Updates to the OptimizerFactory and the MatlabInterface. Better access to EvAClient.

resources/MatlabInterface/@JEInterface/JEInterface.m

@@ -1,41 +1,46 @@
-function int = JEInterface(interfaceName, fhandle, range, varargin)
+function int = JEInterface(fhandle, range, varargin)
 % EvA2 Interface for Matlab
-%       JEInterface(interfaceName, fhandle, range [, optset, defaultargs])
+%       JEInterface(interfaceName, fhandle, range)
+%       JEInterface(interfaceName, fhandle, range, defaultargs)
+%       JEInterface(interfaceName, fhandle, range, defaultargs, options...)
+
+
 % arguments: 
-%   interfaceName: a JEInterface instance needs to know its own
-%       name as a String to allow callbacks from Java.
 %   fhandle: a function handle defining the optimization target.
 %   range: a 2 x dim array defining the solution subspace with lower and
-%      upper bounds - or a scalar defining the bitwidth for binary problems.
+%      upper bounds - or a scalar defining the bitwidth for binary
-%   optset: (optional) an optimset struct defining optimization parameters,
+%      problems.
-%       especially tolerance and maximum function calls. Defaults to the
-%       EvA2 default values.
 %   defaultArgs: (optional) additional constant argument to the target
 %       function, empty by default.
-% Recognized options are:
+%   options: (optional) options as name-value pairs defining optimization parameters,
+%       especially tolerance and maximum function calls.
+%       Check makeOoptions for default settings.
+
+% Further options may be specified using setOptions with a JE options struct.
+% Main options are:
 %   TolX: convergence criterion in the solution space
 %   TolFun: convergence criterion in the target space
 %   MaxFunEvals: maximum number of function evaluations
 %   Display: 'off'/'final'/'notify'/'iter', where 'notify' corresponds to
-%       displaying every k-th iteration, which k=10 as default.
+%       displaying every k-th iteration, with k=10 as default.
 % The termination criterion of a run is a combination of the TolX, TolFun and
 % MaxFunEvals criteria. The run terminates if MaxFunEvals has been reached
 % or the best solution changes both in domain and codomain less than TolX 
-% and TolFun for a certain time, e.g. 100 evaluations.
+% and TolFun for a certain number of evaluations, which may be set using 
+% TolXEvals and TolFunEvals, respectively.
 % To ignore a criterion, set it to 0. E.g. to perform 10^5 evaluations in
 % any case, set TolX=TolFun=0 and MaxFunEvals=10^5.
 %
-% You may define a 2xdim range with a double valued function handle or for
+% Define a 2 x dim range with a double valued function, or for
 % binary problems set a scalar as range defining the number of bits to be
 % used. The values passed to the function handle will then be arrays of 
 % uint32, each of them representing 32 bits.
 
 int.args = [];
-int.opts = optimset('MaxFunEvals', eva2.OptimizerFactory.getDefaultFitCalls, 'TolX', 1e-4, 'TolFun', 1e-4);
+int.opts = [];
 int.finished = 1;
 int.result = [];
 int.resultArr = [];
-int.callback='';
 int.f = '';
 int.dim = 0;
 int.range = [];
@@ -47,50 +52,51 @@ int.optParams = [];
 int.optParamValues = [];
 int.hexMask=hex2dec('ffffffff');
 
-if (isa(interfaceName, 'char'));
-    int.callback = interfaceName;
-else 
-    error('Wrong first argument type, expected char');
-end
 if (isa(fhandle, 'function_handle'))
     int.f = fhandle;
 else
     error('Wrong second argument type, expected function_handle');
 end
 
+disp('Setting up JEInterface...');
 if (isa(range, 'double') && (size(range,1) == 2))
-    int.dim=size(range, 2);
+    int.dim=size(range,2);
     int.range=transpose(range);
+    s = sprintf('Double valued search space, dimension: %d', int.dim);
+    disp(s);
 else
-    %error('Wrong third argument type, expected double array of 2 x dim');
+    if (length(range)==1)
-    if (size(range,1)==size(range,2)==1)
         int.range=[];
         int.dim=range;
+        s = sprintf('Binary valued search space, dimension: %d', int.dim);
+        disp(s);
+    else 
+        error('Wrong third argument type, expected double array of 2 x dim (double ranges) or scalar (binary bit width).');
     end
 end
 
 int = class(int,'JEInterface');
+int.opts = makeOptions(int);
 
-switch nargin
+if (nargin>2)
-    case {3}
+    int.args = varargin{1};
-    case {4,5}
+    disp('Fitness function argument: '); disp(int.args);
-        if (isa(varargin{1}, 'struct'))
+    if (nargin > 3)
-            int.opts = varargin{1};
+        if (rem(nargin,2)==0)
-            % DONT set default values if user leaves them blank
+            error('Invalid number of arguments!');
-%            if (isempty(int.opts.TolX)) ; int.opts.TolX = 1e-4; end
+        end
-%            if (isempty(int.opts.TolFun)) ; int.opts.TolFun = 1e-4; end
+        disp('Reading options...');
-        else
+        for i=2:2:nargin-2
-            error('Wrong fifth argument type, expected optimset struct');
+            int=setOpt(int, varargin{i}, varargin{i+1});
         end
-        if (nargin > 4)        
-            int.args = varargin{2};
     end
-    otherwise
-        error('Wrong number of arguments!')
 end  
 
