def build_models(tag01, tag02, tmin, T):
tdata = range(T)
tfit = range(tmin, T + 1 - tmin) # all ts
tp = T # periodic
models = [
Corr2(datatag=tag01,
tp=tp,
tdata=tdata,
tfit=tfit,
a=('a1:vec:s', 'ao:vec:s'),
b=('a1:vec:s', 'ao:vec:s'),
dE=('dE:vec:s', 'dEo:vec:s'),
s=(1., -1.)),
Corr2(datatag=tag02,
tp=tp,
tdata=tdata,
tfit=tfit,
a=('a1:vec:qed:s', 'ao:vec:qed:s'),
b=('a1:vec:qed:s', 'ao:vec:qed:s'),
dE=('dE:vec:qed:s', 'dEo:vec:qed:s'),
s=(1., -1.)),
]
return models
def single_fit(tag_, tstar, CHARGED=False):
w0 = gv.gvar('0.1715(9)')
w0overa = gv.gvar('1.1367(5)')
ZV = gv.gvar('0.9837(20)')
ZVqed = gv.gvar('0.999544(14)') * ZV
hbarc = 0.197326968
a_vcoarse = (w0 / w0overa) / hbarc
if CHARGED == True:
ZV = ZVqed
else:
ZV = ZV
dataf = dsetavg[tag_]
tmin = 2
# replace data after t* with fit
# t* can be changed
fitter = CorrFitter(models=build_models(tmin, 48, tag_))
svdcut = 1e-6
for nexp in [4]:
print('=== nexp =', nexp, ' tmin = ', tmin, ' svdcut = ', svdcut)
fit = fitter.lsqfit(data=dsetavg,
prior=build_prior(nexp),
p0=pfile,
maxit=10000,
svdcut=svdcut) #,fitter='gsl_multifit')
print(fit)
newdata = dataf[:tstar]
#print("Before append/concatenate")
#print(newdata, len(newdata))
fitdata = Corr2(datatag=tag_,
tdata=range(48),
a=('a:rho', 'a:rhoo'),
b=('b:rho', 'b:rhoo'),
dE=('dE:rho', 'dE:rhoo'),
s=(1, -1)).fitfcn(fit.p)
newdata = np.append(np.array(newdata), fitdata[tstar:])
#print(fitdata[tstar:], fitdata[tstar:].size)
#print("After append/concatenate")
#print(newdata, newdata.size)
#sys.exit(0)
# use Z_V from appendix of 1909.00756; divided by u_0 to make the 1-link currents used match
vpol = g2.fourier_vacpol(newdata, Z=ZV, ainv=1 / a_vcoarse, periodic=False)
a_mu = g2.a_mu(vpol, Q=1. / 3.)
print('a_mu:', a_mu, "for", tag_, "t* = ", tstar)
return a_mu
def build_models(tmin, length, tag):
""" build models """
tdata = range(length)
tfit = range(tmin, length - tmin) # all ts
models = [
Corr2(datatag=tag,
tdata=tdata,
tfit=tfit,
tp=length,
a=('a:rho', 'a:rhoo'),
b=('b:rho', 'b:rhoo'),
dE=('dE:rho', 'dE:rhoo'),
s=(1, -1)),
]
return models
def main(tstr):
dfile = '/home/gray/Desktop/lattice-analysis/data/qed/coarse/rho_coarse_ms.gpl'
madedata = make_data(
dfile, norm=3.) # factor of 3 for colour (missed in extraction)
data = madedata[0]
T = data.size / len(madedata[1]) # extent in time dir
tag01 = madedata[1][0]
tag02 = madedata[1][1]
print("time extent is: ", T)
print(dfile)
suggestedsvdcut = madedata[2]
pfile = None #"vector_fit.p" # last fit
tmin = 2
svdcut = 1e-10 #suggestedsvdcut
fitter = CorrFitter(models=build_models(tag01, tag02, tmin, T))
for nexp in [2, 3, 4, 5]:
fit = fitter.lsqfit(data=data,
prior=build_prior(nexp),
p0=None,
maxit=20000,
svdcut=svdcut,
add_svdnoise=False)
print(fit)
tdata = range(T)
tfit = range(tmin, T + 1 - tmin) # all ts
tp = T
tstar = tstr
tcut = 200
newdata = {}
tags = ['nocharge', 'charge']
newdata[tags[0]] = data[tag01][:tstar + 1]
newdata[tags[1]] = data[tag02][:tstar + 1]
# do replacement of data with fit
fitdatauncharged = Corr2(datatag=tags[0],
tdata=range(T),
a=('a1:vec:s', 'ao:vec:s'),
b=('a1:vec:s', 'ao:vec:s'),
dE=('dE:vec:s', 'dEo:vec:s'),
s=(1., -1.)).fitfcn(fit.p)
for index in range(T):
if index >= tcut:
newdata[tags[0]] = np.append(newdata[tags[0]], 0.)
