def __init__(self, params):
# https://github.com/rmanzoni/triggertools/blob/master/objects/FitFunctions.py#L153
alpha = params['alpha']
sigma = params['sigma']
norm = params['norm']
m0 = params['m_{0}']
n = params['n']
sqrtPi2 = sqrt(pi / 2)
sqrt2 = sqrt(2.)
absSig = abs(sigma)
absAlpha = abs(alpha / absSig)
a = (n / absAlpha)**n * TMath.Exp(-0.5 * absAlpha * absAlpha)
b = absAlpha - n / absAlpha
arg = absAlpha / sqrt2
erf = 1 if arg > 5. else -1 if arg < -5. else TMath.Erf(arg)
leftArea = (1. + erf) * sqrtPi2
rightArea = (a * 1. / (absAlpha - b)**(n - 1)) / (n - 1)
area = leftArea + rightArea
self.norm = norm
self.alpha = alpha
self.sigma = sigma
self.m0 = m0
self.nm1 = n - 1
self.absAlpha = absAlpha
self.b = b
self.sqrt2 = sqrt2
self.norm1 = norm * sqrtPi2 / area
self.norm2 = norm * a / (1 - n) / area
self.sigma1 = absSig * alpha / abs(alpha)
self.A = norm * leftArea / area - self.norm2 / (absAlpha - b)**self.nm1
def eval(self, x):
t = (x - self.m0) / self.sigma1
if t <= self.absAlpha:
arg = t / self.sqrt2
erf = 1 if arg > 5. else -1 if arg < -5. else TMath.Erf(arg)
return self.norm1 * (1 + erf)
else:
return self.A + self.norm2 / (t - self.b)**self.nm1
def err_func(p0, p1, p2, p3, p4, x):
return p2 + p3 * TMath.Erf((p4 * x - p1) / p0)
def normCDF(x, par):
mu = par[0]
sigma = par[1]
return 0.5 * (1.0 + TMath.Erf((x[0] - mu) / (math.sqrt(2.0) * sigma)))
def normCDF(x, par):
return (0.5 * par[2] * (1.0 + TMath.Erf((x[0] - par[0]) / (math.sqrt(2.0) * par[1]))) + par[3])
c1 = canvas("large")
F = F1 = Frame("200 PU t#bar{t}", "PU", 0., 320., "# reconstructed vertices", 0., 160)
F1.add(hreal3d, "fullcircle", color=1, label="3d matched")
F1.add(hreal4d, "fullcircle", color=2, label="4d matched")
#F1.add(hsplit3d, "fullcircle", label="3d", add_to_legend = False)
#F1.add(hsplit4d, "fullcircle", label="4d")
#F1.add(hother3d, "fullcircle", label="3d")
#F1.add(hother4d, "fullcircle", label="4d")
F1.add(hfake4d, "opencircle", color=2, label="4d fake")
F1.add(hfake3d, "opencircle", color=1, label="3d fake")
if True:
sigmaz=4.26 # beamspot
dzeff = 0.018
alpha=TMath.Erf(dzeff/sigmaz/2.)
epsilon = 0.70
print alpha
#lf3d = TF1("f","x*%f-0.5*%f*x*x"%(epsilon, epsilon**2*alpha),0., 300.)
lf3d = TF1("f","x*[0]-0.5*[1]*x*x",0., 300.)
lf3d.SetParameter(0, epsilon)
lf3d.SetParameter(1, epsilon**2*alpha)
lf3d.SetLineColor(1)
lf3d.SetLineWidth(1)
lf3d.SetLineStyle(2)
hreal3d.Fit(lf3d, "")
#lf3d.Draw("same")
eff3d_200 = lf3d.GetParameter(0) -0.5 * lf3d.GetParameter(1)*200
dzeff = 0.0185
def fitFuncErf(xVal, par):
return par[3]+par[0]*(1.+TMath.Erf((xVal[0]-par[1])/par[2]/TMath.Sqrt(2.)))
