def plot_hg_radiative(fin,outpath):
"""h-g radiative corrections for comparison with Albert's numbers"""
Q = QFile(fin)
ep = Q.getItemF("decayInfo","endpt")
corrs = [spectrumCorrs(m) for m in Q.dat["spectrumPoint"]]
ghg=graph.graphxy(width=24,height=16,
x=graph.axis.lin(title="Kinetic Energy [keV]",min=500,max=1300),
y=graph.axis.lin(title="Relative Asymmetry Correction",min=0,max=0.003),
key = graph.key.key(pos="mr"))
setTexrunner(ghg)
ghg.plot(graph.data.points([(c.energy+511,c.hmg) for c in corrs],x=1,y=2,title="Radiative $h - g$ (Shann/Sirlin)"),
[graph.style.line([style.linewidth.Thick,rgb.blue])])
ghg.writetofile(outpath+"/Radiative_h-g.pdf")
def alpha_eloss_plot(basePath = os.environ["UCNA_ANA_PLOTS"]+"/test/"):
dat = QFile(basePath+"/AlphaEnergyLossSim.txt").dat["alpha_eloss"]
for d in dat:
d.loadFloats()
e0 = 5485.56
gdat = [(2*d.thickness,(5485.6-d.mean)/1000) for d in dat]
g=graph.graphxy(width=15,height=15,
x=graph.axis.lin(title="Mylar foil thickness [$\\mu$m]",parter=graph.axis.parter.linear(tickdists=[5,1])),
y=graph.axis.lin(title="$^{241}$Am $\\alpha$ energy loss [MeV]"),
key = graph.key.key(pos="tl"))
setTexrunner(g)
g.plot(graph.data.points(gdat,x=1,y=2,title="Geant4 prediction"),[graph.style.symbol(symbol.circle,size=0.15)])
LF = LinearFitter(terms=[polyterm(i) for i in range(3)])
LF.fit(gdat)
g.plot(graph.data.points(LF.fitcurve(0,20,200),x=1,y=2,title="$\\Delta E = %.2f + %.3f \\cdot l + %.4f \\cdot l^2$"%tuple(LF.coeffs)),[graph.style.line([style.linestyle.dashed])])
g.plot(graph.data.points([[6,0.690]],x=1,y=2,title="Nominal 6$\\mu$m foil, 0.69 MeV measured"),[graph.style.symbol(symbol.plus,size=0.3,symbolattrs=[style.linewidth.Thick])])
x0 = inverseFunction(LF,(1,15))(1.120)
g.plot(graph.data.points([[x0,LF(x0)]],x=1,y=2,title="Source foil: 1.12 MeV loss $\\Rightarrow$ $l = %.1f$ $\\mu$m"%x0),[graph.style.symbol(symbol.diamond,size=0.3,symbolattrs=[style.linewidth.Thick])])
print "6 um ->",LF(6)
g.writetofile(basePath+"/AlphaEnergyLossSim.pdf")
def offsetPlot(basedir,fname): poffs = [posOffset(p) for p in QFile(basedir+"/"+fname).dat["posOffset"]] (xShift,yShift,sinTh,LFx,LFy) = fitOffsets(poffs) print "Average offset:",(xShift,yShift),sinTh gwid = 15 rwid = 50 lscale = gwid/(2.*rwid)*unit.v_cm gOffs=graph.graphxy(width=gwid,height=gwid, x=graph.axis.lin(title = "x [mm]",min=-rwid,max=rwid), y=graph.axis.lin(title="y [mm]",min=-rwid,max=rwid), key = None) setTexrunner(gOffs) gdat = [(p.x,p.y,p.dr,p.theta*180/pi) for p in poffs] for p in poffs: p.applyFit(LFx,LFy); fdat = [(p.x,p.y,p.dr,p.theta*180/pi) for p in poffs] gOffs.plot(graph.data.points(fdat,x=1,y=2,size=3,angle=4), [graph.style.arrow(linelength=lscale,arrowsize=0.7*lscale,lineattrs=[style.linewidth.THIck,rgb.red])]) gOffs.plot(graph.data.points(gdat,x=1,y=2,size=3,angle=4), [graph.style.arrow(linelength=lscale,arrowsize=0.7*lscale,lineattrs=[style.linewidth.THIck])]) gOffs.writetofile(basedir+"/MWPCOffsets.pdf")
def thesisCorrsPlot(fin,outpath):
Q = QFile(fin)
A = Q.getItemF("decayInfo","A")
Z = Q.getItemF("decayInfo","Z")
ep = Q.getItemF("decayInfo","endpt")
corrs = [spectrumCorrs(m) for m in Q.dat["spectrumPoint"]]
##############
# Fine spectrum shape corrections
##############
gWC=graph.graphxy(width=16,height=8,
x=graph.axis.lin(title="Kinetic Energy [keV]",min=0,max=ep),
y=graph.axis.lin(title="Spectrum Correction"),
key = graph.key.key(pos="bc",columns=3))
setTexrunner(gWC)
gWC.plot(graph.data.points([(c.energy,c.g) for c in corrs],x=1,y=2,title="$g \\alpha/2\\pi$"),[graph.style.line([style.linestyle.dashdotted,style.linewidth.THick])])
gWC.plot(graph.data.points([(c.energy,c.ACm1+c.L0m1) for c in corrs],x=1,y=2,title="${^AC}L_0-1$"),[graph.style.line([style.linewidth.Thick])])
gWC.plot(graph.data.points([(c.energy,c.VCm1+c.L0m1) for c in corrs],x=1,y=2,title="${^VC} L_0-1$"),[graph.style.line([style.linestyle.dotted,style.linewidth.Thick])])
gWC.writetofile(outpath+"/ThesisSpecCorr_%i_%i_%f.pdf"%(A,Z,ep))
###############
# spectrum shapes
###############
gSpec=graph.graphxy(width=10,height=8,
