SimulatedDensityOfStates.py

#pylint: disable=no-init,invalid-name,too-many-locals,too-many-lines, redefined-builtin
from __future__ import (absolute_import, division, print_function)
from six.moves import range

import numpy as np
import re
import os.path
import math

from mantid.kernel import *
from mantid.api import *
import mantid.simpleapi as s_api

from dos.load_phonon import parse_phonon_file
from dos.load_castep import parse_castep_file

PEAK_WIDTH_ENERGY_FLAG = 'energy'


class SimulatedDensityOfStates(PythonAlgorithm):

    _spec_type = None
    _peak_func = None
    _out_ws_name = None
    _peak_width = None
    _zero_threshold = None
    _ions_of_interest = None
    _scale_by_cross_section = None
    _calc_partial = None
    _num_ions = None
    _num_branches = None
    _element_isotope = dict()

#----------------------------------------------------------------------------------------

    def category(self):
        return "Simulation"

#----------------------------------------------------------------------------------------

    def summary(self):
        return "Calculates phonon densities of states, Raman and IR spectrum."

#----------------------------------------------------------------------------------------

    def PyInit(self):
        # Declare properties
        self.declareProperty(FileProperty('CASTEPFile', '',
                                          action=FileAction.OptionalLoad,
                                          extensions = ["castep"]),
                             doc='Filename of the CASTEP file.')

        self.declareProperty(FileProperty('PHONONFile', '',
                                          action=FileAction.OptionalLoad,
                                          extensions = ["phonon"]),
                             doc='Filename of the PHONON file.')

        self.declareProperty(name='Function',defaultValue='Gaussian',
                             validator=StringListValidator(['Gaussian', 'Lorentzian']),
                             doc="Type of function to fit to peaks.")

        self.declareProperty(name='PeakWidth', defaultValue='10.0',
                             doc='Set Gaussian/Lorentzian FWHM for broadening. Default is 10')

        self.declareProperty(name='SpectrumType', defaultValue='DOS',
                             validator=StringListValidator(['IonTable', 'DOS', 'IR_Active', 'Raman_Active', 'BondTable']),
                             doc="Type of intensities to extract and model (fundamentals-only) from .phonon.")

        self.declareProperty(name='CalculateIonIndices', defaultValue=False,
                             doc="Calculates the individual index of all Ions in the simulated data.")

        self.declareProperty(name='StickHeight', defaultValue=0.01,
                             doc='Intensity of peaks in stick diagram.')

        self.declareProperty(name='Scale', defaultValue=1.0,
                             doc='Scale the intesity by the given factor. Default is no scaling.')

        self.declareProperty(name='BinWidth', defaultValue=1.0,
                             doc='Set histogram resolution for binning (eV or cm**-1). Default is 1')

        self.declareProperty(name='Temperature', defaultValue=300.0,
                             doc='Temperature to use (in raman spectrum modelling). Default is 300')

        self.declareProperty(name='ZeroThreshold', defaultValue=3.0,
                             doc='Ignore frequencies below the this threshold. Default is 3.0')

        self.declareProperty(StringArrayProperty('Ions', Direction.Input),
                             doc="List of Ions to use to calculate partial density of states."
                                 "If left blank, total density of states will be calculated")

        self.declareProperty(name='SumContributions', defaultValue=False,
                             doc="Sum the partial density of states into a single workspace.")

        self.declareProperty(name='ScaleByCrossSection', defaultValue='None',
                             validator=StringListValidator(['None', 'Total', 'Incoherent', 'Coherent']),
                             doc="Sum the partial density of states by the scattering cross section.")

        self.declareProperty(WorkspaceProperty('OutputWorkspace', '', Direction.Output),
                             doc="Name to give the output workspace.")


#----------------------------------------------------------------------------------------

    def validateInputs(self):
        """
        Performs input validation.

