def __init__(self,
Info={},
thissym='Not Set',
thiscol='Not Set',
thisshift=0.0,
name='',
LLname='',
Auto=True):
## A infront of variable is for Ahmed file convention
## Initialising plotting parameters
self.thisshift = thisshift
self.thiscol = thiscol
self.thissym = thissym
# Opboot { it } bs
self.alphaAvg = ODNested()
self.alphaStd = ODNested()
## kappa up down (in integer form)
if 'kud' in list(Info.keys()): self.kud = 'kud' + str(Info['kud'])
else: self.kud = ''
## kappa strange (in integer form)
if 'ks' in list(Info.keys()): self.ks = 'ks' + str(Info['ks'])
else: self.ks = ''
## Current obersvables are TopCharge and Weinberg
if 'Observable' in list(Info.keys()): self.Observ = Info['Observable']
else: self.Observ = 'TopCharge' ## default to TopCharge
self.latparams = mp.LatticeParameters(Info=Info)
self.latparams.LoadPickle()
if self.Observ == 'TopCharge':
self.thisconv = chitcoeff(self.latparams.nt, self.latparams.nxyz,
self.latparams.latspace, 'QQ')
else:
self.thisconv = chitcoeff(self.latparams.nt, self.latparams.nxyz,
self.latparams.latspace, 'WW')
## Ahmed only gave me a single flow time result, this will be changed when he gives me all flow times.
if 'flowtime' in list(Info.keys()): self.flowtime = Info['flowtime']
else: self.flowtime = 't_f6.00' ## default to read all flow times
self.kappafolder = 'Kud0' + self.kud.replace(
'kud', '') + 'Ks0' + self.ks.replace('ks', '')
self.AObserv = self.Observ.lower().replace('weinberg', 'weinopp')
self.Akud = self.kud.replace('kud', 'K')[:-2]
self.Aflowtime = self.flowtime.replace('t_f', '').replace('.', '')
self.Auto = Auto
self.SetCustomName(name, LLname)
thisdir = outputdir + '/AhmedResults/'
if self.Auto:
self.readdir = thisdir + 'ratio_' + self.AObserv + '_' + self.Akud + '_at_flow_time_' + self.Aflowtime + '/'
else:
self.readdir = thisdir + 'ratio_boot_' + self.AObserv + '_' + self.Akud + '_at_flow_time_' + self.Aflowtime + '/'
self.thisfile = 'Tauint_at_flow_time_' + self.Aflowtime + 'time_value_dvalue.txt'
def SetMass(self, mass):
self.mass = ODNested()
if isinstance(mass, TwoPointCorr):
if 'boot' not in mass.C2_Fit_Stats:
raise IOError(
'C2_Fit_Stats in TwoPointCorr not calculated, please run Fit() on TwoPointCorr instance'
)
for (istate, ip), fitdata in mass.C2_Fit_Stats['boot'].items():
if ip != 'p000': continue
ifitr, this_data = fitdata.GetMaxFitr()
self.mass['C2_' + '_'.join([istate, ifitr])] = this_data.iloc[
0].fit_data['Params']['Energy']
elif isinstance(mass, Fitting):
if 'Energy' not in list(mass.fit_data['Params'].keys()):
print(list(mass.fit_data['Params'].keys()))
raise IOError('Fitting class instance has no parameter Energy')
self.mass['C2_' + mass.name] = mass.fit_data['Params']['Energy']
elif isinstance(mass, BootStrap):
self.mass['C2_' + mass.name] = mass
elif mass == 'Not Set':
self.mass = 'Not Set'
else:
raise IOError(
'mass input type not recognisied (see FormFactors.py, SetMass())'
)
list,vals = zip(*[[y,x] for y,x in sorted(zip(list,vals))])
list
vals
import numpy as np
str.zfill()
zfill(10)
n=5
print(f'{n:03}')
from MiscFuns import ODNested
print('abc',end='')
alpha = ODNested()
alpha['one']['two'] = 5
alpha.values()[0].values()[0]
from uncertainties import ufloat
this_val = ufloat(0.0005,0.0025)
print r'${:.1eSL}$'.format(this_val)
print 'a\rightarrow'.replace('\rightarrow','RIGHTARROW')
1.0 == 1.0000000000000001
xvalssize = (5,5)
xdata_1 = np.array([range(xvalssize[1]) for _ in range(xvalssize[0])])
xdata_2 = xdata_1.swapaxes(0,1).flatten()
xdata_1 = xdata_1.flatten()
def __init__(self,
Info={},
thissym='Not Set',
thiscol='Not Set',
thisshift=0.0,
name='',
LLname=''):
## A infront of variable is for Ahmed file convention
## Initialising plotting parameters
self.thisshift = thisshift
self.thiscol = thiscol
self.thissym = thissym
# Opboot { it } bs
self.Chi2Avg = ODNested()
self.Chi2Std = ODNested()