x=graph.axis.lin(title="Kinetic Energy [keV]",min=0,max=ep),
y=graph.axis.lin(title="Decay Rate",min=0,max=1.1),
key = graph.key.key(pos="bc"))
setTexrunner(gSpec)
gdat = [[c.energy,c.S0,c.S0*(1+c.F0m1)*(1+c.L0m1)*(1+c.VCm1)*(1+c.g)] for c in corrs]
gdat.sort()
print "Uncorrected beta energy:",sum([g[0]*g[1] for g in gdat])/sum([g[1] for g in gdat])
print "Average beta energy:",sum([g[0]*g[2] for g in gdat])/sum([g[2] for g in gdat])
vnorm = 1./max([g[1] for g in gdat])
snorm = sum([g[1] for g in gdat])/sum([g[2] for g in gdat])*vnorm
gdat = [ (g[0],g[1]*vnorm,g[2]*snorm) for g in gdat]
gSpec.plot(graph.data.points(gdat,x=1,y=2,title="plain phase space"),[graph.style.line([style.linestyle.dotted,style.linewidth.Thick])])
gSpec.plot(graph.data.points(gdat,x=1,y=3,title="corrected"),[graph.style.line([style.linewidth.Thick])])
gSpec.writetofile(outpath+"/Thesis_Spectrum_%i_%i_%f.pdf"%(A,Z,ep))
def load_octetruns(fname, tplist=octSegments[0]):
rnlist = []
for m in QFile(fname).dat.get("Octet", []):
for k in m.dat:
if k in tplist:
for rns in m.dat[k]:
for rn in rns.split(","):
rnlist.append(int(rn))
return rnlist
def plot_hg_radiative(fin, outpath):
"""h-g radiative corrections for comparison with Albert's numbers"""
Q = QFile(fin)
ep = Q.getItemF("decayInfo", "endpt")
corrs = [spectrumCorrs(m) for m in Q.dat["spectrumPoint"]]
ghg = graph.graphxy(width=24,
height=16,
x=graph.axis.lin(title="Kinetic Energy [keV]",
min=500,
max=1300),
y=graph.axis.lin(title="Relative Asymmetry Correction",
min=0,
max=0.003),
key=graph.key.key(pos="mr"))
setTexrunner(ghg)
ghg.plot(
graph.data.points([(c.energy + 511, c.hmg) for c in corrs],
x=1,
y=2,
title="Radiative $h - g$ (Shann/Sirlin)"),
[graph.style.line([style.linewidth.Thick, rgb.blue])])
ghg.writetofile(outpath + "/Radiative_h-g.pdf")
def sep23effic(basedir=os.environ["UCNA_ANA_PLOTS"] + "/test/23Separation/"):
cdat = [
count23(c)
for c in QFile(basedir + "/23Separation.txt").dat["23counts"]
]
for s in ["East", "West"]:
gdat = [(c.e0, c.e1, c.total, c.II / c.total, c.IIIx / c.total,
c.III / c.total, c.IIx / c.total, 0.5 * (c.e0 + c.e1))
for c in cdat if c.side == s]
gdat.sort()
g23 = graph.graphxy(width=10,
height=7,
x=graph.axis.lin(title="Energy [keV]",
min=0,
max=700),
y=graph.axis.lin(title="Fraction of II+III",
min=0,
max=1),
key=graph.key.key(pos="tc", columns=2))
setTexrunner(g23)
print gdat
iiCol, iiiCol = rgb.red, rgb.blue
iiCol, iiiCol = rgb.black, rgb.black
g23.plot(graph.data.points(gdat, x=-1, y=4, title="II"),
[graph.style.line(lineattrs=[iiCol, style.linestyle.dashed])])
g23.plot(
graph.data.points(gdat, x=-1, y=5, title="III*"),
[graph.style.line(lineattrs=[iiiCol, style.linestyle.dashdotted])])
g23.plot(graph.data.points(gdat, x=-1, y=6, title="III"),
[graph.style.line(lineattrs=[iiiCol, style.linestyle.solid])])
g23.plot(graph.data.points(gdat, x=-1, y=7, title="II*"),
[graph.style.line(lineattrs=[iiCol, style.linestyle.dotted])])
g23.writetofile(basedir + "frac23_%s.pdf" % s)
def XenonEnergyShift():
baseDir = os.environ["UCNA_ANA_PLOTS"] + "/SimSpectrum/XenonEndpoint/"
kFits = QFile(baseDir + "/EndpointEnergyShift.txt").dat["kurieFit"]
gHeight = 12
g = graph.graphxy(width=20,
height=gHeight,
x=graph.axis.lin(title="energy nonuniformity",
min=-0.06,
max=0.06),
y=graph.axis.lin(title="simulated endpoint shift [keV]"),
key=graph.key.key(pos="tl"))
setTexrunner(g)
sigmas = []
for s in ["E", "W"]:
for t in range(4):
shdat = {}
for k in kFits:
k.loadFloats(["endpoint", "dendpoint", "shift", "tube"])
k.loadStrings(["side"])
if not k.tube == t and k.side == s:
continue
shdat.setdefault(k.shift, []).append(k.endpoint)
gdat = [[
k,
] + musigma(shdat[k]) for k in shdat]
sigmas.append(gdat[0][2])
QF = LinearFitter([polyterm(i) for i in range(2)])
QF.fit(gdat, cols=(0, 1))
print "Shift factor", QF.toLatex()
g.plot(graph.data.points(gdat, x=1, y=2, dy=3, title=None),
[graph.style.symbol(symbol.circle)])
g.writetofile(baseDir + "EndpointShift.pdf")
print sigmas, musigma(sigmas)
def thesisCorrsPlot(fin, outpath):
Q = QFile(fin)
A = Q.getItemF("decayInfo", "A")
Z = Q.getItemF("decayInfo", "Z")