        Used to ensure the user is requesting a valid mode.
        """
        issues = dict()

        castep_filename = self.getPropertyValue('CASTEPFile')
        phonon_filename = self.getPropertyValue('PHONONFile')

        if castep_filename == '' and phonon_filename == '':
            msg = 'Must have at least one input file'
            issues['CASTEPFile'] = msg
            issues['PHONONFile'] = msg

        spec_type = self.getPropertyValue('SpectrumType')
        sum_contributions = self.getProperty('SumContributions').value
        scale_by_cross_section = self.getPropertyValue('ScaleByCrossSection') != 'None'

        ions = self.getProperty('Ions').value
        calc_partial = len(ions) > 0

        if spec_type == 'IonTable' and phonon_filename == '':
            issues['SpectrumType'] = 'Require a .phonon file for ion table output'

        if spec_type == 'BondAnalysis' and phonon_filename == '' and castep_filename == '':
            issues['SpectrumType'] = 'Require both a .phonon and .castep file for bond analysis'

        if spec_type == 'BondTable' and castep_filename == '':
            issues['SpectrumType'] = 'Require a .castep file for bond table output'

        if spec_type != 'DOS' and calc_partial:
            issues['Ions'] = 'Cannot calculate partial density of states when using %s' % spec_type

        if spec_type != 'DOS' and scale_by_cross_section:
            issues['ScaleByCrossSection'] = 'Cannot scale contributions by cross sections when using %s' % spec_type

        if phonon_filename == '' and scale_by_cross_section:
            issues['ScaleByCrossSection'] = 'Must supply a PHONON file when scaling by cross sections'

        if not calc_partial and sum_contributions:
            issues['SumContributions'] = 'Cannot sum contributions when not calculating partial density of states'

        return issues

#----------------------------------------------------------------------------------------

    def PyExec(self):
        # Run the algorithm
        self._get_properties()

        file_data = self._read_file()

        # Get variables from file_data
        frequencies = file_data['frequencies']
        ir_intensities = file_data['ir_intensities']
        raman_intensities = file_data['raman_intensities']
        weights = file_data['weights']
        eigenvectors = file_data.get('eigenvectors', None)
        ion_data = file_data.get('ions', None)
        unit_cell = file_data.get('unit_cell', None)
        self._num_branches = file_data['num_branches']

        logger.debug('Unit cell: {0}'.format(unit_cell))

        prog_reporter = Progress(self, 0.0, 1.0, 1)

        # Output a table workspace with ion information
        if self._spec_type == 'IonTable':
            self._create_ion_table(unit_cell, ion_data)

        # Output a table workspace with bond information
        if self._spec_type == 'BondTable':
            bonds = file_data.get('bonds', None)
            self._create_bond_table(bonds)

        # Calculate a partial DoS
        elif self._calc_partial and self._spec_type == 'DOS':
            logger.notice('Calculating partial density of states')
            prog_reporter.report('Calculating partial density of states')
            self._calculate_partial_dos(ion_data, frequencies, eigenvectors, weights)

        # Calculate a total DoS with scaled intensities
        elif self._spec_type == 'DOS' and self._scale_by_cross_section != 'None':
            logger.notice('Calculating summed density of states with scaled intensities')
            prog_reporter.report('Calculating density of states')
            self._calculate_total_dos_with_scale(ion_data, frequencies, eigenvectors, weights)

        # Calculate a total DoS without scaled intensities
        elif self._spec_type == 'DOS':
            logger.notice('Calculating summed density of states without scaled intensities')
            prog_reporter.report('Calculating density of states')

            out_ws = self._compute_DOS(frequencies, np.ones_like(frequencies), weights)
            out_ws.setYUnit('(D/A)^2/amu')
            out_ws.setYUnitLabel('Intensity')

        # Calculate a DoS with IR active
        elif self._spec_type == 'IR_Active':
            if ir_intensities.size == 0:
                raise ValueError('Could not load any IR intensities from file.')

            logger.notice('Calculating IR intensities')
            prog_reporter.report('Calculating IR intensities')

            out_ws = self._compute_DOS(frequencies, ir_intensities, weights)
            out_ws.setYUnit('(D/A)^2/amu')
            out_ws.setYUnitLabel('Intensity')

        # Create a DoS with Raman active
        elif self._spec_type == 'Raman_Active':
            if raman_intensities.size == 0:
                raise ValueError('Could not load any Raman intensities from file.')

            logger.notice('Calculating Raman intensities')
            prog_reporter.report('Calculating Raman intensities')

            out_ws = self._compute_raman(frequencies, raman_intensities, weights)
            out_ws.setYUnit('A^4')
            out_ws.setYUnitLabel('Intensity')

        self.setProperty('OutputWorkspace', self._out_ws_name)

