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ThisIn this module the "median algorithm" is intendedimplemented for peak finding in CSPad data array shaped as \[5920=4*8*185\]\[388\]. It extends features of the module [ImgAlgos::CSPadArrNoise|PCDS:Psana Module Catalog#Module ImgAlgos::CSPadArrNoise]) and works as follows\]. The "median algorithm" assumes that the amplitude level of background and noise for each pixel can be estimated as a mean and RMS of the surrounding pixels, located in the ring with parameters {{rmin}} and {{dr}} around the pixel in question. The threshold {{SoNThr_noise}} on signal over noise (S/N) ratio allow to asset the pixel amplitude as a large noise fluctuation. Statistics of pixels above the S/N threshold accumulated over many images can be used to form the noisy-pixel mask. For example, if the fraction of images where pixel exceeds the S/N threshold grater than certain value ({{frac_noisy_imgs}}=0.9), the pixel is considered as noisy. The permanent bad pixel mask (see module [ImgAlgos::CSPadMaskApply|PCDS:Psana Module Catalog#Module ImgAlgos::CSPadMaskApply]) and dynamically evaluated noisy pixel mask are used to get rid of bad pixels and improve the image quality. Healthy pixels with S/N above threshold ({{SoNThr_signal}} about 3-5) are treated as potential signals. Using recursive flood-filling algorithm the groups of connected signal pixels can be found and considered as a candidate for a diffraction peaks. Peak finding algorithm uses the amplitude, S/N thresholds, and limits on number of pixels in the connected region (parameters {{peak_amp_tot_thr}}, {{peak_SoN_thr}}, {{peak_npix_min}}, and {{peak_npix_max}}) in order to define the peak. Finally, the event is selected or discarded depending on number of found peaks and total amplitude threshold, defined by the parameters {{event_npeak_min}}, {{event_npeak_max}}, and {{event_amp_tot_thr}}, respectively.