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Well, what do you know, major commit.

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Changed the signature of eoMon, eoBin and eoQuadOp to return a bool,
without invalidating fitness. Added a set of invalidators to take over
that job (see for instance eoSGA and eoSGATransform how this can transparantly used)

Derived eoState from eoFunctorStore (for convenience, from a design perspective this may sound wrong)

Added a wrap_op function that does the wrapping for you (see eoOpContainer how this made this functor
exceedingly less hairy). Checked all the tests removed the eoGeneric*Op family (not needed anymore)
and of course changed all the operators to reflect the change (and found a few that didn't
invalidate the fitness, thus really pointing out the advantage of the current approach)
This commit is contained in:
maartenkeijzer 2001-02-14 10:35:26 +00:00
commit 3a9b5a0e7e
30 changed files with 651 additions and 564 deletions
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25
eo/src/es/eoNormalMutation.h
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@ -41,7 +41,7 @@
* to enable dynamic mutations (see eoOenFithMutation below).
*
* As for the bounds, the values are here folded back into the bounds.
* The other possiblity would be to iterate until we fall inside the bounds -
* The other possiblity would be to iterate until we fall inside the bounds -
* but this sometimes takes a long time!!!
*/
@ -55,7 +55,7 @@ template<class EOT> class eoNormalMutation: public eoMonOp<EOT>
* @param _sigma the range for uniform nutation
* @param _p_change the probability to change a given coordinate
*/
eoNormalMutation(double & _sigma, const double& _p_change = 1.0):
eoNormalMutation(double & _sigma, const double& _p_change = 1.0):
sigma(_sigma), bounds(eoDummyVectorNoBounds), p_change(_p_change) {}
/**
@ -64,33 +64,32 @@ template<class EOT> class eoNormalMutation: public eoMonOp<EOT>
* @param _sigma the range for uniform nutation
* @param _p_change the probability to change a given coordinate
*/
eoNormalMutation(eoRealVectorBounds & _bounds,
double & _sigma, const double& _p_change = 1.0):
eoNormalMutation(eoRealVectorBounds & _bounds,
double & _sigma, const double& _p_change = 1.0):
sigma(_sigma), bounds(_bounds), p_change(_p_change) {}
/// The class name.
string className() const { return "eoNormalMutation"; }
/**
* Do it!
* @param _eo The cromosome undergoing the mutation
*/
void operator()(EOT& _eo)
bool operator()(EOT& _eo)
{
bool hasChanged=false;
for (unsigned lieu=0; lieu<_eo.size(); lieu++)
for (unsigned lieu=0; lieu<_eo.size(); lieu++)
{
if (rng.flip(p_change))
if (rng.flip(p_change))
{
_eo[lieu] += sigma*rng.normal();
bounds.foldsInBounds(lieu, _eo[lieu]);
hasChanged = true;
}
}
if (hasChanged)
_eo.invalidate();
return hasChanged;
}
protected:
double & sigma;
private:
@ -98,9 +97,9 @@ private:
double p_change;
};
/** the dynamic version: just say it is updatable -
/** the dynamic version: just say it is updatable -
* and write the update() method!
* here the 1 fifth rule: count the proportion of successful mutations, and
* here the 1 fifth rule: count the proportion of successful mutations, and
* increase sigma if more than threshold (1/5 !)
*/