Skip to content

GitLab

Commit 7bf02f47 authored by kruger's avatar kruger
Browse files

Merge branch 'master' of git+ssh://easea-dev@atia/home/easea-dev/src

parents 55135426 2434f345
Hide whitespace changes
Inline Side-by-side
EaseaLex.l 100755 → 100644
View file @ 7bf02f47
......@@ -26,7 +26,7 @@ Centre de Math
bool genomeSizeValidity=false;
int lineCounter = 0;
// local functions
// local functions
char* selectorDetermination(int nMINIMISE, char* sSELECTOR){
char selectorName[50];
......@@ -75,7 +75,7 @@ Centre de Math
%start COPY_EO_INITIALISER
%start COPY COPY_INITIALISER COPY_CROSSOVER COPY_MUTATOR COPY_EVALUATOR COPY_FINALIZATION_FUNCTION
%start COPY_DISPLAY COPY_USER_FUNCTION COPY_USER_GENERATION PARAMETERS_ANALYSIS GET_PARAMETERS
%start COPY_USER_FUNCTIONS COPY_GENERATION_FUNCTION_BEFORE_REPLACEMENT GET_METHODS COPY_MAKEFILE_OPTION COPY_BOUND_CHECKING_FUNCTION COPY_BEG_GENERATION_FUNCTION COPY_END_GENERATION_FUNCTION
%start COPY_USER_FUNCTIONS COPY_GENERATION_FUNCTION_BEFORE_REPLACEMENT GET_METHODS COPY_MAKEFILE_OPTION COPY_BOUND_CHECKING_FUNCTION COPY_BEG_GENERATION_FUNCTION COPY_END_GENERATION_FUNCTION COPY_INSTEAD_EVAL
// lexical analyser name and class definition
%name CEASEALexer {
......@@ -187,6 +187,15 @@ exponent ([Ee][+-]?[0-9]+)
}
<TEMPLATE_ANALYSIS>"\\INSTEAD_EVAL_FUNCTION" {
//DEBUG_PRT_PRT("insert beg");
yyreset();
yyin = fpGenomeFile;
if (bVERBOSE) printf ("Evaluation population in a single function!!.\n");
BEGIN COPY_INSTEAD_EVAL;
}
<TEMPLATE_ANALYSIS>"\\INSERT_END_GENERATION_FUNCTION" {
//DEBUG_PRT_PRT("insert end");
if (bVERBOSE) printf ("Inserting at the end of each generation function.\n");
......@@ -497,7 +506,7 @@ exponent ([Ee][+-]?[0-9]+)
if (bVERBOSE) printf ("Inserting user functions.\n");
yyreset();
yyin = fpGenomeFile;
lineCounter=1; // switch to .ez file and analyser
lineCounter=2; // switch to .ez file and analyser
BEGIN COPY_USER_FUNCTIONS;
}
<TEMPLATE_ANALYSIS>"\\INSERT_EO_INITIALISER" {
......@@ -531,11 +540,13 @@ exponent ([Ee][+-]?[0-9]+)
<TEMPLATE_ANALYSIS>"\\INSERT_MUTATOR" {
yyreset();
yyin = fpGenomeFile; // switch to .ez file and analyser
lineCounter=1;
BEGIN COPY_MUTATOR;
}
<TEMPLATE_ANALYSIS>"\\INSERT_EVALUATOR" {
yyreset();
yyin = fpGenomeFile; // switch to .ez file and analyser
lineCounter=1;
BEGIN COPY_EVALUATOR;
}
......@@ -543,6 +554,7 @@ exponent ([Ee][+-]?[0-9]+)
yyreset();
yyin = fpGenomeFile; // switch to .ez file and analyser
bWithinCUDA_Evaluator = 1;
lineCounter=1;
BEGIN COPY_EVALUATOR;
}
......@@ -960,6 +972,29 @@ if(OPERATING_SYSTEM=WINDOWS)
}
}
<COPY_INSTEAD_EVAL>"\\Instead"[ \t\n]+"evaluation"[ \t\n]+"function:" {
//DEBUG_PRT_PRT("at each beg");
if( (TARGET==CUDA || TARGET==STD)){
fprintf (fpOutputFile,"{\n");
bFunction=1;
BEGIN COPY_USER_GENERATION;
}
}
<COPY_INSTEAD_EVAL>.|\n {}
<COPY_INSTEAD_EVAL><<EOF>> {
bBeginGenerationFunction=0; // No Generation function was found in the .ez file
