// Calculate the RDF normalisation for the Box
bool Box::calculateRDFNormalisation(ProcessPool& procPool, Data2D& boxNorm, double rdfRange, double rdfBinWidth, int nPoints) const
{
// Setup array - we will use a nominal bin width of 0.1 Angstroms and then interpolate to the rdfBinWidth afterwards
const double binWidth = 0.1;
const double rBinWidth = 1.0/binWidth;
int bin, nBins = rdfRange / binWidth;
Data2D normData;
normData.initialise(nBins);
Array<double>& y = normData.arrayY();
for (int n=0; n<nBins; ++n) normData.arrayX()[n] = (n+0.5)*binWidth;
Vec3<double> centre = axes_*Vec3<double>(0.5,0.5,0.5);
// Divide points over processes
const int nPointsPerProcess = nPoints / procPool.nProcesses();
Messenger::print("--> Number of insertion points (per process) is %i\n", nPointsPerProcess);
y = 0.0;
for (int n=0; n<nPointsPerProcess; ++n)
{
bin = (randomCoordinate() - centre).magnitude() * rBinWidth;
if (bin < nBins) y[bin] += 1.0;
}
if (!procPool.allSum(y.array(), nBins)) return false;
// Normalise histogram data, and scale by volume and binWidth ratio
y /= double(nPointsPerProcess*procPool.nProcesses());
y *= volume_ * (rdfBinWidth / binWidth);
normData.interpolate();
// Write histogram data for random distribution
if (procPool.isMaster()) normData.save("duq.box.random");
// Now we have the interpolated data, create the proper interpolated data
nBins = rdfRange/rdfBinWidth;
boxNorm.clear();
// Rescale against expected volume for spherical shells
double shellVolume, r = 0.0, maxHalf = inscribedSphereRadius(), x = 0.5*rdfBinWidth;
for (int n=0; n<nBins; ++n)
{
// We know that up to the maximum (orthogonal) half-cell width the normalisation should be exactly 1.0...
if (x < maxHalf) boxNorm.addPoint(x, 1.0);
else
{
shellVolume = (4.0/3.0)*PI*(pow(r+rdfBinWidth,3.0) - pow(r,3.0));
boxNorm.addPoint(x, shellVolume / normData.interpolated(x));
// boxNorm[n] = normData.interpolated(r);
}
r += rdfBinWidth;
x += rdfBinWidth;
}
// Interpolate normalisation array
boxNorm.interpolate();
// Write final box normalisation file
if (procPool.isMaster()) boxNorm.save("duq.box.norm");
return true;
}
/*!
* \brief Smooth data
*/
void Data2D::smooth(int avgSize, int skip)
{
// First, create a new dataset using Y-averages of the current data
Data2D avg;
double y;
int n, m, i = avgSize/2;
for (n=i; n < x_.nItems()-i; n += (1+skip))
{
y = 0.0;
for (m=n-i; m <= n+i; ++m) y += y_[m];
y /= avgSize;
avg.addPoint(x_[n], y);
}
avg.interpolate();
// Now go through old data, setting new Y values from the interpolation
for (n=0; n<x_.nItems(); ++n) y_[n] = avg.interpolated(x_[n]);
}
/*!
* \brief Subtract interpolated data
*/
void Data2D::subtractInterpolated(Data2D& source)
{
for (int n=0; n<x_.nItems(); ++n) addY(n, -source.interpolated(x_.value(n)));
}
