analysis/webservice/algorithms/Tomogram.py [608:649]:
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        min_elevation = get_required_int('minElevation')
        max_elevation = get_required_int('maxElevation')

        horizontal_margin = compute_options.get_float_arg('horizontalMargin', 0.001)

        ch_ds = compute_options.get_argument('canopy_ds', None)
        g_ds = compute_options.get_argument('ground_ds', None)

        if ch_ds is not None:
            ch_ds = [v.strip() for v in ch_ds.split(',')]
        else:
            ch_ds = []

        if len(ch_ds) > 2:
            raise NexusProcessingException(
                reason='Too many datasets provided for canopy_ds', code=400
            )

        if g_ds is not None:
            g_ds = [v.strip() for v in g_ds.split(',')]
        else:
            g_ds = []

        if len(g_ds) > 2:
            raise NexusProcessingException(
                reason='Too many datasets provided for ground_ds', code=400
            )

        percentiles = compute_options.get_boolean_arg('elevPercentiles')

        if percentiles and (ch_ds is None or g_ds is None):
            raise NexusProcessingException(
                code=400,
                reason='\'elevPercentiles\' argument requires \'canopy_ds\' and \'ground_ds\' be set'
            )

        peaks = compute_options.get_boolean_arg('peaks') and not percentiles

        cmap = mpl.colormaps.get(
            compute_options.get_argument('cmap', 'viridis'),
            mpl.colormaps['viridis']
        )
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analysis/webservice/algorithms/Tomogram.py [951:992]:
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        min_elevation = get_required_int('minElevation')
        max_elevation = get_required_int('maxElevation')

        horizontal_margin = compute_options.get_float_arg('horizontalMargin', 0.001)

        ch_ds = compute_options.get_argument('canopy_ds', None)
        g_ds = compute_options.get_argument('ground_ds', None)

        if ch_ds is not None:
            ch_ds = [v.strip() for v in ch_ds.split(',')]
        else:
            ch_ds = []

        if len(ch_ds) > 2:
            raise NexusProcessingException(
                reason='Too many datasets provided for canopy_ds', code=400
            )

        if g_ds is not None:
            g_ds = [v.strip() for v in g_ds.split(',')]
        else:
            g_ds = []

        if len(g_ds) > 2:
            raise NexusProcessingException(
                reason='Too many datasets provided for ground_ds', code=400
            )

        percentiles = compute_options.get_boolean_arg('elevPercentiles')

        if percentiles and (ch_ds is None or g_ds is None):
            raise NexusProcessingException(
                code=400,
                reason='\'elevPercentiles\' argument requires \'canopy_ds\' and \'ground_ds\' be set'
            )

        peaks = compute_options.get_boolean_arg('peaks') and not percentiles

        cmap = mpl.colormaps.get(
            compute_options.get_argument('cmap', 'viridis'),
            mpl.colormaps['viridis']
        )
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