averaging_time

ska_sdp_func_python.preprocessing.averaging.averaging_time(data: Visibility, timestep, flag_threshold=0.5) → Visibility

Averaging in the time direction. New visibilities are the summation of the unflagged old ones with weights taken into account divided by the sum of unflagged weights. New weights are the sum of the old ones. New flags are True if the number of old True flags are above a threshold (within the bin of freqstep data points). New uvw’s are the average of the old ones New time is the average of the old ones New integration time is the sum of the old ones

Parameters:

• data – SKA data model visibility

• timestep – integer, number of time samples to average

• flag_threshold – the threshold on the fraction of old flags (in the bin of size timestep) to flag the new (averaged) data point (should be between 0 and 1)

Returns:

resulting (averaged) SKA data model visibility