emodpy_tbhiv.demographics.TBHIVDemographics module

class emodpy_tbhiv.demographics.TBHIVDemographics.TBHIVDemographics(nodes=None, idref='Gridded world grump2.5arcmin', base_file=None)

Bases: emod_api.demographics.Demographics.Demographics

This class is derived from emod_api.demographics’ Demographics class so that we can set certain defaults for TBHIV in construction. Keen observers will note thatt SetDefaultProperties does not look like a TBHIV-specific function. But as we add other disease types the generatlizations and speicfics will become clearer. The architectural point is solid.

SetHIVCoInfectionDistribution()

Insert some notion of a default HIVCoInfection distribution.

SetHIVTBCoInfectionMortalityDistribution()

Insert some notion of a default HIVTBCoInfection Mortality distribution.

class emodpy_tbhiv.demographics.TBHIVDemographics.TBHIVDemographicsWithGenderExtrapolation(file_male, file_female, pop=1000000.0, regression_interval=[1970, 1980], which_point='mid', predict_horizon=2050)

Bases: emodpy_tbhiv.demographics.TBHIVDemographics.TBHIVDemographics

do_extrapolation(add_to_list=True)

makeplots(save=None)

create_json_overlay(template, output_name='Extract_demog.json', csv_out=False, n=0, results_scale_factor=0.0027397260273972603)

This almost certainly needs to be refactored to use the base class ‘generate_file’ functionality.

emodpy_tbhiv.demographics.TBHIVDemographics.fromBasicNode(lat=0, lon=0, pop=1000000.0, name=1, forced_id=1, implicit_config_fns=None)

This function creates a single-node TBHIVDemographics instance from the params you give it.

emodpy_tbhiv.demographics.TBHIVDemographics.fromData(pop=1000000.0, filename_male='Malawi_male_mortality.csv', filename_female='Malawi_female_mortality.csv')