if (bVERBOSE) printf("*** No Instead evaluation step function was found. ***\n");
fprintf(fpOutputFile,"\n// No Instead evaluation step function.\n");
rewind(fpGenomeFile);
yyin = fpTemplateFile;
BEGIN TEMPLATE_ANALYSIS;
bNotFinishedYet=1;
}
<COPY_BEG_GENERATION_FUNCTION><<EOF>> {
bBeginGenerationFunction=0; // No Generation function was found in the .ez file
if (bVERBOSE) printf("*** No beginning generation function was found. ***\n");
......@@ -1301,16 +1336,23 @@ if(OPERATING_SYSTEM=WINDOWS)
<COPY_CROSSOVER>\n {lineCounter++;}
<COPY_MUTATOR>"\\GenomeClass::mutator"[ \t\n]*":" {
bWithinMutator=1;
if( bLINE_NUM_EZ_FILE )
fprintf(fpOutputFile,"#line %d \"%s.ez\"\n",lineCounter, sRAW_PROJECT_NAME);
BEGIN COPY_USER_FUNCTION;
return USER_MUTATOR;
}
<COPY_MUTATOR>.|\n {}
<COPY_MUTATOR>. {}
<COPY_MUTATOR>\n {lineCounter++;}
<COPY_EVALUATOR>"\\GenomeClass::evaluator"[ \t\n]*":" {
BEGIN COPY_USER_FUNCTION;
bWithinEvaluator=1;
if( bLINE_NUM_EZ_FILE )
fprintf(fpOutputFile,"#line %d \"%s.ez\"\n",lineCounter, sRAW_PROJECT_NAME);
return USER_EVALUATOR;
}
<COPY_EVALUATOR>.|\n {}
<COPY_EVALUATOR>. {}
<COPY_EVALUATOR>\n {lineCounter++;}
//****************************************
// Basic copy to .cpp file with major changes
......
dev/tgp_regression/tgp_regression.ez 100755 → 100644
View file @ 7bf02f47
......@@ -14,20 +14,20 @@ __________________________________________________________*/
// number of input variables
#define VAR_LEN 4
#define VAR_LEN 1
// Here, some well known parameters for GP.
#define MAX_ARITY 2 // maximum arrity for GP nodes
#define NB_TREES 1 // number of co-evolved trees
#define TREE_DEPTH_MIN 5 // minimum size of (initial) trees (included)
#define TREE_DEPTH_MAX 6 // maximum size of (initial) trees (excluded)
#define GROW_FULL_RATIO 0 // ratio between grow and full construction method
#define TREE_DEPTH_MIN 4 // minimum size of (initial) trees (included)
#define TREE_DEPTH_MAX 5 // maximum size of (initial) trees (excluded)
#define GROW_FULL_RATIO 0.5 // ratio between grow and full construction method
#define DIV_ERR_VALUE 1 // Returned value, in case of non defined input value
#define MAX_XOVER_DEPTH 15
#define MAX_MUTAT_DEPTH 15
#define MAX_XOVER_DEPTH 4
#define MAX_MUTAT_DEPTH 4
float** inputs;
float* outputs;
float** outputs;
int fitnessCasesSetLength;
/** For the sake of simplicity, constant operators become first in the function set
......@@ -46,10 +46,10 @@ int opArrity[] = { 0 , 0 , 0 , 0 , 0 , 2 , 2 , 2
int constLen = 5;
int totalLen = OPCODE_SIZE;
#else
enum OPCODE { OP_ERC, OP_W, OP_X, OP_Y, OP_Z, OP_MUL, OP_ADD, OP_SUB, OP_DIV, OPCODE_SIZE };
const string opCodeName[]={ "erc" , "w" , "x" , "y" , "z" , "*" , "+" , "-" , "/" };
int opArrity[] = { 0 , 0 , 0 , 0 , 0 , 2 , 2 , 2 , 2 };
int constLen = 5;
enum OPCODE { OP_ERC, OP_W, OP_MUL, OP_ADD, OP_SUB, OP_DIV, OPCODE_SIZE };
const string opCodeName[]={ "erc" , "w" , "*" , "+" , "-" , "/" };