## kappa up down (in integer form)
if 'kud' in list(Info.keys()): self.kud = 'kud' + str(Info['kud'])
else: self.kud = ''
## kappa strange (in integer form)
if 'ks' in list(Info.keys()): self.ks = 'ks' + str(Info['ks'])
else: self.ks = ''
## Current obersvables are TopCharge and Weinberg
if 'Observable' in list(Info.keys()): self.Observ = Info['Observable']
else: self.Observ = 'TopCharge' ## default to TopCharge
self.latparams = mp.LatticeParameters(Info=Info)
self.latparams.LoadPickle()
if 'TopCharge' in self.Observ:
self.thisconv = chitcoeff(self.latparams.nt, self.latparams.nxyz,
self.latparams.latspace, 'QQ')
else:
self.thisconv = chitcoeff(self.latparams.nt, self.latparams.nxyz,
self.latparams.latspace, 'WW')
# ## this is used display only these flowtimes, Still reads and writes all
# if 'tflowlist' in Info.keys(): self.tflowlist = Info['tflowlist']
# else: self.tflowlist = defxlimOp ## default to read all flow times
# listout = []
# for ict,itflow in enumerate(self.tflowlist):
# if 't_f' not in str(itflow):
# listout.append(tflowstr(itflow))
# else:
# listout.append(itflow)
# self.tflowfloat = [untflowstr(itflow) for itflow in listout]
# self.tflowlist = np.array(listout)
self.kappafolder = 'Kud0' + self.kud.replace(
'kud', '') + 'Ks0' + self.ks.replace('ks', '')
if 'topcharge' in self.Observ.lower().replace('weinberg', 'weinopp'):
self.AObserv = 'topcharge'
elif 'weinopp' in self.Observ.lower().replace('weinberg', 'weinopp'):
self.AObserv = 'weinopp'
self.Akud = self.kud.replace('kud', '')[:-2]
self.SetCustomName(name, LLname)
thisdir = outputdir + '/AhmedResults/'
self.readdir = thisdir + self.AObserv + self.Akud + '/'
self.thisfile = self.AObserv + self.Akud + '.txt'
def Write(self):
def FixDictArray(thislist, ikey):
outDict = OrderedDict()
for ic, ilist in enumerate(thislist):
outDict[ikey + str(ic + 1)] = ilist
return outDict
self.outDict = ODNested()
self.outDict['Type'] = self.currtype
self.outDict['FFparams'] = FixDictArray(self.ffpars, 'FF')
self.outDict['tflowlist'] = FixDictArray(self.tflowlist, 'flow')
## TODO, output more information about momenta if you would like
self.outDict['nt'] = self.nt
self.outDict['nxyz'] = self.nxyz
self.outDict['q2max'] = self.qparams.mom2max
self.outDict['q2min'] = self.qparams.mom2min
self.outDict['pp2max'] = self.ppparams.mom2max
self.outDict['pp2min'] = self.ppparams.mom2min
excel_params = pa.Series(deepcopy(self.outDict))
firstkey = list(self.mass.keys())[0]
excel_params['massAvg_' + firstkey] = list(self.mass.values())[0].Avg
excel_params['massStd_' + firstkey] = list(self.mass.values())[0].Std
for icFF, iFF in excel_params['FFparams'].items():
excel_params[icFF] = iFF
for ictflow, itflow in excel_params['tflowlist'].items():
excel_params[ictflow] = itflow
del excel_params['FFparams']
del excel_params['tflowlist']
if self.doflow:
for itflow in self.tflowlist:
firstdata = list(self.alpha[itflow].values())[0]
if isinstance(firstdata, BootStrap):
excel_params['AlphaAvg_' + firstkey + '_' +
itflow] = firstdata.Avg
else:
excel_params['AlphaAvg_' + firstkey + '_' +
itflow] = firstdata
for itflow in self.tflowlist:
firstdata = list(self.alpha[itflow].values())[0]
if isinstance(firstdata, BootStrap):
excel_params['AlphaStd_' + firstkey + '_' +
itflow] = firstdata.Std
for ikey, massdata in self.mass.items():
if isinstance(massdata, BootStrap):
self.outDict['mass'][ikey] = AvgStdToFormat(
massdata.Avg, massdata.Std)
else:
self.outDict['mass'][ikey] = massdata
if self.doflow:
for itflow, alphatflow in self.alpha.items():
firstalpha = list(alphatflow.values())[0]
alpha_key = list(alphatflow.keys())[0]
if isinstance(firstalpha, BootStrap):
self.outDict['alpha'][alpha_key][itflow] = AvgStdToFormat(
firstalpha.Avg, firstalpha.Std)
else:
self.outDict['alpha'][alpha_key][itflow] = firstalpha
if self.doflow:
for (gammakey, ipp, iq, imass, itflow,
ipar), paramdata in self.items():
thisqsqrd = self.qparams.Getpsqrdform(iq, pre='q')
