function osr_res = osr1(i_params,i_var,weights)
% Compute the Optimal Simple Rules
% INPUTS
%   i_params                  vector           index of optimizing parameters in M_.params
%   i_var                     vector           variables indices in declaration order
%   weights                   vector           weights in the OSRs
%
% OUTPUTS
%   osr_res:    [structure] results structure containing:
%    - objective_function [scalar double]   value of the objective
%                                               function at the optimum
%    - optim_params       [structure]       parameter values at the optimum
%
% Algorithm:
%
%   Uses Newton-type optimizer csminwel to directly solve quadratic
%   osr-problem
%
% Copyright © 2005-2019 Dynare Team
%
% This file is part of Dynare.
%
% Dynare is free software: you can redistribute it and/or modify
% it under the terms of the GNU General Public License as published by
% the Free Software Foundation, either version 3 of the License, or
% (at your option) any later version.
%
% Dynare is distributed in the hope that it will be useful,
% but WITHOUT ANY WARRANTY; without even the implied warranty of
% MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the
% GNU General Public License for more details.
%
% You should have received a copy of the GNU General Public License
% along with Dynare.  If not, see <https://www.gnu.org/licenses/>.

global M_ oo_ options_ it_

it_ = M_.maximum_lag + 1 ;

osr_res.error_indicator = 1; %initialize indicator

if M_.exo_nbr == 0
    oo_.exo_steady_state = [] ;
end

if ~ M_.lead_lag_incidence(M_.maximum_lag+1,:) > 0
    error ('OSR: Error in model specification: some variables don''t appear as current') ;
end

if M_.maximum_lead == 0
    error ('OSR: Backward or static model: no point in using OSR') ;
end

if any(any(isinf(weights)))
    error ('OSR: At least one of the optim_weights is infinite.') ;
end

if any(isnan(M_.params(i_params)))
    error ('OSR: At least one of the initial parameter values for osr_params is NaN') ;
end

%restore backward compatibility with maxit and tolf
if isfield(options_.osr,'maxit') || isfield(options_.osr,'tolf')
    warning('OSR: The use of maxit and tolf is now deprecated. Please use the optim-option instead.')
    if options_.osr.opt_algo~=4
        error ('OSR: The maxit and tolf options are not supported when not using the default opt_algo=4. Use the optim-option instead.') ;
    else
        if isfield(options_.osr,'maxit')
            if ~isempty(options_.optim_opt)
                options_.optim_opt=[options_.optim_opt,','];
            end
            options_.optim_opt=[options_.optim_opt,'''MaxIter'',',num2str(options_.osr.maxit),''];
        end
        if isfield(options_.osr,'tolf')
            if ~isempty(options_.optim_opt)
                options_.optim_opt=[options_.optim_opt,','];
            end
            options_.optim_opt=[options_.optim_opt,'''TolFun'',',num2str(options_.osr.tolf),''];
        end
    end
end

oo_.dr = set_state_space(oo_.dr,M_,options_);


np = size(i_params,1);
t0 = M_.params(i_params);


inv_order_var = oo_.dr.inv_order_var;


%extract unique entries of covariance
i_var=unique(i_var);
%% do initial checks
[loss,info]=osr_obj(t0,i_params,inv_order_var(i_var),weights(i_var,i_var));
if info~=0
    print_info(info, options_.noprint, options_);
else
    if ~options_.noprint
        fprintf('\nOSR: Initial value of the objective function: %g \n\n',loss);
    end
end
if ~options_.noprint && isinf(loss)
    fprintf('\nOSR: The initial value of the objective function is infinite.\n');
    fprintf('\nOSR: Check whether the unconditional variance of a target variable is infinite\n');
    fprintf('\nOSR: due to the presence of a unit root.\n');
    error('OSR: Initial likelihood is infinite')
end


if isequal(options_.osr.opt_algo,5)
    error('OSR: OSR does not support opt_algo=5.')
elseif isequal(options_.osr.opt_algo,6)
    error('OSR: OSR does not support opt_algo=6.')
elseif isequal(options_.osr.opt_algo,10)
    error('OSR: OSR does not support opt_algo=10.')
elseif isequal(options_.osr.opt_algo,11)
    error('OSR: OSR does not support opt_algo=11.')
else

    if ~isempty(M_.osr.param_bounds) && ~(ismember(options_.osr.opt_algo,[1,2,5,9]) || ischar(options_.osr.opt_algo))
        error('OSR: OSR with bounds on parameters requires a constrained optimizer, i.e. opt_algo= 1,2 or 9.')
    end
    %%do actual optimization
    [p, f] = dynare_minimize_objective(str2func('osr_obj'),t0,options_.osr.opt_algo,options_,M_.osr.param_bounds,M_.param_names(i_params),[],[], i_params,...
                                       inv_order_var(i_var),weights(i_var,i_var));
end

osr_res.objective_function = f;
M_.params(i_params)=p; %make sure optimal parameters are set (and not the last draw used in csminwel)
for i=1:length(i_params)
    osr_res.optim_params.(M_.param_names{i_params(i)}) = p(i);
end

if ~options_.noprint
    skipline()
    disp('OPTIMAL VALUE OF THE PARAMETERS:')
    skipline()
    for i=1:np
        fprintf('%16s %16.6g\n\n', M_.param_names{i_params(i)}, p(i));
    end
    fprintf('Objective function : %16.6g\n\n',f);
    skipline()
end
[oo_.dr,info,M_,oo_] = resol(0,M_,options_,oo_);
if ~info
    osr_res.error_indicator=0;
end