int opArrity[] = { 0 , 0 , 2 , 2 , 2 , 2 };
int constLen = 2;
int totalLen = OPCODE_SIZE;
#endif
\end
......@@ -63,7 +63,7 @@ int totalLen = OPCODE_SIZE;
x[m,1], x[m,2], ..., x[m,n], f(x[m])
This function allocates inputs and outputs wrt the size written in the file*/
int load_data(float*** inputs, float** outputs, string filename){
int load_data(float*** inputs, float*** outputs, string filename){
int i;
FILE* file = fopen(filename.c_str(),"r");
int loaded_size;
......@@ -79,7 +79,7 @@ int load_data(float*** inputs, float** outputs, string filename){
assert(match==1);
(*inputs) = (float**)malloc(sizeof(**inputs)*loaded_size);
(*outputs) = (float*)malloc(sizeof(**outputs)*loaded_size);
(*outputs) = (float**)malloc(sizeof(**outputs)*loaded_size);
for( i=0 ; i<loaded_size ; i++){
(*inputs)[i] = (float*)malloc(sizeof(**inputs)*VAR_LEN);
......@@ -87,8 +87,11 @@ int load_data(float*** inputs, float** outputs, string filename){
match = fscanf(file,"%f,",((*inputs)[i])+variable);
assert(match==1);
}
match = fscanf(file,"%f\n",(*outputs)+i);
assert(match==1);
(*outputs)[i] = (float*)malloc(sizeof(**outputs)*NB_TREES);
for( int output_vals = 0 ; output_vals<NB_TREES ; output_vals++ ){
match = fscanf(file,"%f,\n",(*outputs)[i]+output_vals);
assert(match==1);
}
}
fclose(file);
return loaded_size;
......@@ -98,6 +101,8 @@ void free_data(){
for( int i=0 ; i<fitnessCasesSetLength ;i++ )
free( inputs[i] );
for( int i=0 ; i<NB_TREES ; i++ )
free( outputs[i] );
free( inputs );
free( outputs );
}
......@@ -143,7 +148,7 @@ GPNode* construction_method( const int constLen, const int totalLen , const int
node->children[i] = NULL;
if( node->opCode==OP_ERC ){
node->erc_value = random(0,1);
node->erc_value = random(0.,1.);
}
return node;
......@@ -193,7 +198,8 @@ void toDotFile(GPNode* root, const char* baseFileName, int treeId){
}
fprintf(outputFile,"digraph trees {\n");
toDotFile_r( root, outputFile);
if(root)
toDotFile_r( root, outputFile);
fprintf(outputFile,"}\n");
fclose(outputFile);
}
......@@ -241,7 +247,7 @@ double recEvale(GPNode* root, float* inputs){
#ifdef OP_SIN
case OP_SIN: return sin(a);
#endif
#ifdef OP_COS:
#ifdef OP_COS
case OP_COS: return cos(a);
#endif
#ifdef OP_EXP
......@@ -256,9 +262,14 @@ double recEvale(GPNode* root, float* inputs){
switch( root->opCode ){
case OP_ERC: return root->erc_value;
case OP_W: return inputs[0];
#ifdef OP_X
case OP_X: return inputs[1];
#endif
#ifdef OP_Y
case OP_Y: return inputs[2];
#ifdefOP_Z
case OP_Z: return inputs[3];
#endif
default:
fprintf(stderr,"unknown terminal opcode %d\n",root->opCode);
exit(-1);
......@@ -287,16 +298,29 @@ int collectNodesDepth(const int goalDepth, GPNode** collection, int collected, i
}
/**
Pick a node in a tree. It first pick a depth and then, it pick a
node amongst nodes at this depth. It returns the parent node,
and by pointer, the childId of the choosen child.
