% Section 6.5.4
% Boyd & Vandenberghe "Convex Optimization"
% Original by Lieven Vandenberghe
% Adapted for CVX by Argyris Zymnis - 11/27/2005
%
% Here we find a sparse basis for a signal y out of
% a set of Gabor functions. We do this by solving
%       minimize  ||A*x-y||_2 + ||x||_1
%
% where the columns of A are sampled Gabor functions.
% We then fix the sparsity pattern obtained and solve
%       minimize  ||A*x-y||_2
%
% NOTE: The file takes a while to run

clear

% Problem parameters
sigma = 0.05;  % Size of Gaussian function
Tinv  = 500;   % Inverse of sample time
Thr   = 0.001; % Basis signal threshold
kmax  = 30;    % Number of signals are 2*kmax+1
w0    = 5;     % Base frequency (w0 * kmax should be 150 for good results)

% Build sine/cosine basis
fprintf(1,'Building dictionary matrix...');
% Gaussian kernels
TK = (Tinv+1)*(2*kmax+1);
t  = (0:Tinv)'/Tinv;
A  = exp(-t.^2/(sigma^2));
ns = nnz(A>=Thr)-1;
A  = A([ns+1:-1:1,2:ns+1],:);
ii = (0:2*ns)';
jj = ones(2*ns+1,1)*(1:Tinv+1);
oT = ones(1,Tinv+1);
A  = sparse(ii(:,oT)+jj,jj,A(:,oT));
A  = A(ns+1:ns+Tinv+1,:);
% Sine/Cosine basis
k  = [ 0, reshape( [ 1 : kmax ; 1 : kmax ], 1, 2 * kmax ) ];
p  = zeros(1,2*kmax+1); p(3:2:end) = -pi/2;
SC = cos(w0*t*k+ones(Tinv+1,1)*p);
% Multiply
ii = 1:numel(SC);
jj = rem(ii-1,Tinv+1)+1;
A  = sparse(ii,jj,SC(:)) * A;
A  = reshape(A,Tinv+1,(Tinv+1)*(2*kmax+1));
fprintf(1,'done.\n');

% Construct example signal
a = 0.5*sin(t*11)+1;
theta = sin(5*t)*30;
b = a.*sin(theta);

% Solve the Basis Pursuit problem
disp('Solving Basis Pursuit problem...');
tic
cvx_begin
    variable x(30561)
    minimize(sum_square(A*x-b)+norm(x,1))
cvx_end
disp('done');
toc

% Reoptimize problem over nonzero coefficients
p = find(abs(x) > 1e-5);
A2 = A(:,p);
x2 = A2 \ b;

% Constants
M = 61; % Number of different Basis signals
sk = 250; % Index of s = 0.5

% Plot example basis functions;
%if (0) % to do this, re-run basispursuit.m to create A
figure(1); clf;
subplot(3,1,1); plot(t,A(:,M*sk+1)); axis([0 1 -1 1]);
title('Basis function 1');
subplot(3,1,2); plot(t,A(:,M*sk+31)); axis([0 1 -1 1]);
title('Basis function 2');
subplot(3,1,3); plot(t,A(:,M*sk+61)); axis([0 1 -1 1]);
title('Basis function 3');
%print -deps bp-dict_helv.eps

% Plot reconstructed signal
figure(2); clf;
subplot(2,1,1);
plot(t,A2*x2,'--',t,b,'-'); axis([0 1 -1.5 1.5]);
xlabel('t'); ylabel('y_{hat} and y');
title('Original and Reconstructed signals')
subplot(2,1,2);
plot(t,A2*x2-b); axis([0 1 -0.06 0.06]);
title('Reconstruction error')
xlabel('t'); ylabel('y - y_{hat}');
%print -deps bp-approx_helv.eps

% Plot frequency plot
figure(3); clf;

subplot(2,1,1);
plot(t,b); xlabel('t'); ylabel('y'); axis([0 1 -1.5 1.5]);
title('Original Signal')
subplot(2,1,2);
plot(t,150*abs(cos(w0*t)),'--');
hold on;
for k = 1:length(t);
  if(abs(x((k-1)*M+1)) > 1e-5), plot(t(k),0,'o'); end;
  for j = 2:2:kmax*2
    if((abs(x((k-1)*M+j)) > 1e-5) | (abs(x((k-1)*M+j+1)) > 1e-5)),
      plot(t(k),w0*j/2,'o');
    end;
  end;
end;
xlabel('t'); ylabel('w');
title('Instantaneous frequency')
hold off;
Building dictionary matrix...done.
Solving Basis Pursuit problem...
 
Calling Mosek 9.1.9: 61625 variables, 502 equality constraints
------------------------------------------------------------

MOSEK Version 9.1.9 (Build date: 2019-11-21 11:32:15)
Copyright (c) MOSEK ApS, Denmark. WWW: mosek.com
Platform: MACOSX/64-X86

MOSEK warning 710: #1 (nearly) zero elements are specified in sparse col '' (505) of matrix 'A'.
MOSEK warning 710: #1 (nearly) zero elements are specified in sparse col '' (507) of matrix 'A'.
MOSEK warning 710: #1 (nearly) zero elements are specified in sparse col '' (509) of matrix 'A'.
MOSEK warning 710: #1 (nearly) zero elements are specified in sparse col '' (511) of matrix 'A'.
MOSEK warning 710: #1 (nearly) zero elements are specified in sparse col '' (513) of matrix 'A'.
MOSEK warning 710: #1 (nearly) zero elements are specified in sparse col '' (515) of matrix 'A'.
MOSEK warning 710: #1 (nearly) zero elements are specified in sparse col '' (517) of matrix 'A'.
MOSEK warning 710: #1 (nearly) zero elements are specified in sparse col '' (519) of matrix 'A'.
MOSEK warning 710: #1 (nearly) zero elements are specified in sparse col '' (521) of matrix 'A'.
MOSEK warning 710: #1 (nearly) zero elements are specified in sparse col '' (523) of matrix 'A'.
Warning number 710 is disabled.
Problem
  Name                   :                 
  Objective sense        : min             
  Type                   : CONIC (conic optimization problem)
  Constraints            : 502             
  Cones                  : 30562           
  Scalar variables       : 61625           
  Matrix variables       : 0               
  Integer variables      : 0               

