apply_drifts_to_channel_data

sofia_redux.scan.integration.integration_numba_functions.apply_drifts_to_channel_data(channel_indices, offsets, average_drifts, inconsistencies, hardware_gain, filter_time_scale, source_filtering, integration_filter_time_scale, crossing_time, is_detector_stage, update_filtering)

Apply the average drifts to channel data.

After calculating the average channel drifts for all channels, the offset attribute of the channel data is modified by:

offset += average_drifts * G

where G = 1 if the detector is not staged (is_detector_stage`=`False) or set to hardware_gain if the detector is staged.

If update_filtering is True, the source filtering will be updated by:

sf *= 1 - (crossing_time / filter_time_scale)

Note that the previous correction will be removed first. Also, the filtering_time_scale will be set to the minimum of the integration filtering time scale and the current filtering time scale.

Parameters:

channel_indicesnumpy.ndarray (int)

The channel indices for which to apply the drifts to of shape (n_channels,). Should map n_channels -> all_channels.

offsetsnumpy.ndarray (float)

The channel gain offsets of shape (all_channels,). Will be updated in-place.

average_driftsnumpy.ndarray (float)

The average drifts to apply to the channel offsets of shape (n_channels,).

inconsistenciesnumpy.ndarray (int)

The channel inconsistencies of shape (all_channels,).

hardware_gainnumpy.ndarray (float)

The channel hardware gains of shape (all_channels,).

filter_time_scalenumpy.ndarray (float)

The filter time scale for all channels of shape (all_channels,). Will be updated in-place.

source_filteringnumpy.ndarray (float)

The channel source filtering of shape (all_channels,). Will be updated in-place.

integration_filter_time_scalefloat

The integration filter time scale.

crossing_timefloat

The point-crossing time for the integration.

is_detector_stagebool

If True indicates that the detector is staged and hardware gains should be applied.

update_filteringbool

If True updates the source filtering and filter time scale for the given channels. This should be set to False if the drift block size (number of frames in a single drift) is greater than the total number of frames in the integration.

Returns:

inconsistent_channels, total_inconsistenciesint, int

The total number of channels containing one or more inconsistencies, and the total number of inconsistencies in the given channels.