@arg root : the root node of the tree, amongt which we have to choose the node
@arg chilId : pointer to an allocated int, children position of the choosen node will be stored here
@arg depth : pointer to an allocated int, will contain the choosen depth.
@return : return the address of the parent of the choosen node. Return null if the root node has been choosen
*/
GPNode* selectNode( GPNode* root, int* childId, int* depth){
int xoverDepth = random(0,depthOfTree(root));
(*depth) = xoverDepth;
GPNode** dNodes = new GPNode*[1<<(xoverDepth-1)];
GPNode** dNodes;
int collected;
if(xoverDepth!=0)
if(xoverDepth!=0){
dNodes = new GPNode*[1<<(xoverDepth-1)];
collected = collectNodesDepth(xoverDepth-1,dNodes,0,0,root);
}
else{
return NULL;
}
......@@ -316,9 +340,10 @@ GPNode* selectNode( GPNode* root, int* childId, int* depth){
else i+=dNodes[parentIndexP++]->currentArity;
*childId = reminderP;
cout << "d of x : " << xoverDepth << "/" << depthOfTree(root)<< " n : "<< xoverP << endl;
delete dNodes;
return dNodes[parentIndexP];
//cout << "d of x : " << xoverDepth << "/" << depthOfTree(root)<< " n : "<< xoverP << endl;
GPNode* ret = dNodes[parentIndexP];
delete[] dNodes;
return ret;
}
\end
......@@ -326,9 +351,14 @@ GPNode* selectNode( GPNode* root, int* childId, int* depth){
\Before everything else function:
{
// load data from csv file.
cout<<"Before everything else function called "<<endl;
fitnessCasesSetLength = load_data(&inputs,&outputs,"data.csv");
fitnessCasesSetLength = load_data(&inputs,&outputs,"quadra_reg_data.csv");
cout << "number of point in fitness cases set : " << fitnessCasesSetLength << endl;
// Adding another stopping, as we are minimizing, the goal is 0
CGoalCriterion* gc = new CGoalCriterion(0,true);
EA->stoppingCriteria.push_back(gc);
}
\end
......@@ -339,8 +369,13 @@ GPNode* selectNode( GPNode* root, int* childId, int* depth){
std::ostringstream oss;
oss << "out/indiv-" << i << "-trees" ;
toDotFile( ((IndividualImpl*)population->parents[i])->root[0],oss.str().c_str(),0);
//toDotFile( ((IndividualImpl*)population->parents[i])->root,oss.str().c_str(),1);
}
// not sure that the population is not sorted now. So lets do another time (or check in the code;))
// and dump the best individual in a graphviz file.
population->sortParentPopulation();
toDotFile( ((IndividualImpl*)population->parents[0])->root[0], "best-of-run",0);
free_data();
}
\end
......@@ -357,6 +392,10 @@ GPNode* selectNode( GPNode* root, int* childId, int* depth){
//cout << "At each generation before replacement function called" << endl;
\end
\Instead evaluation function:
cout << "yopyop" << endl;
\end
\User classes :
GPNode {
GPNode* children[MAX_ARITY];
......@@ -392,12 +431,10 @@ GenomeClass {
if( GROW_FULL_RATIO==0 ) full=true;
else full = (id%seg)/(int)(seg*GROW_FULL_RATIO);
cout << seg << " " << currentDepth << " " << full ;
//cout << seg << " " << currentDepth << " " << full ;
for( int i=0 ; i<NB_TREES ; i++ ){
Genome.root[i] = construction_method( constLen, totalLen , 1, currentDepth ,full);
cout << " " << depthOfTree(Genome.root[i]);
}
cout << endl;
}
\end
......@@ -409,160 +446,160 @@ GenomeClass {
It selects depths of cross, then selects which nodes
will be exchanged at those depths.