 % finally create the java object
 int.mp = eva2.server.go.problems.MatlabProblem(int.dim, int.range);
+disp('Java object created');
+
+testEvalFunc(int);
 
         
 

resources/MatlabInterface/@JEInterface/getOpt.m

@@ -5,4 +5,4 @@ function val = getOpt(int, optName)
 %           optName: name of the option to change, e.g. 'MaxFunEvals'
 %           optVal: new value
 
-val = optimget(int.opts, optName);
+val = int.opts.(optName);

resources/MatlabInterface/@JEInterface/makeOptions.m

@@ -0,0 +1,65 @@
+function opts = makeOptions(int, varargin)
+% Create a JEInterface options set from scratch. Possible fields are:
+%'Display';
+%'MaxFunEvals';'MaxIter';'TolFun';'TolFunEvals';TolX';'TolXEvals', where
+% all but 'TolFunEvals', 'TolXEvals' are used similar to the optimset. 
+% The latter two are interpreted as the numbers of evaluations required
+% to assume convergence. Default values are TolXEvals=TolFunEvals=200,
+% TolX=TolFun=1e-4, MaxFunEvals uses a default from EvA2.
+% Notice that this method creates a parameter set but does not assign it
+% to the interface instance. Use setOptions to do that.
+
+allfields = {'Display'; 'MaxFunEvals';'MaxIter';'TolFun';'TolFunEvals';...
+    'TolX';'TolXEvals'};
+
+specialfields={'TolFunEvals', 'TolXEvals'};
+
+nvararg=nargin-1;
+if rem(nvararg,2)==1
+    error('Pass options in name-value pairs!');
+end
+
+% create cell array
+structinput = cell(2,length(allfields));
+% fields go in first row
+structinput(1,:) = allfields';
+% []'s go in second row
+structinput(2,:) = {[]};
+% turn it into correctly ordered comma separated list and call struct
+opts = struct(structinput{:});
+
+stdSet=optimset();
+
+% standard options:
+opts.('MaxFunEvals') = eva2.OptimizerFactory.getDefaultFitCalls;
+opts.('TolX') = 1e-4;
+opts.('TolXEvals') = 200;
+opts.('TolFun') = 1e-4;
+opts.('TolFunEvals') = 200;
+
+for i=1:nvararg/2
+    name=varargin{2*i-1};
+    value=varargin{(2*i)};
+    % parse arguments
+    if ~ischar(name)
+        error('Expected char parameter name at index %d!', 2*i+1);
+    else
+        optIndex=strmatch(name,allfields, 'exact');
+        if isempty(optIndex)
+            error('Unknown option %s !', name);
+        else
+            if ~isempty(strmatch(name, specialfields,'exact'))
+                % test for integer
+                if (~isscalar(value) || ~isnumeric(value) || round(value)<1)
+                    error('invalid value type for %s, expecting numeric scalar > 1!', name);
+                end
+                value=round(value);
+            else
+                % test using optimset
+                optimset(stdSet, name, value);
+            end
+            % assign to struct
+            opts.(allfields{optIndex,:}) = value;
+        end
+    end
+end

resources/MatlabInterface/@JEInterface/optimize.m

@@ -43,15 +43,14 @@ if ((nargin == 2) || (nargin == 3))
     if (isempty(int.opts.TolX)) ; xTol = 1e-4; end
     if (isempty(int.opts.TolFun)) ; fTol = 1e-4; end
     
-    evalsForConv=100;
     % construct Terminators
     if ((xTol > 0) && (fTol > 0))
         % both criteria are given, use combination
-        convTerm = CombinedTerminator(FitnessConvergenceTerminator(fTol, evalsForConv, 1, 1), PhenotypeConvergenceTerminator(xTol, evalsForConv, 1, 1), 1);
+        convTerm = CombinedTerminator(FitnessConvergenceTerminator(fTol, int.opts.TolFunEvals, 1, 1), PhenotypeConvergenceTerminator(xTol, int.opts.TolXEvals, 1, 1), 1);
     else if (xTol > 0)  % only phenotye convergence
-            convTerm = PhenotypeConvergenceTerminator(xTol, evalsForConv, 1, 1);
+            convTerm = PhenotypeConvergenceTerminator(xTol, int.opts.TolXEvals, 1, 1);
         else if (fTol > 0 )             % only fitness covnergence
-                convTerm = FitnessConvergenceTerminator(fTol, evalsForConv, 1, 1);
+                convTerm = FitnessConvergenceTerminator(fTol, int.opts.TolFunEvals, 1, 1);
             else
                convTerm = 'undef'; % signal that there is no terminator yet
             end

resources/MatlabInterface/@JEInterface/setOpt.m

@@ -1,9 +1,13 @@
 function int = setOpt(int, optName, optVal)
-% Set a single optimset value within the JI instance.
+% Set a single option value within the JI instance.
 % Arguments: 
 %           int: the JEInterface instance
 %           optName: name of the option to change, e.g. 'MaxFunEvals'
 %           optVal: new value
 
