def __init__(self, role, monitor_params):
self.max_num_peaks = monitor_params['Peakfinder8PeakDetection']['max_num_peaks']
self.asic_nx = monitor_params['Peakfinder8PeakDetection']['asics_nx']
self.asic_ny = monitor_params['Peakfinder8PeakDetection']['asics_ny']
self.nasics_x = monitor_params['Peakfinder8PeakDetection']['nasics_x']
self.nasics_y = monitor_params['Peakfinder8PeakDetection']['nasics_y']
self.adc_thresh = monitor_params['Peakfinder8PeakDetection']['adc_threshold']
self.minimum_snr = monitor_params['Peakfinder8PeakDetection']['minimum_snr']
self.min_pixel_count = monitor_params['Peakfinder8PeakDetection']['min_pixel_count']
self.max_pixel_count = monitor_params['Peakfinder8PeakDetection']['max_pixel_count']
self.local_bg_radius = monitor_params['Peakfinder8PeakDetection']['local_bg_radius']
self.mask_filename = monitor_params['Peakfinder8PeakDetection']['mask_filename']
self.mask_hdf5_path = monitor_params['Peakfinder8PeakDetection']['mask_hdf5_path']
self.accumulated_shots = monitor_params['Peakfinder8PeakDetection']['accumulated_shots']
if role == 'master':
self.apply = self.master
self.accumulator = ([], [], [])
self.events_in_accumulator = 0
# Initialized on worker
if role == 'worker':
self.apply = self.worker
from utils.io_utils import load_nparray_from_hdf5_file
self.mask = load_nparray_from_hdf5_file(self.mask_filename, self.mask_hdf5_path)
def __init__(self, role, monitor_params):
# Initialized on worker
if role == 'worker':
from utils.io_utils import load_nparray_from_hdf5_file
self.apply = self.worker
# load the darkcals
self.darkcal = load_nparray_from_hdf5_file(monitor_params['DarkCalCorrection']['filename'],
monitor_params['DarkCalCorrection']['hdf5_group'])
if ['gain_map'] in monitor_params['DarkCalCorrection'].keys() and monitor_params['DarkCalCorrection']['gain_map'] == True:
self.gain_map = load_nparray_from_hdf5_file(monitor_params['DarkCalCorrection']['gain_map_filename'],
monitor_params['DarkCalCorrection']['gain_map_hdf5_group'])
else:
self.gain_map = True
