Changeset 168 for cpp/frams/genetics/oper_fx.cpp

Timestamp:

03/11/14 14:45:29 (11 years ago)

Author:

sz

Message:

reformatting

File:

• cpp/frams/genetics/oper_fx.cpp (modified) (4 diffs)

cpp/frams/genetics/oper_fx.cpp ¶

@@ -9 +9 @@
 #include <frams/util/rndutil.h>
 
-static double distrib_force[]=   // for '!'
-{
-3,                 // distribution 0 -__/ +1
-0.001, 0.2,        // "slow" neurons
-0.001, 1,
-    1, 1,          // "fast" neurons
+static double distrib_force[] =   // for '!'
+{
+        3,             // distribution 0 -__/ +1
+        0.001, 0.2,    // "slow" neurons
+        0.001, 1,
+        1, 1,          // "fast" neurons
 };
-static double distrib_inertia[]=  // for '='
-{
-2,                 // distribution 0 |..- +1
-  0, 0,            // "fast" neurons
-0.7, 0.98,
+static double distrib_inertia[] =  // for '='
+{
+        2,             // distribution 0 |..- +1
+        0, 0,          // "fast" neurons
+        0.7, 0.98,
 };
-static double distrib_sigmo[]=  // for '/'
-{
-5,                 // distribution -999 -..-^-..- +999
--999, -999,        //"perceptron"
- 999, 999,
-  -5, -1,          // nonlinear
-   1, 5,
-  -1, 1,           // ~linear
+static double distrib_sigmo[] =  // for '/'
+{
+        5,             // distribution -999 -..-^-..- +999
+        -999, -999,    //"perceptron"
+        999, 999,
+        -5, -1,        // nonlinear
+        1, 5,
+        -1, 1,         // ~linear
 };
 
 
-int GenoOperators::roulette(const double *probtab,const int count)
-{
-   double sum=0;
-   int i;
-   for (i=0;i<count;i++) sum+=probtab[i];
-   double sel=rnd01*sum;
-   for (sum=0,i=0;i<count;i++) {sum+=probtab[i]; if (sel<sum) return i;}
-   return -1;
-}
-
-bool GenoOperators::getMinMaxDef(ParamInterface *p,int i,double &mn,double &mx,double &def)
-{
-   mn=mx=def=0;
-   int defined=0;
-   if (p->type(i)[0]=='f')
-   {
-      double _mn=0,_mx=1,_def=0.5;
-      defined=p->getMinMax(i,_mn,_mx,_def);
-      if (defined==1) _mx=_mn+1.0;
-      if (_mx<_mn && defined==3) _mn=_mx=_def; //only default was defined, let's assume min=max=default
-      if (defined<3) _def=(_mn+_mx)/2.0;
-      mn=_mn; mx=_mx; def=_def;
-   }
-   if (p->type(i)[0]=='d')
-   {
-      long _mn=0,_mx=1,_def=0;
-      defined=p->getMinMax(i,_mn,_mx,_def);
-      if (defined==1) _mx=_mn+1;
-      if (_mx<_mn && defined==3) _mn=_mx=_def; //only default was defined, let's assume min=max=default
-      if (defined<3) _def=(_mn+_mx)/2;
-      mn=_mn; mx=_mx; def=_def;
-   }
-   return defined==3;
+int GenoOperators::roulette(const double *probtab, const int count)
+{
+        double sum = 0;
+        int i;
+        for (i = 0; i < count; i++) sum += probtab[i];
+        double sel = rnd01*sum;
+        for (sum = 0, i = 0; i < count; i++) { sum += probtab[i]; if (sel < sum) return i; }
+        return -1;
+}
+
+bool GenoOperators::getMinMaxDef(ParamInterface *p, int i, double &mn, double &mx, double &def)
+{
+        mn = mx = def = 0;
+        int defined = 0;
+        if (p->type(i)[0] == 'f')
+        {
+                double _mn = 0, _mx = 1, _def = 0.5;
+                defined = p->getMinMax(i, _mn, _mx, _def);
+                if (defined == 1) _mx = _mn + 1.0;
+                if (_mx < _mn && defined == 3) _mn = _mx = _def; //only default was defined, let's assume min=max=default
+                if (defined < 3) _def = (_mn + _mx) / 2.0;
+                mn = _mn; mx = _mx; def = _def;
+        }
+        if (p->type(i)[0] == 'd')
+        {
+                long _mn = 0, _mx = 1, _def = 0;
+                defined = p->getMinMax(i, _mn, _mx, _def);
+                if (defined == 1) _mx = _mn + 1;
+                if (_mx < _mn && defined == 3) _mn = _mx = _def; //only default was defined, let's assume min=max=default
+                if (defined < 3) _def = (_mn + _mx) / 2;
+                mn = _mn; mx = _mx; def = _def;
+        }
+        return defined == 3;
 }
 
