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]