*/
int depthOfStock, depthOfGraft;
GPNode** d1Nodes = NULL, ** d2Nodes = NULL;
int reminderP1, reminderP2;
int parentIndexP1, parentIndexP2;
do{
int depthP1 = depthOfTree(parent1.root[0]);
int depthP2 = depthOfTree(parent2.root[0]);
int xoverD1 = random(0,depthP1);
int xoverD2 = random(0,depthP2);
int maxNode1 = 1<<(depthP1-1);
int maxNode2 = 1<<(depthP2-1);
if( d1Nodes ) free( d1Nodes );
if( d2Nodes ) free( d2Nodes );
d1Nodes = new GPNode*[maxNode1];
d2Nodes = new GPNode*[maxNode2];
int collected1 = 0;
int collected2 = 0;
if(xoverD1!=0)
collected1 = collectNodesDepth(xoverD1-1,d1Nodes,0,0,child1.root[0]);
else{
d1Nodes[0]=child1.root[0];
collected1=1;
}
if( xoverD2!=0)
collected2 = collectNodesDepth(xoverD2-1,d2Nodes,0,0,parent2.root[0]);
else{
d2Nodes[0]=parent2.root[0];
collected2=1;
}
#if 0
cout << "dp1 : " << depthP1 << " xovd1 : " << xoverD1 << " maxnodeCount1 : " << maxNode1 << " collected1 : "<< collected1 << endl;
cout << "dp2 : " << depthP2 << " xovd2 : " << xoverD2 << " maxnodeCount2 : " << maxNode2 << " collected2 : "<< collected2 << endl;
for( int tree=0 ; tree<NB_TREES ; tree++ ){
int depthOfStock, depthOfGraft;
GPNode** d1Nodes = NULL, ** d2Nodes = NULL;
int reminderP1, reminderP2;
int parentIndexP1, parentIndexP2;
bool graftIsRoot = false;
bool stockIsRoot = false;
do{
int depthP1 = depthOfTree(parent1.root[tree]);
int depthP2 = depthOfTree(parent2.root[tree]);
for( int i=0 ; i<collected1 ; i++ )
printf("%s | ",opCodeName[(int)d1Nodes[i]->opCode].c_str());
printf("\n");
int xoverD1 = random(0,depthP1);
int xoverD2 = random(0,depthP2);
int maxNode1 = 1<<(depthP1-1);
int maxNode2 = 1<<(depthP2-1);
if( d1Nodes ) delete[] d1Nodes;
if( d2Nodes ) delete[] d2Nodes;
for( int i=0 ; i<collected2 ; i++ )
printf("%s | ",opCodeName[(int)d2Nodes[i]->opCode].c_str());
printf("\n");
#endif
d1Nodes = new GPNode*[maxNode1];
d2Nodes = new GPNode*[maxNode2];
graftIsRoot = false;
stockIsRoot = false;
int stockPointCountP1=0;
for( int i=0 ; i<collected1 ; i++ ){
stockPointCountP1+=d1Nodes[i]->currentArity;
}
int collected1 = 0;
int collected2 = 0;
if( xoverD1!=0 )
collected1 = collectNodesDepth(xoverD1-1,d1Nodes,0,0,child1.root[tree]);
else
stockIsRoot = true;
int stockPointCountP2=0;
for( int i=0 ; i<collected2 ; i++ ){
stockPointCountP2+=d2Nodes[i]->currentArity;
}
#if 0
cout << "stock point count parent 1 : " << stockPointCountP1 << endl;
cout << "stock point count parent 2 : " << stockPointCountP2 << endl;
#endif
if( xoverD2!=0 )
collected2 = collectNodesDepth(xoverD2-1,d2Nodes,0,0,parent2.root[tree]);
else
graftIsRoot = true;
int xoverP1 = random(0,stockPointCountP1);
int xoverP2 = random(0,stockPointCountP2);
int stockPointCountP1=0;
for( int i=0 ; i<collected1 ; i++ )
stockPointCountP1+=d1Nodes[i]->currentArity;
int stockPointCountP2=0;
for( int i=0 ; i<collected2 ; i++ )
stockPointCountP2+=d2Nodes[i]->currentArity;
reminderP1 = 0; reminderP2 = 0;
