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
