Source code for safe.impact_functions.generic.classified_raster_population.metadata_definitions

# coding=utf-8
"""InaSAFE Disaster risk tool by Australian Aid - Metadata for generic Impact
function on Population for Classified Hazard.

Contact : [email protected]

.. note:: This program is free software; you can redistribute it and/or modify
     it under the terms of the GNU General Public License as published by
     the Free Software Foundation; either version 2 of the License, or
     (at your option) any later version.


__author__ = 'lucernae'
__project_name__ = 'inasafe'
__filename__ = 'metadata_definitions'
__date__ = '24/03/15'
__copyright__ = '[email protected]'

from safe.common.utilities import OrderedDict
from safe.defaults import default_minimum_needs
from safe.defaults import (
from safe.utilities.i18n import tr
from safe.impact_functions.impact_function_metadata import \
from safe.definitions import (
from safe.impact_functions.generic.parameter_definitions import \

[docs]class ClassifiedRasterHazardPopulationMetadata(ImpactFunctionMetadata): """Metadata for Classified Hazard Population Impact Function. .. versionadded:: 2.1 We only need to re-implement as_dict(), all other behaviours are inherited from the abstract base class. """ @staticmethod
[docs] 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': 'ClassifiedRasterHazardPopulationFunction', 'name': tr('Classified raster hazard on population'), 'impact': tr('Be affected in each class'), 'title': tr('Be affected in each hazard class'), 'function_type': 'old-style', 'author': 'Dianne Bencito', 'date_implemented': 'N/A', 'overview': tr( 'To assess the impacts of classified hazards in raster ' 'format on a population raster layer.'), 'detailed_description': tr( 'This function will treat the values in the hazard raster ' 'layer as classes representing low, medium and high ' 'impact. You need to ensure that the keywords for the hazard ' 'layer have been set appropriately to define these classes.' 'The number of people that will be affected will be ' 'calculated for each class. The report will show the total ' 'number of people that will be affected for each ' 'hazard class.'), 'hazard_input': tr( 'A hazard raster layer where each cell represents the ' 'class of the hazard. There should be three classes: e.g. ' '1, 2, and 3.'), 'exposure_input': tr( 'An exposure raster layer where each cell represents the' 'population count for that cell.'), 'output': tr( 'Map of population exposed to the highest class and a table ' 'with the number of people in each class'), 'actions': tr( 'Provide details about how many people would likely be ' 'affected for each hazard class.'), 'limitations': [tr('The number of classes is three.')], 'citations': [], 'layer_requirements': { 'hazard': { 'layer_mode': layer_mode_classified, 'layer_geometries': [layer_geometry_raster], 'hazard_categories': [ hazard_category_single_event, hazard_category_multiple_event ], 'hazard_types': hazard_all, 'continuous_hazard_units': [], 'vector_hazard_classifications': [], 'raster_hazard_classifications': [ generic_raster_hazard_classes ], 'additional_keywords': [] }, 'exposure': { 'layer_mode': layer_mode_continuous, 'layer_geometries': [layer_geometry_raster], 'exposure_types': [exposure_population], 'exposure_units': [ count_exposure_unit, density_exposure_unit], 'exposure_class_fields': [], 'additional_keywords': [] } }, 'parameters': OrderedDict([ ('Categorical hazards', categorical_hazards()), ('postprocessors', OrderedDict([ ('Gender', default_gender_postprocessor()), ('Age', age_postprocessor()), ('MinimumNeeds', minimum_needs_selector()), ])), ('minimum needs', default_minimum_needs()) ]) } return dict_meta