-opts = optimset(int.opts, optName, optVal);
+% this only makes sure the option actally exists and is valid
+makeOptions(int, optName, optVal);
+
+opts = int.opts;
+opts.(optName) = optVal;
 int.opts = opts;

resources/MatlabInterface/@JEInterface/setOptions.m

@@ -1,7 +1,25 @@
-function int = setOptions(int, options)
+function int = setOptions(int, usrOpts)
-% Set the optimization options for the interface.
+% Set the optimization options for the interface. The existing options are
+% overwritten by the given setings.
 %   parameters:
 %       int:    an interface instance
-%       options:    an optimset instance
+%       usrOpts:    a JE options structure
+
+fn=fieldnames(usrOpts);
+
+options = int.opts;
+
+try
+    for i=1:length(fn)
+        % make sure all option fields and values are valid
+        % fn(i)
+        % ischar(fn(i))
+        makeOptions(int, char(fn(i)), usrOpts.(char(fn(i))));
+        options.(char(fn(i))) = usrOpts.(char(fn(i)));
+    end
+catch ME
+    error('invalid option "%s"... check makeOptions to learn about available options', char(fn(i)));
+
+end
 
 int.opts = options;

resources/MatlabInterface/@JEInterface/setVerbose.m

@@ -0,0 +1,24 @@
+function int=setVerbose(int, bOn, varargin)
+% Activate debug output for the MatlabProblem.
+%      setVerbose(JI, bOn [, dbgfile])
+% It is written to a file with given name or to matlabproblem-debug.log 
+% if none is given.
+%   JI: the interface instance
+%   bOn: 1 activates debug output, 0 deactivates it
+%   dbgfile: optional filename
+%
+
+if (nargin > 2)
+    if ischar(varargin{1})
+        fname=varargin{1};
+        disp('Writing debug output to ');
+        disp(fname);
+    else
+        disp('Invalid third argument, expected char. Using default output file name');
+    end
+else
+    fname=null;
+end
+        
+int.mp.setDebugOut( bOn==1, fname);
+

resources/MatlabInterface/@JEInterface/testEvalFunc.m

@@ -0,0 +1,56 @@
+function testEvalFunc(int) 
+% Test the fitness function output format.
+wordwidth=32;
+
+if (isempty(int.range)==1)
+    % binary problem
+    s=sprintf('Binary problem of bitwidth %d', int.dim);
+    disp(s);
+    numInts=ceil(int.dim/wordwidth);
+    % generate trial vector
+    x=ceil(rand(1,numInts).*(2^wordwidth));
+    overheadBits=numInts*wordwidth-int.dim;
+    x(numInts)=bitshift(x(numInts),-overheadBits); % shift right by overhead
+else
+    % double problem
+    x=rand(1, int.dim);
+    s=sprintf('Real valued problem in %d dimensions and range %s ', int.dim, mat2str(int.range));
+    disp(s);
+    for i=1:int.dim
+        x(i)=int.range(i,1)+x(i)*(int.range(i,2)-int.range(i,1));
+    end
+end
+
+disp('Testing value: ')
+disp(x);
+
+try
+    if (isempty(int.args))
+        res = feval(int.f, x);
+    else
+        res = feval(int.f, x, int.args);
+    end
+catch ME
+    disp('Function evaluation failed:');
+    disp(ME.message);
+    error('Test failed!');
+end
+            
+disp('Function returned: ');
+disp(res);
+
+if (min(size(res)) > 1)
+    disp('Warning: unable to optimize matrix representations - use 1 times m output only');
+else
+    if (size(res,1)>1)
+        disp('Warning: use dimensions 1 times m instead of m times 1');
+    else
+        if ~(sum(isnumeric(res))==size(res,1)*size(res,2))
+            disp('Warning: result seems to contain non-numeric elements!');
+        else
+            disp('Ok.');
+        end
+    end;
+end
+
+    

src/eva2/EvAInfo.java

@@ -4,6 +4,8 @@ package eva2;
  * Main product and version information strings.
  * 
  * --- Changelog
+ * 2.031: Some updates to the OptimizerFactory. Review of the MatlabInterface with adding an own options structure.
+ * 			Better access to the EvAClient, which now may have a RemoteStateListener added monitoring the optimization run.
  * 2.030: Added an EnumEditor to access enums easily through the GUI, which will replace SelectedTags sometimes.
  * 			IPOP-ES and RankMuCMA mutator have been added lately (wow!).
  * 			Cleaned up the IndividualInterface and reduced the usage of InterfaceESIndividual. This

src/eva2/OptimizerFactory.java

@@ -35,7 +35,6 @@ import eva2.server.go.operators.selection.InterfaceSelection;
 import eva2.server.go.operators.selection.SelectBestIndividuals;
 import eva2.server.go.operators.terminators.CombinedTerminator;
 import eva2.server.go.operators.terminators.EvaluationTerminator;
-import eva2.server.go.operators.terminators.FitnessConvergenceTerminator;
 import eva2.server.go.populations.Population;
 import eva2.server.go.problems.AbstractOptimizationProblem;
 import eva2.server.go.strategies.ClusterBasedNichingEA;
@@ -67,9 +66,8 @@ import eva2.server.modules.GOParameters;
  * the methods initialize the respective optimization procedure. To perform an
  * optimization one has to do the following: <code>
  * InterfaceOptimizer optimizer = OptimizerFactory.createCertainOptimizer(arguments);
- * EvaluationTerminator terminator = new EvaluationTerminator();
+ * EvaluationTerminator terminator = new EvaluationTerminator(numOfFitnessCalls);
- * terminator.setFitnessCalls(numOfFitnessCalls);
+ * while (!terminator.isTerminated(optimizer.getPopulation())) optimizer.optimize();
- * while (!terminator.isTerminated(mc.getPopulation())) mc.optimize();
  * </code>
  * </p>
  *
@@ -80,7 +78,7 @@ import eva2.server.modules.GOParameters;
  * @date 17.04.2007
  */
 public class OptimizerFactory {
-	private static InterfaceTerminator term = null;
+	private static InterfaceTerminator userTerm = null;
 
 	public final static int STD_ES = 1;
 