 int GenoOperators::selectRandomProperty(Neuro* n)
 {
-   int neuext=n->extraProperties().getPropCount(),
-       neucls=n->getClass()==NULL?0:n->getClass()->getProperties().getPropCount();
-   if (neuext+neucls==0) return -1; //no properties in this neuron
-   int index=randomN(neuext+neucls);
-   if (index>=neuext) index=index-neuext+100;
-   return index;
-}
-
-double GenoOperators::mutateNeuProperty(double current,Neuro *n,int i)
-{
-   if (i==-1) return mutateCreepNoLimit('f',current,-10,10); //i==-1: mutating weight of neural connection
-   Param p;
-   if (i>=100) {i-=100; p=n->getClass()->getProperties();}
-      else p=n->extraProperties();
-   double newval=current;
-   /*bool ok=*/getMutatedProperty(p,i,current,newval);
-   return newval;
-}
-
-bool GenoOperators::mutatePropertyNaive(ParamInterface &p,int i)
-{
-   double mn,mx,df;
-   if (p.type(i)[0]!='f' && p.type(i)[0]!='d') return false; //don't know how to mutate
-   getMinMaxDef(&p,i,mn,mx,df);
-
-   ExtValue ev;
-   p.get(i,ev);
-   ev.setDouble(mutateCreep(p.type(i)[0],ev.getDouble(),mn,mx));
-   p.set(i,ev);
-   return true;
-}
-
-bool GenoOperators::mutateProperty(ParamInterface &p,int i)
-{
-   double newval;
-   ExtValue ev;
-   p.get(i,ev);
-   bool ok=getMutatedProperty(p,i,ev.getDouble(),newval);
-   if (ok) {ev.setDouble(newval); p.set(i,ev);}
-   return ok;
-}
-
-bool GenoOperators::getMutatedProperty(ParamInterface &p,int i,double oldval,double &newval)
-{
-   newval=0;
-   if (p.type(i)[0]!='f' && p.type(i)[0]!='d') return false; //don't know how to mutate
-   const char *n=p.id(i),*na=p.name(i);
-     if (strcmp(n,"si")==0 && strcmp(na,"Sigmoid")==0) newval=CustomRnd(distrib_sigmo); else
-     if (strcmp(n,"in")==0 && strcmp(na,"Inertia")==0) newval=CustomRnd(distrib_inertia); else
-     if (strcmp(n,"fo")==0 && strcmp(na,"Force")==0) newval=CustomRnd(distrib_force); else
-     {
-       double mn,mx,df;
-       getMinMaxDef(&p,i,mn,mx,df);
-       newval=mutateCreep(p.type(i)[0],oldval,mn,mx);
-     }
-   return true;
-}
-
-double GenoOperators::mutateCreepNoLimit(char type,double current,double mn,double mx)
-{
-   double result=RndGen.Gauss(current,(mx-mn)/2/5); // /halfinterval, 5 times narrower
-   if (type=='d') {result=int(result+0.5); if (result==current) result+=randomN(2)*2-1;}
-    else result=floor(result*1000+0.5)/1000.0; //round
-   return result;
+        int neuext = n->extraProperties().getPropCount(),
+                neucls = n->getClass() == NULL ? 0 : n->getClass()->getProperties().getPropCount();
+        if (neuext + neucls == 0) return -1; //no properties in this neuron
+        int index = randomN(neuext + neucls);
+        if (index >= neuext) index = index - neuext + 100;
+        return index;
+}
+
+double GenoOperators::mutateNeuProperty(double current, Neuro *n, int i)
+{
+        if (i == -1) return mutateCreepNoLimit('f', current, -10, 10); //i==-1: mutating weight of neural connection
+        Param p;
+        if (i >= 100) { i -= 100; p = n->getClass()->getProperties(); }
+        else p = n->extraProperties();
+        double newval = current;
+        /*bool ok=*/getMutatedProperty(p, i, current, newval);
+        return newval;
+}
+
+bool GenoOperators::mutatePropertyNaive(ParamInterface &p, int i)
+{
+        double mn, mx, df;
+        if (p.type(i)[0] != 'f' && p.type(i)[0] != 'd') return false; //don't know how to mutate
+        getMinMaxDef(&p, i, mn, mx, df);
+
+        ExtValue ev;
+        p.get(i, ev);
+        ev.setDouble(mutateCreep(p.type(i)[0], ev.getDouble(), mn, mx));
+        p.set(i, ev);
+        return true;
+}
+
+bool GenoOperators::mutateProperty(ParamInterface &p, int i)
+{
+        double newval;
+        ExtValue ev;
+        p.get(i, ev);
+        bool ok = getMutatedProperty(p, i, ev.getDouble(), newval);
+        if (ok) { ev.setDouble(newval); p.set(i, ev); }
+        return ok;
+}
+
+bool GenoOperators::getMutatedProperty(ParamInterface &p, int i, double oldval, double &newval)
+{
+        newval = 0;
+        if (p.type(i)[0] != 'f' && p.type(i)[0] != 'd') return false; //don't know how to mutate
+        const char *n = p.id(i), *na = p.name(i);
+        if (strcmp(n, "si") == 0 && strcmp(na, "Sigmoid") == 0) newval = CustomRnd(distrib_sigmo); else
+                if (strcmp(n, "in") == 0 && strcmp(na, "Inertia") == 0) newval = CustomRnd(distrib_inertia); else
+                        if (strcmp(n, "fo") == 0 && strcmp(na, "Force") == 0) newval = CustomRnd(distrib_force); else
+                        {
+                                double mn, mx, df;
+                                getMinMaxDef(&p, i, mn, mx, df);
+                                newval = mutateCreep(p.type(i)[0], oldval, mn, mx);
+                        }
+        return true;
+}
+
+double GenoOperators::mutateCreepNoLimit(char type, double current, double mn, double mx)
+{
+        double result = RndGen.Gauss(current, (mx - mn) / 2 / 5); // /halfinterval, 5 times narrower
+        if (type == 'd') { result = int(result + 0.5); if (result == current) result += randomN(2) * 2 - 1; }
+        else result = floor(result * 1000 + 0.5) / 1000.0; //round
+        return result;
 }
 