ep = Q.getItemF("decayInfo", "endpt")
corrs = [spectrumCorrs(m) for m in Q.dat["spectrumPoint"]]
##############
# Fine spectrum shape corrections
##############
gWC = graph.graphxy(width=16,
height=8,
x=graph.axis.lin(title="Kinetic Energy [keV]",
min=0,
max=ep),
y=graph.axis.lin(title="Spectrum Correction"),
key=graph.key.key(pos="bc", columns=3))
setTexrunner(gWC)
gWC.plot(
graph.data.points([(c.energy, c.g) for c in corrs],
x=1,
y=2,
title="$g \\alpha/2\\pi$"),
[
graph.style.line(
[style.linestyle.dashdotted, style.linewidth.THick])
])
gWC.plot(
graph.data.points([(c.energy, c.ACm1 + c.L0m1) for c in corrs],
x=1,
y=2,
title="${^AC}L_0-1$"),
[graph.style.line([style.linewidth.Thick])])
gWC.plot(
graph.data.points([(c.energy, c.VCm1 + c.L0m1) for c in corrs],
x=1,
y=2,
title="${^VC} L_0-1$"),
[graph.style.line([style.linestyle.dotted, style.linewidth.Thick])])
gWC.writetofile(outpath + "/ThesisSpecCorr_%i_%i_%f.pdf" % (A, Z, ep))
###############
# spectrum shapes
###############
gSpec = graph.graphxy(width=10,
height=8,
x=graph.axis.lin(title="Kinetic Energy [keV]",
min=0,
max=ep),
y=graph.axis.lin(title="Decay Rate", min=0, max=1.1),
key=graph.key.key(pos="bc"))
setTexrunner(gSpec)
gdat = [[
c.energy, c.S0,
c.S0 * (1 + c.F0m1) * (1 + c.L0m1) * (1 + c.VCm1) * (1 + c.g)
] for c in corrs]
gdat.sort()
print "Uncorrected beta energy:", sum([g[0] * g[1] for g in gdat]) / sum(
[g[1] for g in gdat])
print "Average beta energy:", sum([g[0] * g[2] for g in gdat]) / sum(
[g[2] for g in gdat])
vnorm = 1. / max([g[1] for g in gdat])
snorm = sum([g[1] for g in gdat]) / sum([g[2] for g in gdat]) * vnorm
gdat = [(g[0], g[1] * vnorm, g[2] * snorm) for g in gdat]
gSpec.plot(
graph.data.points(gdat, x=1, y=2, title="plain phase space"),
[graph.style.line([style.linestyle.dotted, style.linewidth.Thick])])
gSpec.plot(graph.data.points(gdat, x=1, y=3, title="corrected"),
[graph.style.line([style.linewidth.Thick])])
gSpec.writetofile(outpath + "/Thesis_Spectrum_%i_%i_%f.pdf" % (A, Z, ep))
def plotWilkinsonCorrs(fin, outpath):
#os.system("mkdir -p %s"%outpath)
#os.system("cd ..; ./UCNAnalyzer rc x");
Q = QFile(fin)
A = Q.getItemF("decayInfo", "A")
Z = Q.getItemF("decayInfo", "Z")
ep = Q.getItemF("decayInfo", "endpt")
corrs = [spectrumCorrs(m) for m in Q.dat["spectrumPoint"]]
##############
# individual spectrum shape corrections
##############
gWC = graph.graphxy(
width=18,
height=12,
x=graph.axis.lin(title="Energy [keV]", min=0, max=ep), #max=ep*1.25),
#y=graph.axis.log(title="Spectrum Correction",min=5e-6,max=0.5),
y=graph.axis.log(title="Spectrum Correction", min=5e-6),
key=graph.key.key(pos="tc", columns=4))
setTexrunner(gWC)
gdat = [
[
c.energy, # 0
c.F0m1, # 1
abs(c.L0m1), # 2
-c.Qm1, # 3
c.RVm1, # 4
c.RAm1, # 5
abs(c.BiRWM), # 6
-c.VCm1, # 7
-c.ACm1, # 8
c.g, # 9
0.000401, # 10
0.0004 * (1 + 0.2 * sin(c.energy / 30)), # 11
-c.Cm1, # 12
c.Rm1 # 13
] for c in corrs
]
gWC.plot(
graph.data.points([(c.energy, c.F0m1) for c in corrs],
x=1,
y=2,
title="$F_0-1$"),
[graph.style.line([style.linewidth.THICk])])
gWC.plot(
graph.data.points([(c.energy, abs(c.g)) for c in corrs],
x=1,
y=2,
title="$|g \\alpha/2\\pi|$"),
[graph.style.line([style.linestyle.dashed, style.linewidth.THick])])
gWC.plot(
graph.data.points([(c.energy, abs(c.BiRWM)) for c in corrs],
x=1,
y=2,
title="$|R+{\\rm WM}|$"),
[graph.style.line([style.linestyle.dotted, style.linewidth.THIck])])
#gWC.plot(graph.data.points([(c.energy,-c.ACm1) for c in corrs],x=1,y=2,title="$1-{^AC}$"),[graph.style.line([style.linewidth.thick])])
#gWC.plot(graph.data.points([(c.energy,-c.VCm1) for c in corrs],x=1,y=2,title="$1-{^VC}$"),[graph.style.line([style.linestyle.dashdotted,style.linewidth.thick])])
gWC.plot(
graph.data.points([(c.energy, -c.Cm1) for c in corrs],
x=1,
y=2,
title="$1-C$"),
[
graph.style.line(
[style.linestyle.dashdotted, style.linewidth.thick])
])
gWC.plot(
graph.data.points([(c.energy, -c.L0m1) for c in corrs],
x=1,
y=2,
title="$1-L_0$"),
[graph.style.line([style.linestyle.dashed, style.linewidth.thick])])
gWC.plot(
graph.data.points([(c.energy, -c.Qm1) for c in corrs],
x=1,
y=2,
