diff util/SMALL_solve.m @ 8:33850553b702

(none)

--- a/util/SMALL_solve.m	Mon Mar 22 10:47:17 2010 +0000
+++ b/util/SMALL_solve.m	Mon Mar 22 10:56:54 2010 +0000
@@ -1,32 +1,77 @@
-function SMALL = SMALL_solve(SMALL)
-  % Ivan Damnjanovic 2009
-  % Function gets as input SMALL structure that contains SPARCO problem to
-  % be solved, name of the toolbox and solver, and parameters file for particular solver
-  % Outputs are solution, reconstructed signal and time spent
-  %%
-  
-  A  = @(x) SMALL.Problem.A(x,1);  % The operator
-  AT = @(y) SMALL.Problem.A(y,2);  % and its transpose.
-  b  = SMALL.Problem.b;            % The right-hand-side vector.
-  m = SMALL.Problem.sizeA(1);      % m is the no. of rows.
-  n = SMALL.Problem.sizeA(2);      % n is the no. of columns.
-  
-  fprintf('\nStarting solver %s... \n', SMALL.solver.name);
-  start=cputime;
-  %%
-  if strcmpi(SMALL.solver.toolbox,'sparselab')
-    y = eval([SMALL.solver.name,'(''SL_A'', b, n,',SMALL.solver.param,');']);
-  elseif strcmpi(SMALL.solver.toolbox,'sparsify')
-    y = eval([SMALL.solver.name,'(b, A, n, ''P_trans'', AT,',SMALL.solver.param,');']);
-  elseif (strcmpi(SMALL.solver.toolbox,'spgl1')||strcmpi(SMALL.solver.toolbox,'gpsr'))
-    y = eval([SMALL.solver.name,'(b, A,',SMALL.solver.param,');']);
-  else
-    y = eval([SMALL.solver.name,'(A, b, n,',SMALL.solver.param,',AT);']);
-  end
-  %%
-  SMALL.solver.time = cputime - start;
-  fprintf('Solver %s finished task in %2f seconds. \n', SMALL.solver.name, SMALL.solver.time);
-  SMALL.solver.solution = full(y);
-  SMALL.solver.reconstructed  = SMALL.Problem.reconstruct(SMALL.solver.solution);
+function solver = SMALL_solve(Problem, solver)
+%%% SMALL sparse solver
+%   Ivan Damnjanovic 2009
+%   Function gets as input SMALL structure that contains SPARCO problem to
+%   be solved, name of the toolbox and solver, and parameters file for
+%   particular solver.
+%
+%   Outputs are solution, reconstructed signal and time spent
+%%
+
+if isa(Problem.A,'float')
+    A = Problem.A;
+    SparseLab_A=Problem.A;
+    m = size(Problem.A,1);      % m is the no. of rows.
+    n = size(Problem.A,2);      % n is the no. of columns.
+else
+    A  = @(x) Problem.A(x,1);  % The operator
+    AT = @(y) Problem.A(y,2);  % and its transpose.
+    SparseLab_A =@(mode, m, n, x, I, dim) SL_A(Problem.A, mode, m, n, x, I, dim);
+    m = Problem.sizeA(1);      % m is the no. of rows.
+    n = Problem.sizeA(2);      % n is the no. of columns.
+    
 end
-  
\ No newline at end of file
+b  = Problem.b;            % The right-hand-side vector.
+%%
+fprintf('\nStarting solver %s... \n', solver.name);
+start=cputime;
+
+if strcmpi(solver.toolbox,'sparselab')
+    y = eval([solver.name,'(SparseLab_A, b, n,',solver.param,');']);
+elseif strcmpi(solver.toolbox,'sparsify')
+    y = eval([solver.name,'(b, A, n, ''P_trans'', AT,',solver.param,');']);
+elseif (strcmpi(solver.toolbox,'spgl1')||strcmpi(solver.toolbox,'gpsr'))
+    y = eval([solver.name,'(b, A,',solver.param,');']);
+elseif (strcmpi(solver.toolbox,'SPAMS'))
+    y = eval([solver.name,'(b, A, solver.param);']);
+elseif (strcmpi(solver.toolbox,'SMALL'))
+    if isa(Problem.A,'float')
+        y = eval([solver.name,'(A, b, n,',solver.param,');']);
+    else
+        y = eval([solver.name,'(A, b, n,',solver.param,',AT);']);
+    end
+    
+%   To introduce new sparse representation algorithm put the files in
+%   your Matlab path. Next, unique name <TolboxID> for your toolbox and
+%   prefferd API <Preffered_API> needs to be defined.
+%
+% elseif strcmpi(solver.toolbox,'<ToolboxID>')
+%
+%     % - Evaluate the function (solver.name - defined in the main) with
+%     %   parameters given above
+%
+%     y = eval([solver.name,'(<Preffered_API>);']);
+
+else
+    printf('\nToolbox has not been registered. Please change SMALL_solver file.\n');
+    return
+end
+
+%%
+%   Sparse representation time
+
+solver.time = cputime - start;
+fprintf('Solver %s finished task in %2f seconds. \n', solver.name, solver.time);
+
+% geting around out of memory problem when converting big matrix from
+% sparse to full...
+
+if (Problem.sparse==1)
+    solver.solution = y;
+else
+    solver.solution = full(y);
+end
+
+%   Reconstruct the signal from the solution
+solver.reconstructed  = Problem.reconstruct(solver.solution);
+end