#----------------------------------------------------------------------------------------

    def _get_properties(self):
        """
        Set the properties passed to the algorithm
        """
        self._spec_type = self.getPropertyValue('SpectrumType')
        self._peak_func = self.getPropertyValue('Function')
        self._out_ws_name = self.getPropertyValue('OutputWorkspace')
        self._peak_width = self.getProperty('PeakWidth').value
        self._zero_threshold = self.getProperty('ZeroThreshold').value
        self._ions_of_interest = self.getProperty('Ions').value
        self._scale_by_cross_section = self.getPropertyValue('ScaleByCrossSection')
        self._calc_partial = (len(self._ions_of_interest) > 0)


#----------------------------------------------------------------------------------------

    def _read_file(self):
        """
        Decides if a castep or phonon file should be read then reads the file data
        Raises RuntimeError if no valid file is found.

        @return file_data dictionary holding all required data from the castep or phonon file
        """
        castep_filename = self.getPropertyValue('CASTEPFile')
        phonon_filename = self.getPropertyValue('PHONONFile')

        if phonon_filename != '' and self._spec_type != 'BondTable':
            return self._read_data_from_file(phonon_filename)
        elif castep_filename != '':
            return self._read_data_from_file(castep_filename)
        else:
            raise RuntimeError('No valid data file')

#----------------------------------------------------------------------------------------

    def _create_ion_table(self, unit_cell, ions):
        """
        Creates an ion table from the ions and unit cell in the file_data object
        populated when the phonon/castep file is parsed.
        @param unit_cell    :: The unit cell read from the castep/phonon file
        @param ions         :: The ion data obtained from the castep/phonon file
        """
        ion_table = s_api.CreateEmptyTableWorkspace(OutputWorkspace=self._out_ws_name)
        ion_table.addColumn('str', 'Species')
        ion_table.addColumn('int', 'FileIndex')
        ion_table.addColumn('int', 'Number')
        ion_table.addColumn('float', 'FractionalX')
        ion_table.addColumn('float', 'FractionalY')
        ion_table.addColumn('float', 'FractionalZ')
        ion_table.addColumn('float', 'CartesianX')
        ion_table.addColumn('float', 'CartesianY')
        ion_table.addColumn('float', 'CartesianZ')
        ion_table.addColumn('float', 'Isotope')

        self._convert_to_cartesian_coordinates(unit_cell, ions)

        for ion in ions:
            ion_table.addRow([ion['species'],
                              ion['index'],
                              ion['bond_number'],
                              ion['fract_coord'][0],
                              ion['fract_coord'][1],
                              ion['fract_coord'][2],
                              ion['cartesian_coord'][0],
                              ion['cartesian_coord'][1],
                              ion['cartesian_coord'][2],
                              ion['isotope_number']])

#----------------------------------------------------------------------------------------

    def _create_bond_table(self, bonds):
        """
        Creates a bond table from the bond data obtained when the castep file is read
        @param bonds       :: The bond data read from the castep file
        """
        if bonds is None or len(bonds) == 0:
            raise RuntimeError('No bonds found in CASTEP file')

        bond_table = s_api.CreateEmptyTableWorkspace(OutputWorkspace=self._out_ws_name)
        bond_table.addColumn('str', 'SpeciesA')
        bond_table.addColumn('int', 'NumberA')
        bond_table.addColumn('str', 'SpeciesB')
        bond_table.addColumn('int', 'NumberB')
        bond_table.addColumn('float', 'Length')
        bond_table.addColumn('float', 'Population')

        for bond in bonds:
            bond_table.addRow([bond['atom_a'][0],
                               bond['atom_a'][1],
                               bond['atom_b'][0],
                               bond['atom_b'][1],
                               bond['length'],
                               bond['population']])


#----------------------------------------------------------------------------------------

    def _calculate_partial_dos(self, ions, frequencies, eigenvectors, weights):
        """
        Calculate the partial Density of States for all the ions of interest to the user
        @param frequencies      :: frequency data from file
        @param eigenvectors     :: eigenvector data from file
        @param weights          :: weight data from file
        """
        # Build a dictionary of ions that the user cares about
        partial_ions = dict()

        calc_ion_index = self.getProperty('CalculateIonIndices').value

        if not calc_ion_index:
            for ion in self._ions_of_interest:
                partial_ions[ion] = [i['index'] for i in ions if i['species'] == ion]
        else:
            for ion in ions:
                if ion['species'] in self._ions_of_interest:
                    ion_identifier = ion['species'] + str(ion['index'])
                    partial_ions[ion_identifier] = ion['index']

        partial_workspaces, sum_workspace = self._compute_partial_ion_workflow(partial_ions, frequencies, eigenvectors, weights)

        if self.getProperty('SumContributions').value:
            # Discard the partial workspaces
            for partial_ws in partial_workspaces:
                s_api.DeleteWorkspace(partial_ws)

