This is the class used to control the model simulation. More...

#include <ecosystem.h>

Collaboration diagram for Ecosystem:

Public Member Functions
	Ecosystem ()
	This is the default Ecosystem constructor. More...

	Ecosystem (const MainInfo &main)
	This is the Ecosystem constructor specifying details about the model. More...

	~Ecosystem ()
	This is the default Ecosystem destructor. More...

void	readMain (CommentStream &infile, const MainInfo &main)
	This function will read the model data from the main input file. More...

void	readLikelihood (CommentStream &infile)
	This function will read the likelihood data from the input file. More...

void	readPrinters (CommentStream &infile)
	This function will read the printer data from the input file. More...

void	readFleet (CommentStream &infile)
	This function will read the fleet data from the input file. More...

void	readTagging (CommentStream &infile)
	This function will read the tagging data from the input file. More...

void	readOtherFood (CommentStream &infile)
	This function will read the otherfood data from the input file. More...

void	readStock (CommentStream &infile)
	This function will read the stock data from the input file. More...

void	readOptimisation (CommentStream &infile)
	This function will read in the optimisation parameters from the input file. More...

void	writeStatus (const char *filename) const
	This function will write the current model status to file. More...

void	writeInitialInformation (const char *const filename)
	This function will write header information about the model parameters to file. More...

void	writeValues ()
	This function will write current information about the model parameters to file. More...

void	writeParams (const char *const filename, int prec) const
	This function will write final information about the model parameters to file in a column format (which can then be used as the starting point for a subsequent model run) More...

void	writeBestValues ()
	This function will display information about the best values of the parameters found so far during an optimisation run. More...

void	writeOptValues ()
	This function will display information about the optimised values of the parameters. More...

void	Optimise ()
	This is the function that will optimise the likelihood score. More...

void	Initialise ()
	This function will initialise the Ecosystem parameters. More...

void	Update (const StochasticData *const Stochastic) const
	This function will update the Ecosystem parameters with new values from StochasticData. More...

void	Reset ()
	This function will reset the Ecosystem information. More...

void	storeVariables (double likvalue, const DoubleVector &point)
	This function will store the current value of the variables from the optimisation process. More...

void	resetVariables ()
	This function will reset the variables that have been scaled, to be optimised using the Simulated Annealing optimisation algorithm. More...

void	scaleVariables ()
	This function will scale the variables to be optimised, for the Hooke & Jeeves and BFGS optimisation algorithms. More...

void	getOptInitialValues (DoubleVector &val) const
	This function will return a copy of the initial value of the variables to be optimised. More...

void	getOptScaledValues (DoubleVector &val) const
	This function will return a copy of the scaled value of the variables to be optimised. More...

void	getOptLowerBounds (DoubleVector &lbs) const
	This function will return a copy of the lower bounds of the variables to be optimised. More...

void	getOptUpperBounds (DoubleVector &ubs) const
	This function will return a copy of the upper bounds of the variables to be optimised. More...

void	checkBounds () const
	This function will check that the values of the parameters are within the specified bounds. More...

int	numVariables () const
	This function will return the number of variables. More...

int	numOptVariables () const
	This function will return the number of variables to be optimised. More...

void	Simulate (int print)
	This function will simulate the population in the model. More...

void	updatePredationOneArea (int area=0)
	This function will calculate the predation, and update the population, on an area. More...

void	updatePopulationOneArea (int area=0)
	This function will update the population numbers on an area. More...

void	updateAgesOneArea (int area=0)
	This function will update the ages of the population on an area. More...

double	SimulateAndUpdate (const DoubleVector &x)
	This function will update the model parameters, run the model and calculate a likelihood score. More...

double	getLikelihood () const
	This function will return the likelihood score from the current simulation. More...

int	getFuncEval () const
	This function will return the total number of iterations completed. More...

int	getCurrentTime () const
	This function will return the current time in the simulation. More...

int	getCurrentYear () const
	This function will return the current year in the simulation. More...

int	getCurrentStep () const
	This function will return the current step in the simulation. More...

int	numTotalSteps () const
	This function will return the total number of timestep in the simulation. More...

