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': 'TsunamiRasterBuildingFunction', 'name': tr('Raster tsunami on buildings'), 'impact': tr('Be inundated'), 'title': tr('Be inundated'), 'function_type': 'old-style', # should be a list, but we can do it later. 'author': 'Ole Nielsen, Kristy van Putten, and Ismail Sunni', 'date_implemented': 'N/A', 'overview': tr( 'To assess the impacts of tsunami inundation on building ' 'footprints in vector format 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 ' 'tsunami threshold. The threshold can be configured in ' 'impact function options.'), 'hazard_input': tr( 'A hazard raster layer where each cell represents tsunami ' 'inundation depth (in meters).'), 'exposure_input': tr( 'Vector polygon or point layer where each feature represents ' 'the footprint of a building.'), 'output': tr( 'Vector layer contains building is estimated to be ' 'inundated and the breakdown of the building by type.'), 'actions': tr( 'Provide details about where critical infrastructure ' 'might be inundated.'), 'limitations': [tr( 'This function only flags buildings as impacted or not either ' 'based on a fixed threshold') ], 'citations': [ tr('Papadopoulos, Gerassimos A., and Fumihiko Imamura. ' '"A proposal for a new tsunami intensity scale." ' 'ITS 2001 proceedings, no. 5-1, pp. 569-577. 2001.') ], 'legend_notes': '', 'map_title': tr('Inundated buildings'), 'legend_title': tr('Inundated structure status'), 'legend_units': tr('(low, medium, high, and very high)'), 'layer_name': tr('Estimated buildings affected'), '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_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( [ ('low_threshold', low_threshold()), ('medium_threshold', medium_threshold()), ('high_threshold', high_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': 'TsunamiRasterRoadFunction', 'name': tr('Raster tsunami on roads'), 'impact': tr('Be inundated'), 'title': tr('Be inundated'), 'function_type': 'qgis2.0', # should be a list, but we can do it later. 'author': 'Ole Nielsen, Kristy van Putten, and Ismail Sunni', 'date_implemented': 'N/A', 'overview': tr( 'To assess the impacts of tsunami inundation on roads in ' 'vector format with hazard in raster format.'), 'detailed_description': tr( 'The inundation status is calculated for each roads based on ' 'the tsunami threshold. The threshold can be configured in ' 'impact function options.'), 'hazard_input': tr( 'A hazard raster layer where each cell represents tsunami ' 'inundation depth (in meters).'), 'exposure_input': tr( 'Vector line where each feature represents the road.'), 'output': tr( 'Vector layer contains road is estimated to be ' 'inundated and the breakdown of the road by type.'), 'actions': tr( 'Provide details about where critical road ' 'might be inundated.'), 'limitations': [], 'citations': [ { 'text': None, 'link': None } ], 'legend_units': '', 'legend_notes': '', 'legend_title': tr('Road inundated status'), '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_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_line], 'exposure_types': [exposure_road], 'exposure_units': [], 'exposure_class_fields': [road_class_field], 'additional_keywords': [] } }, 'parameters': OrderedDict( [ ('low_threshold', low_threshold()), ('medium_threshold', medium_threshold()), ('high_threshold', high_threshold()), ('postprocessors', OrderedDict([ ('RoadType', road_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': 'TsunamiRasterRoadFunction', 'name': tr('Raster tsunami on roads'), 'impact': tr('Be inundated'), 'title': tr('Be inundated'), 'function_type': 'qgis2.0', # should be a list, but we can do it later. 'author': 'Ole Nielsen, Kristy van Putten, and Ismail Sunni', 'date_implemented': 'N/A', 'overview': tr( 'To assess the impacts of tsunami inundation on roads in ' 'vector format with hazard in raster format.'), 'detailed_description': tr( 'The inundation status is calculated for each roads based on ' 'the tsunami threshold. The threshold can be configured in ' 'impact function options.'), 'hazard_input': tr( 'A hazard raster layer where each cell represents tsunami ' 'inundation depth (in meters).'), 'exposure_input': tr( 'Vector line where each feature represents the road.'), 'output': tr( 'Vector layer contains road is estimated to be ' 'inundated and the breakdown of the road by type.'), 'actions': tr( 'Provide details about where critical road ' 'might be inundated.'), 'limitations': [], 'citations': [ { 'text': None, 'link': None } ], 'legend_units': '', 'legend_notes': '', 'map_title': tr('Roads inundated'), 'legend_title': tr('Road inundated status'), 'layer_name': tr('Flooded roads'), '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_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_line], 'exposure_types': [exposure_road], 'exposure_units': [], 'exposure_class_fields': [road_class_field], 'additional_keywords': [] } }, 'parameters': OrderedDict( [ ('low_threshold', low_threshold()), ('medium_threshold', medium_threshold()), ('high_threshold', high_threshold()), ('postprocessors', OrderedDict([ ('RoadType', road_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': 'TsunamiRasterBuildingFunction', 'name': tr('Raster tsunami on buildings'), 'impact': tr('Be inundated'), 'title': tr('Be inundated'), 'function_type': 'old-style', # should be a list, but we can do it later. 'author': 'Ole Nielsen, Kristy van Putten, and Ismail Sunni', 'date_implemented': 'N/A', 'overview': tr('To assess the impacts of tsunami inundation on building ' 'footprints in vector format 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 ' 'tsunami threshold. The threshold can be configured in ' 'impact function options.'), 'hazard_input': tr('A hazard raster layer where each cell represents tsunami ' 'inundation depth (in meters).'), 'exposure_input': tr('Vector polygon or point layer where each feature represents ' 'the footprint of a building.'), 'output': tr('Vector layer contains building is estimated to be ' 'inundated and the breakdown of the building by type.'), 'actions': tr('Provide details about where critical infrastructure ' 'might be inundated.'), 'limitations': [ tr('This function only flags buildings as impacted or not either ' 'based on a fixed threshold') ], 'citations': [{ 'text': tr('Papadopoulos, Gerassimos A., and Fumihiko Imamura. ' '"A proposal for a new tsunami intensity scale." ' 'ITS 2001 proceedings, no. 5-1, pp. 569-577. 2001.'), 'link': None }], 'legend_notes': '', 'legend_title': tr('Inundated structure status'), 'legend_units': tr('(low, medium, high, and very high)'), '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_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([('low_threshold', low_threshold()), ('medium_threshold', medium_threshold()), ('high_threshold', high_threshold()), ('postprocessors', OrderedDict([('BuildingType', building_type_postprocessor())]))]) } return dict_meta