@@ -110,24 +108,6 @@ public class OptimizerFactory {
 
 	private static OptimizerRunnable lastRunnable = null;
 
-	/**
-	 * Add an InterfaceTerminator to any new optimizer in a boolean combination.
-	 * The old and the given terminator will be combined as in (TOld && TNew) if
-	 * bAnd is true, and as in (TOld || TNew) if bAnd is false.
-	 *
-	 * @param newTerm
-	 *            a new InterfaceTerminator instance
-	 * @param bAnd
-	 *            indicate the boolean combination
-	 */
-	public static void addTerminator(InterfaceTerminator newTerm, boolean bAnd) {
-		if (OptimizerFactory.term == null)
-			OptimizerFactory.term = term;
-		else
-			setTerminator(new CombinedTerminator(OptimizerFactory.term,
-					newTerm, bAnd));
-	}
-
 	/**
 	 * This method optimizes the given problem using differential evolution.
 	 *
@@ -501,10 +481,8 @@ public class OptimizerFactory {
 	}
 
 	// /////////////////////////// Termination criteria
-	public static InterfaceTerminator defaultTerminator() {
+	public static InterfaceTerminator makeDefaultTerminator() {
-		if (term == null)
+		return new EvaluationTerminator(defaultFitCalls);
-			term = new EvaluationTerminator(defaultFitCalls);
-		return term;
 	}
 
 	/**
@@ -582,21 +560,38 @@ public class OptimizerFactory {
 	public static OptimizerRunnable getOptRunnable(final int optType,
 			AbstractOptimizationProblem problem, int fitCalls,
 			String outputFilePrefix) {
+		return getOptRunnable(optType, problem, new EvaluationTerminator(fitCalls), outputFilePrefix);
+	}
+
+	/**
+	 * Produce a runnable optimizer from a strategy identifier, a problem instance and with a given
+	 * terminator. Output is written to a file if the prefix String is given. If the terminator is null
+	 * the current user-defined terminator will be used and if none is set, the default number of fitness
+	 * calls will be performed.
+	 * 
+	 * @param optType
+	 * @param problem
+	 * @param terminator
+	 * @param outputFilePrefix
+	 * @return a runnable optimizer
+	 */
+	public static OptimizerRunnable getOptRunnable(final int optType,
+			AbstractOptimizationProblem problem, InterfaceTerminator terminator,
+			String outputFilePrefix) {
 		OptimizerRunnable opt = null;
 		GOParameters params = getParams(optType, problem);
 		if (params != null) {
 			opt = new OptimizerRunnable(params, outputFilePrefix);
-			if (fitCalls != defaultFitCalls)
+			if (terminator != null) opt.getGOParams().setTerminator(terminator);
-				opt.getGOParams().setTerminator(
+			else opt.getGOParams().setTerminator(getTerminator());
-						new EvaluationTerminator(fitCalls));
 		}
 		return opt;
 	}
 	
 	// /////////////////////////// constructing a default OptimizerRunnable
 	/**
-	 * Produce a runnable optimizer from a strategy identifier, a problem instance and with the default
+	 * Produce a runnable optimizer from a strategy identifier, a problem instance and with the current
-	 * number of fitness calls to be performed. Output is written to a file if the prefix String is given.
+	 * static terminator in use. Output is written to a file if the prefix String is given.
 	 * @see #getOptRunnable(int, AbstractOptimizationProblem, int, String)
 	 * @param optType
 	 * @param problem
@@ -605,17 +600,17 @@ public class OptimizerFactory {
 	 */
 	public static OptimizerRunnable getOptRunnable(final int optType,
 			AbstractOptimizationProblem problem, String outputFilePrefix) {
-		return getOptRunnable(optType, problem, defaultFitCalls,
+		return getOptRunnable(optType, problem, getTerminator(), outputFilePrefix);
-				outputFilePrefix);
 	}
 
 	/**
-	 * Return the current default terminator.
+	 * Return the current user-defined or, if none was set, the default terminator.
 	 * 
 	 * @return the current default terminator
 	 */
 	public static InterfaceTerminator getTerminator() {
-		return OptimizerFactory.term;
+		if (OptimizerFactory.userTerm != null) return OptimizerFactory.userTerm;
+		else return makeDefaultTerminator();
 	}
 
 	/**
@@ -638,7 +633,7 @@ public class OptimizerFactory {
 	 */
 	public static GOParameters makeESParams(EvolutionStrategies es,
 			AbstractOptimizationProblem problem) {
-		return makeParams(es, es.getLambda(), problem, randSeed, defaultTerminator());
+		return makeParams(es, es.getLambda(), problem, randSeed, makeDefaultTerminator());
 	}
 
