def as_dict(): """Return metadata as a dictionary. This is a static method. You can use it to get the metadata in dictionary format for an impact function. :returns: A dictionary representing all the metadata for the concrete impact function. :rtype: dict """ dict_meta = { 'id': 'FloodRasterBuildingFunction', 'name': tr('Raster flood on buildings'), 'impact': tr('Be flooded'), 'title': tr('Be flooded'), 'function_type': 'old-style', # should be a list, but we can do it later. 'author': 'Ole Nielsen and Kristy van Putten', 'date_implemented': 'N/A', 'overview': tr( 'To assess the impacts of (flood or tsunami) inundation ' 'on building footprints originating from OpenStreetMap ' '(OSM) with hazard in raster format.'), 'detailed_description': tr( 'The inundation status is calculated for each building ' '(using the centroid if it is a polygon) based on the ' 'flood threshold. The threshold can be configured in ' 'impact function options.'), 'hazard_input': tr( 'A hazard raster layer where each cell represents flood ' 'depth (in meters).'), 'exposure_input': tr( 'Vector polygon or point layer extracted from OSM where ' 'each feature represents the footprint of a building.'), 'output': tr( 'Vector layer contains building is estimated to be ' 'flooded and the breakdown of the building by type.'), 'actions': tr( 'Provide details about where critical infrastructure ' 'might be flooded.'), 'limitations': [ tr('This function only flags buildings as impacted or not ' 'either based on a fixed threshold') ], 'citations': [ { 'text': None, 'link': None } ], 'legend_notes': '', 'legend_title': tr('Flooded structure status'), 'legend_units': tr('(flooded, wet, or dry)'), 'layer_requirements': { 'hazard': { 'layer_mode': layer_mode_continuous, 'layer_geometries': [layer_geometry_raster], 'hazard_categories': [ hazard_category_single_event, hazard_category_multiple_event ], 'hazard_types': [hazard_flood], 'continuous_hazard_units': [unit_feet, unit_metres], 'vector_hazard_classifications': [], 'raster_hazard_classifications': [], 'additional_keywords': [] }, 'exposure': { 'layer_mode': layer_mode_classified, 'layer_geometries': [ layer_geometry_point, layer_geometry_polygon ], 'exposure_types': [exposure_structure], 'exposure_units': [], 'exposure_class_fields': [structure_class_field], 'additional_keywords': [] } }, 'parameters': OrderedDict([ ('threshold', threshold()), ('postprocessors', OrderedDict([ ('BuildingType', building_type_postprocessor()) ])) ]) } return dict_meta
def as_dict(): """Return metadata as a dictionary. This is a static method. You can use it to get the metadata in dictionary format for an impact function. :returns: A dictionary representing all the metadata for the concrete impact function. :rtype: dict """ dict_meta = { 'id': 'FloodRasterBuildingFunction', 'name': tr('Raster flood on buildings'), 'impact': tr('Be flooded'), 'title': tr('Be flooded'), 'function_type': 'old-style', # should be a list, but we can do it later. 'author': 'Ole Nielsen and Kristy van Putten', 'date_implemented': 'N/A', 'overview': tr( 'To assess the impacts of (flood or tsunami) inundation ' 'on building footprints originating from OpenStreetMap ' '(OSM).'), 'detailed_description': tr( 'The inundation status is calculated for each building ' '(using the centroid if it is a polygon) based on the ' 'hazard levels provided. if the hazard is given as a ' 'raster a threshold of 1 meter is used. This is ' 'configurable through the InaSAFE interface. If the ' 'hazard is given as a vector polygon layer buildings are ' 'considered to be impacted depending on the value of ' 'hazard attributes (in order) affected" or "FLOODPRONE": ' 'If a building is in a region that has attribute ' '"affected" set to True (or 1) it is impacted. If ' 'attribute "affected" does not exist but "FLOODPRONE" ' 'does, then the building is considered impacted if ' '"FLOODPRONE" is "yes". If neither affected" nor ' '"FLOODPRONE" is available, a building will be impacted ' 'if it belongs to any polygon. The latter behaviour is ' 'implemented through the attribute "inapolygon" which is ' 'automatically assigned.'), 'hazard_input': tr( 'A hazard raster layer where each cell represents flood ' 'depth (in meters).'), 'exposure_input': tr( 'Vector polygon or point layer extracted from OSM where ' 'each feature represents the footprint of a building.'), 'output': tr( 'Vector layer contains building is estimated to be ' 'flooded and the breakdown of the building by type.'), 'actions': tr( 'Provide details about where critical infrastructure ' 'might be flooded.'), 'limitations': [ tr('This function only flags buildings as impacted or not ' 'either based on a fixed threshold in case of raster ' 'hazard or the the attributes mentioned under input ' 'in case of vector hazard.') ], 'citations': [], 'layer_requirements': { 'hazard': { 'layer_mode': layer_mode_continuous, 'layer_geometries': [layer_geometry_raster], 'hazard_categories': [ hazard_category_single_event, hazard_category_multiple_event ], 'hazard_types': [hazard_flood, hazard_tsunami], 'continuous_hazard_units': [unit_feet, unit_metres], 'vector_hazard_classifications': [], 'raster_hazard_classifications': [], 'additional_keywords': [] }, 'exposure': { 'layer_mode': layer_mode_classified, 'layer_geometries': [ layer_geometry_point, layer_geometry_polygon ], 'exposure_types': [exposure_structure], 'exposure_units': [], 'exposure_class_fields': [structure_class_field], 'additional_keywords': [] } }, 'parameters': OrderedDict([ ('threshold', threshold()), ('postprocessors', OrderedDict([ ('BuildingType', building_type_postprocessor()) ])) ]) } return dict_meta