@@ -180 +180 @@
 {
         SListTempl<NeuroClass*> active;
-   for(int i=0;i<Neuro::getClassCount();i++)
-      if (Neuro::getClass(i)->genactive) active+=Neuro::getClass(i);
-   if (!active==0) return NULL; else return active(randomN(!active));
+        for (int i = 0; i < Neuro::getClassCount(); i++)
+                if (Neuro::getClass(i)->genactive) active += Neuro::getClass(i);
+        if (!active == 0) return NULL; else return active(randomN(!active));
 }
 
 NeuroClass* GenoOperators::parseNeuroClass(char*& s)
 {
-   int len=strlen(s);
-   int Len=0;
-   NeuroClass *I=NULL;
-   for(int i=0;i<Neuro::getClassCount();i++)
-   {
-      const char *n=Neuro::getClass(i)->name;
-      int l=strlen(n);
-      if (len>=l && l>Len && (strncmp(s,n,l)==0)) {I=Neuro::getClass(i); Len=l;}
-   }
-   s+=Len;
-   return I;
-}
-
-Neuro* GenoOperators::findNeuro(const Model *m,const NeuroClass *nc)
-{
-  if (!m) return NULL;
-  for(int i=0;i<m->getNeuroCount();i++)
-     if (m->getNeuro(i)->getClass()==nc) return m->getNeuro(i);
-  return NULL; //neuron of class 'nc' was not found
-}
-
-int GenoOperators::neuroClassProp(char*& s,NeuroClass *nc,bool also_v1_N_props)
-{
-   int len=strlen(s);
-   int Len=0,I=-1;
-   if (nc)
-   {
-      Param p=nc->getProperties();
-      for(int i=0;i<p.getPropCount();i++)
-      {
-         const char *n=p.id(i);
-         int l=strlen(n);
-         if (len>=l && l>Len && (strncmp(s,n,l)==0)) {I=100+i; Len=l;}
-         if (also_v1_N_props) //recognize old properties symbols /=!
-         {
-            if (strcmp(n,"si")==0) n="/"; else
-            if (strcmp(n,"in")==0) n="="; else
-            if (strcmp(n,"fo")==0) n="!";
-            l=strlen(n);
-            if (len>=l && l>Len && (strncmp(s,n,l)==0)) {I=100+i; Len=l;}
-         }
-      }
-   }
-   Neuro n;
-   Param p=n.extraProperties();
-   for(int i=0;i<p.getPropCount();i++)
-   {
-      const char *n=p.id(i);
-      int l=strlen(n);
-      if (len>=l && l>Len && (strncmp(s,n,l)==0)) {I=i; Len=l;}
-   }
-   s+=Len;
-   return I;
+        int len = strlen(s);
+        int Len = 0;
+        NeuroClass *I = NULL;
+        for (int i = 0; i<Neuro::getClassCount(); i++)
+        {
+                const char *n = Neuro::getClass(i)->name;
+                int l = strlen(n);
+                if (len >= l && l>Len && (strncmp(s, n, l) == 0)) { I = Neuro::getClass(i); Len = l; }
+        }
+        s += Len;
+        return I;
+}
+
+Neuro* GenoOperators::findNeuro(const Model *m, const NeuroClass *nc)
+{
+        if (!m) return NULL;
+        for (int i = 0; i < m->getNeuroCount(); i++)
+                if (m->getNeuro(i)->getClass() == nc) return m->getNeuro(i);
+        return NULL; //neuron of class 'nc' was not found
