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