def fitBVoltage(bdata, name):
"""Fit ramp for b-field
Arguments:
bdata -- data
name -- filename
"""
# make canvas and graphs
c = TCanvas("fitBV_%s" % name, "", 1280, 720)
g = bdata.makeGraph("gBV_%s" % name, "Zeit t / s", "Spannung U / V")
prepareGraph(g)
g.Draw("AP")
g.Draw("PX") # set points in foreground, errors in background
# fit linear ramp, start and end value of x-axis (time) are obtained by getXStart and getXend
xmin = getXStart(bdata, bdata.getLength() / 10, 0.25) + 0.1
xmax = getXEnd(bdata, bdata.getLength() / 10, 0.25) - 0.1
fit = Fitter("fitBV_%s" % name, "pol1(0)")
fit.setParam(0, "a", 0)
fit.setParam(1, "b", -2.0 / 3)
fit.fit(g, xmin, xmax, "M")
fit.saveData("../calc/fitBV_%s.txt" % name, "w")
# draw legend
l = TLegend(0.55, 0.6, 0.85, 0.85)
l.SetTextSize(0.03)
l.AddEntry(g, "Messdaten", "p")
l.AddEntry(fit.function, "Fit mit U(t) = a + b*t", "l")
fit.addParamsToLegend(
l, [("%.4f", "%.4f"), ("%.4f", "%.4f")], chisquareformat="%.2f", advancedchi=True, units=["U", "U/s"]
)
l.Draw()
# print canvas to file
c.Update()
c.Print("../img/fitBV_%s.pdf" % name, "pdf")
return fit.function
def fitLorentzPeak(name, phi, T):
"""fit lorentz peak
Arguments:
name -- filename
phi -- angle
T -- temperature
"""
# read data
data = HanleData.fromPath("../data/messungen/%s.tab" % name, 1)
data.setYErrorFunc(lambda x: np.sqrt((0.01 * x) ** 2 + data.points[0][3] ** 2)) # bin error and relative error
bdata = HanleData.fromPath("../data/messungen/%s.tab" % name, 2)
# convert time to B-field and show only points with -0.2mT < x < 0.2mT
data.convertTimeToB(fitBVoltage(bdata, name))
data.filterX(-0.2, 0.2)
# make canvas + graph
canvas = TCanvas("c_%s" % name, "", 1280, 720)
g = data.makeGraph("g_%s" % name, "Magnetfeld B / T", "Intensit#ddot{a}t I / V")
prepareGraph(g)
g.Draw("AP")
g.Draw("PX") # redraw points without errors to set points in front of errors
# get initial fit parameters
gJ = 1.4838
muB = 9.27400968e-24
hbar = 1.05457126e-34
a = gJ * muB / hbar / 1e12 # in 1/(mT*ns)
b = 0
if phi == 45:
xmin, xmax = -0.05, 0.05
A = 0.02
c = -0.5
else:
xmin, xmax = -0.1, 0.1
A = -0.02
c = 1
if T == -8 and phi == 0: # special case, wont fit with 0.01
xmin, xmax = -0.075, 0.075
phipar = np.deg2rad(phi)
# fit data
fit = Fitter("fit_%s" % name, fitFuncLorentz, (xmin, xmax, 6))
fit.setParam(0, "#tau", 120)
fit.setParam(1, "#phi", phipar)
fit.setParam(2, "A", A)
fit.setParam(3, "a", a, True)
fit.setParam(4, "b", b)
fit.setParam(5, "c", c)
fit.fit(g, xmin, xmax, "M")
fit.saveData("../calc/fit_%s.txt" % name, "w")
# add legend
if phi == 90:
l = TLegend(0.11, 0.15, 0.4, 0.55)
else:
l = TLegend(0.11, 0.45, 0.4, 0.85)
l.SetTextSize(0.03)
l.AddEntry(g, "Messdaten", "p")
l.AddEntry(fit.function, "Fit mit Lorentzkurve", "l")
fit.addParamsToLegend(
l,
format=[("%.2f", "%.2f"), ("%.2e", "%.1e"), ("%.2e", "%.1e"), "%.2e", ("%.2e", "%.1e"), ("%.3f", "%.3f")],
chisquareformat="%.2f",
advancedchi=True,
units=["ns", "rad", "V/ns", "1/(mT*ns)", "T", "V"],
)
l.Draw()
# print to file
canvas.Update()
canvas.Print("../img/fit_%s.pdf" % name, "pdf")
# return lifespan (tau) and angle (phi)
return (fit.params[0]["value"], fit.params[0]["error"]), (normPhi(fit.params[1]["value"]), fit.params[1]["error"])