 	/**
@@ -651,7 +646,7 @@ public class OptimizerFactory {
 	 * @return
 	 */
 	public static GOParameters makeParams(InterfaceOptimizer opt, int popSize, AbstractOptimizationProblem problem) {
-		return makeParams(opt, popSize, problem, randSeed, defaultTerminator());
+		return makeParams(opt, popSize, problem, randSeed, makeDefaultTerminator());
 	}
 
 	public static GOParameters makeParams(InterfaceOptimizer opt,
@@ -709,14 +704,36 @@ public class OptimizerFactory {
 	 * @param optType
 	 * @param problem
 	 * @param outputFilePrefix
-	 * @return
+	 * @return the OptimizerRunnable instance just started
 	 */
-	public static OptimizerRunnable optimizeInThread(final int optType,
+	public static OptimizerRunnable optimizeInThread(final int optType, AbstractOptimizationProblem problem, String outputFilePrefix) {
-			AbstractOptimizationProblem problem, String outputFilePrefix) {
+		return optimizeInThread(getOptRunnable(optType, problem, outputFilePrefix));
-		OptimizerRunnable runnable = getOptRunnable(optType, problem,
+	}
-				outputFilePrefix);
+	
-		if (runnable != null)
+	/**
+	 * Create a runnable optimization Runnable and directly start it in an own
+	 * thread. The Runnable will notify waiting threads and set the isFinished
+	 * flag when the optimization is complete. If the optType is invalid, null
+	 * will be returned.
+	 *
+	 * @param params
+	 * @param outputFilePrefix
+	 * @return the OptimizerRunnable instance just started
+	 */
+	public static OptimizerRunnable optimizeInThread(GOParameters params, String outputFilePrefix) {
+		return optimizeInThread(new OptimizerRunnable(params, outputFilePrefix));
+	}
+
+	/**
+	 * Start a runnable optimizer in a concurrent thread.
+	 * @param runnable
+	 * @return the started runnable
+	 */
+	public static OptimizerRunnable optimizeInThread(OptimizerRunnable runnable) {
+		if (runnable != null) {
 			new Thread(runnable).start();
+			lastRunnable = runnable;
+		}
 		return runnable;
 	}
 	
@@ -810,12 +827,30 @@ public class OptimizerFactory {
 		return (lastRunnable == null) ? null : postProcess(lastRunnable, ppp);
 	}
 
+	/**
+	 * Post process the given runnable with given parameters. The runnable will
+	 * not be stored.
+	 *  
+	 * @param runnable
+	 * @param steps
+	 * @param sigma
+	 * @param nBest
+	 * @return
+	 */
 	public static Population postProcess(OptimizerRunnable runnable, int steps,
 			double sigma, int nBest) {
 		PostProcessParams ppp = new PostProcessParams(steps, sigma, nBest);
 		return postProcess(runnable, ppp);
 	}
 
+	/**
+	 * Post process the given runnable with given parameters. The runnable will
+	 * not be stored.
+	 * 
+	 * @param runnable
+	 * @param ppp
+	 * @return
+	 */
 	public static Population postProcess(OptimizerRunnable runnable,
 			InterfacePostProcessParams ppp) {
 		runnable.setDoRestart(true);
@@ -845,6 +880,14 @@ public class OptimizerFactory {
 				nBest));
 	}
 
+	/**
+	 * Post process the given runnable with given parameters. Return the solution set
+	 * as a vector of BitSets. The runnable will not be stored.
+	 * 
+	 * @param runnable
+	 * @param ppp
+	 * @return
+	 */
 	public static Vector<BitSet> postProcessBinVec(OptimizerRunnable runnable,
 			InterfacePostProcessParams ppp) {
 		Population resPop = postProcess(runnable, ppp);
@@ -876,6 +919,14 @@ public class OptimizerFactory {
 				nBest));
 	}
 	
+	/**
+	 * Post process the given runnable with given parameters. Return the solution set
+	 * as a vector of double arrays. The runnable will not be stored.
+	 * 
+	 * @param runnable
+	 * @param ppp
+	 * @return
+	 */
 	public static Vector<double[]> postProcessDblVec(
 			OptimizerRunnable runnable, InterfacePostProcessParams ppp) {
 		Population resPop = postProcess(runnable, ppp);
@@ -907,6 +958,14 @@ public class OptimizerFactory {
 				nBest));
 	}
 	
+	/**
+	 * Post process the given runnable with given parameters. Return the solution set
+	 * as a vector of AbstractEAIndividuals. The runnable will not be stored.
+	 * 
+	 * @param runnable
+	 * @param ppp
+	 * @return
+	 */
 	public static Vector<AbstractEAIndividual> postProcessIndVec(
 			OptimizerRunnable runnable, InterfacePostProcessParams ppp) {
 		Population resPop = postProcess(runnable, ppp);
@@ -922,19 +981,48 @@ public class OptimizerFactory {
 	}
 	
 	///////////////////////////// termination management
+	/**
+	 * Replace the current user-defined terminator by the given one.
+	 * 
+	 * @param term
+	 */
+	public static void setTerminator(InterfaceTerminator term) {
+		OptimizerFactory.userTerm = term;
+	}
+
+	/**
+	 * Add a new InterfaceTerminator to the current user-defined optimizer in a boolean combination.
+	 * The old and the given terminator will be combined as in (TOld && TNew) if
+	 * bAnd is true, and as in (TOld || TNew) if bAnd is false.
+	 * If there was no user-defined terminator (or it was set to null) the new one is used without conjunction. 
+	 *
+	 * @param newTerm
+	 *            a new InterfaceTerminator instance
+	 * @param bAnd
+	 *            indicate the boolean combination
+	 */
+	public static void addTerminator(InterfaceTerminator newTerm, boolean bAnd) {
+		if (OptimizerFactory.userTerm == null)
+			OptimizerFactory.userTerm = newTerm;
+		else
+			setTerminator(new CombinedTerminator(OptimizerFactory.userTerm,
+					newTerm, bAnd));
+	}
+	
+	/**
+	 * Convenience method setting an EvaluationTerminator with the given
+	 * number of evaluations.
+	 * 
+	 * @param maxEvals
+	 */
 	public static void setEvaluationTerminator(int maxEvals) {
 		setTerminator(new EvaluationTerminator(maxEvals));
 	}
 