## TODO, this is incorrectly order with respect to qsqrd, need to write function to fix this somewhere
## also, you can play around with the ordering of keys to get the formating you like !!
# self.outDict[imass][ipp][itflow][self.qparams.Getpsqrdform(iq,pre='q')]['Coeff_of_'+ipar]['_'.join([gammakey,iq])] = AvgStdToFormat(paramdata.Avg,paramdata.Std)
try:
self.outDict['Equations'][imass][ipp][itflow][thisqsqrd][
'_'.join([gammakey, iq])] += ' (' + AvgStdToFormat(
paramdata.Avg, paramdata.Std, dec=5,
numlen=8) + ') ' + ipar + ' +'
except Exception as err:
self.outDict['Equations'][imass][ipp][itflow][thisqsqrd][
'_'.join([gammakey, iq])] = ' (' + AvgStdToFormat(
paramdata.Avg, paramdata.Std, dec=5,
numlen=8) + ') ' + ipar + ' +'
if ipar == self.ffpars[-1]:
self.outDict['Equations'][imass][ipp][itflow][thisqsqrd][
'_'.join([gammakey, iq])] = self.outDict['Equations'][
imass][ipp][itflow][thisqsqrd]['_'.join(
[gammakey, iq])][:-1]
else:
for (gammakey, ipp, iq, imass, ipar), paramdata in self.items():
thisqsqrd = self.qparams.Getpsqrdform(iq, pre='q')
## TODO, this is incorrectly order with respect to qsqrd, need to write function to fix this somewhere
## also, you can play around with the ordering of keys to get the formating you like !!
try:
self.outDict['Equations'][imass][ipp][thisqsqrd]['_'.join(
[gammakey, iq])] += ' (' + AvgStdToFormat(
paramdata.Avg, paramdata.Std, dec=5,
numlen=8) + ') ' + ipar + ' +'
except Exception as err:
self.outDict['Equations'][imass][ipp][thisqsqrd]['_'.join(
[gammakey, iq])] = ' (' + AvgStdToFormat(
paramdata.Avg, paramdata.Std, dec=5,
numlen=8) + ') ' + ipar + ' +'
if ipar == self.ffpars[-1]:
self.outDict['Equations'][imass][ipp][thisqsqrd]['_'.join([
gammakey, iq
])] = self.outDict['Equations'][imass][ipp][thisqsqrd][
'_'.join([gammakey, iq])][:-1]
if self.doflow:
for (gammakey, ipp, iq, imass, itflow,
ipar), paramdata in self.iteritemsRed():
thisqsqrd = self.qparams.Getpsqrdform(iq, pre='q')
## TODO, this is incorrectly order with respect to qsqrd, need to write function to fix this somewhere
## also, you can play around with the ordering of keys to get the formating you like !!
# self.outDict[imass][ipp][itflow][self.qparams.Getpsqrdform(iq,pre='q')]['Coeff_of_'+ipar]['_'.join([gammakey,iq])] = AvgStdToFormat(paramdata.Avg,paramdata.Std)
try:
self.outDict['Equations_Reduced'][imass][ipp][itflow][
thisqsqrd]['_'.join(
[gammakey, iq])] += ' (' + AvgStdToFormat(
paramdata.Avg, paramdata.Std, dec=5,
numlen=8) + ') ' + ipar + ' +'
except Exception as err:
self.outDict['Equations_Reduced'][imass][ipp][itflow][
thisqsqrd]['_'.join(
[gammakey, iq])] = ' (' + AvgStdToFormat(
paramdata.Avg, paramdata.Std, dec=5,
numlen=8) + ') ' + ipar + ' +'
if ipar == self.ffpars[-1]:
self.outDict['Equations_Reduced'][imass][ipp][itflow][
thisqsqrd]['_'.join([
gammakey, iq
])] = self.outDict['Equations_Reduced'][imass][ipp][
itflow][thisqsqrd]['_'.join([gammakey, iq])][:-1]
else:
for (gammakey, ipp, iq, imass,
ipar), paramdata in self.iteritemsRed():
thisqsqrd = self.qparams.Getpsqrdform(iq, pre='q')