title="$1-Q$"),
[graph.style.line([style.linestyle.dotted, style.linewidth.thick])])
#gWC.writetofile(outpath+"/WilkinsonCorrs_%i_%i_%f.pdf"%(A,Z,ep))
###############
# spectrum shapes
###############
gSpec = graph.graphxy(width=10,
height=8,
x=graph.axis.lin(title="Kinetic Energy [keV]",
min=0,
max=ep),
y=graph.axis.lin(title="Decay Rate", min=0),
key=graph.key.key(pos="tr"))
setTexrunner(gSpec)
gdat = [[c.energy, c.S0, c.S] for c in corrs]
gdat.sort()
print "Uncorrected beta energy:", sum([g[0] * g[1] for g in gdat]) / sum(
[g[1] for g in gdat])
print "Average beta energy:", sum([g[0] * g[2] for g in gdat]) / sum(
[g[2] for g in gdat])
snorm = sum([g[1] for g in gdat]) / sum([g[2] for g in gdat])
gdat = [g + [
g[2] * snorm,
] for g in gdat]
if 1 / 1.2 < snorm < 1.2:
gSpec.plot(graph.data.points(gdat, x=1, y=3, title="Corrected"), [
graph.style.line(
[style.linestyle.dashed, rgb.blue, style.linewidth.Thick])
])
gSpec.plot(graph.data.points(gdat, x=1, y=4, title="Normalized"),
[graph.style.line([rgb.red, style.linewidth.Thick])])
else:
gSpec.plot(graph.data.points(gdat, x=1, y=4, title="Corrected"), [
graph.style.line(
[style.linestyle.dashed, rgb.blue, style.linewidth.Thick])
])
gSpec.plot(
graph.data.points(gdat, x=1, y=2, title="Plain"),
[graph.style.line([style.linestyle.dotted, style.linewidth.Thick])])
#gSpec.writetofile(outpath+"/BetaSpectrum_%i_%i_%f.pdf"%(A,Z,ep))
if A != 1:
return
##############
# total spectrum shape corrections
##############
gWCTot = graph.graphxy(width=20,
height=10,
x=graph.axis.lin(title="Kinetic Energy [keV]",
min=0,
max=783),
y=graph.axis.lin(
title="Total spectrum correction factor",
min=1.0,
max=1.2),
key=graph.key.key(pos="tr"))
setTexrunner(gWCTot)
gdat = [[c.energy, c.S / c.S0] for c in corrs if c.S0]
gdat.sort()
gWCTot.plot(graph.data.points(gdat, x=1, y=2, title=None),
[graph.style.line([style.linewidth.Thick])])
#gWCTot.writetofile(outpath+"/WilkinsonCorrsTot.pdf")
################
# Asymmetry corrections
################
gWCA = graph.graphxy(width=15,
height=7,
x=graph.axis.lin(title="Kinetic Energy [keV]",
min=0,
max=782),
y=graph.axis.lin(title="$(A-A_0)/A_0$ [\\%]",
min=0.0000),
key=graph.key.key(pos="tl"))
setTexrunner(gWCA)
gWCA.plot(
graph.data.points([(c.energy, c.RWM * 100) for c in corrs],
x=1,
y=2,
title="Recoil order"),
[graph.style.line([style.linewidth.Thick, style.linestyle.dashed])])
gWCA.plot(
graph.data.points([(c.energy, c.hmg * 100) for c in corrs],
x=1,
y=2,
title="${\\alpha \\over 2\\pi}(h - g)$"),
[graph.style.line([style.linewidth.Thick])])
if 0:
def gluckx2E(x):
return x * (782.6 + 511.) - 511.
gluck_da = [[gluckx2E(0.4), 0.03 / 1.66], [gluckx2E(0.5), 0.01 / 6.55],
[gluckx2E(0.6), 0.01 / 8.08], [gluckx2E(0.7), 0.01 / 8.90],
[gluckx2E(0.8), 0.01 / 9.41], [gluckx2E(0.9), 0.01 / 9.76]]
gluck_hmg = [[gluckx2E(0.4), 0.005 / 1.731],
[gluckx2E(0.5), 0.014 / 6.961],
[gluckx2E(0.6), 0.013 / 8.553],
[gluckx2E(0.7), 0.011 / 9.383],
[gluckx2E(0.8), 0.009 / 9.884],
[gluckx2E(0.9), 0.008 / 10.214]]
#gWCA.plot(graph.data.points(gluck_da,x=1,y=2,title='Gl\\"uck 1992 $\\delta \\alpha_e$ table'),[graph.style.symbol(symbolattrs=[rgb.green])])
gWCA.plot(
graph.data.points(gluck_hmg,
x=1,
y=2,
title='Gl\\"uck private communication'),
[graph.style.symbol(symbolattrs=[rgb.green])])
gWCA.writetofile(outpath + "/A_Rad_Corrections.pdf")
return
################
# Asymmetry curves
################
gAsym = graph.graphxy(width=10,
height=8,
x=graph.axis.lin(title="Kinetic Energy [keV]",
min=0,
max=800),
y=graph.axis.lin(title="Asymmetry $A(E)\\beta/2$"),
key=graph.key.key(pos="tr"))
setTexrunner(gAsym)
gdat = [[c.energy, c.A0, c.A] for c in corrs if c.energy < 783]
gAsym.plot(graph.data.points(gdat, x=1, y=2, title="$A(E)=A_0$"),
[graph.style.line([style.linewidth.Thick])])
gAsym.plot(graph.data.points(gdat, x=1, y=3, title="Corrected"), [
graph.style.line(
[rgb.red, style.linestyle.dashdotted, style.linewidth.Thick])
])
gAsym.writetofile(outpath + "/Asymmetry.pdf")
################
# shape of tensor coupling corrections to A
################
def tensorCoeff(E):
m_e = 511.