-	public static void setFitnessConvergenceTerminator(double fitThresh) {
+	/**
-		setTerminator(new FitnessConvergenceTerminator(fitThresh, 100, true,
+	 * Return the termination message of the last runnable, if available. 
-				true));
+	 * @return
-	}
+	 */
-
-	public static void setTerminator(InterfaceTerminator term) {
-		OptimizerFactory.term = term;
-	}
-
 	public static String terminatedBecause() {
 		return (lastRunnable != null) ? lastRunnable.terminatedBecause() : null;
 	}
@@ -947,12 +1035,12 @@ public class OptimizerFactory {
 	 */
 	public static final GOParameters hillClimbing(
 			AbstractOptimizationProblem problem) {
-		return makeParams(new HillClimbing(), 50, problem, randSeed, defaultTerminator());
+		return makeParams(new HillClimbing(), 50, problem, randSeed, makeDefaultTerminator());
 	}
 
 	public static final GOParameters monteCarlo(
 			AbstractOptimizationProblem problem) {
-		return makeParams(new MonteCarloSearch(), 50, problem, randSeed, defaultTerminator());
+		return makeParams(new MonteCarloSearch(), 50, problem, randSeed, makeDefaultTerminator());
 	}
 	
 	public static final GOParameters cbnES(AbstractOptimizationProblem problem) {
@@ -967,7 +1055,7 @@ public class OptimizerFactory {
 		cbn.setDifferentationCA(clustering);
 		cbn.setShowCycle(0); // don't do graphical output
 
-		return makeParams(cbn, 100, problem, randSeed, defaultTerminator());
+		return makeParams(cbn, 100, problem, randSeed, makeDefaultTerminator());
 	}
 
 	public static final GOParameters clusteringHillClimbing(
@@ -982,7 +1070,7 @@ public class OptimizerFactory {
 		chc.setNotifyGuiEvery(0);
 		chc.setStepSizeThreshold(0.000001);
 		chc.setSigmaClust(0.05);
-		return makeParams(chc, 100, problem, randSeed, defaultTerminator());
+		return makeParams(chc, 100, problem, randSeed, makeDefaultTerminator());
 	}
 
 	public static final GOParameters cmaES(AbstractOptimizationProblem problem) {
@@ -1052,7 +1140,7 @@ public class OptimizerFactory {
 		de.setK(0.6);
 		de.setLambda(0.6);
 		de.setMt(0.05);
-		return makeParams(de, 50, problem, randSeed, defaultTerminator());
+		return makeParams(de, 50, problem, randSeed, makeDefaultTerminator());
 	}
 
 	public static final GOParameters standardES(
@@ -1082,7 +1170,7 @@ public class OptimizerFactory {
 		GeneticAlgorithm ga = new GeneticAlgorithm();
 		ga.setElitism(true);
 
-		return makeParams(ga, 100, problem, randSeed, defaultTerminator());
+		return makeParams(ga, 100, problem, randSeed, makeDefaultTerminator());
 	}
 
 	public static final GOParameters standardPSO(
@@ -1090,10 +1178,10 @@ public class OptimizerFactory {
 		ParticleSwarmOptimization pso = new ParticleSwarmOptimization();
 		pso.setPhiValues(2.05, 2.05);
 		pso.getTopology().setSelectedTag("Grid");
-		return makeParams(pso, 30, problem, randSeed, defaultTerminator());
+		return makeParams(pso, 30, problem, randSeed, makeDefaultTerminator());
 	}
 
 	public static final GOParameters tribes(AbstractOptimizationProblem problem) {
-		return makeParams(new Tribes(), 1, problem, randSeed, defaultTerminator());
+		return makeParams(new Tribes(), 1, problem, randSeed, makeDefaultTerminator());
 	}
 }

src/eva2/OptimizerRunnable.java

@@ -4,6 +4,8 @@ import java.io.PrintWriter;
 import java.io.StringWriter;
 import java.util.BitSet;
 
+import wsi.ra.jproxy.RemoteStateListener;
+
 import eva2.server.go.IndividualInterface;
 import eva2.server.go.InterfaceGOParameters;
 import eva2.server.go.InterfaceTerminator;
@@ -89,6 +91,10 @@ public class OptimizerRunnable implements Runnable {
 		if (listener != null) proc.getStatistics().addTextListener(listener);
 	}
 
+	public void addRemoteStateListener(RemoteStateListener rsl) {
+   		if (proc != null) proc.addListener(rsl);
+    }
+	
 	public void setDoRestart(boolean restart) {
 		doRestart = restart;
 	}

src/eva2/server/go/problems/MatlabEvalMediator.java

@@ -1,8 +1,5 @@
 package eva2.server.go.problems;
 
-import java.lang.reflect.Array;
-import java.util.BitSet;
-
 import eva2.gui.BeanInspector;
 
