analysis/webservice/algorithms/Tomogram.py [468:518]:
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        },
        "minElevation": {
            "name": "Minimum Elevation",
            "type": "int",
            "description": "Minimum Elevation. Required."
        },
        "maxElevation": {
            "name": "Maximum Elevation",
            "type": "int",
            "description": "Maximum Elevation. Required."
        },
        "horizontalMargin": {
            "name": "Horizontal Margin",
            "type": "float",
            "description": "Margin +/- desired lat/lon slice to include in output. Default: 0.001m"
        },
        "peaks": {
            "name": "Calculate peaks",
            "type": "boolean",
            "description": "Calculate peaks along tomogram slice (currently uses simplest approach). "
                           "Ignored with \'elevPercentiles\'"
        },
        "canopy_ds": {
            "name": "Canopy height dataset name",
            "type": "string, comma-separated pair of strings",
            "description": "Dataset(s) containing canopy heights (RH98). This is used to trim out tomogram voxels that "
                           "return over the measured or predicted canopy. If 2 are provided, the first is considered "
                           "more accurate and will be favored for masking."
        },
        "ground_ds": {
            "name": "Ground height dataset name",
            "type": "string, comma-separated pair of strings",
            "description": "Dataset containing ground height (DEM). This is used to trim out tomogram voxels that "
                           "return below the measured or predicted ground. If 2 are provided, the first is considered "
                           "more accurate and will be favored for masking."
        },
        "elevPercentiles": {
            "name": "Elevation percentiles",
            "type": "boolean",
            "description": "Display percentiles of cumulative returns over elevation. Requires both canopy_ds and "
                           "ground_ds be set."
        },
        "cmap": {
            "name": "Color Map",
            "type": "string",
            "description": f"Color map to use. Will default to viridis if not provided or an unsupported map is "
                           f"provided. Supported cmaps: {[k for k in sorted(mpl.colormaps.keys())]}"
        },
        "cbarMin": {
            "name": "Color bar min",
            "type": "float",
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analysis/webservice/algorithms/Tomogram.py [811:861]:
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        },
        "minElevation": {
            "name": "Minimum Elevation",
            "type": "int",
            "description": "Minimum Elevation. Required."
        },
        "maxElevation": {
            "name": "Maximum Elevation",
            "type": "int",
            "description": "Maximum Elevation. Required."
        },
        "horizontalMargin": {
            "name": "Horizontal Margin",
            "type": "float",
            "description": "Margin +/- desired lat/lon slice to include in output. Default: 0.001m"
        },
        "peaks": {
            "name": "Calculate peaks",
            "type": "boolean",
            "description": "Calculate peaks along tomogram slice (currently uses simplest approach). "
                           "Ignored with \'elevPercentiles\'"
        },
        "canopy_ds": {
            "name": "Canopy height dataset name",
            "type": "string, comma-separated pair of strings",
            "description": "Dataset(s) containing canopy heights (RH98). This is used to trim out tomogram voxels that "
                           "return over the measured or predicted canopy. If 2 are provided, the first is considered "
                           "more accurate and will be favored for masking."
        },
        "ground_ds": {
            "name": "Ground height dataset name",
            "type": "string, comma-separated pair of strings",
            "description": "Dataset containing ground height (DEM). This is used to trim out tomogram voxels that "
                           "return below the measured or predicted ground. If 2 are provided, the first is considered "
                           "more accurate and will be favored for masking."
        },
        "elevPercentiles": {
            "name": "Elevation percentiles",
            "type": "boolean",
            "description": "Display percentiles of cumulative returns over elevation. Requires both canopy_ds and "
                           "ground_ds be set."
        },
        "cmap": {
            "name": "Color Map",
            "type": "string",
            "description": f"Color map to use. Will default to viridis if not provided or an unsupported map is "
                           f"provided. Supported cmaps: {[k for k in sorted(mpl.colormaps.keys())]}"
        },
        "cbarMin": {
            "name": "Color bar min",
            "type": "float",
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