LikelihoodPtrVector &	getModelLikelihoodVector ()
	This function will return the likelihood components used in the simulation. More...

PrinterPtrVector &	getModelPrinterVector ()
	This function will return the printer components used in the simulation. More...

FleetPtrVector &	getModelFleetVector ()
	This function will return the fleets used in the simulation. More...

StockPtrVector &	getModelStockVector ()
	This function will return the stocks used in the simulation. More...

Public Attributes
volatile int	interrupted
	This is the flag used to denote whether the user has interrupted the current model run. More...

Protected Attributes
double	likelihood
	This is the value of the likelihood score for the current simulation. More...

int	funceval
	This is the current iteration. More...

BaseClassPtrVector	basevec
	This is the BaseClassPtrVector of the stocks, fleets and otherfood classes for the current model. More...

LikelihoodPtrVector	likevec
	This is the LikelihoodPtrVector of the likelihood components for the current model. More...

PrinterPtrVector	printvec
	This is the PrinterPtrVector of the printer classes for the current model. More...

OptInfoPtrVector	optvec
	This is the OptInfoPtrVector of the optimisation algorithms for the current model. More...

TimeClass *	TimeInfo
	This is the TimeClass for the current model. More...

AreaClass *	Area
	This is the AreaClass for the current model. More...

Keeper *	keeper
	This is the Keeper for the current model. More...

StockPtrVector	stockvec
	This is the StockPtrVector of the stocks for the current model. More...

TagPtrVector	tagvec
	This is the TagPtrVector of the tagging experiments for the current model. More...

OtherFoodPtrVector	otherfoodvec
	This is the OtherFoodPtrVector of the otherfood for the current model. More...

FleetPtrVector	fleetvec
	This is the FleetPtrVector of the fleets for the current model. More...

PrintInfo	printinfo
	This is the PrintInfo specifying the parameter output from the current model. More...

int	printcount
	This is the counter for the printing interval for the -o output from the simualtion. More...

DoubleVector	initialval
	This is the DoubleVector used to store the initial values of the parameters. More...

DoubleVector	currentval
	This is the DoubleVector used to store the current values of the parameters. More...

IntVector	optflag
	This is the IntVector used to store information about whether the parameters are to be optimised. More...

Detailed Description

This is the class used to control the model simulation.

This is the main class for the model simulation. This class contains pointers to all the objects that are to be used in the model simulation - the stocks and fleets, the model variables, any printer classes used to output the modelled population and any likelihood classes used to compare the modelled population to data. This class controls the model simulation, from the reading of the input files, simulating the modelled population on each timestep and printing the results, and finally calculating an overall likelihood score. This class is also used during an optimising run to update the variables to new values from the optimisation algorithm and calculating a new likelihood score based on these new values.

Constructor & Destructor Documentation

◆ Ecosystem() [1/2]

Ecosystem::Ecosystem ( )

inline

This is the default Ecosystem constructor.

◆ Ecosystem() [2/2]

Ecosystem::Ecosystem ( const MainInfo & main )

This is the Ecosystem constructor specifying details about the model.

Parameters

main	is the MainInfo specifying the command line options for the model run

◆ ~Ecosystem()

Ecosystem::~Ecosystem ( )

This is the default Ecosystem destructor.

Member Function Documentation

◆ checkBounds()

void Ecosystem::checkBounds ( ) const

inline

This function will check that the values of the parameters are within the specified bounds.

◆ getCurrentStep()

int Ecosystem::getCurrentStep ( ) const

inline

This function will return the current step in the simulation.

Returns: current step

◆ getCurrentTime()

int Ecosystem::getCurrentTime ( ) const

inline

This function will return the current time in the simulation.

Returns: current time

◆ getCurrentYear()

int Ecosystem::getCurrentYear ( ) const

inline

This function will return the current year in the simulation.

Returns: current year

◆ getFuncEval()

int Ecosystem::getFuncEval ( ) const

inline

This function will return the total number of iterations completed.

Returns: number of iterations

◆ getLikelihood()

double Ecosystem::getLikelihood ( ) const

inline

This function will return the likelihood score from the current simulation.