elif index > tstar:
newdata[tags[0]] = np.append(newdata[tags[0]],
fitdatauncharged[index])
fitdatachargeddown = Corr2(datatag=tags[1],
tdata=range(T),
a=('a1:vec:qed:s', 'ao:vec:qed:s'),
b=('a1:vec:qed:s', 'ao:vec:qed:s'),
dE=('dE:vec:qed:s', 'dEo:vec:qed:s'),
s=(1., -1.)).fitfcn(fit.p)
for index in range(T):
if index >= tcut:
newdata[tags[1]] = np.append(newdata[tags[1]], 0.)
elif index > tstar:
newdata[tags[1]] = np.append(newdata[tags[1]],
fitdatachargeddown[index])
print('THIS IS THE INFORMATION CENTRE')
print(len(newdata[tags[0]]), len(newdata[tags[1]]))
print('tmin, tstar', tmin, tstar)
vpol = g2.fourier_vacpol(newdata[tags[0]],
Z=ZV,
ainv=1 / a,
periodic=False)
unchargedamus = g2.a_mu(vpol, 1 / 3.)
vpol = g2.fourier_vacpol(newdata[tags[1]],
Z=ZVqed,
ainv=1 / a,
periodic=False)
chargedamus = g2.a_mu(vpol, 1 / 3.)
amus_rt = chargedamus / unchargedamus
amu_diff = chargedamus - unchargedamus
amu_diff_rt = amu_diff / unchargedamus
print(
'[s] a_mu[QCD+QED]{0:>20}\n|a_mu[QCD+QED]-a_mu[QCD]{1:>20}\n|a_mu/a_mu {2:>20}'
.format(chargedamus, amu_diff, amu_diff_rt))
def main(tstr):
dfile = '/home/gray/Desktop/lattice-analysis/data/qed/vcoarse/self_b/rho_vcoarse_7ml.gpl'
madedata = make_data(dfile,norm=3.) # factor of 3 for colour (missed in extraction)
data = madedata[0]
T = data.size / len(madedata[1]) # extent in time dir
tag01 = madedata[1][0]
tag02 = madedata[1][1]
tag03 = madedata[1][2] # =tag01 if no isospin breaking
print("time extent is: ", T)
print(dfile)
suggestedsvdcut = madedata[2]
pfile = None #"vector_fit.p" # last fit
tmin = 2
svdcut = 1e-10 #suggestedsvdcut
fitter = CorrFitter(models=build_models(tag01,tag02,tag03,tmin,T))
for nexp in [2,3,4,5]:
fit = fitter.lsqfit(data=data,prior=build_prior(nexp),p0=None,maxit=20000,svdcut=svdcut,add_svdnoise=False)
print(fit)
tdata = range(T)
tfit = range(tmin,T+1-tmin) # all ts
tp = T
tstar = tstr
tcut = 200
newdata = {}
tags = ['nocharge', 'up_charge', 'down-charge']
newdata[tags[0]] = data[tag01][:tstar+1]
newdata[tags[1]] = data[tag02][:tstar+1]
newdata[tags[2]] = data[tag03][:tstar+1]
# do replacement of data with fit
fitdatauncharged = Corr2(datatag=tags[0],tdata=range(T),a=('a1:vec:u','ao:vec:u'),b=('a1:vec:u','ao:vec:u'),dE=('dE:vec:u','dEo:vec:u'),s=(1.,-1.)).fitfcn(fit.p)
for index in range(T):
if index >= tcut:
newdata[tags[0]] = np.append(newdata[tags[0]],0.)
elif index > tstar:
newdata[tags[0]] = np.append(newdata[tags[0]],fitdatauncharged[index])
fitdatachargedup = Corr2(datatag=tags[1],tdata=range(T),a=('a1:vec:qed:u','ao:vec:qed:u'),b=('a1:vec:qed:u','ao:vec:qed:u'),dE=('dE:vec:qed:u','dEo:vec:qed:u'),s=(1.,-1.)).fitfcn(fit.p)
fitdatachargedown = Corr2(datatag=tags[2],tdata=range(T),a=('a1:vec:qed:d','ao:vec:qed:d'),b=('a1:vec:qed:d','ao:vec:qed:d'),dE=('dE:vec:qed:d','dEo:vec:qed:d'),s=(1.,-1.)).fitfcn(fit.p)
for index in range(T):
if index >= tcut:
newdata[tags[1]] = np.append(newdata[tags[1]],0.)