l = 1.2694
return 2 / (1 + 3 * l)**2 / 938000 * (
m_e**2. / E * l**2 * (1 - l) + 782 *
(l**2 + 2. / 3. * l - 1. / 3.) + E * 2. / 3. *
(1 + l + 3 * l**2 + 3 * l**3)) * (1 + 3. * l**2) / (2 * l *
(1 - l))
gT = graph.graphxy(width=20,
height=10,
x=graph.axis.lin(title="Kinetic Energy [keV]",
min=0,
max=800),
y=graph.axis.lin(
title="$\\Delta A/A$ for $g_{II}/g_V=1$",
min=-0.01,
max=0.01),
key=graph.key.key(pos="tr"))
setTexrunner(gT)
gT.plot(
graph.data.points([(c.energy, tensorCoeff(c.energy)) for c in corrs],
x=1,
y=2,
title=None),
[graph.style.line([style.linewidth.Thick])])
gT.writetofile(outpath + "/GardnerTensor.pdf")
def __init__(self, fname):
rcals = [runCal(r) for r in QFile(fname).dat.get("runcal", [])]
self.runcals = dict([(r.run, r) for r in rcals])
self.runs = self.runcals.keys()
self.runs.sort()
def plotWilkinsonCorrs(fin,outpath):
#os.system("mkdir -p %s"%outpath)
#os.system("cd ..; ./UCNAnalyzer rc x");
Q = QFile(fin)
A = Q.getItemF("decayInfo","A")
Z = Q.getItemF("decayInfo","Z")
ep = Q.getItemF("decayInfo","endpt")
corrs = [spectrumCorrs(m) for m in Q.dat["spectrumPoint"]]
##############
# individual spectrum shape corrections
##############
gWC=graph.graphxy(width=18,height=12,
x=graph.axis.lin(title="Energy [keV]",min=0,max=ep), #max=ep*1.25),
#y=graph.axis.log(title="Spectrum Correction",min=5e-6,max=0.5),
y=graph.axis.log(title="Spectrum Correction",min=5e-6),
key = graph.key.key(pos="tc",columns=4))
setTexrunner(gWC)
gdat = [ [ c.energy, # 0
c.F0m1, # 1
abs(c.L0m1), # 2
-c.Qm1, # 3
c.RVm1, # 4
c.RAm1, # 5
abs(c.BiRWM), # 6
-c.VCm1, # 7
-c.ACm1, # 8
c.g, # 9
0.000401, # 10
0.0004*(1+0.2*sin(c.energy/30)), # 11
-c.Cm1, # 12
c.Rm1 # 13
] for c in corrs]
gWC.plot(graph.data.points([(c.energy,c.F0m1) for c in corrs],x=1,y=2,title="$F_0-1$"),[graph.style.line([style.linewidth.THICk])])
gWC.plot(graph.data.points([(c.energy,abs(c.g)) for c in corrs],x=1,y=2,title="$|g \\alpha/2\\pi|$"),[graph.style.line([style.linestyle.dashed,style.linewidth.THick])])
gWC.plot(graph.data.points([(c.energy,abs(c.BiRWM)) for c in corrs],x=1,y=2,title="$|R+{\\rm WM}|$"),[graph.style.line([style.linestyle.dotted,style.linewidth.THIck])])
#gWC.plot(graph.data.points([(c.energy,-c.ACm1) for c in corrs],x=1,y=2,title="$1-{^AC}$"),[graph.style.line([style.linewidth.thick])])
#gWC.plot(graph.data.points([(c.energy,-c.VCm1) for c in corrs],x=1,y=2,title="$1-{^VC}$"),[graph.style.line([style.linestyle.dashdotted,style.linewidth.thick])])
gWC.plot(graph.data.points([(c.energy,-c.Cm1) for c in corrs],x=1,y=2,title="$1-C$"),[graph.style.line([style.linestyle.dashdotted,style.linewidth.thick])])
gWC.plot(graph.data.points([(c.energy,-c.L0m1) for c in corrs],x=1,y=2,title="$1-L_0$"),[graph.style.line([style.linestyle.dashed,style.linewidth.thick])])
gWC.plot(graph.data.points([(c.energy,-c.Qm1) for c in corrs],x=1,y=2,title="$1-Q$"),[graph.style.line([style.linestyle.dotted,style.linewidth.thick])])
#gWC.writetofile(outpath+"/WilkinsonCorrs_%i_%i_%f.pdf"%(A,Z,ep))
###############
# spectrum shapes
###############
gSpec=graph.graphxy(width=10,height=8,
x=graph.axis.lin(title="Kinetic Energy [keV]",min=0,max=ep),
y=graph.axis.lin(title="Decay Rate",min=0),
key = graph.key.key(pos="tr"))
setTexrunner(gSpec)
gdat = [[c.energy,c.S0,c.S] for c in corrs]
gdat.sort()
print "Uncorrected beta energy:",sum([g[0]*g[1] for g in gdat])/sum([g[1] for g in gdat])
print "Average beta energy:",sum([g[0]*g[2] for g in gdat])/sum([g[2] for g in gdat])
snorm = sum([g[1] for g in gdat])/sum([g[2] for g in gdat])
gdat = [g+[g[2]*snorm,] for g in gdat]
if 1/1.2 < snorm < 1.2:
gSpec.plot(graph.data.points(gdat,x=1,y=3,title="Corrected"),[graph.style.line([style.linestyle.dashed,rgb.blue,style.linewidth.Thick])])
gSpec.plot(graph.data.points(gdat,x=1,y=4,title="Normalized"),[graph.style.line([rgb.red,style.linewidth.Thick])])
else:
gSpec.plot(graph.data.points(gdat,x=1,y=4,title="Corrected"),[graph.style.line([style.linestyle.dashed,rgb.blue,style.linewidth.Thick])])
gSpec.plot(graph.data.points(gdat,x=1,y=2,title="Plain"),[graph.style.line([style.linestyle.dotted,style.linewidth.Thick])])
#gSpec.writetofile(outpath+"/BetaSpectrum_%i_%i_%f.pdf"%(A,Z,ep))
if A != 1:
return
##############
# total spectrum shape corrections
##############
gWCTot=graph.graphxy(width=20,height=10,
x=graph.axis.lin(title="Kinetic Energy [keV]",min=0,max=783),
y=graph.axis.lin(title="Total spectrum correction factor",min=1.0,max=1.2),
key = graph.key.key(pos="tr"))
setTexrunner(gWCTot)
gdat = [[c.energy,c.S/c.S0] for c in corrs if c.S0]
gdat.sort()
gWCTot.plot(graph.data.points(gdat,x=1,y=2,title=None),[graph.style.line([style.linewidth.Thick])])
#gWCTot.writetofile(outpath+"/WilkinsonCorrsTot.pdf")
################
# Asymmetry corrections
################
gWCA=graph.graphxy(width=15,height=7,
x=graph.axis.lin(title="Kinetic Energy [keV]",min=0,max=782),
y=graph.axis.lin(title="$(A-A_0)/A_0$ [\\%]",min=0.0000),
key = graph.key.key(pos="tl"))
setTexrunner(gWCA)
gWCA.plot(graph.data.points([(c.energy,c.RWM*100) for c in corrs],x=1,y=2,title="Recoil order"),[graph.style.line([style.linewidth.Thick,style.linestyle.dashed])])
gWCA.plot(graph.data.points([(c.energy,c.hmg*100) for c in corrs],x=1,y=2,title="${\\alpha \\over 2\\pi}(h - g)$"),[graph.style.line([style.linewidth.Thick])])
if 0:
def gluckx2E(x):
return x*(782.6+511.)-511.
