mio::ssir::Model< FP > Class Template Reference

#include <model.h>

Inheritance diagram for mio::ssir::Model< FP >:

Collaboration diagram for mio::ssir::Model< FP >:

Public Types
using	Base = mio::StochasticModel< FP, InfectionState, mio::Populations< FP, InfectionState >, Parameters< FP >, Flows >
Public Types inherited from mio::StochasticModel< FP, InfectionState, mio::Populations< FP, InfectionState >, Parameters< FP >, Flows >
using	Base = std::conditional_t< std::is_same_v< Flows, void >, CompartmentalModel< FP, InfectionState, mio::Populations< FP, InfectionState >, Parameters< FP > >, FlowModel< FP, InfectionState, mio::Populations< FP, InfectionState >, Parameters< FP >, Flows > >

Public Member Functions
void	get_flows (Eigen::Ref< const Eigen::VectorX< FP >> pop, Eigen::Ref< const Eigen::VectorX< FP >> y, FP t, Eigen::Ref< Eigen::VectorX< FP >> flows) const
void	get_noise (Eigen::Ref< const Eigen::VectorX< FP >> pop, Eigen::Ref< const Eigen::VectorX< FP >> y, FP t, Eigen::Ref< Eigen::VectorX< FP >> noise) const
	Calculate random changes to the population at a certain time point. More...
	Model ()
Public Member Functions inherited from mio::StochasticModel< FP, InfectionState, mio::Populations< FP, InfectionState >, Parameters< FP >, Flows >
RandomNumberGenerator &	get_rng () const
	Access the model's RNG. More...
FP	sample_standard_normal_distribution () const
	Sample a standard normal distributed value from the model's RNG. More...
auto	white_noise (Eigen::Index size) const
	Sample a vector of independent standard normal distributed values from the model's RNG. More...

Member Typedef Documentation

Base

template<typename FP >

using mio::ssir::Model< FP >::Base = mio::StochasticModel<FP, InfectionState, mio::Populations<FP, InfectionState>, Parameters<FP>, Flows>

Constructor & Destructor Documentation

Model()

template<typename FP >

mio::ssir::Model< FP >::Model ( )

inline

Member Function Documentation

get_flows()

template<typename FP >

void mio::ssir::Model< FP >::get_flows ( Eigen::Ref< const Eigen::VectorX< FP >>  pop, Eigen::Ref< const Eigen::VectorX< FP >>  y, FP  t, Eigen::Ref< Eigen::VectorX< FP >>  flows  ) const

inline

get_noise()

template<typename FP >

void mio::ssir::Model< FP >::get_noise ( Eigen::Ref< const Eigen::VectorX< FP >>  , Eigen::Ref< const Eigen::VectorX< FP >>  , FP  , Eigen::Ref< Eigen::VectorX< FP >>    ) const

inlinevirtual

Calculate random changes to the population at a certain time point.

This function calculates the random noise part of an SDE model. In general, it represents the result of the deterministic noise matrix multiplied by a white noise vector.

For infectious disease models, the noise matrix usually maps noise contributions from each flow to their respective compartments. In that case, the white noise vector has size #flows. The resulting noise vector must have the same size as the state vector y. This is due to the fact that the integration of SDE models must happen on populations, not flows, as the applied noise can occassionally push compartments into negative values. This can be mitigated by removing negative values and rescaling the population (see map_to_nonnegative), but this mitigation can not (in general) be applied to flows. The noise must still be applied per flow, so both inflow and outflow use the same random value. Otherwise, transitions between compartments would no longer preserve the total population count.

Reimplemented from mio::StochasticModel< FP, InfectionState, mio::Populations< FP, InfectionState >, Parameters< FP >, Flows >.