Optimizer started.
Presolve started.
Linear dependency checker started.
Linear dependency checker terminated.
Eliminator started.
Freed constraints in eliminator : 0
Eliminator terminated.
Eliminator - tries                  : 1                 time                   : 0.00            
Lin. dep.  - tries                  : 1                 time                   : 0.02            
Lin. dep.  - number                 : 0               
Presolve terminated. Time: 0.22    
Problem
  Name                   :                 
  Objective sense        : min             
  Type                   : CONIC (conic optimization problem)
  Constraints            : 502             
  Cones                  : 30562           
  Scalar variables       : 61625           
  Matrix variables       : 0               
  Integer variables      : 0               

Optimizer  - threads                : 8               
Optimizer  - solved problem         : the primal      
Optimizer  - Constraints            : 502
Optimizer  - Cones                  : 30562
Optimizer  - Scalar variables       : 61625             conic                  : 61625           
Optimizer  - Semi-definite variables: 0                 scalarized             : 0               
Factor     - setup time             : 0.57              dense det. time        : 0.00            
Factor     - ML order time          : 0.00              GP order time          : 0.00            
Factor     - nonzeros before factor : 1.26e+05          after factor           : 1.26e+05        
Factor     - dense dim.             : 0                 flops                  : 9.84e+08        
ITE PFEAS    DFEAS    GFEAS    PRSTATUS   POBJ              DOBJ              MU       TIME  
0   1.5e+00  1.0e+00  3.1e+04  0.00e+00   3.056200000e+04   0.000000000e+00   1.0e+00  1.16  
1   1.9e-01  1.3e-01  1.4e+03  1.00e+00   3.820389713e+03   8.384295397e-02   1.3e-01  1.28  
2   9.8e-03  6.6e-03  1.6e+01  1.00e+00   2.037854629e+02   3.417125965e+00   6.6e-03  1.43  
3   3.6e-03  2.4e-03  3.6e+00  1.00e+00   8.224218219e+01   8.938249410e+00   2.4e-03  1.53  
4   8.8e-04  5.9e-04  4.3e-01  1.00e+00   3.018097170e+01   1.216383545e+01   5.9e-04  1.68  
5   1.9e-04  1.3e-04  4.2e-02  1.00e+00   1.658929324e+01   1.272519117e+01   1.3e-04  1.82  
6   1.4e-04  9.4e-05  2.7e-02  1.00e+00   1.562401457e+01   1.275808457e+01   9.4e-05  1.91  
7   2.7e-05  1.8e-05  2.3e-03  1.00e+00   1.338149308e+01   1.283539099e+01   1.8e-05  2.06  
8   1.5e-05  1.0e-05  1.0e-03  1.00e+00   1.315475168e+01   1.284014261e+01   1.0e-05  2.15  
9   2.9e-06  2.0e-06  8.3e-05  1.00e+00   1.290468659e+01   1.284466544e+01   2.0e-06  2.29  
10  5.4e-07  3.6e-07  6.6e-06  1.00e+00   1.285608729e+01   1.284513132e+01   3.6e-07  2.43  
11  2.5e-07  1.7e-07  2.1e-06  1.00e+00   1.285033187e+01   1.284514396e+01   1.7e-07  2.52  
12  2.7e-09  1.8e-09  2.4e-09  1.00e+00   1.284521170e+01   1.284515561e+01   1.8e-09  2.66  
13  8.6e-11  6.5e-11  1.3e-11  1.00e+00   1.284515739e+01   1.284515569e+01   5.6e-11  2.76  
14  1.6e-10  2.2e-10  1.1e-15  1.00e+00   1.284515569e+01   1.284515569e+01   1.1e-13  2.86  
Optimizer terminated. Time: 2.92    


Interior-point solution summary
  Problem status  : PRIMAL_AND_DUAL_FEASIBLE
  Solution status : OPTIMAL
  Primal.  obj: 1.2845155690e+01    nrm: 1e+00    Viol.  con: 2e-10    var: 0e+00    cones: 0e+00  
  Dual.    obj: 1.2845155686e+01    nrm: 1e+00    Viol.  con: 0e+00    var: 2e-10    cones: 0e+00  
Optimizer summary
  Optimizer                 -                        time: 2.92    
    Interior-point          - iterations : 14        time: 2.91    
      Basis identification  -                        time: 0.00    
        Primal              - iterations : 0         time: 0.00    
        Dual                - iterations : 0         time: 0.00    
        Clean primal        - iterations : 0         time: 0.00    
        Clean dual          - iterations : 0         time: 0.00    
    Simplex                 -                        time: 0.00    
      Primal simplex        - iterations : 0         time: 0.00    
      Dual simplex          - iterations : 0         time: 0.00    
    Mixed integer           - relaxations: 0         time: 0.00    

------------------------------------------------------------
Status: Solved
Optimal value (cvx_optval): +12.8452
 
done
Elapsed time is 11.172103 seconds.