def METHOD_NAME(filepath, folderpath, mapper):
    """
    Extracts spectral data from hdf5 file written by fiber raman rig, uses 'mapper' to convert from Acton center wavelength, pixel position to a 
    wavelength.
    Parameters
    ----------
    filepath : string
        Path to HDF5 file containing data. 
    folderpath : string
        Path to group containing spectra inside HDF5 file
    mapper: function
        function signature: (float, int) -> float
        a function generated by a calibration file, mapping Acton center wavelength (float) and pixel offset on CCD (int) to a absolute wavelength (float)
    Returns
    -------
    data : list of 3-tuples
        tuple: (dt,wavelengths, intensity)
            dt : datetime tuple
            wavelengths: numpy.array [type:float], .shape: (1014,)
            intensity: numpy.array [type:integer], .shape: (1014,) 
                CCD size is 1024 but leftmost 10 pixels cut to remove edge effects
    """
    raw_data = extractor(filepath, folderpath)
    pixel_offsets = np.arange(0,1014) #pixel offsets in image
    def array_mapper(center_wavelength,pixel_offsets,mapper):
        wavelengths =  np.array([mapper(center_wavelength, offset) for offset in pixel_offsets])
        assert wavelengths.shape[0] == 1014, "wavelength list should contain 1014 values - one for every pixel/intensity value"
    mapped_data = [ (dt,array_mapper(center_wl, pixel_offsets, mapper),intensity) for (dt, center_wl, intensity) in raw_data]
    return mapped_data
    return mapped_data