public NetworkPatch CreateAndApplyPatch(int changesPerPatch, int wantedNoOfNodes)
{
NetworkPatch patch = new NetworkPatch();
for (int i = 0; i < changesPerPatch; i++)
{
NetworkMutator mutator;
if (rand_.NextDouble() < addRemoveChance_)
{
mutator = CreateAddRemoveMutator(wantedNoOfNodes);
}
else
{
mutator = CreateTypeChangeMutator();
}
patch.mutators_.Add(mutator);
mutator.Apply();
/**
* NOTE: IMPORTANT: applying is here, because next mutator
* can be generated wrongly if this one is not applied
* (it'd fit for unchanged network, but not for changed one)
*/
}
return patch;
}
public NetworkPatch CreateAndApplyPatch(int changesPerPatch, int wantedNoOfNodes)
{
NetworkPatch patch = new NetworkPatch();
for (int i = 0; i < changesPerPatch; i++)
{
NetworkMutator mutator;
if (rand_.NextDouble() < addRemoveChance_)
{
mutator = CreateAddRemoveMutator(wantedNoOfNodes);
}
else
{
mutator = CreateTypeChangeMutator();
}
patch.mutators_.Add(mutator);
mutator.Apply();
/**
* NOTE: IMPORTANT: applying is here, because next mutator
* can be generated wrongly if this one is not applied
* (it'd fit for unchanged network, but not for changed one)
*/
}
return(patch);
}
private void PerformTeachingSerie(int wantedNoOfNodes, int changesPerPatch, int patchesPerTeachingSerie)
{
// patch --> its error change - lower = better
Dictionary <NetworkPatch, double> patchesEfficiency = new Dictionary <NetworkPatch, double>();
double serieStartError = network_.CalculateTrainingSqrError();
int startNetworkHash = network_.GetHashCode();
while (patchesEfficiency.Count < patchesPerTeachingSerie)
{
#if DEBUG
string graphBeforePatch = network_.PrintNetworkStruct();
#endif
NetworkPatch patch = patchFactory_.CreateAndApplyPatch(changesPerPatch, wantedNoOfNodes);
patchesEfficiency[patch] = network_.CalculateTrainingSqrError() - serieStartError;
#if DEBUG
string graphAfterPatch = network_.PrintNetworkStruct();
#endif
patch.Revert();
#if DEBUG
string graphAfterRevert = network_.PrintNetworkStruct();
double errorAfterNotApplyingPatch = network_.CalculateTrainingSqrError();
if (serieStartError != errorAfterNotApplyingPatch)
{
Logger.Log(this, String.Format(
"REVERT WENT WRONG!\n" +
"<<<<<<<<<<<<GRAPH BEFORE PATCH >>>>>>>>>>\n{0}\n" +
"<<<<<<<<<<<<GRAPH AFTER PATCH >>>>>>>>>>\n{1}\n" +
"<<<<<<<<<<<<GRAPH AFTER REVERT >>>>>>>>>>\n{2}\n",
graphBeforePatch,
graphAfterPatch,
graphAfterRevert),
10);
throw new ApplicationException("revert went wrong");
}
#endif
}
//NOTE: what is interesting double.NaN is lowest possible number AND double.NaN != double.NaN //WTF??
double bestChange = patchesEfficiency.Min(x => double.IsNaN(x.Value) ? double.PositiveInfinity : x.Value);
Logger.Log(this, String.Format("best change {0}", bestChange));
if (bestChange <= 0.0d && //IMPORTANT: for now only
!double.IsInfinity(bestChange) &&
!double.IsNaN(bestChange))
{
Logger.Log(this, "applying patch!");
NetworkPatch bestPatch = patchesEfficiency.First(patch => patch.Value == bestChange).Key;
bestPatch.Apply();
double errorAfterApplyingPatch = network_.CalculateTrainingSqrError();
Logger.Log(this, String.Format("error after appplying patch {0}", errorAfterApplyingPatch));
//#if DEBUG
if (bestChange < -1E-2)
{
PrintGraphVisualization(network_);
}
//#endif
double delta = 1E-4;
if (serieStartError + bestChange - errorAfterApplyingPatch > delta)
{
throw new ApplicationException("something went rly bad");
}
}
else
{
Logger.Log(this, "NOT applying patch");
}
}