+}
+
+int GenoOperators::neuroClassProp(char*& s, NeuroClass *nc, bool also_v1_N_props)
+{
+        int len = strlen(s);
+        int Len = 0, I = -1;
+        if (nc)
+        {
+                Param p = nc->getProperties();
+                for (int i = 0; i<p.getPropCount(); i++)
+                {
+                        const char *n = p.id(i);
+                        int l = strlen(n);
+                        if (len >= l && l>Len && (strncmp(s, n, l) == 0)) { I = 100 + i; Len = l; }
+                        if (also_v1_N_props) //recognize old properties symbols /=!
+                        {
+                                if (strcmp(n, "si") == 0) n = "/"; else
+                                        if (strcmp(n, "in") == 0) n = "="; else
+                                                if (strcmp(n, "fo") == 0) n = "!";
+                                l = strlen(n);
+                                if (len >= l && l > Len && (strncmp(s, n, l) == 0)) { I = 100 + i; Len = l; }
+                        }
+                }
+        }
+        Neuro n;
+        Param p = n.extraProperties();
+        for (int i = 0; i<p.getPropCount(); i++)
+        {
+                const char *n = p.id(i);
+                int l = strlen(n);
+                if (len >= l && l>Len && (strncmp(s, n, l) == 0)) { I = i; Len = l; }
+        }
+        s += Len;
+        return I;
 }
 
 bool GenoOperators::isWS(const char c)
-{return c==' ' || c=='\n' || c=='\t' || c=='\r';}
+{
+        return c == ' ' || c == '\n' || c == '\t' || c == '\r';
+}
 
 void GenoOperators::skipWS(char *&s)
 {
-        if (s==NULL)
+        if (s == NULL)
                 FramMessage("GenoOperators", "skipWS", "NULL reference!", FMLV_WARN);
         else
@@ -253 +255 @@
 }
 
-bool GenoOperators::areAlike(char *g1,char *g2)
+bool GenoOperators::areAlike(char *g1, char *g2)
 {
         while (*g1 || *g2)
@@ -260 +262 @@
                 skipWS(g2);
                 if (*g1 != *g2) return false; //when difference
-      if (!*g1 && !*g2) break; //both end
-      g1++;
-      g2++;
+                if (!*g1 && !*g2) break; //both end
+                g1++;
+                g2++;
         }
         return true; //equal
 }
 
-char* GenoOperators::strchrn0(const char *str,char ch)
-{ return ch==0?NULL:strchr((char*)str,ch); }
+char* GenoOperators::strchrn0(const char *str, char ch)
+{
+        return ch == 0 ? NULL : strchr((char*)str, ch);
+}
 
 bool GenoOperators::isNeuroClassName(const char firstchar)
 {
-   return isupper(firstchar) || firstchar=='|' || firstchar=='@' || firstchar=='*';
-}
-
+        return isupper(firstchar) || firstchar == '|' || firstchar == '@' || firstchar == '*';
+}
+