How to use the pythoms.xlsx.XLSX function in pythoms

def test_xlsx(self):
        xlfile = XLSX(
            validation_path / 'xlsx_validation',
            verbose=False
        )
        spec, xunit, yunit = xlfile.pullspectrum('example MS spectrum')
        multispec = xlfile.pullmultispectrum('example multi-spectrum')
        rsimparams = xlfile.pullrsimparams()
        xlout = XLSX(
            validation_path / 'xlsxtestout.xlsx',
            create=True,
            verbose=False
        )
        xlout.writespectrum(spec[0], spec[1], 'test single spectrum out', xunit, yunit)
        for key, val in sorted(multispec.items()):
            xlout.writemultispectrum(
                multispec[key]['x'],
                multispec[key]['y'],

def test_xlsx(self):
        xlfile = XLSX(
            validation_path / 'xlsx_validation',
            verbose=False
        )
        spec, xunit, yunit = xlfile.pullspectrum('example MS spectrum')
        multispec = xlfile.pullmultispectrum('example multi-spectrum')
        rsimparams = xlfile.pullrsimparams()
        xlout = XLSX(
            validation_path / 'xlsxtestout.xlsx',
            create=True,
            verbose=False
        )
        xlout.writespectrum(spec[0], spec[1], 'test single spectrum out', xunit, yunit)
        for key, val in sorted(multispec.items()):
            xlout.writemultispectrum(
                multispec[key]['x'],
                multispec[key]['y'],
                multispec[key]['xunit'],
                multispec[key]['yunit'],
                'Function Chromatograms',
                key
            )
        xlout.save()
        os.remove(

except KeyError:
        raise KeyError('\nThe specified figure setting "%s" is not defined.\nPlease check your spelling' % setting)


if __name__ == '__main__':
    os.chdir(curdir)  # change to current working directory

    keywords = presets(setting)  # pull preset kwargs

    if spectrum.lower().endswith('.mzml.gz') or spectrum.lower().endswith('.raw'):  # if supplied with a mass spec file
        mzml = mzML(spectrum)
        exp = mzml.sum_scans()
        keywords.update({'outname': mzml.filename.split('.')[0]})  # set default output filename

    else:  # otherwise assume that it is an excel file
        xlfile = XLSX(spectrum, verbose=True)  # load excel file
        if sheetname is None:  # otherwise use the first sheet
            sheetname = xlfile.wb.sheetnames[0]
        exp = xlfile.pullspectrum(sheetname, skiplines=skiplines)[0]  # load spectrum from first sheet in workbook
        keywords.update({  # set default output filename
            'outname': f'{xlfile.bookname[:-5]} ({sheetname})',
        })

    keywords.update(override)  # apply any user overrides
    plot_mass_spectrum(exp, simdict, **keywords)
    import gc

    gc.collect()

st.printstart()
    mzml = mzML(filename)  # create mzML object
    if start is None:
        start = mzml.functions[1]['sr'][0] + 1
    if end is None:
        end = mzml.functions[1]['sr'][1] + 1
    x, y = mzml.sum_scans(
        start=start,
        end=end,
        dec=dec,
    )
    if save is not False:
        if type(save) == str:  # if a filename was provided for the Excel file
            xlfile = XLSX(save, create=True)
        else:  # otherwise use the mzML filename
            xlfile = XLSX(filename, create=True)
        xlfile.writespectrum(  # write the spectrum to file
            x,
            y,
            'summed spectra (scans %d-%d)' % (start, end)
        )
        xlfile.save()
    st.printend()
    return x, y  # return if specified

xvals = op.chart.Reference(ws, min_col=1, min_row=2, max_row=len(x) + 1)  # define the x values
            chart.x_axis.title = 'm/z'  # x axis title
            if norm is False:  # if there is no normalized data
                yvals = op.chart.Reference(ws, min_col=2, min_row=1, max_row=len(x) + 1)
                chart.y_axis.title = 'Intensity (counts)'
            if norm is True:  # if there is normalized data
                yvals = op.chart.Reference(ws, min_col=3, min_row=1, max_row=len(x) + 1)
                chart.y_axis.title = 'Normalized Intensity'
            series = op.chart.Series(yvals, xvals)
            chart.series.append(series)  # add the data to the chart
            ws.add_chart(chart, 'E1')  # add the chart to the worksheet


if __name__ == '__main__':
    name = 'Useless delete this'
    xlfile = XLSX(name, create=True)

st = ScriptTime()
    st.printstart()
    mzml = mzML(filename)  # create mzML object
    if start is None:
        start = mzml.functions[1]['sr'][0] + 1
    if end is None:
        end = mzml.functions[1]['sr'][1] + 1
    x, y = mzml.sum_scans(
        start=start,
        end=end,
        dec=dec,
    )
    if save is not False:
        if type(save) == str:  # if a filename was provided for the Excel file
            xlfile = XLSX(save, create=True)
        else:  # otherwise use the mzML filename
            xlfile = XLSX(filename, create=True)
        xlfile.writespectrum(  # write the spectrum to file
            x,
            y,
            'summed spectra (scans %d-%d)' % (start, end)
        )
        xlfile.save()
    st.printend()
    return x, y  # return if specified

# ----------------------------------------------------------
    # -------------------PROGRAM BEGINS-------------------------
    # ----------------------------------------------------------

    if verbose is True:
        stime = ScriptTime()
        stime.printstart()

    n = check_integer(n, 'number of scans to sum')  # checks integer input and converts to list

    if type(xlsx) != dict:
        if verbose is True:
            sys.stdout.write('Loading processing parameters from excel file')
            sys.stdout.flush()
        xlfile = XLSX(xlsx, verbose=verbose)
        sp = xlfile.pullrsimparams()
    else:  # if parameters were provided in place of an excel file
        sp = xlsx

    mskeys = ['+', '-']
    for key in sp:
        if 'formula' in sp[key] and sp[key]['formula'] is not None:  # if formula is specified
            sp[key]['mol'] = IPMolecule(sp[key]['formula'])  # create Molecule object
            sp[key]['bounds'] = sp[key]['mol'].calculate_bounds(
                bounds_confidence
            )  # generate bounds from molecule object with this confidence interval
    if verbose is True:
        sys.stdout.write(' DONE\n')

    rtime = {}  # empty dictionaries for time and tic
    tic = {}

# end m/z for the spectrum
endmz = 700

# colour for the plotted spectrum (see _Colour for more details)
colour = 'k'

# the excel file name to find the x,y values for the spectra
filename = 'Dy'

# the type of the spectrum (either 'continuum' or 'centroid')
spectype = 'continuum'

#########################################################################################
# there is no need to modify the rest of the script
if __name__ == '__main__':
    xlfile = XLSX(filename)  # load excel file

    for sheet in xlfile.wb.sheetnames:  # for each sheet
        sys.stdout.write('Plotting spectrum "%s"' % sheet)
        sys.stdout.flush()
        spec = xlfile.pullspectrum(sheet, 8)[0]  # pull spectrum
        spec[1] = normalize(spec[1], 100.)  # normalize to 100
        outname = filename + ' - ' + sheet + ' (' + str(startmz) + '-' + str(endmz) + ')'
        plot_mass_spectrum(
            spec,
            outname=outname,
            spectype=spectype,
            mz=[startmz, endmz],
            padding=[0.1, 0.95, 0.13, 0.96],
            verbose=False,
            speccolour=colour
        )