Returns: likelihood score

◆ getModelFleetVector()

FleetPtrVector& Ecosystem::getModelFleetVector ( )

inline

This function will return the fleets used in the simulation.

Returns: FleetPtrVector containing all the fleets used in the simulation

◆ getModelLikelihoodVector()

LikelihoodPtrVector& Ecosystem::getModelLikelihoodVector ( )

inline

This function will return the likelihood components used in the simulation.

Returns: LikelihoodPtrVector containing all the likelihood components used in the simulation

◆ getModelPrinterVector()

PrinterPtrVector& Ecosystem::getModelPrinterVector ( )

inline

This function will return the printer components used in the simulation.

Returns: PrinterPtrVector containing all the printer components used in the simulation

◆ getModelStockVector()

StockPtrVector& Ecosystem::getModelStockVector ( )

inline

This function will return the stocks used in the simulation.

Returns: StockPtrVector containing all the stocks used in the simulation

◆ getOptInitialValues()

void Ecosystem::getOptInitialValues ( DoubleVector & val ) const

inline

This function will return a copy of the initial value of the variables to be optimised.

Parameters

val	is the DoubleVector that will contain a copy of the initial values

◆ getOptLowerBounds()

void Ecosystem::getOptLowerBounds ( DoubleVector & lbs ) const

inline

This function will return a copy of the lower bounds of the variables to be optimised.

Parameters

lbs	is the DoubleVector that will contain a copy of the lower bounds

◆ getOptScaledValues()

void Ecosystem::getOptScaledValues ( DoubleVector & val ) const

inline

This function will return a copy of the scaled value of the variables to be optimised.

Parameters

val	is the DoubleVector that will contain a copy of the scaled values

◆ getOptUpperBounds()

void Ecosystem::getOptUpperBounds ( DoubleVector & ubs ) const

inline

This function will return a copy of the upper bounds of the variables to be optimised.

Parameters

ubs	is the DoubleVector that will contain a copy of the upper bounds

◆ Initialise()

void Ecosystem::Initialise ( )

This function will initialise the Ecosystem parameters.

◆ numOptVariables()

int Ecosystem::numOptVariables ( ) const

inline

This function will return the number of variables to be optimised.

Returns: number of variables to be optimised

◆ numTotalSteps()

int Ecosystem::numTotalSteps ( ) const

inline

This function will return the total number of timestep in the simulation.

Returns: number of timesteps

◆ numVariables()

int Ecosystem::numVariables ( ) const

inline

This function will return the number of variables.

Returns: number of variables

◆ Optimise()

void Ecosystem::Optimise ( )

This is the function that will optimise the likelihood score.

◆ readFleet()

void Ecosystem::readFleet ( CommentStream & infile )

This function will read the fleet data from the input file.

Parameters

infile is the CommentStream to read the fleet data from

◆ readLikelihood()

void Ecosystem::readLikelihood ( CommentStream & infile )

This function will read the likelihood data from the input file.

Parameters

infile is the CommentStream to read the likelihood data from

◆ readMain()

void Ecosystem::readMain	(	CommentStream &	infile,
		const MainInfo &	main
	)

This function will read the model data from the main input file.

Parameters

infile	is the CommentStream to read the likelihood data from
main	is the MainInfo specifying the command line options for the model run

◆ readOptimisation()

void Ecosystem::readOptimisation ( CommentStream & infile )

This function will read in the optimisation parameters from the input file.

Parameters

infile is the CommentStream to read the optimisation parameters from

◆ readOtherFood()

void Ecosystem::readOtherFood ( CommentStream & infile )

This function will read the otherfood data from the input file.

Parameters

infile is the CommentStream to read the otherfood data from

◆ readPrinters()

void Ecosystem::readPrinters ( CommentStream & infile )

This function will read the printer data from the input file.

Parameters

infile is the CommentStream to read the printer data from

◆ readStock()

void Ecosystem::readStock ( CommentStream & infile )

This function will read the stock data from the input file.

Parameters

infile is the CommentStream to read the stock data from

◆ readTagging()

void Ecosystem::readTagging ( CommentStream & infile )

This function will read the tagging data from the input file.