gluck_da = [ [gluckx2E(0.4),0.03/1.66],[gluckx2E(0.5),0.01/6.55],[gluckx2E(0.6),0.01/8.08],
[gluckx2E(0.7),0.01/8.90],[gluckx2E(0.8),0.01/9.41],[gluckx2E(0.9),0.01/9.76]]
gluck_hmg = [ [gluckx2E(0.4),0.005/1.731],[gluckx2E(0.5),0.014/6.961],[gluckx2E(0.6),0.013/8.553],
[gluckx2E(0.7),0.011/9.383],[gluckx2E(0.8),0.009/9.884],[gluckx2E(0.9),0.008/10.214]]
#gWCA.plot(graph.data.points(gluck_da,x=1,y=2,title='Gl\\"uck 1992 $\\delta \\alpha_e$ table'),[graph.style.symbol(symbolattrs=[rgb.green])])
gWCA.plot(graph.data.points(gluck_hmg,x=1,y=2,title='Gl\\"uck private communication'),[graph.style.symbol(symbolattrs=[rgb.green])])
gWCA.writetofile(outpath+"/A_Rad_Corrections.pdf")
return
################
# Asymmetry curves
################
gAsym=graph.graphxy(width=10,height=8,
x=graph.axis.lin(title="Kinetic Energy [keV]",min=0,max=800),
y=graph.axis.lin(title="Asymmetry $A(E)\\beta/2$"),
key = graph.key.key(pos="tr"))
setTexrunner(gAsym)
gdat = [[c.energy,c.A0,c.A] for c in corrs if c.energy<783]
gAsym.plot(graph.data.points(gdat,x=1,y=2,title="$A(E)=A_0$"),[graph.style.line([style.linewidth.Thick])])
gAsym.plot(graph.data.points(gdat,x=1,y=3,title="Corrected"),[graph.style.line([rgb.red,style.linestyle.dashdotted,style.linewidth.Thick])])
gAsym.writetofile(outpath+"/Asymmetry.pdf")
################
# shape of tensor coupling corrections to A
################
def tensorCoeff(E):
m_e = 511.
l = 1.2694
return 2/(1+3*l)**2/938000*(m_e**2./E*l**2*(1-l)+782*(l**2+2./3.*l-1./3.)+E*2./3.*(1+l+3*l**2+3*l**3))*(1+3.*l**2)/(2*l*(1-l))
gT=graph.graphxy(width=20,height=10,
x=graph.axis.lin(title="Kinetic Energy [keV]",min=0,max=800),
y=graph.axis.lin(title="$\\Delta A/A$ for $g_{II}/g_V=1$",min=-0.01,max=0.01),
key = graph.key.key(pos="tr"))
setTexrunner(gT)
gT.plot(graph.data.points([(c.energy,tensorCoeff(c.energy)) for c in corrs],x=1,y=2,title=None),[graph.style.line([style.linewidth.Thick])])
gT.writetofile(outpath+"/GardnerTensor.pdf")
def EndpointSmearingDat():
baseDir = os.environ["UCNA_ANA_PLOTS"] + "/SimSpectrum/EndpointSmear/"
#kFits = QFile(baseDir+"/EndpointSmear_150-XXX.txt").dat["kurieFit"] # <--
kFits = QFile(baseDir + "/EndpointSmear_XXX-635.txt").dat["kurieFit"]
gHeight = 12
g = graph.graphxy(width=20,
height=gHeight,
x=graph.axis.lin(
title="PMT average energy resolution [keV at 1 MeV]",
min=40,
max=200),
y=graph.axis.lin(title="simulated endpoint shift [keV]"),
key=graph.key.key(pos="tl"))
setTexrunner(g)
ep0 = 710
sens = []
nn = 0
pmtRes = [75, 100, 125]
resSty = [[style.linestyle.dashed, style.linewidth.THick],
[style.linestyle.solid, style.linewidth.THick],
[style.linestyle.dotted, style.linewidth.THick]]
#for fitEnd in [600,620,640,660,680,700,720][::-1]:
for fitStart in [100, 120, 140, 160, 180, 200, 220, 240][::-1]:
lsty = [[style.linestyle.solid], [style.linestyle.dashed],
[style.linestyle.dotted], [style.linestyle.dashdotted],
[style.linestyle.solid, style.linewidth.THick],
[style.linestyle.dashed, style.linewidth.THick],
[style.linestyle.dotted, style.linewidth.THick],
[style.linestyle.dashdotted, style.linewidth.THick]
#][::-1][nn+1] # <--
][::-1][nn] # <--
nn += 1
resPts = {}
for k in kFits:
k.loadFloats()
#if k.fitEnd != fitEnd: # <--
if k.fitStart != fitStart: # <--
continue
k.endpoint = k.endpoint - ep0
resPts.setdefault(k.PEperMEV, []).append(k)
avgd = [[1000 / sqrt(k)] + mu_uncert([c.endpoint for c in resPts[k]])
for k in resPts]
avgd.sort()
if not avgd:
continue
QF = LinearFitter([polyterm(i) for i in range(3)])
QF.fit(avgd, cols=(0, 1, 2), errorbarWeights=False)
#sens.append([fitEnd,] + [nderiv(QF,x) for x in pmtRes]) # <--
sens.append([
fitStart,
] + [nderiv(QF, x) for x in pmtRes]) # <--
print sens[-1][0], "100keV Res Sensitivity dy/dx =", sens[-1][1]
g.plot(graph.data.points(avgd, x=1, y=2, dy=3, title=None), [
graph.style.errorbar(),
graph.style.symbol(symbol.circle, size=0.15)
])
#g.plot(graph.data.points(QF.fitcurve(40,200,200),x=1,y=2,title="150--%i keV"%fitEnd),[graph.style.line(lsty)]) # <--
g.plot(
graph.data.points(QF.fitcurve(40, 200, 200),
x=1,
y=2,
title="%i--635 keV" % fitStart),
[graph.style.line(lsty)]) # <--
#g.writetofile(baseDir+"Endpoint_End.pdf") # <--
g.writetofile(baseDir + "Endpoint_Start.pdf") # <--
if 0:
g = graph.graphxy(
width=gHeight,
height=gHeight,
#x=graph.axis.lin(title="Kurie fit window end [keV]"), # <--