## TODO, this is incorrectly order with respect to qsqrd, need to write function to fix this somewhere
## also, you can play around with the ordering of keys to get the formating you like !!
try:
self.outDict['Equations_Reduced'][imass][ipp][thisqsqrd][
'_'.join([gammakey, iq])] += ' (' + AvgStdToFormat(
paramdata.Avg, paramdata.Std, dec=5,
numlen=8) + ') ' + ipar + ' +'
except Exception as err:
self.outDict['Equations_Reduced'][imass][ipp][thisqsqrd][
'_'.join([gammakey, iq])] = ' (' + AvgStdToFormat(
paramdata.Avg, paramdata.Std, dec=5,
numlen=8) + ') ' + ipar + ' +'
if ipar == self.ffpars[-1]:
self.outDict['Equations_Reduced'][imass][ipp][thisqsqrd][
'_'.join([gammakey,
iq])] = self.outDict['Equations_Reduced'][
imass][ipp][thisqsqrd]['_'.join(
[gammakey, iq])][:-1]
## Write human readable file with data
WriteXml(self.HumanFile, {'Results': self.outDict})
WriteExcel(self.ExcelFile, {'FF_results': deepcopy(self.param_Stats)},
params=excel_params)
## pickles rest of data for reading
self.RemoveFuns()
WritePickle(self.PickleFile, self.__dict__)
self.GetFuns()
def SetAlpha(self, alpha, tflowlist):
self.alpha = ODNested()
self.tflowlist = tflowlist
if isinstance(alpha, NNQFullCorr):
# if self.kappafolder not in ['',alpha.kappafolder+'/']:
# raise IOError('kappa folders used in FormFact (from FormFactors.py) have changed, check alpha and mass used.')
# self.kappafolder = alpha.kappafolder + '/'
# self.SetCustomName(string=self.name)
if 'boot' not in alpha.NNQFull_Fit_Stats:
raise IOError(
'No fits have been performed on the AlphaFull object passed to Form Factors'
)
for itflow in tflowlist:
if ('p000',
itflow) not in alpha.NNQFull_Fit_Stats['boot'].index:
print(alpha.NNQFull_Fit_Stats['boot'])
raise IOError(
'No zero momentum found in NNQFull_Fit_Stats in TwoPointCorr, try running Fit()'
)
ifitr, this_data = alpha.NNQFull_Fit_Stats.at[(
'p000', itflow), 'boot'].GetMaxFitr()
ifitr = ifitr.replace('fittwor', 'tsumfitr')
self.alpha[itflow][
'alpha_' +
ifitr] = this_data.iloc[0].fit_data['Params'].iloc[0]
return
elif isinstance(alpha, NNQCorr):
# if self.kappafolder not in ['',alpha.kappafolder+'/']:
# raise IOError('kappa folders used in FormFact (from FormFactors.py) have changed, check alpha and mass used.')
# self.kappafolder = alpha.kappafolder + '/'
# self.SetCustomName(string=self.name)
if 'boot' not in alpha.NNQ_Fit_Stats:
raise IOError(
'No fits have been performed on the Alpha object passed to Form Factors'
)
for itflow in tflowlist:
if ('p000', itflow) not in alpha.NNQ_Fit_Stats['boot'].index:
print(alpha.NNQ_Fit_Stats['boot'])
raise IOError(
'No zero momentum found in NNQ_Fit_Stats in TwoPointCorr, try running Fit()'
)
ifitr, this_data = alpha.NNQ_Fit_Stats.at[('p000', itflow),
'boot'].GetMaxFitr()
self.alpha[itflow][
'alpha_' +
ifitr] = this_data.iloc[0].fit_data['Params'].iloc[0]
return
try:
firstflow = list(alpha.keys())[0]
if isinstance(alpha[firstflow], Fitting):
for itflow in tflowlist:
if itflow not in list(alpha.keys()):
raise IOError(
'No tflow found in alpha.keys(), alpha can be dictionary with tflows'
)
if 'Energy' not in list(alpha.fit_data['Params'].keys()):
print(list(alpha[itflow].fit_data['Params'].keys()))
raise IOError(
'Fitting class instance has no parameter Energy')
self.alpha[itflow][
'alpha_' +
alpha.name] = alpha.fit_data['Params'].iloc[0]
elif isinstance(alpha[firstflow], BootStrap):
for itflow in tflowlist:
if itflow not in list(alpha.keys()):
raise IOError(
'No tflow found in alpha.keys(), alpha can be dictionary with tflows'
)
self.alpha[itflow]['alpha_' + alpha.name] = alpha
except Exception as err:
if alpha == 'No Alpha' or alpha == 'PreDef':
self.alpha = 'Not Set'
elif self.alpha != 'Not Set':
print(type(alpha))
if isinstance(alpha, str):
print(alpha)
raise IOError(
'alpha input type not recognisied (see FormFactors.py, SetAlpha())'
)