parentIndexP1 = 0; parentIndexP2 = 0;
for( int i=0 ; ; )
if( (i+d1Nodes[parentIndexP1]->currentArity)>xoverP1 ){
reminderP1 = xoverP1-i;
break;
}
else i+=d1Nodes[parentIndexP1++]->currentArity;
for( int i=0 ; ; )
if( (i+d2Nodes[parentIndexP2]->currentArity)>xoverP2 ){
reminderP2 = xoverP2-i;
break;
}
else i+=d2Nodes[parentIndexP2++]->currentArity;
#if 0
cout << "r : " << reminderP1 << " parentIndex : " << parentIndexP1 << " xoverPt1 : " << xoverP1<<endl;
cout << "r : " << reminderP2 << " parentIndex : " << parentIndexP2 << " xoverPt2 : " << xoverP2<<endl;
cout << "xoverPt2 : " << xoverP2 << endl;
int xoverP1 = random(0,stockPointCountP1);
int xoverP2 = random(0,stockPointCountP2);
reminderP1 = 0; reminderP2 = 0;
parentIndexP1 = 0; parentIndexP2 = 0;
if( !stockIsRoot )
for( int i=0 ; ; )
if( (i+(d1Nodes[parentIndexP1]->currentArity))>xoverP1 ){
reminderP1 = xoverP1-i;
break;
}
else i+=d1Nodes[parentIndexP1++]->currentArity;
if( !graftIsRoot )
for( int i=0 ; ; )
if( (i+(d2Nodes[parentIndexP2]->currentArity))>xoverP2 ){
reminderP2 = xoverP2-i;
break;
}
else i+=d2Nodes[parentIndexP2++]->currentArity;
toDotFile( parent1.root[0],"out/xover/p1-o",0);
toDotFile( parent2.root[0],"out/xover/p2-o",0);
#endif
depthOfStock = xoverD1;
if( !graftIsRoot )
depthOfGraft = depthOfTree(d2Nodes[parentIndexP2]->children[reminderP2]);
else
depthOfGraft = depthOfTree(parent2.root[tree]);
}
while(depthOfStock+depthOfGraft>MAX_XOVER_DEPTH);
depthOfStock = xoverD1;
depthOfGraft = depthOfTree(d2Nodes[parentIndexP2]->children[reminderP2]);
GPNode** stockPointPtr = NULL;
GPNode* graftPointPtr = NULL;
//cout << "depth of resulting tree comp : " << depthOfGraft+depthOfStock;
}
while(depthOfStock+depthOfGraft>MAX_XOVER_DEPTH);
delete d1Nodes[parentIndexP1]->children[reminderP1];
d1Nodes[parentIndexP1]->children[reminderP1] = NULL;
#if 0
toDotFile( child1.root[0],"out/xover/p1",0);
#if 1
toDotFile(parent1.root[0],"out/xover/p1-o",tree);
toDotFile(parent2.root[0],"out/xover/p2-o",tree);
#endif
d1Nodes[parentIndexP1]->children[reminderP1] = d2Nodes[parentIndexP2]->children[reminderP2];
#if 0
toDotFile(d2Nodes[parentIndexP2]->children[reminderP2],"out/xover/graft",0);
if( !stockIsRoot ){
delete d1Nodes[parentIndexP1]->children[reminderP1];
d1Nodes[parentIndexP1]->children[reminderP1] = NULL;
stockPointPtr = &d1Nodes[parentIndexP1]->children[reminderP1];
}
else{
delete child1.root[tree];
child1.root[tree] = NULL;
stockPointPtr = &child1.root[tree];
}
#if 1
toDotFile(child1.root[tree],"out/xover/p1",tree);
#endif
d2Nodes[parentIndexP2]->children[reminderP2] = NULL;
#if 0
toDotFile( parent2.root[0],"out/xover/p2",0);
if( !graftIsRoot ){
graftPointPtr = d2Nodes[parentIndexP2]->children[reminderP2];
d2Nodes[parentIndexP2]->children[reminderP2] = NULL;
}
else {
graftPointPtr = parent2.root[tree];
parent2.root[tree] = NULL;
}
toDotFile(d1Nodes[parentIndexP1]->children[reminderP1],"out/xover/stock",0);
