def read_data(filename, dpath_pion, dpath_kaon, plot='off'):
pion = c51.open_data(filename, dpath_pion)
kaon = c51.open_data(filename, dpath_kaon)
#Fold meson data
pion = c51.fold(pion)
kaon = c51.fold(kaon)
pion_ss = c51.make_gvars(pion[:,:,0,0])
pion_ps = c51.make_gvars(pion[:,:,1,0])
kaon_ss = c51.make_gvars(kaon[:,:,0,0])
kaon_ps = c51.make_gvars(kaon[:,:,1,0])
if plot=='on':
dat = pion_ps
E0 = 0.237
meff = c51.effective_mass(dat,1,'cosh')
x = np.arange(len(meff))
xlim = [4,15]
ylim = c51.find_yrange(meff, xlim[0], xlim[1])
c51.scatter_plot(x, meff, 'meff', xlim = xlim, ylim = ylim)
scaled2pt = c51.scaled_correlator(dat, E0)
ylim = c51.find_yrange(scaled2pt, xlim[0], xlim[1])
c51.scatter_plot(x, scaled2pt, 'scaled 2pt', xlim=xlim, ylim=ylim)
ylim = c51.find_yrange(dat, xlim[0], xlim[1])
c51.scatter_plot(x, dat, 'data', xlim=xlim, ylim=ylim)
else: pass
pion_ss_ps = np.concatenate((pion[:,:,0,0],pion[:,:,1,0]), axis=1)
kaon_ss_ps = np.concatenate((kaon[:,:,0,0],kaon[:,:,1,0]), axis=1)
pion_ss_ps_gv = c51.make_gvars(pion_ss_ps)
kaon_ss_ps_gv = c51.make_gvars(kaon_ss_ps)
return pion_ss_ps_gv, kaon_ss_ps_gv
def read_data(filename, dpath_pion, dpath_kaon, plot='off'):
pion = c51.open_data(filename, dpath_pion)
kaon = c51.open_data(filename, dpath_kaon)
#Fold meson data
pion = c51.fold(pion)
kaon = c51.fold(kaon)
pion_ss = c51.make_gvars(pion[:, :, 0, 0])
pion_ps = c51.make_gvars(pion[:, :, 1, 0])
kaon_ss = c51.make_gvars(kaon[:, :, 0, 0])
kaon_ps = c51.make_gvars(kaon[:, :, 1, 0])
if plot == 'on':
dat = pion_ps
E0 = 0.237
meff = c51.effective_mass(dat, 1, 'cosh')
x = np.arange(len(meff))
xlim = [4, 15]
ylim = c51.find_yrange(meff, xlim[0], xlim[1])
c51.scatter_plot(x, meff, 'meff', xlim=xlim, ylim=ylim)
scaled2pt = c51.scaled_correlator(dat, E0)
ylim = c51.find_yrange(scaled2pt, xlim[0], xlim[1])
c51.scatter_plot(x, scaled2pt, 'scaled 2pt', xlim=xlim, ylim=ylim)
ylim = c51.find_yrange(dat, xlim[0], xlim[1])
c51.scatter_plot(x, dat, 'data', xlim=xlim, ylim=ylim)
else:
pass
pion_ss_ps = np.concatenate((pion[:, :, 0, 0], pion[:, :, 1, 0]), axis=1)
kaon_ss_ps = np.concatenate((kaon[:, :, 0, 0], kaon[:, :, 1, 0]), axis=1)
pion_ss_ps_gv = c51.make_gvars(pion_ss_ps)
kaon_ss_ps_gv = c51.make_gvars(kaon_ss_ps)
return pion_ss_ps_gv, kaon_ss_ps_gv
import c51lib as c51
import matplotlib.pyplot as plt
#Read meson data
filename = 'l2464f211b600m0102m0509m635a_avg.h5'
datapath = 'l2464f211b600m0102m0509m635/wf1p0_m51p2_l58_a51p5_smrw5p0_n75/spectrum/ml0p0126_ms0p0693/pion/corr'
data_ss = c51.read_data(filename, datapath, 0, 0)
data_ps = c51.read_data(filename, datapath, 1, 0)
data = np.concatenate((data_ss, data_ps), axis=1)
data = c51.make_gvars(data)
#data = data_ps
#Plot effective mass
T = len(data) * 0.5
meff = c51.effective_mass(data, 1)
x = np.arange(len(meff))
ylim = c51.find_yrange(meff, 1, 10)
#ylim = [0.47, 0.57]
xr = [1, 15]
c51.scatter_plot(x, meff, 'effective mass', xlim=[xr[0], xr[1]], ylim=ylim)
#ylim = c51.find_yrange(meff, 65, 79)
c51.scatter_plot(x,
meff,
'effective mass ps',
xlim=[T + xr[0], T + xr[1]],
ylim=ylim)
#Fit
inputs = c51.read_yaml('temp.yml')
prior = c51.dict_of_tuple_to_gvar(inputs['prior'])
##READ SPIN AND PARITY AVG'D DATA
#filename = 'l2464f211b600m0102m0509m635_tune_avg.h5'
#datapath = 'prot_w6p1_n94'
#datapath = 'prot_w5p6_n94'
filename = 'l2464f211b600m0102m0509m635a_avg.h5'
datapath = 'l2464f211b600m0102m0509m635/wf1p0_m51p2_l58_a51p5_smrw5p0_n75/spectrum/ml0p0126_ms0p0693/pion/corr'
data_ss = c51.read_data(filename, datapath, 0, 0)
data_ps = c51.read_data(filename, datapath, 3, 0)
data = np.concatenate((data_ss, data_ps), axis=1)
data = c51.make_gvars(data)
#data = data_ps
#Plot effective mass
T = len(data)*0.5
meff = c51.effective_mass(data, 1)
x = np.arange(len(meff))
ylim = c51.find_yrange(meff, 1, 10)
#ylim = [0.47, 0.57]
xr = [1,15]
c51.scatter_plot(x, meff, 'effective mass', xlim=[xr[0],xr[1]], ylim=ylim)
#ylim = c51.find_yrange(meff, 65, 79)
c51.scatter_plot(x, meff, 'effective mass ps', xlim=[T+xr[0],T+xr[1]], ylim=ylim)
#Fit
inputs = c51.read_yaml('temp.yml')
prior = c51.dict_of_tuple_to_gvar(inputs['prior'])
trange = inputs['trange']
fitfcn = c51.fit_function(T, nstates=2)
fit = c51.fitscript(trange, data, prior, fitfcn.twopt_fitfcn_ss_ps, sets=2, result_flag='on')
c51.stability_plot(fit, 'E0')