 /**
@@ -34,7 +31,7 @@ public class MatlabEvalMediator implements Runnable {
 	boolean quit = false;
 	volatile Object optSolution = null;
 	volatile Object[] optSolSet = null;
-//	MatlabProblem mp = null;
+	MatlabProblem mp = null;
 	// no good: even when waiting for only 1 ms the Matlab execution time increases by a factor of 5-10
 	final static int sleepTime = 0;
 
@@ -45,7 +42,7 @@ public class MatlabEvalMediator implements Runnable {
 	 * @return
 	 */
 	double[] requestEval(MatlabProblem mp, Object x) {
-//		this.mp = mp;
+		this.mp = mp;
 		question = x;
 //		System.err.println("IN REQUESTEVAL, x is " + BeanInspector.toString(x));
 		if (question.getClass().isArray()) {
@@ -54,11 +51,12 @@ public class MatlabEvalMediator implements Runnable {
 //			BitSet b = (BitSet)x;
 //			Integer.decode()
 //			
+			if (question == null) System.err.println("Error: requesting evaluation for null array!");
 		} else System.err.println("Error, requesting evaluation for non array!"); 
 		
 		requesting = true;
 //		int k=0;
-//		System.out.println("Requesting eval for " + BeanInspector.toString(x) + ", req state is " + requesting + "\n"); 
+		mp.log("-- Requesting eval for " + BeanInspector.toString(x) + ", req state is " + requesting + "\n"); 
 		while (requesting && !quit) {
 			// 	wait for matlab to answer the question
 			if (sleepTime > 0) try { Thread.sleep(sleepTime); } catch(Exception e) {};
@@ -67,8 +65,9 @@ public class MatlabEvalMediator implements Runnable {
 //			}
 //			k++;
 		}
-//		System.out.println("Requesting done \n");
+		mp.log("-- Requesting done\n");
 		// matlab is finished, answer is here
+		//return null;
 		return getAnswer(); // return to JE with answer
 	}
 
@@ -102,11 +101,12 @@ public class MatlabEvalMediator implements Runnable {
 	 * @return
 	 */
 	public Object getQuestion() {
-//		mp.log("-- Question: " + BeanInspector.toString(question) + "\n");
+		mp.log("-- Question: " + BeanInspector.toString(question) + "\n");
 		return question;
 	}
 
 	double[] getAnswer() {
+		mp.log("-- mediator delivering " + BeanInspector.toString(answer) + "\n");
 		return answer;
 	}
 
@@ -116,10 +116,14 @@ public class MatlabEvalMediator implements Runnable {
 	 * @param y
 	 */
 	public void setAnswer(double[] y) {
-//		mp.log("-- setAnswer: " + BeanInspector.toString(y) + "\n"); 
 //		System.err.println("answer is " + BeanInspector.toString(y)); 
+		if (y==null) {
+			System.err.println("Error: Matlab function returned null array - this is bad.");
+			System.err.println("X-value was " + BeanInspector.toString(getQuestion()));
+		}
 		answer = y;
 		requesting = false; // answer is finished, break request loop
+		mp.log("-- setAnswer: " + BeanInspector.toString(y) + ", req state is " + requesting + "\n"); 
 	}
 
 	void setFinished(boolean val) {

src/eva2/server/go/problems/MatlabProblem.java

@@ -30,13 +30,13 @@ import eva2.server.stat.InterfaceTextListener;
  */
 public class MatlabProblem extends AbstractOptimizationProblem implements InterfaceTextListener, Serializable {
 	private static final long serialVersionUID = 4913310869887420815L;
-	public static final boolean 		TRACE = true; 
+	public static boolean 				TRACE = false; 
 	transient OptimizerRunnable			runnable = null;
 	protected boolean 					allowSingleRunnable = true;	
 	protected int 						problemDimension = 10;
 	transient PrintStream 				dos = null;
 	private double 						range[][] =	null;
-	private static final String			defTestOut = "matlabproblem-testout.dat";
+	private static String				defTestOut = "matlabproblem-debug.log";
 	int 								verbosityLevel	= 0;
 	private MatlabEvalMediator 			handler = null;
 	private boolean isDouble = true;
@@ -123,16 +123,33 @@ public class MatlabProblem extends AbstractOptimizationProblem implements Interf
 //		System.err.println("range: " + BeanInspector.toString(range));
 		initTemplate();
 //		res = new ResultArr();
-		if ((dos == null) && TRACE) {
+		
+		setDebugOut(TRACE, defTestOut);
+
+//		log("range is " + BeanInspector.toString(range)+ "\n");
+//		log("template len: " + ((ESIndividualDoubleData)m_Template).getDGenotype().length + "\n");
+	}
+
+	/**
+	 * If swtch is true and no output file is open yet, open a new one which will be used for debug output.
+	 * if fname is null, the default filename will be used.
+	 * if swtch is false, close the output file and deactivate debug output.
+	 * 
+	 * @param swtch
+	 * @param fname
+	 */
+	public void setDebugOut(boolean swtch, String fname) {
+		TRACE=swtch;
+		if (!swtch && (dos != null)) {
+			dos.close();
+			dos = null;
+		} else if ((dos == null) && swtch) {
 			try {
-				dos = new PrintStream(new FileOutputStream(outFile));
+				dos = new PrintStream(new FileOutputStream(fname==null ? defTestOut : fname));
 			} catch (FileNotFoundException e) {
 				e.printStackTrace();
 			}
 		}
-
-//		log("range is " + BeanInspector.toString(range)+ "\n");
-//		log("template len: " + ((ESIndividualDoubleData)m_Template).getDGenotype().length + "\n");
 	}
 	
 	public void setStatsOutput(int verboLevel) {
@@ -386,10 +403,10 @@ public class MatlabProblem extends AbstractOptimizationProblem implements Interf
 