toDotFile( child1.root[0],"out/xover/c",0);
#if 1
toDotFile(graftPointPtr,"out/xover/graft",tree);
#endif
//cout << " real : " << depthOfTree(child1.root[0]) << endl;
assert( depthOfStock+depthOfGraft<=depthOfTree(child1.root[0]));
(*stockPointPtr) = graftPointPtr;
#if 1
toDotFile(child1.root[tree],"out/xover/c",tree);
#endif
delete[] d1Nodes;
delete[] d2Nodes;
}
child1.valid=false;
delete[] d1Nodes;
delete[] d2Nodes;
}
\end
\GenomeClass::mutator : // Must return the number of mutations
{
int mutationPointChildId = 0;
int mutationPointDepth = 0;
GPNode* mutationPointParent = selectNode(Genome.root[0], &mutationPointChildId, &mutationPointDepth);
//mutationPointParent = Genome.root[0];
if( mutationPointParent ){
// Cassical mutation
// select a node
for( int tree=0 ; tree<NB_TREES ; tree++ ){
int mutationPointChildId = 0;
int mutationPointDepth = 0;
toDotFile( Genome.root[tree], "out/mutation/p", tree);
GPNode* mutationPointParent = selectNode(Genome.root[tree], &mutationPointChildId, &mutationPointDepth);
cout << "mutation output" << endl;
toDotFile( mutationPointParent->children[mutationPointChildId], "out/mutation/mp", 0);
toDotFile( Genome.root[0], "out/mutation/p", 0);
free( mutationPointParent->children[mutationPointChildId] );
if( !mutationPointParent ){
mutationPointParent = Genome.root[tree];
mutationPointDepth = 0;
}
toDotFile( Genome.root[tree], "out/mutation/p", tree);
delete mutationPointParent->children[mutationPointChildId] ;
mutationPointParent->children[mutationPointChildId] = NULL;
mutationPointParent->children[mutationPointChildId] =
construction_method( constLen, totalLen , 1, MAX_MUTAT_DEPTH-mutationPointDepth ,0);
toDotFile( Genome.root[0], "out/mutation/f", 0);
toDotFile( Genome.root[tree], "out/mutation/f", tree);
}
return 0;
return NB_TREES;
}
\end
......@@ -574,12 +611,15 @@ GenomeClass {
the standardized fitness.
*/
double fitness = 0.;
for( int i=0 ; i<fitnessCasesSetLength ; i++ ){
double evolvedValue = recEvale(Genome.root[0],inputs[i]);
//cout << evolvedValue << ":" << outputs[i] << " ";
fitness += fabs(evolvedValue-outputs[i]);
}
//cout << "->" << fitness <<endl;
double fFit [NB_TREES];
for( int tree=0 ; tree<NB_TREES ; tree++ ){
fFit[tree] = 0.;
for( int i=0 ; i<fitnessCasesSetLength ; i++ ){
double evolvedValue = recEvale(Genome.root[tree],inputs[i]);
fFit[tree] += fabs(evolvedValue-outputs[i][tree]);
}
fitness += fFit[tree];
}
Genome.valid = true;
Genome.fitness = fitness;
return fitness;
......@@ -593,12 +633,12 @@ CPPFLAGS+=
\Default run parameters : // Please let the parameters appear in this order
Number of generations : 1 // NB_GEN
Time limit: 0 // In seconds, 0 to deactivate
Population size : 10 //POP_SIZE
Offspring size : 1 // 40%
Mutation probability : 1 // MUT_PROB
Crossover probability : 1 // XOVER_PROB
Population size : 200 //POP_SIZE
Offspring size : 200 // 40%
Mutation probability : 0.1 // MUT_PROB
Crossover probability : 0.9 // XOVER_PROB