%AK Specify parameters in a vector that can be read in separately to avoid
%updating code every optimization
%Can enter this vector differently if pulling in from other files, etc.
%In this code, we are trying to fit the old T cell data with only allowing
%two parameters to change: V_crac, and V_pmca

clock = clock

% %First, load in results from the Tcell model fit
%'AK_fmincon_20150412_TCell_oldbounds_10000.mat'
% %Second, set p2 = pminf 
load('20151120_20151119_RedParam_TCell_1400_1','pmin');
% p3(1) = pmin(2); %V_serca
p3(1) = pmin(3); %K_serca
p3(2) = pmin(4); %Vpmca
p3(3) = pmin(7); % Vcrac
p3(4) = pmin(9); %K_stim
p3(5) = pmin(13); %K_ip3
p3(6) = pmin(15); %K_IP3prod
p3(7) = pmin(16); %K_IP3deg
p3(8) = pmin(18); %Kmitin

%X Vcrac - need
%X Kip3deg X
%X Kip3 X
%X Kip3prod X
%X Kserca X 
%X Vpmca - need
%X Kstim X
%X Kmitin - need

%Previous runs showed these
% Kserca X
% kIP3Prod X
% Kstim X
% Vserca X - remove
% kIP3deg X
% Kip3 X


%Bounds as specified before, but only for the 5 specified above

lowbounds = [0.15,0.01,0.01,150,...      %10 values
    0.1,0.1,0.01,100];                            
upbounds = [0.8,50,10,250,...                %10 values
    1,1,0.1,800];

% lowbounds = [1500,0.2,0.15,0.01,0.1,0.0005,0.01,2.5e-07,150,0.05,...      %10 values
%     0.001,0.015,0.1,0.05,0.1,0.01,0.01,100,0.5,50,...                    %10 values
%     0.01,0.08,0.001,5,1,50,0.001,1,0.5,0.001,...                          %10 values
%     0.1 280];                            
% upbounds = [1500,250,0.8,50,0.5,0.05,10,3.5e-05,250,80,...                %10 values
%     1,0.015,1,0.5,1,0.1,0.1,800,1.5,500,...                              %10 values
%     0.5,0.08,1,450,10,1000,1,1,1.5,0.01,...                               %10 values
%     0.5 420];  

%specify the size of the population
popsize = 2100;
%Develop the initial population
M = zeros(popsize,length(lowbounds));
r = rand(popsize,length(lowbounds));
%Alters population by +/- 20%
for i = 1:popsize
    for j = 1:length(lowbounds)
        M(i,j) = 0.8*p3(j)+0.4.*r(i,j).*(p3(j)); 
    end
end


%Need to perform minimization of parameter sets

%*******Sets options for running the genetic algorithm
%--------------------------------------------------------------------------
%Added output into the output of ga on March 2, 2015
%PopulationSize specifies the size of the population
%IniialPopulation is used to seed the genetic algorithm
%PlotFcns is an array of handles to functions that plot data computed by
% the algorithm
options = gaoptimset('PopulationSize',popsize,'Generations',100, ...
    'InitialPopulation',M,'PlotFcns', ...
    {@gaplotbestf,@gaplotscores,@gaplotstopping,@gaplotdistance});

[pmin,Smin,exitflag,output] = ga(@AK_Optimization_ToMinimize_20151123_TCellOLD_DiffS_8Var_5,...
    length(lowbounds),[],[],[],[],lowbounds,upbounds,[],options);


%*******Sets options for running the fmincon
%--------------------------------------------------------------------------
%This enables plotting of the results
% options = optimset('MaxFunEvals',6000,'PlotFcns',{@optimplotfval,@optimplotstepsize});
% % % Try running fmincon: find minimum of constrained nonlinear multivariable
% % % function
% % 
% % %Here, load in pmin
% % from AK_ga_20150610_TCellOLD_2param_1000.mat
% 
% [p3minf,Smin,exitflag,output]=fmincon(@AK_Optimization_ToMinimize_20150624_TCellOLD_DiffS_8Var,...
%     pmin,[],[],[],[],lowbounds,upbounds,[],options);

% 

%********Sets options for running the patternsearch
%--------------------------------------------------------------------------
%This enables plotting of the results
% options = psoptimset('PlotFcns',{@psplotbestf,@psplotmeshsize});
% 
% % %Here, load in pminf from
% % from AK_fmincon_20150411_TCell_oldbounds_1000_2
% 
% [p3minp,Smin,exitflag,output] = ...
%     patternsearch(@AK_Optimization_ToMinimize_20150623_TCellOLD_DiffS_5Var, ...
%     p3minf,[],[],[],[],lowbounds,upbounds,[],options);
% 

%  
%*******Sets options for running the simulannealbnd
%--------------------------------------------------------------------------
%Find minimum of function using simulated annealing algorithm
%This enables plotting of the results
% options = saoptimset('PlotFcns',...
%     {@saplotbestf,@saplotbestx,@saplotf,@saplottemperature});
% 
% [pmin,Smin,exitflag,output] = simulannealbnd(@AK_Optimization_ToMinimize_20150331_TCell,...
%     pmin,lowbounds,upbounds,options);