            # Rename the summed workspace, this will be the output
            s_api.RenameWorkspace(InputWorkspace=sum_workspace, OutputWorkspace=self._out_ws_name)

        else:
            s_api.DeleteWorkspace(sum_workspace)
            partial_ws_names = [ws.name() for ws in partial_workspaces]
            # Sort workspaces
            if calc_ion_index:
                # Sort by index after '_'
                partial_ws_names.sort(key=lambda item: (int(item[(item.rfind('_')+1):])))
            group = ','.join(partial_ws_names)
            s_api.GroupWorkspaces(group, OutputWorkspace=self._out_ws_name)

#----------------------------------------------------------------------------------------

    def _calculate_total_dos_with_scale(self, ions, frequencies, eigenvectors, weights):
        """
        Calculate the complete Density of States for all the ions of interest to the user with scaled intensities
        @param frequencies      :: frequency data from file
        @param eigenvectors     :: eigenvector data from file
        @param weights          :: weight data from file
        """
        # Build a dict of all ions
        all_ions = dict()
        for ion in set([i['species'] for i in ions]):
            all_ions[ion] = [i['index'] for i in ions if i['species'] == ion]

        partial_workspaces, sum_workspace = self._compute_partial_ion_workflow(all_ions, frequencies, eigenvectors, weights)

        # Discard the partial workspaces
        for partial_ws in partial_workspaces:
            s_api.DeleteWorkspace(partial_ws)

        # Rename the summed workspace, this will be the output
        s_api.RenameWorkspace(InputWorkspace=sum_workspace, OutputWorkspace=self._out_ws_name)

#----------------------------------------------------------------------------------------

    def _convert_to_cartesian_coordinates(self, unit_cell, ions):
        """
        Converts fractional coordinates to Cartesian coordinates given the unit
        cell vectors and adds to existing list of ions.

        @param unit_cell Unit cell vectors
        @param ions Ion list to be updated
        """
        for ion in ions:
            cell_pos = ion['fract_coord'] * unit_cell
            ion['cartesian_coord'] = np.apply_along_axis(np.sum, 0, cell_pos)

#----------------------------------------------------------------------------------------

    def _draw_peaks(self, xmin, hist, peaks):
        """
        Draw Gaussian or Lorentzian peaks to each point in the data

        @param xmin - minimum X value
        @param hist - array of counts for each bin
        @param peaks - the indicies of each non-zero point in the data
        @return the fitted y data
        """
        energies = np.arange(xmin, xmin + hist.size)

        if PEAK_WIDTH_ENERGY_FLAG in self._peak_width:
            try:
                peak_widths = np.fromiter([eval(self._peak_width.replace(PEAK_WIDTH_ENERGY_FLAG, str(energies[p])))
                                           for p in peaks], dtype=float)
            except SyntaxError:
                raise ValueError('Invalid peak width function (must be either a decimal or function containing "energy")')
            peak_widths = np.abs(peak_widths)
            logger.debug('Peak widths: %s' % (str(peak_widths)))
        else:
            single_val = np.array([float(self._peak_width)])
            peak_widths = np.repeat(single_val, len(peaks))

        if self._peak_func == "Gaussian":
            n_gauss = int(3.0 * np.max(peak_widths))
            dos = np.zeros(len(hist) - 1 + n_gauss)

            for index, width in zip(peaks, peak_widths.tolist()):
                sigma = width / 2.354
                for g in range(-n_gauss, n_gauss):
                    if index + g > 0:
                        dos[index + g] += hist[index] * math.exp(-g ** 2 / (2 * sigma ** 2)) /\
                                          (math.sqrt(2 * math.pi) * sigma)

        elif self._peak_func == "Lorentzian":
            n_lorentz = int(25.0 * np.max(peak_widths))
            dos = np.zeros(len(hist) - 1 + n_lorentz)

            for index, width in zip(peaks, peak_widths.tolist()):
                gamma_by_2 = width / 2
                for l in range(-n_lorentz, n_lorentz):
                    if index + l > 0:
                        dos[index + l] += hist[index] * gamma_by_2 / (l ** 2 + gamma_by_2 ** 2) / math.pi

        return dos

#----------------------------------------------------------------------------------------

    def _draw_sticks(self, peaks, dos_shape):
        """
        Draw a stick diagram for peaks.

