void testMassFit()
{
TFile* file = TFile::Open("plots_btodmunu_TTJets_Filtered.root");
TH1F* correctedBHisto = (TH1F*)file->Get("massBCorrected/massBCorrected_sig");
RooRealVar correctedBMass("correctedBMass", "correctedBMass", 2.0, 10.0);
RooDataHist data("data", "data", correctedBMass, correctedBHisto);
RooRealVar mean1("mean1", "mean1", 5.1, 4.0, 6.0);
RooRealVar sigma1("sigma1", "sigma1", 0.5, 0.1, 1.0);
RooGaussian gaus1("gaus1", "gaus1", correctedBMass, mean1, sigma1);
RooRealVar mean2("mean2", "mean2", 4.8, 3.0, 6.0);
RooRealVar sigma2("sigma2", "sigma2", 0.9, 0.1, 3.5);
RooGaussian gaus2("gaus2", "gaus2", correctedBMass, mean2, sigma2);
RooRealVar fGaus1("fGaus1", "fGaus1", 0.7, 0.0, 1.0);
RooAddPdf model("model", "model", gaus1, gaus2, fGaus1);
model.fitTo(data);
RooPlot* frame = correctedBMass.frame();
data.plotOn(frame);
model.plotOn(frame);
model.paramOn(frame);
frame->Draw();
}
real_t total2 (int i) const { return mean2(i) + fluctuating2(i); }
void BVHAccel::FindBestSplit(std::vector<BVHAccelTreeNode *> &list, unsigned int begin, unsigned int end, float *splitValue, unsigned int *bestAxis) {
if (end - begin == 2) {
// Trivial case with two elements
*splitValue = (list[begin]->bbox.pMax[0] + list[begin]->bbox.pMin[0] +
list[end - 1]->bbox.pMax[0] + list[end - 1]->bbox.pMin[0]) / 2;
*bestAxis = 0;
} else {
// Calculate BBs mean center (times 2)
Point mean2(0, 0, 0), var(0, 0, 0);
for (unsigned int i = begin; i < end; i++)
mean2 += list[i]->bbox.pMax + list[i]->bbox.pMin;
mean2 /= static_cast<float>(end - begin);
// Calculate variance
for (unsigned int i = begin; i < end; i++) {
Vector v = list[i]->bbox.pMax + list[i]->bbox.pMin - mean2;
v.x *= v.x;
v.y *= v.y;
v.z *= v.z;
var += v;
}
// Select axis with more variance
if (var.x > var.y && var.x > var.z)
*bestAxis = 0;
else if (var.y > var.z)
*bestAxis = 1;
else
*bestAxis = 2;
if (costSamples > 1) {
BBox nodeBounds;
for (unsigned int i = begin; i < end; i++)
nodeBounds = Union(nodeBounds, list[i]->bbox);
Vector d = nodeBounds.pMax - nodeBounds.pMin;
const float invTotalSA = 1.f / nodeBounds.SurfaceArea();
// Sample cost for split at some points
float increment = 2 * d[*bestAxis] / (costSamples + 1);
float bestCost = INFINITY;
for (float splitVal = 2 * nodeBounds.pMin[*bestAxis] + increment; splitVal < 2 * nodeBounds.pMax[*bestAxis]; splitVal += increment) {
int nBelow = 0, nAbove = 0;
BBox bbBelow, bbAbove;
for (unsigned int j = begin; j < end; j++) {
if ((list[j]->bbox.pMax[*bestAxis] + list[j]->bbox.pMin[*bestAxis]) < splitVal) {
nBelow++;
bbBelow = Union(bbBelow, list[j]->bbox);
} else {
nAbove++;
bbAbove = Union(bbAbove, list[j]->bbox);
}
}
const float pBelow = bbBelow.SurfaceArea() * invTotalSA;
const float pAbove = bbAbove.SurfaceArea() * invTotalSA;
float eb = (nAbove == 0 || nBelow == 0) ? emptyBonus : 0.f;
float cost = traversalCost + isectCost * (1.f - eb) * (pBelow * nBelow + pAbove * nAbove);
// Update best split if this is lowest cost so far
if (cost < bestCost) {
bestCost = cost;
*splitValue = splitVal;
}
}
} else {
// Split in half around the mean center
*splitValue = mean2[*bestAxis];
}
}
}
real_t total2 () const { return mean2() + fluctuating2(); }