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DriverScriptCase3.m
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%%% ============== =========================================================
%%% = DriverScript.m
%%% = Alex Turner
%%% = Originally created on 04/12/2016
%%% Modified by Newton Nguyen for Fig. 4 in Nguyen et al
%%% =----------------------------------------------------------------------
%%% = NOTES:
%%% =
%%% = Case: +I/+SCO
%%% =Interactive OH chemistry with fitting for CO sources
%%% =
%%% = This is the driver script for the 2-box model methane inversion.
%%% = There are currently two different inversions implemented: (1) a
%%% = linear or non-linear deterministic inversion following Rodgers (2000)
%%% = and (2) an inversion using the non-linear Covariance Matrix Adaptation
%%% = Evolution Strategy (CMA-ES). Case (1) requires us to compute gradients
%%% = and only allows for Gaussian errors. Case (2) is a stochastic method
%%% = that automatically tunes the proposal distribution to improve the sampling,
%%% = however it does not provide error statistics that are consistent with
%%% = the distributions. Case (2) also allows one to specify non-analytic
%%% = distributions (e.g., bounded Gaussians or uniform distributions).
%%% =======================================================================
%%
%%% =======================================================================
%%% 1. Initialize
%%% =======================================================================
profile off
%%% Clear the MatLab space
clf
clear all
close all
clc
%%% Header
fprintf('\n ***********************************\n')
fprintf(' *** STARTING GLOBAL 2-BOX MODEL ***\n')
fprintf(' ***********************************\n')
%%% Define the directories
baseDir = pwd;
utilDir = sprintf('%s/funcs/', baseDir);
dataDir = sprintf('%s/data/', baseDir);
outDir = sprintf('%s/output/',baseDir);
%%% Add the utility functions
addpath(utilDir);
addpath(sprintf('%s/obs', utilDir));
addpath(sprintf('%s/ems', utilDir));
addpath(sprintf('%s/model', utilDir));
addpath(sprintf('%s/util', utilDir));
addpath(sprintf('%s/plot', utilDir));
addpath(sprintf('%s/inv', utilDir));
addpath(sprintf('%s/inv/deterministic', utilDir));
addpath(sprintf('%s/inv/stochastic', utilDir));
%%% Define the time period
sYear = 1980;
eYear = 2019;
tRes = 'year'; % Can be 'year' or 'month' (year preferred)
tAvg = 'year'; % Smooth the observations
St = getTime(sYear,eYear,tRes); % Time vector
nT = length(St);
%%% Export variables to mat file
export_data = true; % do we want to export data to data_filename.mat?
data_filename = 'case3';
%%% Describing experiment to be exported to .mat file
experiment_description = 'Case 3: Fixed OH source, Turned on OH feedbacks, and turned on CO.'
%%% Execute in parallel?
run_parallel = false;
if run_parallel
nWorkers = 4;
setupParallel(run_parallel,nWorkers);
end
%%% What kind of inversions do we want to do?
do_deterministic = true; % Rodgers (2000)
do_cmaes = false; % Covariance Matrix Adaptation Evolution Strategy
%%% For reading the observations
% Do we want to reread the raw data?
reread.flag = false;
% Other flags for re-reading
reread.sYear = sYear;
reread.eYear = eYear;
reread.tRes = tRes;
reread.tAvg = tAvg;
reread.dir = dataDir;
%%% Other options and flags
% Use globals for some flags
global fixedCH4 fixedOH onlyCH4 onlyMCF schaefer % Linear inversion
global k_mcf_flag smooth_MCF set_MCF_EMS MCF_EMS_val % Methyl Chloroform
global k_co_flag use_strat interactive_OH use_other_sinks ignoreCO % Other
global use_MOPIT_CO
global no_temporal_correlation large_prior % inversion tests on prior constraints
% Plotting flags
ftype = 'pdf'; % Type of plots to make? (eps, pdf, tif, or png)
plot_prior = false; % Plot the prior?
plot_raw = false; % Plot the raw observations?
plot_old_cmaes = false; % Plot an old CMA-ES solution (false means run a new one)
% General flags
use_strat = false; % Use a stratosphere?
interactive_OH = true; % Allow OH feedbacks?
use_other_sinks = false; % Use non-OH sinks?
