A one-dimensional seed-skewness algorithm adapted for X-ray diffraction signal detection is presented and discussed. The method, primarily designed for photocrystallographic time-resolved Laue data processing, was shown to work well for the type of data collected at the Advanced Photon Source and European Synchrotron Radiation Facility. Nevertheless, it is also applicable in the case of standard single-crystal X-ray diffraction data. The reported algorithm enables reasonable separation of signal from the background in single one-dimensional data vectors as well as the capability to determine small changes of reflection shapes and intensities resulting from exposure of the sample to laser light. Otherwise, the procedure is objective, and relies only on skewness computation and its subsequent minimization. The new algorithm was proved to yield comparable results to the Kruskal-Wallis test method [Kalinowski, J. A. et al. (2012). J. Synchrotron Rad. 19, 637], while the processing takes a similar amount of time. Importantly, in contrast to the Kruskal-Wallis test, the reported seed-skewness approach does not need redundant input data, which allows for faster data collections and wider applications. Furthermore, as far as the structure refinement is concerned, the reported algorithm leads to the excited-state geometry closest to the one modelled using the quantum-mechanics/molecular-mechanics approach reported previously [Jarzembska, K. N. et al. (2014). Inorg. Chem. 53, 10594], when the t and s algorithm parameters are set to the recommended values of 0.2 and 3.0, respectively.
Keywords: X-ray diffraction; background estimation; data processing; skewness; statistical analysis.