IN16B_QENS

This module is used for importation of raw data from IN16B instrument.

class in16b_qens_scans_reduction.IN16B_QENS(scanList, sumScans=True, unmirroring=True, vanadiumRef=None, peakFindingMask=None, detGroup=None, normalize=True, strip=10, observable='time', roll=0, slidingSum=None)

This class can handle raw QENS data from IN16B at the ILL in the hdf5 format.

Parameters:
  • scanList – a string or a list of files to be read and parsed to extract the data. It can be a path to a folder as well.
  • sumScans – whether the scans should be summed or not.
  • unmirroring – whether the data should be unmirrored or not.
  • vanadiumRef – if :arg unmirroring: is True, then the peaks positions are identified using the data provided with this argument. If it is None, then the peaks positions are identified using the data in scanList.
  • detGroup – detector grouping, i.e. the channels that are summed over along the position-sensitive detector tubes. It can be an integer, then the same number is used for all detectors, where the integer defines a region (middle of the detector +/- detGroup). It can be a list of integers, then each integers of the list should corresponds to a detector. Or it can be a string, defining a path to an xml file as used in Mantid. If set to no, no detector gouping is performed and the data represents the signal for each pixel on the detectors. In this case, the observable become the momentum transfer q in the vertical direction.
  • normalize – whether the data should be normalized to the monitor
  • strip – an integer defining the number of points that are ignored at each extremity of the spectrum.
  • observable – the observable that might be changing over scans. It can be time or temperature
  • roll – Amount of shift on the energy axis to be given to the measured data in case they are not properly aligned with the monitor.
  • slidingSum – If not None, the size of the window to perform a sliding sum over the observables (default None).
process()

Extract data from the provided files and reduce them using the given parameters.