% Linear inversion flags
use_other_sinks = false; % Use non-OH sinks?
% Linear inversion flags
det_linear = false; % Use a linear deterministic inversion?
fixedCH4 = false; % Use fixed methane emissions
fixedOH = true; % Use fixed OH anomalies
onlyCH4 = false; % Only invert for methane emissions
ignoreCO = false; % keep CO emissions fixed
onlyMCF = false; % Only invert for MCF emissions
schaefer = false; % Case that is most similar to Schaefer et al.
% Flags for priors in inversions
no_temporal_correlation = true; % Run with no temporal correlation? Should be run with large_prior
large_prior = true; % Run with large prior in emissions?
% MCF sensitivity test flags
k_co_flag = true; % Use k_CO that AJT derived
k_mcf_flag = true; % Use k_MCF that AJT derived
smooth_MCF = false; % Smooth the MCF emissions with a 5-year filter?
set_MCF_EMS = false; % Set post-2000 emissions to a fixed value?
MCF_EMS_val = 0.0; % Fixed post-2000 MCF emissions value (Gg/yr)
reduce_MCFerr = false; % Reduce the errors in MCF observations?
MCF_ERR_val = 2.0; % Error in MCF observations (ppt)
% Flags for other tests to run
use_OH_stratMLO = false; % Use the OH derived from MLO strat ozone?
use_Ed = false; % Use Ed Dlugokencky's hemispheric averages?
use_Turner_Bootstrap = false; % use data from Turner et al, 2017?
use_MOPIT_CO = false ; % Use MOPIT data?
%%% Set the seed for repeatability
rng('default');
%%
%%% =======================================================================
%%% 2. Load the obs
%%% =======================================================================
%%% Diagnostic
fprintf('\n *** LOADING THE OBSERVATIONS *** \n');
%%% Load the observations
% Structures with with three fields:
% - "obs": Observations from each NOAA site (ppb)
% - "tim": Julian date for the observation
% - "lat": Latitude of the NOAA site
try % Add a try-catch statement in case the user hasn't downloaded the data
ch4_obs = getCH4(dataDir,reread); % CH4 observations (ppb)
ch4c13_obs = getCH4C13(dataDir,reread); % delta13C observations (permil)
ch4h2_obs = getCH4H2(dataDir,reread); % deltaD observations (permil)
mcf_obs = getMCF(dataDir,reread); % Methylchloroform observations (ppt)
n2o_obs = getN2O(dataDir,reread); % N2O observations (ppb)
c2h6_obs = getC2H6(dataDir,reread); % Ethane observations (ppt)
co_obs = getCO(dataDir,reread); % carbon monoxide observations (ppb)
o3strat_obs = getO3strat(dataDir,reread); % Stratospheric ozone observations (DU)
catch % Some data is missing
try % See if ethane is the only problem
fprintf(' * SOME DATA IS MISSING\n');
ch4_obs = getCH4(dataDir,reread);
ch4c13_obs = getCH4C13(dataDir,reread);
ch4h2_obs = getCH4H2(dataDir,reread);
mcf_obs = getMCF(dataDir,reread);
n2o_obs = getN2O(dataDir,reread);
co_obs = getCO(dataDir,reread);
o3strat_obs = getO3strat(dataDir,reread);
c2h6_obs = NaN;
catch % Otherwise, set the observation structures to NaN
fprintf(' * UNABLE TO READ OBSERVATIONS!\n');
ch4_obs = NaN;
ch4c13_obs = NaN;
ch4h2_obs = NaN;
mcf_obs = NaN;
n2o_obs = NaN;
c2h6_obs = NaN;
co_obs = NaN;
o3strat_obs = NaN;
end
end
%%% Make the observation structure
% Structure with 12 fields:
% - NH/SH CH4 obs & err (ppb)
% - NH/SH CH4C13 obs & err (permil)
% - NH/SH MCF obs & err (ppt)
% - NH/SH N2O obs & err (ppb)
% - NH/SH C2H6 obs & err (ppt)
% - NH/SH CO obs & err (ppb)
obs = makeObs(St,tAvg,ch4_obs,ch4c13_obs,mcf_obs,n2o_obs,c2h6_obs,co_obs,dataDir,reread);
if use_MOPIT_CO
obs = useMopit(St, obs, tRes);
end
%
if use_Turner_Bootstrap
turnerFname = sprintf('%sobs/StoredData/Turner_InputData_%4i-%4i_%s-%s.mat',...