newdata[tags[2]] = np.append(newdata[tags[2]],0.)
elif index > tstar:
newdata[tags[1]] = np.append(newdata[tags[1]],fitdatachargedup[index])
newdata[tags[2]] = np.append(newdata[tags[2]],fitdatachargedown[index])
print('THIS IS THE INFORMATION CENTRE')
print(len(newdata[tags[0]]), len(newdata[tags[1]]), len(newdata[tags[2]]))
print('tmin, tstar', tmin, tstar)
vpol = g2.fourier_vacpol(newdata[tags[0]], Z=ZV, ainv=1/a, periodic=False)
unchargedamuu = g2.a_mu(vpol,2/3.)
vpol = g2.fourier_vacpol(newdata[tags[1]], Z=ZVqed, ainv=1/a, periodic=False)
chargedamuu = g2.a_mu(vpol,2/3.)
vpol = g2.fourier_vacpol(newdata[tags[0]], Z=ZV, ainv=1/a, periodic=False)
unchargedamud = g2.a_mu(vpol,1/3.)
vpol = g2.fourier_vacpol(newdata[tags[2]], Z=ZVqed, ainv=1/a, periodic=False)
chargedamud = g2.a_mu(vpol,1/3.)
d_rt = chargedamud/unchargedamud
u_rt = chargedamuu/unchargedamuu
amu_qcd = unchargedamud+unchargedamuu
amu_qcdqed = chargedamuu+chargedamud
amu_rt = amu_qcdqed/amu_qcd
amu_diff = (amu_qcdqed-amu_qcd)/amu_qcd
amu_diff2 = amu_qcdqed-amu_qcd
print('[d] a_mu[QCD+QED]||a_mu[QCD+QED]/a_mu[QCD]{0:>20}||{1}'.format(chargedamud,d_rt))
print('[u] a_mu[QCD+QED]||a_mu[QCD+QED]/a_mu[QCD]{0:>20}||{1}'.format(chargedamuu,u_rt))
print('\n[u+d] a_mu[QCD+QED]||a_mu[QCD]||ratio||diff\n{0:20}{1:20}{2:20}{3:20}'.format(amu_qcdqed, amu_qcd, amu_rt, amu_diff))
def main(tstr):
dfile = '/home/gray/Desktop/lattice-analysis/data/qed/vcoarse/comb/comb_rho_vcoarse_physud.gpl'
# tag01 = 'rho_m' + str(mq)
# tag02 = 'rho_m' + str(mq) + '_ucav'
# tag03 = 'rho_m' + str(mq)
# tag04 = 'rho_m' + str(mq) + '_dcav'
madedata = make_data(
dfile, norm=3.) # factor of 3 for colour (missed in extraction)
data = madedata[0]
T = data.size / len(madedata[1]) # extent in time dir
tag01 = madedata[1][0]
tag02 = madedata[1][1]
tag03 = madedata[1][2] # =tag01 if no isospin breaking
tag04 = madedata[1][3]
#sys.exit(0)
#ratiodata = {}
#ratiodata['up'] = data[tag02]/data[tag01]
#ratiodata['down'] = data[tag04]/data[tag03]
suggestedsvdcut = madedata[2]
pfile = "vector_fit.p" # last fit
tmin = 2
svdcut = 1e-10 #suggestedsvdcut
fitter = CorrFitter(
models=build_models(tag01, tag02, tag03, tag04, tmin, T))
for nexp in [2, 3, 4, 5]:
fit = fitter.lsqfit(data=data,
prior=build_prior(nexp),
p0=None,
maxit=20000,
svdcut=svdcut,
add_svdnoise=False)
print(fit)
tdata = range(T)
tfit = range(tmin, T + 1 - tmin) # all ts
tp = T
tstar = tstr
tcut = 200
newdata = {}
tags = ['up', 'up_qed', 'down', 'down_qed']
newdata[tags[0]] = data[tag01][:tstar + 1]
newdata[tags[1]] = data[tag02][:tstar + 1]
newdata[tags[2]] = data[tag03][:tstar + 1]
newdata[tags[3]] = data[tag04][:tstar + 1]
# do replacement of data with fit
fitdataunchargedup = Corr2(datatag=tags[0],
tdata=range(T),
a=('a1:vec:u', 'ao:vec:u'),
b=('a1:vec:u', 'ao:vec:u'),
dE=('dE:vec:u', 'dEo:vec:u'),
s=(1., -1.)).fitfcn(fit.p)
fitdataunchargeddown = Corr2(datatag=tags[2],
tdata=range(T),
a=('a1:vec:d', 'ao:vec:d'),
b=('a1:vec:d', 'ao:vec:d'),
dE=('dE:vec:d', 'dEo:vec:d'),
s=(1., -1.)).fitfcn(fit.p)
for index in range(48):
if index >= tcut:
newdata[tags[0]] = np.append(newdata[tags[0]], 0.)
