def centroid_detector(self, tic, rt): noise_std = self.chromatogram_settings.std_noise_threshold method = self.chromatogram_settings.noise_threshold_method #peak picking min_height = self.chromatogram_settings.peak_height_min_percent min_datapoints = self.chromatogram_settings.min_peak_datapoints # baseline detection max_prominence = self.chromatogram_settings.peak_max_prominence_percent max_height = self.chromatogram_settings.peak_height_max_percent peak_indexes_generator = sp.peak_detector_generator( tic, noise_std, method, rt, max_height, min_height, max_prominence, min_datapoints) return peak_indexes_generator
def centroid_detector(self, tic, rt): ''' this function has been replaced with sp.peak_picking_first_derivative and it not used ''' noise_std = self.chromatogram_settings.std_noise_threshold method = self.chromatogram_settings.noise_threshold_method ''' peak picking''' min_height = self.chromatogram_settings.peak_height_min_percent min_datapoints = self.chromatogram_settings.min_peak_datapoints ''' baseline detection''' max_prominence = self.chromatogram_settings.peak_max_prominence_percent max_height = self.chromatogram_settings.peak_height_max_percent peak_indexes_generator = sp.peak_detector_generator(tic, noise_std, method, rt, max_height, min_height, max_prominence, min_datapoints) return peak_indexes_generator
def centroid_detector(self, tic, rt): # need to change the parameter to accommodate EIC peak picking # needs a better algorithm to detect start and end of a peak noise_std = self.chromatogram_settings.std_noise_threshold method = self.chromatogram_settings.noise_threshold_method #peak picking min_height = self.chromatogram_settings.peak_height_min_percent min_datapoints = self.chromatogram_settings.min_peak_datapoints # baseline detection max_prominence = self.chromatogram_settings.peak_max_prominence_percent max_height = self.chromatogram_settings.peak_height_max_percent peak_indexes_generator = sp.peak_detector_generator( tic, noise_std, method, rt, max_height, min_height, max_prominence, min_datapoints) return peak_indexes_generator