dataDir,reread.sYear,reread.eYear,reread.tRes,reread.tAvg);
ajt_obs = load(turnerFname);
obs = ajt_obs.out;
% Get rid of CO data before 1990
coYear = datenum(1991, 1, 1);
ind = find(St<coYear);
obs.nh_co(ind(1) : ind(end)) = nan;
obs.sh_co(ind(1) : ind(end)) = nan;
end
% blow up CO error:
%obs.nh_co_err(:) =500;
%obs.sh_co_err(:) =500;
%%% Use Ed Dlugokencky's obs? (sensitivity test)
if use_Ed
ajt_obs = obs;
ed_obs = getEdObs(dataDir,ajt_obs,St,tAvg,reread);
obs = ed_obs;
plotEdObs(St,ajt_obs,ed_obs,sprintf('%s/%s/raw_EdObs.%s',outDir,tRes,ftype))
end
%%% Reduce MCF errors? (sensitivity test)
if reduce_MCFerr
obs.nh_mcf_err = min([obs.nh_mcf_err,MCF_ERR_val*ones(size(obs.nh_mcf_err))],[],2);
obs.sh_mcf_err = min([obs.sh_mcf_err,MCF_ERR_val*ones(size(obs.sh_mcf_err))],[],2);
end
%%% Diagnostics (check the raw data)
if plot_raw
deseasonalize = true;
plot_all_sites = false;
plotAllObs(St,obs,ch4_obs, tAvg, 'ch4' ,sprintf('%s/%s/raw_%%s_%%s.%s',outDir,tRes,ftype),deseasonalize,plot_all_sites);
plotAllObs(St,obs,ch4c13_obs,tAvg, 'd13C',sprintf('%s/%s/raw_%%s_%%s.%s',outDir,tRes,ftype),deseasonalize,plot_all_sites);
%plotAllObs(St,obs,ch4h2_obs, tAvg, 'dD', sprintf('%s/%s/raw_%%s_%%s.%s',outDir,tRes,ftype),deseasonalize,plot_all_sites);
plotAllObs(St,obs,mcf_obs, tAvg, 'mcf' ,sprintf('%s/%s/raw_%%s_%%s.%s',outDir,tRes,ftype),deseasonalize,plot_all_sites);
plotAllObs(St,obs,n2o_obs, tAvg, 'n2o' ,sprintf('%s/%s/raw_%%s_%%s.%s',outDir,tRes,ftype),deseasonalize,plot_all_sites);
plotAllObs(St,obs,c2h6_obs, tAvg, 'c2h6',sprintf('%s/%s/raw_%%s_%%s.%s',outDir,tRes,ftype),deseasonalize,plot_all_sites);
plotAllObs(St,obs,co_obs, tAvg, 'co' ,sprintf('%s/%s/raw_%%s_%%s.%s',outDir,tRes,ftype),deseasonalize,plot_all_sites);
end
%%
%%% =======================================================================
%%% 3. Load the emissions (all will be arrays with a length matching "St")
%%% =======================================================================
%%% Diagnostic
fprintf('\n *** LOADING THE EMISSIONS *** \n');
%%% Get the CH4 emissions
% Stucture with two fields
% - "nh": CH4 emissions from the Northern hemisphere (Tg/yr)
