* whitespace cleanup
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195 changed files with 1763 additions and 1873 deletions
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@ -5,7 +5,7 @@ However, see there first for the creation of new projects.
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========================================================================
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This directory contains sample files that should make it easy to
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create an EO algorithm to evolve any type of structure
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create an EO algorithm to evolve any type of structure
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(EO comes with two examples, bitstrings and vector of real variables,
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so you'll need this as soon as you want to evolve something else).
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@ -13,7 +13,7 @@ At the moment, only algorithms involving a scalar fitness (double)
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are implemented (see test dir for Pareto optimization of multiple-
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objective fitness - or be patient :-)
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This file will help you to build the same algorithm than the ones
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This file will help you to build the same algorithm than the ones
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in the Lesson4 of the tutorial, but with YOUR genotype instead of
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bitstrings or vector<double>. More details in Lesson5 of the tutorial.
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@ -30,7 +30,7 @@ mutation and the computation of its fitness.
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The helper script * create.sh * will create for you the files you need
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from the samples in tutorial/Templates dir, and all you'll have to do
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is to include the actual code where indicated in those files (between
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keywords START and END).
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keywords START and END).
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First, let's choose a name: let's call the new EO class eoAppli.
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All newly created classes will be named eoAppliXXX (in the file
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@ -41,24 +41,24 @@ eoAppliXXX)
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2- create the directory for your application (let's assume you call it
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APPLICATION): type in
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mkdir APPLICATION
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mkdir APPLICATION
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3- go to the Templates dir
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3- go to the Templates dir
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cd Templates
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cd Templates
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and run the helper script create.sh with the following arguments
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and run the helper script create.sh with the following arguments
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./create.sh Appli ../APPLICATION
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./create.sh Appli ../APPLICATION
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4- cd to the APPLICATION dir (cd ../APPLICATION).
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4- cd to the APPLICATION dir (cd ../APPLICATION).
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You should see there the following files:
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AppliEA.cpp the main file, includes all other, to be compiled
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Makefile with default target eoAppliEA
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eoAppli.h class eoAppli<FitT>, FitT = template fitness
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eoAppliEvalFunc.h class for the computation of fotness
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eoAppliInit.h class for genotype initlialization
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eoAppliMutation.h class for mutation
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eoAppliMutation.h class for mutation
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eoAppliQuadCrossover.h class for (quadratic) crossover
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make_genotype_Appli.h helper function that create the initializer
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make_op_Appli.h helper function that creates the variatin operators
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@ -78,11 +78,11 @@ HINT: look for keywords START and END and modify code in between.
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6- Compile eoAppliEA.cpp. If your APPLICATION dir is in the tutorial
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dir, you don't need to modify Makefile. Just type in
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% make
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% make
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7- Run the resulting program:
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% eoAppliEA
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% eoAppliEA
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The default output is one line per generation with the generation
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number, the number of evaluations performed, the best and average
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@ -93,7 +93,7 @@ The algorithm stops by default after 100 generations.
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e.g. eoAppliEA.param, edit eoAppliEA.param (uncomment the lines you
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want to become active), and run
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% eoAppliEA @eoAppliEA.param
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% eoAppliEA @eoAppliEA.param
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(see the Lesson 5 of the tutorial for more details now).
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@ -121,19 +121,19 @@ To add another operator, you have to create another class by mimicking
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what has been done for the first operator.
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For instance, let's suppose you want to create another mutation.
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* duplicate the code for eoAppliMutation class
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* duplicate the code for eoAppliMutation class
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* in the second version, change the class name (eoAppliMutation) into
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another name (let's say eoAppliBetterMutation) - you must change the
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name in the class declaration, in the constructor and in the
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className() method.
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* in the new eoAppliBetterMutation class, change the code for the
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operator() - and eventually the code for the constructor.
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* in the make_op_Appli.h file, in the mutation section, uncomment the
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lines
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* in the make_op_Appli.h file, in the mutation section, uncomment the
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lines
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mut = new eoAppliSecondMutation<Indi>(varType _anyVariable);
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_state.storeFunctor(mut);
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double mut2Rate = _parser.createParam(1.0, "mut2Rate", "Relative rate for mutation 2", '2', "Variation Operators").value();
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propMutation.add(*mut, mut2Rate);
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double mut2Rate = _parser.createParam(1.0, "mut2Rate", "Relative rate for mutation 2", '2', "Variation Operators").value();
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propMutation.add(*mut, mut2Rate);
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and change the name of the class from eoAppliSecondMutation to your
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name eoAppliBetterMutation (you can also change the keyword from
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