hgps::RiskFactorAdjustableModel Class Reference

Risk factor model interface with mean adjustment by sex and age. More...

#include <risk_factor_adjustable_model.h>

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Public Member Functions
	RiskFactorAdjustableModel (std::shared_ptr< RiskFactorSexAgeTable > expected, std::shared_ptr< std::unordered_map< core::Identifier, double > > expected_trend, std::shared_ptr< std::unordered_map< core::Identifier, int > > trend_steps, TrendType trend_type=TrendType::Null, std::shared_ptr< std::unordered_map< core::Identifier, double > > expected_income_trend=nullptr, std::shared_ptr< std::unordered_map< core::Identifier, double > > expected_income_trend_decay_factors=nullptr)
	Constructs a new RiskFactorAdjustableModel instance.
virtual double	get_expected (RuntimeContext &context, core::Gender sex, int age, const core::Identifier &factor, OptionalRange range, bool apply_trend) const
	Gets a person's expected risk factor value.
void	adjust_risk_factors (RuntimeContext &context, const std::vector< core::Identifier > &factors, OptionalRanges ranges, bool apply_trend, const RiskFactorSexAgeTable *expected_override=nullptr, std::optional< std::size_t > income_stratum_filter=std::nullopt, std::vector< IncomeStratumAdjustmentExampleRow > *debug_example_rows=nullptr) const
	Adjust risk factors such that mean sim value matches expected value.
int	get_trend_steps (const core::Identifier &factor) const
	Gets the number of time steps to apply the trend.
const std::shared_ptr< std::unordered_map< core::Identifier, double > > &	get_expected_trend () const noexcept
	Gets the expected trend values.
void	set_logistic_factors (const std::unordered_set< core::Identifier > &logistic_factors)
	Sets the logistic factors for simulated mean calculation.
Public Member Functions inherited from hgps::RiskFactorModel
virtual	~RiskFactorModel ()=default
	Destroys a RiskFactorModel instance.
virtual RiskFactorModelType	type () const noexcept=0
	Gets the model type identifier.
virtual std::string	name () const noexcept=0
	Gets the model name.
virtual void	generate_risk_factors (RuntimeContext &context)=0
	Generates the initial risk factors for a population and newborns.
virtual void	update_risk_factors (RuntimeContext &context)=0
	Update risk factors for population.

Detailed Description

Risk factor model interface with mean adjustment by sex and age.

Constructor & Destructor Documentation

RiskFactorAdjustableModel()

hgps::RiskFactorAdjustableModel::RiskFactorAdjustableModel	(	std::shared_ptr< RiskFactorSexAgeTable >	expected,
		std::shared_ptr< std::unordered_map< core::Identifier, double > >	expected_trend,
		std::shared_ptr< std::unordered_map< core::Identifier, int > >	trend_steps,
		TrendType	trend_type = TrendType::Null,
		std::shared_ptr< std::unordered_map< core::Identifier, double > >	expected_income_trend = nullptr,
		std::shared_ptr< std::unordered_map< core::Identifier, double > >	expected_income_trend_decay_factors = nullptr
	)

Constructs a new RiskFactorAdjustableModel instance.

Parameters

expected	The risk factor expected values by sex and age
expected_trend	The expected trend of risk factor values (for UPF trends)
trend_steps	The number of time steps to apply the trend (for UPF trends)
trend_type	The type of trend to apply to factors mean adjustment
expected_income_trend	The expected income trend of risk factor values
expected_income_trend_decay_factors	The exponential decay factors for income trends

Member Function Documentation

adjust_risk_factors()

void hgps::RiskFactorAdjustableModel::adjust_risk_factors	(	RuntimeContext &	context,
		const std::vector< core::Identifier > &	factors,
		OptionalRanges	ranges,
		bool	apply_trend,
		const RiskFactorSexAgeTable *	expected_override = nullptr,
		std::optional< std::size_t >	income_stratum_filter = std::nullopt,
		std::vector< IncomeStratumAdjustmentExampleRow > *	debug_example_rows = nullptr
	)		const

Adjust risk factors such that mean sim value matches expected value.

Parameters

context	The simulation run-time context
factors	A list of risk factors to be adjusted
ranges	An optional list of risk factor value boundaries
apply_trend	Whether to apply expected value time trend

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get_expected()

double hgps::RiskFactorAdjustableModel::get_expected ( RuntimeContext &  context, core::Gender  sex, int  age, const core::Identifier &  factor, OptionalRange  range, bool  apply_trend  ) const

virtual

Gets a person's expected risk factor value.

Parameters

context	The simulation run-time context
sex	The sex key to get the expected value
age	The age key to get the expected value
factor	The risk factor to get the expected value
range	An optional expected value range
apply_trend	Whether to apply expected value time trend

Returns

The person's expected risk factor value

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get_expected_trend()

const std::shared_ptr< std::unordered_map< core::Identifier, double > > & hgps::RiskFactorAdjustableModel::get_expected_trend ( ) const

inlinenoexcept

Gets the expected trend values.

Returns

The expected trend values

get_trend_steps()

int hgps::RiskFactorAdjustableModel::get_trend_steps

(

const core::Identifier &

factor

)

const

Gets the number of time steps to apply the trend.

Parameters

factor

The risk factor to get the trend steps

Returns

The number of time steps to apply the trend

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set_logistic_factors()

void hgps::RiskFactorAdjustableModel::set_logistic_factors

(

const std::unordered_set< core::Identifier > &

logistic_factors

)

Sets the logistic factors for simulated mean calculation.

Parameters

logistic_factors

Set of factors that have logistic models

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The documentation for this class was generated from the following files:

• HealthGPS/risk_factor_adjustable_model.h
• HealthGPS/risk_factor_adjustable_model.cpp