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/*
* ratefreeinvar.h
*
* Created on: Nov 7, 2014
* Author: minh
*/
#ifndef RATEFREEINVAR_H_
#define RATEFREEINVAR_H_
#include "rateinvar.h"
#include "ratefree.h"
class RateFreeInvar: public RateInvar, public RateFree {
public:
/**
constructor
@param ncat number of rate categories
@param tree associated phylogenetic tree
*/
RateFreeInvar(int ncat, double start_alpha, string params, bool sorted_rates, double p_invar_sites, string opt_alg, PhyloTree *tree);
/**
save object into the checkpoint
*/
virtual void saveCheckpoint();
/**
restore object from the checkpoint
*/
virtual void restoreCheckpoint();
/**
return the number of dimensions
*/
virtual int getNDim() { return RateInvar::getNDim() + RateFree::getNDim(); }
/**
get the proportion of sites under a specified category.
@param category category ID from 0 to #category-1
@return the proportion of the specified category
*/
virtual double getProp(int category) { return prop[category]; }
/**
get the rate of a specified category. Default returns 1.0 since it is homogeneous model
@param category category ID from 0 to #category-1
@return the rate of the specified category
*/
virtual double getRate(int category) { return RateFree::getRate(category); }
/**
* @return model name with parameters in form of e.g. GTR{a,b,c,d,e,f}
*/
virtual string getNameParams() {
return RateInvar::getNameParams() + RateFree::getNameParams();
}
/**
override function from Optimization class, used by the minimizeOneDimen() to optimize
p_invar or gamma shape parameter.
@param value value of p_invar (if cur_optimize == 1) or gamma shape (if cur_optimize == 0).
*/
virtual double computeFunction(double value);
/**
* setup the bounds for joint optimization with BFGS
*/
virtual void setBounds(double *lower_bound, double *upper_bound, bool *bound_check);
/**
optimize parameters
@return the best likelihood
*/
virtual double optimizeParameters(double gradient_epsilon);
/**
the target function which needs to be optimized
@param x the input vector x
@return the function value at x
*/
virtual double targetFunk(double x[]);
/**
write information
@param out output stream
*/
virtual void writeInfo(ostream &out);
/**
write parameters, used with modeltest
@param out output stream
*/
virtual void writeParameters(ostream &out);
virtual void setNCategory(int ncat);
protected:
/**
this function is served for the multi-dimension optimization. It should pack the model parameters
into a vector that is index from 1 (NOTE: not from 0)
@param variables (OUT) vector of variables, indexed from 1
*/
virtual void setVariables(double *variables);
/**
this function is served for the multi-dimension optimization. It should assign the model parameters
from a vector of variables that is index from 1 (NOTE: not from 0)
@param variables vector of variables, indexed from 1
@return TRUE if parameters are changed, FALSE otherwise (2015-10-20)
*/
virtual bool getVariables(double *variables);
private:
/**
current parameter to optimize. 0 if gamma shape or 1 if p_invar.
*/
int cur_optimize;
};
#endif /* RATEFREEINVAR_H_ */
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