        @param hist - array of counts for each bin
        @param peaks - the indicies of each non-zero point in the data
        @param dos_shape - shape of the DOS array with broadened peaks
        @return the y data
        """
        dos = np.zeros(dos_shape)
        stick_intensity = self.getProperty('StickHeight').value

        for index in peaks:
            dos[index] = stick_intensity

        return dos

#----------------------------------------------------------------------------------------

    def _compute_partial_ion_workflow(self, partial_ions, frequencies, eigenvectors, weights):
        """
        Computes the partial DoS workspaces for a given set of ions (optionally scaling them by
        the cross scattering sections) and sums them into a single spectra.

        Both the partial workspaces and the summed total are returned.

        @param partial_ions Dict of ions to caculate DoS for
        @param frequencies Frequencies read from file
        @param eigenvectors Eigenvectors read from file
        @param weights Weights for each frequency block
        @returns Tuple of list of partial workspace names and summed contribution workspace name
        """
        logger.debug('Computing partial DoS for: ' + str(partial_ions))

        partial_workspaces = []
        total_workspace = None

        # Output each contribution to it's own workspace
        for ion_name, ions in partial_ions.items():
            partial_ws_name = self._out_ws_name + '_'

            partial_ws = self._compute_partial(ions, frequencies, eigenvectors, weights)

            # Set correct units on partial workspace
            partial_ws.setYUnit('(D/A)^2/amu')
            partial_ws.setYUnitLabel('Intensity')

            # Add the sample material to the workspace
            match = re.search(r'\d', ion_name)
            element_index = ion_name
            if match:
                element_index = ion_name[:match.start()]
            chemical, ws_suffix = self._parse_chemical_and_ws_name(ion_name,
                                                                   self._element_isotope[element_index])
            partial_ws_name += ws_suffix

            s_api.SetSampleMaterial(InputWorkspace=self._out_ws_name,
                                    ChemicalFormula=chemical)

            # Multiply intensity by scatttering cross section
            if self._scale_by_cross_section == 'Incoherent':
                scattering_x_section = partial_ws.mutableSample().getMaterial().incohScatterXSection()
            elif self._scale_by_cross_section == 'Coherent':
                scattering_x_section = partial_ws.mutableSample().getMaterial().cohScatterXSection()
            elif self._scale_by_cross_section == 'Total':
                scattering_x_section = partial_ws.mutableSample().getMaterial().totalScatterXSection()

            if self._scale_by_cross_section != 'None':
                scale_alg = self.createChildAlgorithm('Scale')
                scale_alg.setProperty('InputWorkspace',self._out_ws_name)
                scale_alg.setProperty('OutputWorkspace',self._out_ws_name)
                scale_alg.setProperty('Operation','Multiply')
                scale_alg.setProperty('Factor', scattering_x_section)
                scale_alg.execute()

            rename_alg = self.createChildAlgorithm('RenameWorkspace')
            rename_alg.setProperty('InputWorkspace',self._out_ws_name)
            rename_alg.setProperty('OutputWorkspace',partial_ws_name)
            rename_alg.execute()
            partial_workspaces.append(rename_alg.getProperty('OutputWorkspace').value)

        total_workspace = self._out_ws_name + "_Total"

        # If there is more than one partial workspace need to sum first spectrum of all
        if len(partial_workspaces) > 1:
            initial_partial_ws = partial_workspaces[0]
            data_x = initial_partial_ws.dataX(0)
            dos_specs = np.zeros_like(initial_partial_ws.dataY(0))
            stick_specs = np.zeros_like(initial_partial_ws.dataY(0))

            for partial_ws in partial_workspaces:
                dos_specs += partial_ws.dataY(0)
                stick_specs += partial_ws.dataY(1)

            stick_specs[stick_specs > 0.0] = self.getProperty('StickHeight').value

            total_ws = self._create_dos_workspace(data_x, dos_specs, stick_specs, total_workspace)

            # Set correct units on total workspace
            total_ws.setYUnit('(D/A)^2/amu')
            total_ws.setYUnitLabel('Intensity')