Parameters

infile is the CommentStream to read the tagging data from

◆ Reset()

void Ecosystem::Reset ( )

This function will reset the Ecosystem information.

◆ resetVariables()

void Ecosystem::resetVariables ( )

inline

This function will reset the variables that have been scaled, to be optimised using the Simulated Annealing optimisation algorithm.

◆ scaleVariables()

void Ecosystem::scaleVariables ( )

inline

This function will scale the variables to be optimised, for the Hooke & Jeeves and BFGS optimisation algorithms.

◆ Simulate()

void Ecosystem::Simulate ( int print )

This function will simulate the population in the model.

Parameters

print is the flag to denote whether the model output should be printed or not

Note: This function covers a single running of the model, calculating the population structure and also calculating the likelihood score obtained from comparing the modelled population to the data specified in the likelihood components

◆ SimulateAndUpdate()

double Ecosystem::SimulateAndUpdate ( const DoubleVector & x )

This function will update the model parameters, run the model and calculate a likelihood score.

Parameters

x	is the DoubleVector containing the updated values for the parameters

Returns: likelihood score

Note: This function gets updated values for the model parameters from the optimisation algorithm and performs a model run based on these new values, calculating a new likelihood score that is then returned to the optimisation algorithm

◆ storeVariables()

void Ecosystem::storeVariables	(	double	likvalue,
		const DoubleVector &	point
	)

inline

This function will store the current value of the variables from the optimisation process.

Parameters

likvalue	is the current likelihood value
point	is the DoubleVector of the current parameter values

◆ Update()

void Ecosystem::Update ( const StochasticData *const Stochastic ) const

inline

This function will update the Ecosystem parameters with new values from StochasticData.

Parameters

Stochastic is the StochasticData containing the new values of the parameters

◆ updateAgesOneArea()

void Ecosystem::updateAgesOneArea ( int area = 0 )

This function will update the ages of the population on an area.

Parameters

area	is the area to update the population on (default value 0)

Note: This function covers the increase in age and the simple 'doesmove' option for movement between stocks

◆ updatePopulationOneArea()

void Ecosystem::updatePopulationOneArea ( int area = 0 )

This function will update the population numbers on an area.

Parameters

area	is the area to update the population on (default value 0)

Note: This function covers the growth, various movements between stocks due to maturity and straying, spawning, and adding new recruits into the model

◆ updatePredationOneArea()

void Ecosystem::updatePredationOneArea ( int area = 0 )

This function will calculate the predation, and update the population, on an area.

Parameters

area	is the area to calculate the predation on (default value 0)

Note: This function covers the predation of the preys by the predators, and consequent population changes, for a sub-step within a timestep of the model

◆ writeBestValues()

void Ecosystem::writeBestValues ( )

inline

This function will display information about the best values of the parameters found so far during an optimisation run.

◆ writeInitialInformation()

void Ecosystem::writeInitialInformation ( const char *const filename )

This function will write header information about the model parameters to file.

Parameters

filename is the name of the file to write the model information to

◆ writeOptValues()

void Ecosystem::writeOptValues ( )

This function will display information about the optimised values of the parameters.

◆ writeParams()

void Ecosystem::writeParams	(	const char *const	filename,
		int	prec
	)		const

This function will write final information about the model parameters to file in a column format (which can then be used as the starting point for a subsequent model run)

Parameters

filename	is the name of the file to write the model information to
prec	is the precision to use in the output file

◆ writeStatus()

void Ecosystem::writeStatus ( const char * filename ) const

This function will write the current model status to file.

Parameters

filename is the name of the file to write the model information to

◆ writeValues()

void Ecosystem::writeValues ( )

This function will write current information about the model parameters to file.

Member Data Documentation

◆ Area

AreaClass* Ecosystem::Area

protected

This is the AreaClass for the current model.

◆ basevec

BaseClassPtrVector Ecosystem::basevec

protected

This is the BaseClassPtrVector of the stocks, fleets and otherfood classes for the current model.

◆ currentval

DoubleVector Ecosystem::currentval

protected

This is the DoubleVector used to store the current values of the parameters.

