ewoksfluo.tasks.example_data.deadtime.apply_dualchannel_signal_processing

ewoksfluo.tasks.example_data.deadtime.apply_dualchannel_signal_processing(spectra, max_dt_fast=0.1, max_dt_slow=20, elapsed_time=0.1, counting_noise=True, integral_type=<class 'numpy.uint32'>)[source]

MCA spectra with statistics measured by a dual-channel digital signal processor: one channel with low deadtime and low energy precision and one channel with high deadtime and high energy precision.

The last dimension of spectra is the MCA channel/energy dimension. An MCA spectrum (multi-channel analyzer) contains measured photons binned by their energy.

Parameters:

  • spectra (ndarray) –

  • counting_noise (bool) –

  • integral_type (Union[dtype[Any], None, Type[Any], _SupportsDType[dtype[Any]], str, Tuple[Any, int], Tuple[Any, Union[SupportsIndex, Sequence[SupportsIndex]]], List[Any], _DTypeDict, Tuple[Any, Any]]) –

Return type:

Dict[str, ndarray]