newdata[tags[2]] = np.append(newdata[tags[2]], 0.)
elif index > tstar:
newdata[tags[0]] = np.append(newdata[tags[0]],
fitdataunchargedup[index])
newdata[tags[2]] = np.append(newdata[tags[2]],
fitdataunchargeddown[index])
fitdatachargedup = Corr2(datatag=tags[1],
tdata=range(T),
a=('a1:vec:qed:u', 'ao:vec:qed:u'),
b=('a1:vec:qed:u', 'ao:vec:qed:u'),
dE=('dE:vec:qed:u', 'dEo:vec:qed:u'),
s=(1., -1.)).fitfcn(fit.p)
fitdatachargedown = Corr2(datatag=tags[3],
tdata=range(T),
a=('a1:vec:qed:d', 'ao:vec:qed:d'),
b=('a1:vec:qed:d', 'ao:vec:qed:d'),
dE=('dE:vec:qed:d', 'dEo:vec:qed:d'),
s=(1., -1.)).fitfcn(fit.p)
for index in range(48):
if index >= tcut:
newdata[tags[1]] = np.append(newdata[tags[1]], 0.)
newdata[tags[3]] = np.append(newdata[tags[3]], 0.)
elif index > tstar:
newdata[tags[1]] = np.append(newdata[tags[1]],
fitdatachargedup[index])
newdata[tags[3]] = np.append(newdata[tags[3]],
fitdatachargedown[index])
w0 = gv.gvar('0.1715(9)')
w0overa = gv.gvar('1.1367(5)')
ZV = gv.gvar('0.9837(20)')
ZVqed = gv.gvar('0.999544(14)') * ZV
hbarc = 0.197326968
a = (w0 / w0overa) / hbarc
print('THIS IS THE INFORMATION CENTRE')
print(len(newdata[tags[0]]), len(newdata[tags[1]]), len(newdata[tags[2]]),
len(newdata[tags[3]]))
print('tmin, tstar', tmin, tstar)
#moments = g2.moments(newdata[tags[0]],Z=ZV,ainv=1/a,periodic=False)
#vpol = g2.vacpol(moments,order=(2,1))
vpol = g2.fourier_vacpol(newdata[tags[0]],
Z=ZV,
ainv=1 / a,
periodic=False)
unchargedamuu = g2.a_mu(vpol, 2 / 3.)
#moments = g2.moments(newdata[tags[1]],Z=ZVqed,ainv=1/a,periodic=False)
#vpol = g2.vacpol(moments,order=(2,1))
vpol = g2.fourier_vacpol(newdata[tags[1]],
Z=ZVqed,
ainv=1 / a,
periodic=False)
chargedamuu = g2.a_mu(vpol, 2 / 3.)
#moments = g2.moments(newdata[tags[2]],Z=ZV,ainv=1/a,periodic=False)
#vpol = g2.vacpol(moments,order=(2,1))
vpol = g2.fourier_vacpol(newdata[tags[2]],
Z=ZV,
ainv=1 / a,
periodic=False)
unchargedamud = g2.a_mu(vpol, 1 / 3.)
#moments = g2.moments(newdata[tags[3]],Z=ZVqed,ainv=1/a,periodic=False)
#vpol = g2.vacpol(moments,order=(2,1))
vpol = g2.fourier_vacpol(newdata[tags[3]],
Z=ZVqed,
ainv=1 / a,
periodic=False)
chargedamud = g2.a_mu(vpol, 1 / 3.)
d_rt = chargedamud / unchargedamud
u_rt = chargedamuu / unchargedamuu
amu_qcd = unchargedamud + unchargedamuu
amu_qcdqed = chargedamuu + chargedamud
amu_rt = amu_qcdqed / amu_qcd
amu_diff = (amu_qcdqed - amu_qcd) / amu_qcd
print('[d] a_mu[QCD+QED]||a_mu[QCD+QED]/a_mu[QCD]{0:>20}||{1}'.format(
chargedamud, d_rt))
print('[u] a_mu[QCD+QED]||a_mu[QCD+QED]/a_mu[QCD]{0:>20}||{1}'.format(
chargedamuu, u_rt))
print(
'\n[u+d] a_mu[QCD+QED]||a_mu[QCD]||ratio||diff\n{0:20}{1:20}{2:20}{3:20}'
.format(amu_qcdqed, amu_qcd, amu_rt, amu_diff))