Note: This vector is only used to temporarily store values during an optimising run

◆ fleetvec

FleetPtrVector Ecosystem::fleetvec

protected

This is the FleetPtrVector of the fleets for the current model.

◆ funceval

int Ecosystem::funceval

protected

This is the current iteration.

◆ initialval

DoubleVector Ecosystem::initialval

protected

This is the DoubleVector used to store the initial values of the parameters.

Note: This vector is only used to temporarily store values during an optimising run

◆ interrupted

volatile int Ecosystem::interrupted

This is the flag used to denote whether the user has interrupted the current model run.

◆ keeper

Keeper* Ecosystem::keeper

protected

This is the Keeper for the current model.

◆ likelihood

double Ecosystem::likelihood

protected

This is the value of the likelihood score for the current simulation.

◆ likevec

LikelihoodPtrVector Ecosystem::likevec

protected

This is the LikelihoodPtrVector of the likelihood components for the current model.

◆ optflag

IntVector Ecosystem::optflag

protected

This is the IntVector used to store information about whether the parameters are to be optimised.

Note: This vector is only used to temporarily store values during an optimising run

◆ optvec

OptInfoPtrVector Ecosystem::optvec

protected

This is the OptInfoPtrVector of the optimisation algorithms for the current model.

◆ otherfoodvec

OtherFoodPtrVector Ecosystem::otherfoodvec

protected

This is the OtherFoodPtrVector of the otherfood for the current model.

◆ printcount

int Ecosystem::printcount

protected

This is the counter for the printing interval for the -o output from the simualtion.

◆ printinfo

PrintInfo Ecosystem::printinfo

protected

This is the PrintInfo specifying the parameter output from the current model.

◆ printvec

PrinterPtrVector Ecosystem::printvec

protected

This is the PrinterPtrVector of the printer classes for the current model.

◆ stockvec

StockPtrVector Ecosystem::stockvec

protected

This is the StockPtrVector of the stocks for the current model.

◆ tagvec

TagPtrVector Ecosystem::tagvec

protected

This is the TagPtrVector of the tagging experiments for the current model.

◆ TimeInfo

TimeClass* Ecosystem::TimeInfo

protected

This is the TimeClass for the current model.

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

Public Member Functions

Public Attributes

Protected Attributes

Detailed Description

Constructor & Destructor Documentation

◆ Ecosystem() [1/2]

◆ Ecosystem() [2/2]

◆ ~Ecosystem()

Member Function Documentation

◆ checkBounds()

◆ getCurrentStep()

◆ getCurrentTime()

◆ getCurrentYear()

◆ getFuncEval()

◆ getLikelihood()

◆ getModelFleetVector()

◆ getModelLikelihoodVector()

◆ getModelPrinterVector()

◆ getModelStockVector()

◆ getOptInitialValues()

◆ getOptLowerBounds()

◆ getOptScaledValues()

◆ getOptUpperBounds()

◆ Initialise()

◆ numOptVariables()

◆ numTotalSteps()

◆ numVariables()

◆ Optimise()

◆ readFleet()

◆ readLikelihood()

◆ readMain()

◆ readOptimisation()

◆ readOtherFood()

◆ readPrinters()

◆ readStock()

◆ readTagging()

◆ Reset()

◆ resetVariables()

◆ scaleVariables()

◆ Simulate()

◆ SimulateAndUpdate()

◆ storeVariables()

◆ Update()

◆ updateAgesOneArea()

◆ updatePopulationOneArea()

◆ updatePredationOneArea()

◆ writeBestValues()

◆ writeInitialInformation()

◆ writeOptValues()

◆ writeParams()

◆ writeStatus()

◆ writeValues()

Member Data Documentation

◆ Area

◆ basevec

◆ currentval

◆ fleetvec

◆ funceval

◆ initialval

◆ interrupted

◆ keeper

◆ likelihood

◆ likevec

◆ optflag

◆ optvec

◆ otherfoodvec

◆ printcount

◆ printinfo

◆ printvec

◆ stockvec

◆ tagvec

◆ TimeInfo