% - "sh": CH4 emissions from the Southern hemisphere (Tg/yr)
ch4_ems = getCH4ems(St,tRes,dataDir);
%%% Get the delta13C composition for NH/SH CH4 emissions
% Stucture with two fields
% - "nh": delta13C composition from the Northern hemisphere (permil)
% - "sh": delta13C composition from the Southern hemisphere (permil)
ch4c13_ems = getCH4C13ems(St,tRes,dataDir);
%%% Get the MCF emissions (assumed to be in NH only)
% Stucture with two fields
% - "prinn": MCF emissions from Prinn (Gg/yr)
% - "mcculloch": MCF emissions from McCulloch (Gg/yr)
mcf_ems = getMCFems(St,tRes,dataDir);
%%% Get the N2O emissions
% Stucture with two fields
% - "nh": N2O emissions from the Northern hemisphere (Tg/yr)
% - "sh": N2O emissions from the Southern hemisphere (Tg/yr)
n2o_ems = getN2Oems(St,tRes,dataDir);
%%% Get the C2H6 emissions
% Stucture with two fields
% - "nh": C2H6 emissions from the Northern hemisphere (Tg/yr)
% - "sh": C2H6 emissions from the Southern hemisphere (Tg/yr)
c2h6_ems = getC2H6ems(St,tRes,dataDir);
%%% Get the OH emissions
% Stucture with two fields
% - "nh": OH emissions from the Northern hemisphere (Tg/yr)
% - "sh": OH emissions from the Southern hemisphere (Tg/yr)
oh_ems = getOHems(St,tRes,dataDir);
%%% Get the CO emissions
% Stucture with two fields
% - "nh": CO emissions from the Northern hemisphere (Tg/yr)
% - "sh": CO emissions from the Southern hemisphere (Tg/yr)
co_ems = getCOems(St,tRes,dataDir);
% somehow, the NH emissions are way too low:
%co_ems.nh(:) = 1400;
%%
%%% =======================================================================
%%% 4. Initialize the 2-box model
%%% =======================================================================
%%% Diagnostic
fprintf('\n *** RUN THE 2-BOX MODEL WITH PRIOR FLUXES *** \n');
%%% OH scaling factor
oh_scale.nh = ones(nT,1);
oh_scale.sh = ones(nT,1);
% Derive OH from the stratospheric ozone?
if use_OH_stratMLO
OH_sensitivity = 4.2; % a 1% increase in strat O3 leads to a 4.2% decrease in OH (Murray et al., 2013)
O3_site = 'mlo_NOAA'; % which site to use?
fDays = 365.25*2; % How long of a smoothing?