 	@Override
 	public void evaluate(AbstractEAIndividual indy) {
-		log("evaluating " + BeanInspector.toString(indy) + "\n");
+		log("evaluating " + AbstractEAIndividual.getDefaultStringRepresentation(indy) + "\n");
 		double[] res = handler.requestEval(this, AbstractEAIndividual.getIndyData(indy));
+		log("evaluated to " + BeanInspector.toString(res) + "\n");
 		indy.SetFitness(res);
-//		System.err.println("evaluated to " + BeanInspector.toString(res));
 	}
 
 	@Override

src/eva2/server/go/problems/WaitForEvARunnable.java

@@ -19,24 +19,23 @@ class WaitForEvARunnable implements Runnable {
 	public void run() {
 		if (runnable != null) {
 			mp.log("\nStarting optimize runnable!\n");
-
 			synchronized (runnable) {
 				try {
 					// whole optimization thread goes in here
 					new Thread(runnable).start();
-					mp.log("Starting optimize thread done!\n");
+					mp.log("Started optimize thread\n");
 					runnable.wait();
 					// wait for the runnable to finish
-					mp.log("After wait!\n");
+					mp.log("runnable continues...\n");
 				} catch (InterruptedException e) {
 					e.printStackTrace();
 					mp.log("WaitForEvARunnable was interrupted with " + e.getMessage());
 				}
 			}
 			try {
-				mp.log("runnable.getDoubleSolution: " + BeanInspector.toString(runnable.getDoubleSolution()));
+				mp.log("runnable.getDoubleSolution: " + BeanInspector.toString(runnable.getDoubleSolution()) + "\n");
-				mp.log("runnable.getIntegerSolution: " + BeanInspector.toString(runnable.getIntegerSolution()));
+				mp.log("runnable.getIntegerSolution: " + BeanInspector.toString(runnable.getIntegerSolution()) + "\n");
-				mp.log("\ngetAllSols best: " + AbstractEAIndividual.getDefaultDataString(runnable.getGOParams().getOptimizer().getAllSolutions().getSolutions().getBestEAIndividual()));
+				mp.log("getAllSols best: " + AbstractEAIndividual.getDefaultDataString(runnable.getGOParams().getOptimizer().getAllSolutions().getSolutions().getBestEAIndividual()) + "\n");
 				mp.log("\n");
 				// write results back to matlab
 				mp.exportResultToMatlab(runnable);

src/eva2/server/go/strategies/ClusterBasedNichingEA.java

@@ -150,13 +150,13 @@ public class ClusterBasedNichingEA implements InterfacePopulationChangedEventLis
         population.incrGeneration();
     }
 
-    private void plot() {
+    private void plot(int gen) {
         double[]   a = new double[2];
         a[0] = 0.0;
         a[1] = 0.0;
         if (this.m_Problem instanceof TF1Problem) {
             // now i need to plot the pareto fronts
-            Plot plot = new Plot("TF3Problem", "y1", "y2", a, a);
+            Plot plot = new Plot("TF3Problem at gen. "+gen, "y1", "y2", a, a);
             plot.setUnconnectedPoint(0,0,0);
             plot.setUnconnectedPoint(1,5,0);
             GraphPointSet   mySet = new GraphPointSet(10, plot.getFunctionArea());
@@ -191,7 +191,7 @@ public class ClusterBasedNichingEA implements InterfacePopulationChangedEventLis
             InterfaceDataTypeDouble tmpIndy1, best;
             Population              pop;
 
-            this.m_Topology          = new TopoPlot("CBN-Species","x","y",a,a);
+            this.m_Topology          = new TopoPlot("CBN-Species at gen. " + gen,"x","y",a,a);
             this.m_Topology.gridx = 60;
             this.m_Topology.gridy = 60;
             this.m_Topology.setTopology((Interface2DBorderProblem)this.m_Problem);
@@ -358,9 +358,9 @@ public class ClusterBasedNichingEA implements InterfacePopulationChangedEventLis
     	// plot the populations
     	if (this.m_ShowCycle > 0) {
             if ((this.m_Undifferentiated.getGeneration() == 0) || (this.m_Undifferentiated.getGeneration() == 1) || (this.m_Undifferentiated.getGeneration() == 2)) {
-                this.plot();
+                this.plot(this.m_Undifferentiated.getGeneration());
             } else {
-                if (this.m_Undifferentiated.getGeneration()%this.m_ShowCycle == 0) this.plot();
+                if (this.m_Undifferentiated.getGeneration()%this.m_ShowCycle == 0) this.plot(this.m_Undifferentiated.getGeneration());
             }
         }
 
@@ -706,7 +706,7 @@ public class ClusterBasedNichingEA implements InterfacePopulationChangedEventLis
      * @return description
      */
     public String globalInfo() {
-        return "This is a versatible species based niching EA method.";
+        return "This is a versatile species based niching EA method.";
     }
     /** This method will return a naming String
      * @return The name of the algorithm