Source code for safe.impact_functions.earthquake.itb_earthquake_fatality_model.metadata_definitions

# coding=utf-8
"""InaSAFE Disaster risk tool by Australian Aid - Metadata for ITB Earthquake
Impact Function on Population.

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.

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 (

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

[docs]class ITBFatalityMetadata(ImpactFunctionMetadata): """Metadata for ITB Fatality 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': 'ITBFatalityFunction', 'name': tr('Earthquake ITB fatality function'), 'impact': tr('Die or be displaced'), 'title': tr('Die or be displaced'), 'function_type': 'old-style', 'author': 'Hadi Ghasemi', 'date_implemented': 'N/A', 'overview': tr( 'To assess the impact of earthquake on population based ' 'on the earthquake model for Indonesia developed by ITB.'), 'detailed_description': tr( 'This model was developed by Institut Teknologi Bandung ' '(ITB) and implemented by Dr. Hadi Ghasemi, Geoscience ' 'Australia\n' 'Algorithm:\n' 'In this study, the same functional form as Allen (2009) ' 'is adopted o express fatality rate as a function of ' 'intensity (see Eq. 10 in the report). The Matlab ' 'built-in function (fminsearch) for Nelder-Mead algorithm ' 'was used to estimate the model parameters. The objective ' 'function (L2G norm) that is minimized during the ' 'optimisation is the same as the one used by Jaiswal ' 'et al. (2010).\n' 'The coefficients used in the indonesian model are ' 'x=0.62275231, y=8.03314466, zeta=2.15'), 'hazard_input': '', 'exposure_input': '', 'output': '', 'actions': tr( 'Provide details about the population including ' 'estimates for mortalities and displaced persons.'), 'limitations': [ tr('The model is based on a limited number of observed ' 'fatality rates during four previous fatal events.'), tr('The model clearly over-predicts the fatality rates at ' 'intensities higher than VIII.'), tr('The model only estimates the expected fatality rate ' 'for a given intensity level. The associated ' 'uncertainty for the proposed model is not addressed.'), tr('There are few known issues in the current model:\n\n' '* rounding MMI values to the nearest 0.5,\n' '* Implemention of Finite-Fault models of candidate ' ' events, and\n' '* consistency between selected GMPEs with those in ' ' use by BMKG.\n') ], 'citations': [ tr('Indonesian Earthquake Building-Damage and Fatality ' 'Models and Post Disaster Survey Guidelines ' 'Development Bali, 27-28 February 2012, 54pp.'), tr('Allen, T. I., Wald, D. J., Earle, P. S., Marano, K. ' 'D., Hotovec, A. J., Lin, K., and Hearne, M., 2009. An ' 'Atlas of ShakeMaps and population exposure catalog ' 'for earthquake loss modeling, Bull. Earthq. Eng. 7, ' '701-718.'), tr('Jaiswal, K., and Wald, D., 2010. An empirical model ' 'for global earthquake fatality estimation, Earthq. ' 'Spectra 26, 1017-1037.') ], '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_earthquake], 'continuous_hazard_units': [unit_mmi], '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], 'exposure_class_fields': [], 'additional_keywords': [] } }, 'parameters': OrderedDict([ ('postprocessors', OrderedDict([ ('Gender', default_gender_postprocessor()), ('Age', age_postprocessor()), ('MinimumNeeds', minimum_needs_selector()), ])), ('minimum needs', default_minimum_needs()) ]) } return dict_meta