--- /dev/null	Thu Jan 01 00:00:00 1970 +0000
+++ b/m-toolbox/classes/@ssm/doSimulate.m	Wed Nov 23 19:22:13 2011 +0100
@@ -0,0 +1,145 @@
+% DOSIMULATE simulates a discrete ssm with given inputs
+%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
+%
+% DESCRIPTION: DOSIMULATE simulates a discrete ssm with given inputs.
+%
+% CALL:  [x, y, lastX] = doSimulate(SSini, Nsamples, A, Baos, Coutputs, Cstates, Daos, Bnoise, Dnoise, Bcst, Dcst, aos_vect, doTerminate, terminationCond, displayTime, timestep)
+
+%
+% INPUTS:
+%
+% OUTPUTS:
+%
+%
+% VERSION: $Id: doSimulate.m,v 1.8 2010/09/08 11:39:20 adrien Exp $
+%
+%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
+
+% TO DO: Check input aos for the timestep, tsdata, and ssm.timestep
+% options to be defined (NL case)
+% add check if one input mach no ssm input variable
+% allow use of other LTPDA functions to generate white noise
+
+
+function [x, y, lastX] = doSimulate(SSini, Nsamples, A, Baos, Coutputs, Cstates, Daos, Bnoise, Dnoise, Bcst, Dcst, aos_vect, doTerminate, terminationCond, displayTime, timestep, forceComplete)
+  
+  % We do a simple simulate if all these are satisfied:
+  % 1) Bnoise is empty or all zeros
+  % 2) Cstates is empty
+  % 3) Dnoise is empty or all zeros
+  % 4) Bcst is empty or all zeros
+  % 5) Dcst is empty or all zeros
+  % 6) doTerminate is false
+  
+  if  (isempty(Bnoise) || all(all(Bnoise==0))) && ...
+      isempty(Cstates) && ...
+      (isempty(Dnoise) || all(all(Dnoise==0))) && ...
+      (isempty(Bcst) || all(all(Bcst==0))) && ...
+      (isempty(Dcst) || all(all(Dcst==0))) && ...
+      ~doTerminate && ...
+      ~forceComplete
+    % do a fast simulation
+    Nstates = numel(SSini);
+    
+    if Nstates >= 100
+      % except if Matlab is faster
+      [x,y,lastX] = doSimulateSimple(SSini, Nsamples, A, Baos, Coutputs, Daos, aos_vect);
+    else
+      try
+        % call to the mex file
+        x = [];
+        [y,lastX] = ltpda_ssmsim(SSini, A.', Coutputs.', Cstates.', Baos.', Daos.', aos_vect);
+      catch
+        % backup if the mex-file is broken
+        warning('Failed to run mex file ltpda_ssmsim');
+        [x,y,lastX] = doSimulateSimple(SSini, Nsamples, A, Baos, Coutputs, Daos, aos_vect);
+      end
+    end
+  else
+    % the standard old script, more complete (DC and noise inputs)
+    [x,y,lastX] = doSimulateComplete(SSini, Nsamples, A, Baos, Coutputs, Cstates, Daos, Bnoise, Dnoise, Bcst, Dcst, aos_vect, doTerminate, terminationCond, displayTime, timestep);
+  end
+  
+end
+
+
+function [x,y,lastX] = doSimulateSimple(lastX, Nsamples, A, Baos, Coutputs, Daos, aos_vect)
+  
+  disp('Running simulate simple...');
+  % initializing fields
+  x = [];
+  y = zeros(size(Coutputs,1), Nsamples);
+  lastX  = A*lastX + Baos*aos_vect(:,1);
+  % time for displaying remaining time
+  
+  % simulation loop
+  for k = 1:Nsamples
+    % computing and storing outputs
+    y(:,k) = Coutputs*lastX + Daos*aos_vect(:,k);
+    % computing and storing states
+    lastX  = A*lastX + Baos*aos_vect(:,k);
+  end
+  
+end
+
+function [x,y,lastX] = doSimulateComplete(lastX, Nsamples, A, Baos, Coutputs, Cstates, Daos, Bnoise, Dnoise, Bcst, Dcst, aos_vect, doTerminate, terminationCond, displayTime, timestep)
+  
+  disp('Running simulate complete...');
+  
+  %% converting to sparse matrices
+  if numel(A)>0; if(sum(sum(A==0))/numel(A))>0.5; A = sparse(A); end, end
+  if numel(Baos)>0; if(sum(sum(Baos==0))/numel(Baos))>0.5; Baos = sparse(Baos); end, end
+  if numel(Coutputs)>0; if(sum(sum(Coutputs==0))/numel(Coutputs))>0.5; Coutputs = sparse(Coutputs); end, end
+  if numel(Cstates)>0; if(sum(sum(Cstates==0))/numel(Cstates))>0.5; Cstates = sparse(Cstates); end, end
+  if numel(Daos)>0; if(sum(sum(Daos==0))/numel(Daos))>0.5; Daos = sparse(Daos); end, end
+  if numel(Bnoise)>0; if(sum(sum(Bnoise==0))/numel(Bnoise))>0.5; Bnoise = sparse(Bnoise); end, end
+  if numel(Dnoise)>0; if(sum(sum(Dnoise==0))/numel(Dnoise))>0.5; Dnoise = sparse(Dnoise); end, end
+  if numel(Bcst)>0; if(sum(sum(Bcst==0))/numel(Bcst))>0.5; Bcst = sparse(Bcst); end, end
+  if numel(Dcst)>0; if(sum(sum(Dcst==0))/numel(Dcst))>0.5; Dcst = sparse(Dcst); end, end
+  
+  %% initializing fields
+  x = zeros(size(Cstates,1), Nsamples);
+  y = zeros(size(Coutputs,1), Nsamples);
+  Nnoise = size(Bnoise,2);
+  BLOCK_SIZE = min( [ floor(1e6/(size(Baos,2) + size(Baos,1) + size(Bnoise,2) + 1)) , Nsamples]);
+  noise_array = randn(Nnoise, BLOCK_SIZE);
+  lastX  = A*lastX +  Bcst + Bnoise*noise_array(:,1) + Baos*aos_vect(:,1);
+  % time for displaying remaining time
+  time1=time;
+  
+  %% simulation loop
+  for k = 1:Nsamples
+    %% writing white noise and displaying time
+    if rem(k,BLOCK_SIZE)==0
+      noise_array = randn(Nnoise, BLOCK_SIZE);
+      if displayTime
+        display( ['         simulation time : ',num2str(k*timestep) ]);
+        time2 = time;
+        tloop = floor(time2.utc_epoch_milli-time1.utc_epoch_milli)/1000;
+        display( ['remaining computing time : ',num2str(tloop*(Nsamples-k+1)/k), 's' ]);
+      end
+    end
+    
+    %% evaluating differences
+    knoise = rem(k,BLOCK_SIZE-1)+1;
+    
+    %% computing and storing outputs
+    y(:,k) = Coutputs*lastX +  Dcst + Dnoise*noise_array(:,knoise) + Daos*aos_vect(:,k);
+    
+    %% computing and storing states
+    x(:,k) = Cstates*lastX;
+    lastX  = A*lastX +  Bcst + Bnoise*noise_array(:,knoise) + Baos*aos_vect(:,k);
+    
+    %% checking possible termination condition
+    if doTerminate
+      if eval(terminationCond)
+        x = x(:,1:k);
+        y = y(:,1:k);
+        break;
+      end
+    end
+    
+  end
+  
+end
+