tO3 = o3strat_obs.tim.(O3_site);
yO3 = o3strat_obs.obs.(O3_site);
yO3 = DeseasonalizeData(tO3,yO3,fDays);
[tO3, yO3, ~] = BlockAverage_AltError(tO3,yO3,ones(size(tO3)),365.25);
oh_change = yO3 / nanmean(yO3); % Convert strat O3 to OH change
oh_change = 1 ./ ((oh_change - 1) * OH_sensitivity + 1);
yOH = interp1(tO3,oh_change,St);
yOH(isnan(yOH)) = 1;
% Store this OH
oh_scale.nh = yOH;
oh_scale.sh = yOH;
end
%%% Strat-trop exchange
tau_TS = 9.0 * ones(nT,1); % years
if ~use_strat
% Set this to something high, Inf results in trouble:
%tau_TS(:) = Inf; % No exchange with stratosphere
tau_TS(:) = 1e4;
end
%%% Arbitrary reactions with OH
% CF Needed to adapt NH as there would otherwise be a rather large IH
% difference in OH
kX_NH = 0.99*ones(nT,1); % s^-1 for 6600 tg/yr OH source
kX_SH = 1.23*ones(nT,1); % s^-1
%%% Structure of sources with 17 fields:
% - NH CH4 emissions
% - SH CH4 emissions
% - NH CH4C13 composition
% - SH CH4C13 composition
% - NH MCF emissions
% - SH MCF emissions
% - NH N2O emissions
% - SH N2O emissions
% - NH C2H6 emissions
% - SH C2H6 emissions
% - NH OH emissions
% - SH OH emissions
% - NH CO emissions
% - SH CO emissions
% - Strat-trop exchange
% - NH arbitrary OH reaction rate
% - SH arbitrary OH reaction rate
ems.nh_ch4 = ch4_ems.nh;
ems.sh_ch4 = ch4_ems.sh;
ems.nh_ch4c13 = ch4c13_ems.nh;
ems.sh_ch4c13 = ch4c13_ems.sh;
ems.nh_mcf = mcf_ems.nh;
ems.sh_mcf = mcf_ems.sh;
ems.nh_n2o = n2o_ems.nh;
ems.sh_n2o = n2o_ems.sh;
ems.nh_c2h6 = c2h6_ems.nh;
ems.sh_c2h6 = c2h6_ems.sh;
ems.nh_oh = oh_ems.nh;
ems.sh_oh = oh_ems.sh;
ems.nh_co = co_ems.nh;
ems.sh_co = co_ems.sh;
ems.tau_TS = tau_TS;
ems.kX_NH = kX_NH;
ems.kX_SH = kX_SH;
% Convert the structure to a matrix
ems = assembleEms(ems);
%%% Run the box model
params = getParameters(St); % Only need to do this once
IC = params.IC; % Guess for the inital conditions
out = boxModel_wrapper(St,ems,IC,params);
if plot_prior
plotNewObs(St,out,obs,sprintf('%s/%s/prior_%%s.%s',outDir,tRes,ftype));
%writeData(St,obs,out,ems,IC,sprintf('%s/%s/prior_%%s.csv',outDir,tRes));
%plotObs(St,out,obs,sprintf('%s/%s/prior_%%s.%s',outDir,tRes,ftype));
%plotDrivers(St,ems,NaN*ems,sprintf('%s/%s/prior_%%s.%s',outDir,tRes,ftype),dataDir);
end
%%
%%% =======================================================================
%%% 5. Deterministic inversion (Rodgers, 2000)
%%% =======================================================================
if do_deterministic
%%% Diagnostic
fprintf('\n *** DETERMINISTIC INVERSION *** \n');
%%% Invert
% Newton: here is the problem
[anal_soln,jacobian_ems,jacobian_IC,reltol,abstol, mati] = invert_methane(St,obs,ems,IC,params,det_linear,run_parallel);
%%% Plot the Jacobians
%[jacobian_ems,jacobian_IC] = define_Jacobian( St, ems, IC, params, run_parallel );
plotJacobian(St,jacobian_ems,tRes,sprintf('%s/%s/jacobian_%%s.%s',outDir,tRes,ftype));
%%% Try plotting the solution
ems_anal = anal_soln{1};
IC_anal = anal_soln{2};
% Comment this out for now:
out_anal = boxModel_wrapper(St,ems_anal,IC_anal,params);
plotNewObs(St,out_anal,obs,sprintf('%s/%s/anal_%%s.%s',outDir,tRes,ftype));
