# coding=utf-8
"""InaSAFE Disaster risk tool by Australian Aid - Metadata for generic Impact
function on Population for Continuous 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'
__date__ = '24/03/15'
from safe.common.utilities import OrderedDict
from safe.defaults import default_minimum_needs
from safe.defaults import (
default_gender_postprocessor,
age_postprocessor,
minimum_needs_selector)
from safe.utilities.i18n import tr
from safe.impact_functions.impact_function_metadata import \
ImpactFunctionMetadata
from safe.definitions import (
layer_mode_continuous,
layer_geometry_raster,
hazard_all,
hazard_category_multiple_event,
count_exposure_unit,
exposure_population,
hazard_category_single_event,
unit_generic,
density_exposure_unit
)
from safe.impact_functions.generic.continuous_hazard_population\
.parameter_definitions import categorical_thresholds
[docs]class ContinuousHazardPopulationMetadata(ImpactFunctionMetadata):
"""Metadata for Continuous 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': 'ContinuousHazardPopulationFunction',
'name': tr('Continuous raster hazard on population'),
'impact': tr('Be impacted'),
'title': tr('Be impacted'),
'function_type': 'old-style',
'author': 'AIFDR',
'date_implemented': 'N/A',
'overview': tr(
'To assess the impacts of continuous hazards in raster '
'format on population raster layer.'),
'detailed_description': tr(
'This function will categorised the continuous hazard '
'level into 3 category based on the threshold that has '
'been input by the user. After that, this function will '
'calculate how many people will be impacted per category '
'for all categories in the hazard layer.'),
'hazard_input': tr(
'A hazard raster layer where each cell represents the '
'level of the hazard. The hazard has continuous value of '
'hazard level.'),
'exposure_input': tr(
'An exposure raster layer where each cell represent '
'population count.'),
'output': tr(
'Map of population exposed to high category and a table '
'with number of people in each category'),
'actions': tr(
'Provide details about how many people would likely '
'be impacted in each category.'),
'limitations': [tr('Only three categories can be used.')],
'citations': [],
'layer_requirements': {
'hazard': {
'layer_mode': layer_mode_continuous,
'layer_geometries': [layer_geometry_raster],
'hazard_categories': [
hazard_category_multiple_event,
hazard_category_single_event
],
'hazard_types': hazard_all,
'continuous_hazard_units': [unit_generic],
'vector_hazard_classifications': [],
'raster_hazard_classifications': [],
'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': []
}
},
# Configurable parameters
'parameters': OrderedDict([
('Categorical thresholds', categorical_thresholds()),
('postprocessors', OrderedDict([
('Gender', default_gender_postprocessor()),
('Age', age_postprocessor()),
('MinimumNeeds', minimum_needs_selector()),
])),
('minimum needs', default_minimum_needs())
])
}
return dict_meta