x=graph.axis.lin(
title="Kurie fit window end [keV]",
min=100,
max=240,
parter=graph.axis.parter.linear(tickdists=[20, 5])), # <--
y=graph.axis.lin(title="sensitivity to energy resolution keV/keV"),
key=graph.key.key(pos="tl"))
setTexrunner(g)
for (n, p0) in enumerate(pmtRes):
QF = LinearFitter([polyterm(i) for i in range(3)])
QF.fit(sens, cols=(0, n + 1))
g.plot(graph.data.points(sens, x=1, y=n + 2, title=None),
[graph.style.symbol(symbol.circle)])
g.plot(
graph.data.points(QF.fitcurve(600, 720, 200),
x=1,
y=2,
title="%i keV @ 1 MeV" % p0),
[graph.style.line(resSty[n])]) # <--
#g.writetofile(baseDir+"Endpoint_EndSens.pdf") # <--
g.writetofile(baseDir + "Endpoint_StartSens.pdf") # <--
if 0:
g = graph.graphxy(width=15,
height=8,
x=graph.axis.lin(title="predicted sigma"),
y=graph.axis.lin(title="observed sigma"))
setTexrunner(g)
g.plot(graph.data.points(avgd, x=4, y=3),
[graph.style.symbol(symbol.circle)])
g.writetofile(baseDir + "EndpointSigma.pdf")
def paperFig1(inColor=False):
pdat = [
asymplot(a) for a in QFile(os.environ["UCNA_ANA_PLOTS"] +
"/Paper/PlotData.txt").dat["asymplot"]
]
xrange = (0, 800)
gwid = 12
gCorr = graph.graphxy(width=gwid,
height=0.2 * gwid,
x=graph.axis.lin(title="Reconstructed Energy [keV]",
min=xrange[0],
max=xrange[1]),
y=graph.axis.lin(title="\\% Corr.", min=-5, max=5),
key=graph.key.key(pos="tl"))
setTexrunner(gCorr)
gAsym = graph.graphxy(width=gwid,
height=0.4 * gwid,
ypos=gCorr.height + 0.5,
x=graph.axis.linkedaxis(gCorr.axes["x"]),
y=graph.axis.lin(title="$A_0$", min=-0.14,
max=-0.10),
key=graph.key.key(pos="tr"))
setTexrunner(gAsym)
gSpec = graph.graphxy(width=gwid,
height=0.5 * gwid,
ypos=gCorr.height + gAsym.height + 1.0,
x=graph.axis.linkedaxis(gCorr.axes["x"]),
y=graph.axis.lin(title="Decay Rate [Hz/keV]",
min=0,
max=0.065),
key=graph.key.key(pos="tr"))
setTexrunner(gSpec)
cnvs = canvas.canvas()
cnvs.insert(gCorr)
cnvs.insert(gAsym)
cnvs.insert(gSpec)
specCircAttrs = None
bgCircAttrs = [deco.filled]
if inColor:
specCircAttrs = [color.rgb.blue]
bgCircAttrs += [color.rgb(0, 0.7, 0)]
gSpec.plot(
graph.data.points([(p.KE, p.ssfg) for p in pdat],
x=1,
y=2,
title="Data"),
[
graph.style.symbol(
symbol.circle, size=0.1, symbolattrs=specCircAttrs),
])
gSpec.plot(
graph.data.points([(p.KE, p.ssMC) for p in pdat],
x=1,
y=2,
title="Geant4 MC"), [
graph.style.line(),
])
gSpec.plot(
graph.data.points([(p.KE, p.ssbg) for p in pdat],
x=1,
y=2,
title="Background"),
[
graph.style.symbol(
symbol.circle, size=0.1, symbolattrs=bgCircAttrs),
])
pdat = [p for p in pdat if p.KE > 60]
area = errorBand([(p.KE, 100. * p.corr, 100. * p.dcorr) for p in pdat], 0,
1, 2)
asLineAttrs = [style.linewidth.THick]
if inColor:
gCorr.fill(area, [deco.filled([color.rgb(0.5, 0.5, 1)])])
asLineAttrs += [color.rgb.green]
else:
gCorr.fill(area, [pattern.hatched(0.10, -45)])
gCorr.fill(area, [pattern.hatched(0.10, 45)])
gCorr.plot(
graph.data.points([(p.KE, 100. * p.corr, 100. * p.dcorr)
for p in pdat],
x=1,
y=2,
dy=3,
title=None), [
graph.style.line(asLineAttrs),
]
) #[graph.style.symbol(symbol.circle,size=0.1), ]) #graph.style.errorbar()])
for y in [-2.5, 0, 2.5]:
gCorr.plot(graph.data.points([(0, y), (800, y)], x=1, y=2, title=None),
[graph.style.line([style.linestyle.dashed])])
if False:
d = gCorr.plot(
graph.data.points([(p.KE, 100. * p.dcorr) for p in pdat],
x=1,
y=2,
title=None), [graph.style.line()])
gCorr.finish()
p = d.path
pa = gCorr.xgridpath(100)
pb = gCorr.xgridpath(750)
p0 = gCorr.ygridpath(0)
(splita, ), (splitpa, ) = p.intersect(pa)
(splitb, ), (splitpb, ) = p.intersect(pb)
splitp0a = p0.intersect(pa)[1][0]
splitp0b = p0.intersect(pb)[1][0]
area = (
pa.split([splitp0a, splitpa])[1] << p.split([splita, splitb])[1] <<
pb.split([splitp0b, splitpb])[1].reversed())
area[-1].close()
gCorr.stroke(area, [deco.filled([color.gray(0.8)])])
asymBarAttrs = None
asymCircAttrs = [deco.filled([color.gray(1.0)])]
asymFitAttrs = [style.linewidth.THIck]
if inColor:
asymBarAttrs = [color.rgb.blue]
asymCircAttrs += [color.rgb.blue]
asymFitAttrs += [color.rgb(0, 0.7, 0)]
gAsym.plot(
graph.data.points([(p.KE, p.A0, p.dA0) for p in pdat],
x=1,
y=2,
dy=3,
title=None),
[
graph.style.errorbar(errorbarattrs=asymBarAttrs),
graph.style.symbol(
symbol.circle, size=0.1, symbolattrs=asymCircAttrs)
])
A0 = -0.11954