        # Otherwise just repackage the WS we have as the total
        else:
            s_api.CloneWorkspace(InputWorkspace=partial_workspaces[0],
                                 OutputWorkspace=total_workspace)

        logger.debug('Partial workspaces: ' + str(partial_workspaces))
        logger.debug('Summed workspace: ' + str(total_workspace))

        return partial_workspaces, total_workspace

#----------------------------------------------------------------------------------------
    def _parse_chemical_and_ws_name(self, ion_name, isotope):
        """
        @param ion_name     :: Name of the element used
        @param isotope      :: Isotope of the element
        @return The chemical formula of the element and isotope
                expected by SetSampleMaterial
                AND
                The expected suffix for the partial workspace
        """
        # Get the index of the element (if present)
        match = re.search(r'\d', ion_name)
        element_index = ''
        if match:
            element_index = '_' + ion_name[match.start():]

        # If the chemical is a isotope
        if ':' in ion_name:
            chemical = ion_name.split(':')[0]
            # Parse isotope to rounded int
            chemical_formula = '(' + chemical + str(int(round(isotope))) + ')'
            ws_name_suffix = chemical + '('  + str(int(round(isotope))) + ')' + element_index
            return chemical_formula, ws_name_suffix
        # If the chemical has an index
        if match:
            chemical = ion_name[:match.start()]
            return chemical, chemical + element_index
        else:
            return ion_name, ion_name

#----------------------------------------------------------------------------------------

    def _compute_partial(self, ion_numbers, frequencies, eigenvectors, weights):
        """
        Compute partial Density Of States.

        This uses the eigenvectors in a .phonon file to calculate
        the partial density of states.

        @param ion_numbers - list of ion number to use in calculation
        @param frequencies - frequencies read from file
        @param eigenvectors - eigenvectors read from file
        @param weights - weights for each frequency block
        """

        intensities = []
        for block_vectors in eigenvectors:
            block_intensities = []
            for mode in range(self._num_branches):
                # Only select vectors for the ions we're interested in
                lower, upper = mode * self._num_ions, (mode + 1) * self._num_ions
                vectors = block_vectors[lower:upper]
                vectors = vectors[ion_numbers]

                # Compute intensity
                exponent = np.empty(vectors.shape)
                exponent.fill(2)
                vectors = np.power(vectors, exponent)
                total = np.sum(vectors)

                block_intensities.append(total)

            intensities += block_intensities

        intensities = np.asarray(intensities)
        return self._compute_DOS(frequencies, intensities, weights)


#----------------------------------------------------------------------------------------

    def _compute_DOS(self, frequencies, intensities, weights):
        """
        Compute Density Of States

        @param frequencies - frequencies read from file
        @param intensities - intensities read from file
        @param weights - weights for each frequency block
        """
        if frequencies.size > intensities.size:
            # If we have less intensities than frequencies fill the difference with ones.
            diff = frequencies.size - intensities.size
            intensities = np.concatenate((intensities, np.ones(diff)))

        if frequencies.size != weights.size or frequencies.size != intensities.size:
            raise ValueError("Number of data points must match!")

        # Ignore values below fzerotol
        zero_mask = np.where(np.absolute(frequencies) < self._zero_threshold)
        intensities[zero_mask] = 0.0

        # Sort data to follow natural ordering
        permutation = frequencies.argsort()
        frequencies = frequencies[permutation]
        intensities = intensities[permutation]
        weights = weights[permutation]

        # Weight intensities
        intensities = intensities * weights

        # Create histogram x data
        xmin, xmax = frequencies[0], frequencies[-1] + 1
        bins = np.arange(xmin, xmax, 1)

        # Sum values in each bin
        hist = np.zeros(bins.size)
        for index, (lower, upper) in enumerate(zip(bins, bins[1:])):
            bin_mask = np.where((frequencies >= lower) & (frequencies < upper))
            hist[index] = intensities[bin_mask].sum()

