Scheme of the data analysis procedure. (a) Collection of azimuthally integrated SAXS/WAXS intensity curves , for , where r is the number of points. (b) M ₂ is formed by selecting only the d intensities where inflection points occur. (c) Dimensionality reduction: principal component analysis is applied to M ₂ and the number of main variables is reduced to m principal components PC_j, for . The optimal number of clusters n is evaluated and the signals are classified into n clusters. We assume n = 4 in this example. The scanned map is segmented according to the clustering results. (d) Estimation of a representative signal by selecting points that are located furthest from all centroids, for . Further details about each step can be found in the text.

Inline graphic — Scheme of the data analysis procedure. (a) Collection of azimuthally integrated SAXS/WAXS intensity curves , for , where r is the number of points. (b) M ₂ is formed by selecting only the d intensities where inflection points occur. (c) Dimensionality reduction: principal component analysis is applied to M ₂ and the number of main variables is reduced to m principal components PC_j, for . The optimal number of clusters n is evaluated and the signals are classified into n clusters. We assume n = 4 in this example. The scanned map is segmented according to the clustering results. (d) Estimation of a representative signal by selecting points that are located furthest from all centroids, for . Further details about each step can be found in the text.