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

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This commit is contained in:
Marcel Kronfeld 2008-12-09 15:18:54 +00:00
parent c76f046faf
commit 245d8892ef
15 changed files with 433 additions and 145 deletions
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80
resources/MatlabInterface/@JEInterface/JEInterface.m
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@ -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.
% optset: (optional) an optimset struct defining optimization parameters,
% especially tolerance and maximum function calls. Defaults to the
% EvA2 default values.
% upper bounds - or a scalar defining the bitwidth for binary
% problems.
% 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 (size(range,1)==size(range,2)==1)
if (length(range)==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
case {3}
case {4,5}
if (isa(varargin{1}, 'struct'))
int.opts = varargin{1};
% DONT set default values if user leaves them blank
% if (isempty(int.opts.TolX)) ; int.opts.TolX = 1e-4; end
% if (isempty(int.opts.TolFun)) ; int.opts.TolFun = 1e-4; end
else
error('Wrong fifth argument type, expected optimset struct');
if (nargin>2)
int.args = varargin{1};
disp('Fitness function argument: '); disp(int.args);
if (nargin > 3)
if (rem(nargin,2)==0)
error('Invalid number of arguments!');
end
if (nargin > 4)
int.args = varargin{2};
disp('Reading options...');
for i=2:2:nargin-2
int=setOpt(int, varargin{i}, varargin{i+1});
end
otherwise
error('Wrong number of arguments!')
end
end
end
% finally create the java object
int.mp = eva2.server.go.problems.MatlabProblem(int.dim, int.range);
disp('Java object created');
testEvalFunc(int);

2
resources/MatlabInterface/@JEInterface/getOpt.m
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@ -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);

65
resources/MatlabInterface/@JEInterface/makeOptions.m Normal file
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@ -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

7
resources/MatlabInterface/@JEInterface/optimize.m
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@ -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

8
resources/MatlabInterface/@JEInterface/setOpt.m
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@ -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;

24
resources/MatlabInterface/@JEInterface/setOptions.m
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@ -1,7 +1,25 @@
function int = setOptions(int, options)
% Set the optimization options for the interface.
function int = setOptions(int, usrOpts)
% 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;

24
resources/MatlabInterface/@JEInterface/setVerbose.m Normal file
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@ -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);

56
resources/MatlabInterface/@JEInterface/testEvalFunc.m Normal file
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@ -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

2
src/eva2/EvAInfo.java
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@ -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

220
src/eva2/OptimizerFactory.java
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@ -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();
* terminator.setFitnessCalls(numOfFitnessCalls);
* while (!terminator.isTerminated(mc.getPopulation())) mc.optimize();
* EvaluationTerminator terminator = new EvaluationTerminator(numOfFitnessCalls);
* while (!terminator.isTerminated(optimizer.getPopulation())) optimizer.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() {
if (term == null)
term = new EvaluationTerminator(defaultFitCalls);
return term;
public static InterfaceTerminator makeDefaultTerminator() {
return new EvaluationTerminator(defaultFitCalls);
}
/**
@ -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)
opt.getGOParams().setTerminator(
new EvaluationTerminator(fitCalls));
if (terminator != null) opt.getGOParams().setTerminator(terminator);
else opt.getGOParams().setTerminator(getTerminator());
}
return opt;
}
// /////////////////////////// constructing a default OptimizerRunnable
/**
* Produce a runnable optimizer from a strategy identifier, a problem instance and with the default
* number of fitness calls to be performed. Output is written to a file if the prefix String is given.
* Produce a runnable optimizer from a strategy identifier, a problem instance and with the current
* 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,
outputFilePrefix);
return getOptRunnable(optType, problem, getTerminator(), 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,
@ -709,17 +704,39 @@ public class OptimizerFactory {
* @param optType
* @param problem
* @param outputFilePrefix
* @return
* @return the OptimizerRunnable instance just started
*/
public static OptimizerRunnable optimizeInThread(final int optType,
AbstractOptimizationProblem problem, String outputFilePrefix) {
OptimizerRunnable runnable = getOptRunnable(optType, problem,
outputFilePrefix);
if (runnable != null)
new Thread(runnable).start();
return runnable;
public static OptimizerRunnable optimizeInThread(final int optType, AbstractOptimizationProblem problem, String outputFilePrefix) {
return optimizeInThread(getOptRunnable(optType, problem, outputFilePrefix));
}
/**
* 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;
}
// ///////////////////////////// Optimize a given parameter instance
public static BitSet optimizeToBinary(GOParameters params,
String outputFilePrefix) {
@ -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);
@ -875,7 +918,15 @@ public class OptimizerFactory {
return postProcessDblVec(runnable, new PostProcessParams(steps, sigma,
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);
@ -906,7 +957,15 @@ public class OptimizerFactory {
return postProcessIndVec(runnable, new PostProcessParams(steps, sigma,
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,
true));
}
public static void setTerminator(InterfaceTerminator term) {
OptimizerFactory.term = term;
}
/**
* Return the termination message of the last runnable, if available.
* @return
*/
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());
}
}

6
src/eva2/OptimizerRunnable.java
View File

@ -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;
@ -88,6 +90,10 @@ public class OptimizerRunnable implements Runnable {
this.listener = lsnr;
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;

22
src/eva2/server/go/problems/MatlabEvalMediator.java
View File

@ -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) {

39
src/eva2/server/go/problems/MatlabProblem.java
View File

@ -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;
@ -123,18 +123,35 @@ public class MatlabProblem extends AbstractOptimizationProblem implements Interf
// System.err.println("range: " + BeanInspector.toString(range));
initTemplate();
// res = new ResultArr();
if ((dos == null) && TRACE) {
try {
dos = new PrintStream(new FileOutputStream(outFile));
} catch (FileNotFoundException e) {
e.printStackTrace();
}
}
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(fname==null ? defTestOut : fname));
} catch (FileNotFoundException e) {
e.printStackTrace();
}
}
}
public void setStatsOutput(int verboLevel) {
if ((verboLevel >= 0) && (verboLevel <= 3)) {
verbosityLevel = 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

11
src/eva2/server/go/problems/WaitForEvARunnable.java
View File

@ -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.getIntegerSolution: " + BeanInspector.toString(runnable.getIntegerSolution()));
mp.log("\ngetAllSols best: " + AbstractEAIndividual.getDefaultDataString(runnable.getGOParams().getOptimizer().getAllSolutions().getSolutions().getBestEAIndividual()));
mp.log("runnable.getDoubleSolution: " + BeanInspector.toString(runnable.getDoubleSolution()) + "\n");
mp.log("runnable.getIntegerSolution: " + BeanInspector.toString(runnable.getIntegerSolution()) + "\n");
mp.log("getAllSols best: " + AbstractEAIndividual.getDefaultDataString(runnable.getGOParams().getOptimizer().getAllSolutions().getSolutions().getBestEAIndividual()) + "\n");
mp.log("\n");
// write results back to matlab
mp.exportResultToMatlab(runnable);

12
src/eva2/server/go/strategies/ClusterBasedNichingEA.java
View File

@ -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