run_inversions_j.m

% RUN_INVERSIONS_J  Optimize exponential distance regularization w.r.t. a range of parameters.
% Author: Timothy Sipkens, 2020-02-22
%=========================================================================%

%{
guess = [1.3,1/4,log10(1.8),0.84]; % [lambda, ratio, ld, corr]
disp('Optimizing exponential distance regularization (least-sqaures)...');
[x_ed_opt,lambda_ed_opt,out_ed_opt] = optimize.exp_dist_opx(...
    Lb*A,Lb*b,grid_x,[],...
    guess,x0); 
disp('Inversion complete.');
disp(' ');
%}


%{
disp('Parametric study of exponential distance regularization (brute force)...');
[x_ed_par,lambda_ed_par,out_ed_par] = optimize.exp_dist_opbf(...
    Lb*A,Lb*b,grid_x,[],...
    x0); 
disp('Inversion complete.');
disp(' ');
%}


%-{
Gd = phantom.Sigma(:,:,1);
if isempty(Gd) % for Phantom 3
    [~,Gd] = phantom.p2cov(phantom.p(2),phantom.modes(2));
end
[x_ed_corr,out_ed_corr] = ...
    optimize.exp_dist_op1d(Lb*A,Lb*b,lambda_ed_lam,Gd,...
    grid_x,[],x0,...
    [],[],'corr');

[x_ed_lmld,out_ed_lmld] = ...
    optimize.exp_dist_op1d(Lb*A,Lb*b,lambda_ed_lam,Gd,...
    grid_x,[],x0,...
    [],[],'lmld');
%}


%{
%-- Zeroth-order Tikhonov regularization --%
%   Lower limit for correlation lengths.
[x_tk0,D_tk0,L_tk0,Gpo_tk0] = invert.tikhonov(...
    Lb*A,Lb*b,lambda_ed_lam,0,n_x(1));
%}