%writeData(St,obs,out_anal,ems_anal,IC_anal,sprintf('%s/%s/anal_%%s.csv',outDir,tRes));
%plotObs(St,out_anal,obs,sprintf('%s/%s/anal_%%s.%s',outDir,tRes,ftype));
%plotDrivers(St,ems_anal,ems,sprintf('%s/%s/anal_%%s.%s',outDir,tRes,ftype),dataDir);
end
%%
%%% =======================================================================
%%% 6. Invert with CMAES
%%% =======================================================================
if do_cmaes
%%% Diagnostics
fprintf('\n *** STARTING CMA-ES INVERSION *** \n');
%%% Use a log-likelihood and get matrix dimensions
use_log = true;
nE = size(ems,2);
nI = length(IC);
%%% Set the function parameters for the box model
fun_param.run_parallel = run_parallel;
fun_param.p_prior = @(ems,IC,input_param) define_prior(ems,IC,input_param);
fun_param.p_like = @(ems,IC,input_param) define_likelihood(ems,IC,input_param);
fun_param.use_log = use_log;
fun_param.params = params;
fun_param.IC = params.IC;
fun_param.St = St;
fun_param.ch4_ems = ch4_ems;
fun_param.ch4c13_ems = ch4c13_ems;
fun_param.mcf_ems = mcf_ems;
fun_param.n2o_ems = n2o_ems;
fun_param.c2h6_ems = c2h6_ems;
fun_param.oh_scale = oh_scale;
fun_param.tau_TS = tau_TS;
fun_param.nT = nT;
fun_param.nE = nE;
fun_param.nI = nI;
fun_param.obs = obs;
%%% Set the options for CMAES
CMAES_opts = cmaes;
CMAES_opts.EvalParallel = 'yes';
CMAES_opts.SaveFilename = sprintf('output/%s/cmaes_dat/variablescmaes.mat',tRes);
CMAES_opts.LogFilenamePrefix = sprintf('output/%s/cmaes_dat/outcmaes',tRes);
CMAES_opts.Resume = 'no'; % Default is 'no'
CMAES_opts.CMA.active = 2;
CMAES_opts.DiagonalOnly = 100;
% % Full
% CMAES_opts.StopFunEvals = 5000000;
% CMAES_opts.MaxIter = 20000;
% CMAES_opts.Restarts = 10;
% % Medium
% CMAES_opts.StopFunEvals = 1000000;
% CMAES_opts.MaxIter = 5000;
% CMAES_opts.Restarts = 6;
% Small
CMAES_opts.StopFunEvals = 10000;
CMAES_opts.MaxIter = 200;
CMAES_opts.Restarts = 2;
%%% Get the starting point and standard deviations
% Starting point
if do_deterministic % Use the deterministic inversion as a starting point
xstart = ems_anal;
xstart(xstart(:,1)<0,1) = 0+eps; % Enforce positive CH4 emissions
xstart(xstart(:,2)<0,2) = 0+eps; % Enforce positive CH4 emissions
xstart(xstart(:,1)<0,3) = 0+eps; % Enforce positive MCF emissions
xstart(xstart(:,2)<0,4) = 0+eps; % Enforce positive MCF emissions
xstart(xstart(:,7)<0,7) = 0+eps; % Enforce positive N2O emissions
xstart(xstart(:,8)<0,8) = 0+eps; % Enforce positive N2O emissions
xstart(xstart(:,9)<0,9) = 0+eps; % Enforce positive C2H6 emissions
xstart(xstart(:,10)<0,10) = 0+eps; % Enforce positive C2H6 emissions
xstart = assembleStateVector(xstart,IC_anal);
else
xstart = ems;
xstart = assembleStateVector(xstart,IC);
end
% Standard deviations
xsigma.ems = ones(nT,nE);
sig.ch4 = 1.000; % Tg/yr
sig.ch4c13 = 0.050; % permil
sig.mcf_nh = 5.000; % Gg/yr
sig.mcf_sh = 5.000; % Gg/yr
sig.n2o = 0.500; % Tg/yr
sig.c2h6 = 100.000; % Gg/yr
sig.oh = 0.005; % OH scale factor
sig.tau = 0.500; % 1/yr
xsigma.IC = [0.05,0.05,0.01,0.01,0.05,0.05,0.05,0.05,0.05,0.05,...