gAsym.plot(graph.data.points([(220, A0), (670, A0)], x=1, y=2, title=None),
[graph.style.line(asymFitAttrs)])
# different fit ranges
for (e0, e1) in [
(220, 670),
] + [(200 - 10 * x, 700 + 10 * x) for x in range(11)]:
LF = LinearFitter(terms=[polyterm(0)])
fdat = [(p.KE, p.A0, p.dA0) for p in pdat if e0 < p.KE < e1]
LF.fit(fdat, cols=(0, 1, 2), errorbarWeights=True)
print "<A0> [%i,%i] =" % (
e0, e1), LF.coeffs[0], "chi^2/ndf =", LF.chisquared(), LF.nu()
cnvs.writetofile(os.environ["UCNA_ANA_PLOTS"] + "/Paper/Fig1_new.pdf")
if False:
fgtot = bgtot = 0
for p in pdat:
if 100 < p.KE and p.KE < 800:
print p.KE, p.ssbg, p.ssfg, p.ssfg / p.ssbg
if True or (220 < p.KE and p.KE < 670):
fgtot += p.ssfg
bgtot += p.ssbg
print "\n\n", fgtot, bgtot, fgtot / bgtot
def __init__(self):
self.dat = dict([(int(x.getFirst("Z")), x) for x in QFile(
os.environ["UCNA_AUX"] +
"/NuclearDecays/ElectronBindingEnergy.txt").dat["binding"]])
def EQ2ET(fbase, conn=None):
f = QFile(fbase+"/Evis2ETrue.txt")
epts = [EnergyPoint(m) for m in f.dat.get("spectrumInfo",[])]
#scols = {"East":rgb.red,"West":rgb.blue}
scols = {"East":rgb.black,"West":rgb.black}
typeSymbs = {0:symbol.circle,1:symbol.triangle,2:symbol.square,3:symbol.cross}
typeLines = {0:style.linestyle.solid,1:style.linestyle.dashed,2:style.linestyle.dotted,3:style.linestyle.dashdotted}
typeNames = {0:"0",1:"I",2:"II/III",3:"III"}
for forward in [True,]:
xtitle = "mean $E_{\\rm vis}$ [keV]"
#ytitle = "True Initial Energy [keV]"
ytitle = "initial energy $E_{\\rm true}$ [keV]"
if not forward:
xtitle = "Mean True Energy [keV]"
ytitle = "Observed Quenched Energy [keV]"
residTitle = "Residuals [keV]"
gResid = []
gWidth = 12
gResid.append(graph.graphxy(width=gWidth,height=(gWidth-2.)/3.,
x=graph.axis.lin(title=xtitle,min=0,max=800),
y=graph.axis.lin(title=residTitle,min=-5,max=5),
key = graph.key.key(pos="br")))
setTexrunner(gResid[-1]) #.texrunner.set(lfs='10ptex')
for i in range(2):
gResid.append(graph.graphxy(width=gResid[0].width,height=gResid[0].height,ypos=(gResid[0].height+1.0)*(i+1),
x=graph.axis.linkedaxis(gResid[0].axes["x"]),
y=graph.axis.lin(title=residTitle,min=-5,max=5),
key = graph.key.key(pos="br")))
setTexrunner(gResid[-1])
#gEn=graph.graphxy(width=gResid.width,height=gResid.width,ypos=gResid.height+0.5,
# x=graph.axis.linkedaxis(gResid[0].axes["x"]),
# y=graph.axis.lin(title=ytitle,min=0,max=800),
# key = graph.key.key(pos="tl"))
#setTexrunner(gEn) #.texrunner.set(lfs='10ptex')
gEn=graph.graphxy(width=gResid[0].width,height=gResid[0].width,
x=graph.axis.lin(title=xtitle,min=0,max=800),
y=graph.axis.lin(title=ytitle,min=0,max=800),
key = graph.key.key(pos="tl"))
setTexrunner(gEn)
cnvs = canvas.canvas()
#cnvs.insert(gResid)
#cnvs.insert(gEn)
for i in range(3):
cnvs.insert(gResid[i])
types = typeSymbs.keys()
types.sort()
for tp in types:
combodat = []
for s in scols:
gdat = []
if forward:
gdat = [ (p.evis_avg,p.etrue_input,p.evis_rms/sqrt(p.evis_counts)) for p in epts if p.side==s and p.type==tp and p.evis_counts > 50 ]
else:
gdat = [ (p.etrue_avg,p.evis_input,p.etrue_rms/sqrt(p.etrue_counts)) for p in epts if p.side==s and p.type==tp and p.etrue_counts > 50 ]
combodat += gdat
gEn.plot(graph.data.points(gdat,x=1,y=2,dx=3,title=None),
[graph.style.symbol(typeSymbs[tp],size=0.20,symbolattrs=[scols[s],]),graph.style.errorbar(errorbarattrs=[scols[s]])])
combodat.sort()
if not combodat:
print "Missing data for type",tp
continue
LF = LinearFitter(terms=[polyterm(0),polyterm(1),polyterm(-1),polyterm(-2)])
LF.fit([c for c in combodat],cols=(0,1))
print s,LF.toLatex()
LF = piecewiseExtender(LF,combodat[1][0],900)
if forward and conn:
uploadEQ2ET(conn,tp,LF)
gEn.plot(graph.data.points(LF.fitcurve(1,1000,400),x=1,y=2,title=None),
[graph.style.line([typeLines[tp],style.linewidth.Thick])])
# empty plots... for type name labels
ctitle = "Type %s"%typeNames[tp]
#ctitle += ": $E_T = %s$"%LF.toLatex("E_Q")
gEn.plot(graph.data.points([(-1,-1),],x=1,y=2,title=ctitle),
[graph.style.line([typeLines[tp],style.linewidth.Thick]),graph.style.symbol(typeSymbs[tp],size=0.20)])
gResid[tp].plot(graph.data.points([ (g[0],g[1]-LF(g[0])) for g in combodat],x=1,y=2,title=ctitle),
[graph.style.symbol(typeSymbs[tp],size=0.15)])
if forward:
cnvs.writetofile(fbase+"/EvisToETrue_resid.pdf")
gEn.writetofile(fbase+"/EvisToETrue.pdf")
else:
cnvs.writetofile(fbase+"/EtrueToEvis.pdf")