        # Find and fit peaks
        peaks = hist.nonzero()[0]
        dos = self._draw_peaks(xmin, hist, peaks)
        dos_sticks = self._draw_sticks(peaks, dos.shape)

        data_x = np.arange(xmin, xmin + dos.size)
        out_ws = self._create_dos_workspace(data_x, dos, dos_sticks, self._out_ws_name)

        scale = self.getProperty('Scale').value
        if scale != 1:
            scale_alg = self.createChildAlgorithm('Scale')
            scale_alg.setProperty('InputWorkspace',out_ws)
            scale_alg.setProperty('OutputWorkspace',out_ws)
            scale_alg.setProperty('Operation','Multiply')
            scale_alg.setProperty('Factor', scale)
            scale_alg.execute()

        bin_width = self.getProperty('BinWidth').value
        if bin_width != 1:
            x_min = out_ws.readX(0)[0] - (bin_width/2.0)
            x_max = out_ws.readX(0)[-1] + (bin_width/2.0)
            rebin_param = "%f, %f, %f" % (x_min, bin_width, x_max)
            out_ws = s_api.Rebin(Inputworkspace=out_ws, Params=rebin_param, OutputWorkspace=out_ws)

        return out_ws

#----------------------------------------------------------------------------------------

    def _create_dos_workspace(self, data_x, dos, dos_sticks, out_name):
        ws = s_api.CreateWorkspace(DataX=data_x,
                                   DataY=np.ravel(np.array([dos, dos_sticks])),
                                   NSpec=2,
                                   VerticalAxisUnit='Text',
                                   VerticalAxisValues=[self._peak_func, 'Stick'],
                                   OutputWorkspace=out_name,
                                   EnableLogging=False)
        unitx = ws.getAxis(0).setUnit("Label")
        unitx.setLabel("Energy Shift", 'cm^-1')
        return ws

#----------------------------------------------------------------------------------------

    def _compute_raman(self, frequencies, intensities, weights):
        """
        Compute Raman intensities

        @param frequencies - frequencies read from file
        @param intensities - raman intensities read from file
        @param weights - weights for each frequency block
        """
        # We only want to use the first set
        frequencies = frequencies[:self._num_branches]
        intensities = intensities[:self._num_branches]
        weights = weights[:self._num_branches]

        # Wavelength of the laser
        laser_wavelength = 514.5e-9
        # Planck's constant
        planck = scipy.constants.h
        # cm(-1) => K conversion
        cm1_to_K = scipy.constants.codata.value('inverse meter-kelvin relationship') * 100

        factor = (math.pow((2 * math.pi / laser_wavelength), 4) * planck) / (8 * math.pi ** 2 * 45) * 1e12
        x_sections = np.zeros(frequencies.size)

        # Use only the first set of frequencies and ignore small values
        zero_mask = np.where(frequencies > self._zero_threshold)
        frequency_x_sections = frequencies[zero_mask]
        intensity_x_sections = intensities[zero_mask]

        temperature = self.getProperty('Temperature').value

        bose_occ = 1.0 / (np.exp(cm1_to_K * frequency_x_sections / temperature) - 1)
        x_sections[zero_mask] = factor / frequency_x_sections * (1 + bose_occ) * intensity_x_sections

        return self._compute_DOS(frequencies, x_sections, weights)

#----------------------------------------------------------------------------------------

    def _read_data_from_file(self, file_name):
        """
        Select the appropriate file parser and check data was successfully
        loaded from file.

        @param file_name - path to the file.
        @return tuple of the frequencies, ir and raman intensities and weights
        """
        ext = os.path.splitext(file_name)[1]

        if ext == '.phonon':
            record_eigenvectors = self._calc_partial \
                                   or (self._spec_type == 'DOS' and self._scale_by_cross_section != 'None') \
                                   or self._spec_type == 'BondAnalysis'

            file_data, element_isotopes = parse_phonon_file(file_name, record_eigenvectors)
            self._element_isotope = element_isotopes
            self._num_ions = file_data['num_ions']

        elif ext == '.castep':
            if len(self._ions_of_interest) > 0:
                raise ValueError("Cannot compute partial density of states from .castep files.")

            ir_or_raman = self._spec_type == 'IR_Active' or self._spec_type == 'Raman_Active'
            file_data = parse_castep_file(file_name, ir_or_raman)

        if file_data['frequencies'].size == 0:
            raise ValueError("Failed to load any frequencies from file.")

        return file_data

#------------------------------------------------------------------------------------------

try:
    import scipy.constants
    AlgorithmFactory.subscribe(SimulatedDensityOfStates)
except ImportError:
    logger.debug('Failed to subscribe algorithm SimulatedDensityOfStates; The python package scipy may be missing.')