double computeCoeffs(struct Complex** c, int nTerms, int mid, double stddev)
{
int i, j;
for (i = 0; i < nTerms; i++)
{
for (j = mid; j < nTerms; j++)
{
c[i][j].real = randGauss(0, stddev);
c[i][j].imag = randGauss(0, stddev);
c[2*mid-i][2*mid-j].real = c[i][j].real;
c[2*mid-i][2*mid-j].imag = -c[i][j].imag;
}
}
c[mid][mid].real = randGauss(0, 2*stddev*stddev);
c[mid][mid].imag = 0.0;
}
void NewDev2Population::updatePopulation()
{
//normalize dapVals
int tempI = 0;
double tempD = 0;
double tempD2 = 0;
for(int i = 0 ; i < mDSize ; ++i)
{
tempD += mDAPValues[i];
}
if(tempD == 0) tempD = 1;
for(int i = 0 ; i < mDSize ; ++i)
{
mDAPValues[i] = mDAPValues[i] / tempD; //scale values to sum to 1
}
tempI = mSize - mDSize;//tempI = pool size
mPoolIndices[0] = 0;
for(int i = 1 ; i <= mDSize ; ++i)
{
mPoolIndices[i] = mPoolIndices[i-1] + floor(mDAPValues[i-1] * tempI) + 1;
}
mPoolIndices[mDSize] = mSize;
double* tempPm = new double[mDim];
double* tempMean = new double[mDim];
double* tempVariance = new double[mDim];
for(int i = 0 ; i < mDim ; ++i)
{
tempMean[i] = 0;
for(int j = 0 ; j < mDSize ; ++j)
{
tempMean[i] += mDPositions[(j*mDim) + i];
}
tempMean[i] /= mDSize;
}
for(int i = 0 ; i < mDim ; ++i)
{
tempVariance[i] = 0;
for(int j = 0 ; j < mDSize ; ++j)
{
tempVariance[i] += (mDPositions[(j*mDim) + i] - tempMean[i]) * (mDPositions[(j*mDim) + i] - tempMean[i]);
}
tempVariance[i] = sqrt(tempVariance[i]) / mDSize;
//tempVariance[i] /= mDSize;
}
bool pointsEqual = false;
for(int i = 0 ; i < mDSize ; ++i) //Generate points
{
pointsEqual = (i==mBestPointIndex);
if(!pointsEqual)
{
for(int j = 0 ; j < mDim ; ++j)
{
if(!(mDPositions[(i * mDim) + j] == mDPositions[( mBestPointIndex * mDim ) + j]))
{
pointsEqual = false;
break;
}
}
}
for(int j = 0 ; j < mDim ; ++j)
{
tempPm[j] = (mDPositions[(i * mDim) + j] + mDPositions[( mBestPointIndex * mDim ) + j]) / 2;
tempD = mDPositions[(i * mDim) + j] - mDPositions[( mBestPointIndex * mDim ) + j];
if(pointsEqual)
{
tempD = tempVariance[j];
}
for( int k = mPoolIndices[i] ; k < mPoolIndices[i + 1] ; ++k)
{
mPositions[(k * mDim) + j] = tempPm[j] + (randGauss() * tempD);
if(mPositions[(k * mDim) + j] > mBounds[mDim + j])
{
mPositions[(k * mDim) + j] = mBounds[mDim + j];
}
else if(mPositions[(k * mDim) + j] < mBounds[j])
{
mPositions[(k * mDim) + j] = mBounds[j];
}
}
}
}
for(int i = 0 ; i < mSize ; ++i)// evaluate points
mOptFunc->evaluate(&(mPositions[i * mDim]), mValues[i]);
int bestInd;
for(int i = 0 ; i < mDSize ; ++i) //update points
{
bestInd = -1;
mDAPValues[i] = 0;
for( int k = mPoolIndices[i] ; k < mPoolIndices[i + 1] ; ++k)
{
//mDAPValues[i] += mValues[k];
if(mValues[k] < mDValues[i])
{
if(mValues[k] < mDValues[mBestPointIndex])
mBestPointIndex = i;
bestInd = k;
mDValues[i] = mValues[k];
mDAPValues[i] = mDValues[i];
}
}
//mDAPValues[i] /= (double)(mPoolIndices[i + 1]-mPoolIndices[i]);
if(bestInd != -1)
{
for(int j = 0 ; j < mDim ; ++j)
{
mDPositions[(i*mDim) + j] = mPositions[(bestInd * mDim) + j];
}
}
}
delete[] tempPm;
delete[] tempMean;
delete[] tempVariance;
}
