NormaliseSpectra.py

# Mantid Repository : https://github.com/mantidproject/mantid
#
# Copyright © 2018 ISIS Rutherford Appleton Laboratory UKRI,
#   NScD Oak Ridge National Laboratory, European Spallation Source,
#   Institut Laue - Langevin & CSNS, Institute of High Energy Physics, CAS
# SPDX - License - Identifier: GPL - 3.0 +
#pylint: disable=no-init
from mantid.kernel import *
from mantid.api import (MatrixWorkspaceProperty, DataProcessorAlgorithm, AlgorithmFactory)
from mantid.simpleapi import *

import numpy as np


class NormaliseSpectra(DataProcessorAlgorithm):

    _input_ws_name = None
    _input_ws = None
    _output_ws_name = None

    def category(self):
        return 'Workflow\\MIDAS;Inelastic'

    def summary(self):
        return 'Normalise all spectra to have a max value of 1'

    def PyInit(self):
        self.declareProperty(MatrixWorkspaceProperty('InputWorkspace', '',
                                                     direction=Direction.Input),
                             doc='Input workspace')

        self.declareProperty(MatrixWorkspaceProperty('OutputWorkspace', '',
                                                     direction=Direction.Output),
                             doc='Output workspace')

    def PyExec(self):
        self._setup()
        CloneWorkspace(InputWorkspace=self._input_ws,
                       OutputWorkspace=self._output_ws_name)

        num_hists = self._input_ws.getNumberHistograms()
        output_ws = mtd[self._output_ws_name]

        for idx in range(num_hists):
            single_spectrum = ExtractSpectra(InputWorkspace=self._input_ws, WorkspaceIndexList=idx)
            y_data = single_spectrum.readY(0)
            ymax = np.nanmax(y_data)
            # raises a RuntimeError if the ymax is <= 0
            if ymax <= 0:
                spectrum_no = single_spectrum.getSpectrum(0).getSpectrumNo()
                DeleteWorkspace('single_spectrum')
                raise RuntimeError("Spectrum number %d:" % (spectrum_no)
                                   + "has a maximum y value of 0 or less. "
                                   + "All spectra must have a maximum y value more than 0")
            Scale(InputWorkspace=single_spectrum, Operation="Multiply",
                  Factor=(1/ymax), OutputWorkspace=single_spectrum)
            output_ws.setY(idx, single_spectrum.readY(0))
            output_ws.setE(idx, single_spectrum.readE(0))

        # Delete extracted spectra workspace
        DeleteWorkspace('single_spectrum')

        self.setProperty('OutputWorkspace', output_ws)

    def _setup(self):
        """
        Gets properties.
        """

        self._input_ws_name = self.getPropertyValue('InputWorkspace')
        self._input_ws = mtd[self._input_ws_name]
        self._output_ws_name = self.getPropertyValue('OutputWorkspace')


# Register algorithm with Mantid
AlgorithmFactory.subscribe(NormaliseSpectra)