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    Metadata details:
    filename: logLikelihoodJakstat_rampart.m
    path of file: ./repos/PESTO/examples/RAmPART_examples/JakStat
    
    the code of the file until where you have to start completion: function varargout = logLikelihoodJakstat(theta, amiData)
% Objective function for examples/jakstat_signaling
%
% logLikelihoodJakstat.m provides the log-likelihood, its gradient and an
% the Hessian matrix for the model for the JakStat signaling pathway as
% defined in jakstat_pesto_syms.m

    
function varargout = logLikelihoodJakstat(theta, amiData)
% Objective function for examples/jakstat_signaling
%
% logLikelihoodJakstat.m provides the log-likelihood, its gradient and an
% the Hessian matrix for the model for the JakStat signaling pathway as
% defined in jakstat_pesto_syms.m
%
% USAGE:
% [llh] = getParameterProfiles(theta, amiData)
% [llh, sllh] = getParameterProfiles(theta, amiData)
% [llh, sllh, s2llh] = getParameterProfiles(theta, amiData)
%
% Parameters:
%  theta: Model parameters
%  amiData: an amidata object for the AMICI solver
%
% Return values:
%   varargout:
%     llh: Log-Likelihood, only the LogLikelihood will be returned, no
%         sensitivity analysis is performed
%     sllh: Gradient of llh, The LogLikelihood and its gradient will be
%         returned, first order adjoint sensitivity analysis is performed
%     s2llh: Hessian of llh, The LogLikelihood, its gradient and the
%         Hessian matrix will be returned, second order adjoint sensitivity
%         analysis is performed



%% Model Definition
% The ODE model is set up using the AMICI toolbox. To access the AMICI
% model setup, see jakstat_pesto_syms.m
% For a detailed description for the biological model see the referenced
% papers on the JakStat signaling pathway by Swameye et al. and Schelker et
% al.

%% AMICI
% Setting the options for the AMICI solver

amiOptions.rtol = 1e-12;
amiOptions.atol = 1e-12;
amiOptions.sensi_meth = 'adjoint';

%% Objective Function Evaluation
% Assignment
if (nargout == 1)
    amiOptions.sensi = 0;
    sol = simulate_jakstat_pesto([], theta, amiData.condition, amiData, amiOptions);
    varargout{1} = sol.llh;
elseif (nargout == 2)
    amiOptions.sensi = 1;
    sol = simulate_jakstat_pesto([], theta, amiData.condition, amiData, amiOptions);
    varargout{1} = sol.llh;
    varargout{2} = sol.sllh;
elseif (nargout == 3)
    amiOptions.sensi = 2;
    sol = simulate_jakstat_pesto([], theta, amiData.condition, amiData, amiOptions);
    varargout{1} = sol.llh;
    varargout{2} = sol.sllh;
    varargout{3} = sol.s2llh;
end