0.05,0.05,0.01,0.01,0.05,0.05,0.05,0.05,0.05,0.05]; % Initial conditions
xsigma.ems(:,1) = xsigma.ems(:,1) * sig.ch4;
xsigma.ems(:,2) = xsigma.ems(:,2) * sig.ch4;
xsigma.ems(:,3) = xsigma.ems(:,3) * sig.ch4c13;
xsigma.ems(:,4) = xsigma.ems(:,4) * sig.ch4c13;
xsigma.ems(:,5) = xsigma.ems(:,5) * sig.mcf_nh;
xsigma.ems(:,6) = xsigma.ems(:,6) * sig.mcf_sh;
xsigma.ems(:,7) = xsigma.ems(:,7) * sig.n2o;
xsigma.ems(:,8) = xsigma.ems(:,8) * sig.n2o;
xsigma.ems(:,9) = xsigma.ems(:,9) * sig.c2h6;
xsigma.ems(:,10) = xsigma.ems(:,10) * sig.c2h6;
xsigma.ems(:,11) = xsigma.ems(:,11) * sig.oh;
xsigma.ems(:,12) = xsigma.ems(:,12) * sig.oh;
xsigma.ems(:,13) = xsigma.ems(:,13) * sig.tau./params.YrToDay;
xsigma = assembleStateVector(xsigma.ems,xsigma.IC);
%%% Use an old estimate?
use_old = false;
if use_old
fprintf(' * PLOTTING THE OLD CMA-ES RESULTS\n')
fname = sprintf('./%s',CMAES_opts.SaveFilename);
if (exist(fname,'file') == 2)
load(fname);
xstart = bestever.x;
end
end
% Run the CMA-ES inversion or just plot an old one?
if plot_old_cmaes
[cmaes_res.ems,cmaes_res.IC] = disassembleStateVector(bestever.x,nT,nE,nI);
else
%%% Invert with CMAES
% INPUTS
% - fitfun: name of objective/fitness function
% - xstart: objective variables initial point, determines N
% - insigma: initial coordinate wise standard deviation(s)
% - inopts: options struct
% OUTPUTS
% - xmin: minimum search point of last iteration
% - fmin: function value of xmin
% - counteval: number of function evaluations done
% - stopflag: stop criterion reached
% - outCMAES: struct with various histories and solutions
% - bestever: struct containing overall best solution (for convenience)
[xmin,fmin,counteval,stopflag,outCMAES,bestever] = cmaes('cmaes_fun_eval', xstart, xsigma, CMAES_opts, fun_param);
[cmaes_res.ems,cmaes_res.IC] = disassembleStateVector(bestever.x,nT,nE,nI);
%[cmaes_res.ems,cmaes_res.IC] = disassembleStateVector(xmin,nT,nE,nI);
end
%%% Plot the best one
ems_best = cmaes_res.ems;
IC_best = cmaes_res.IC;
out_best = boxModel_wrapper(St,ems_best,IC_best,params);
plotNewObs(St,out_best,obs,sprintf('%s/%s/cmaes_%%s.%s',outDir,tRes,ftype));
%writeData(St,obs,out_best,ems_best,IC_best,sprintf('%s/%s/cmaes_%%s.csv',outDir,tRes));
%plotObs(St,out_best,obs,sprintf('%s/%s/cmaes_%%s.%s',outDir,tRes,ftype));
%plotDrivers(St,ems_best,ems,sprintf('%s/%s/cmaes_%%s.%s',outDir,tRes,ftype),dataDir);
end
if export_data
fprintf('Exporting all variables in this run to %s \n', data_filename)
save(data_filename);
end
%%
%%% Finished simulation
fprintf('\n ***********************************\n')
fprintf(' *** DONE! ***\n')
fprintf(' ***********************************\n\n')