def read_proton(pr):
# read data
p_up = c51.open_data(pr.data_loc['file_loc'], pr.data_loc['proton_spin_up'])
p_dn = c51.open_data(pr.data_loc['file_loc'], pr.data_loc['proton_spin_dn'])
pnp_up = c51.open_data(pr.data_loc['file_loc'], pr.data_loc['proton_np_spin_up'])
pnp_dn = c51.open_data(pr.data_loc['file_loc'], pr.data_loc['proton_np_spin_dn'])
p_savg = c51.ispin_avg(p_up, p_dn)
pnp_savg = c51.ispin_avg(pnp_up, pnp_dn)
p_avg = c51.parity_avg(p_savg, pnp_savg, phase=-1.0)
T = len(p_avg[0])
p_avg = p_avg[:, :T/2] # keep only first half of data ('folded' length)
if pr.plot_data_flag == 'on':
# folded correlator data
p_ss = p_avg[:,:,0,0]
p_ps = p_avg[:,:,3,0]
c51.scatter_plot(np.arange(len(p_ss[0])), c51.make_gvars(p_ss), 'proton ss folded')
c51.scatter_plot(np.arange(len(p_ps[0])), c51.make_gvars(p_ps), 'proton ps folded')
# effective mass
eff = c51.effective_plots(T)
meff_ss = eff.effective_mass(c51.make_gvars(p_ss)[1:], 1, 'cosh')
meff_ps = eff.effective_mass(c51.make_gvars(p_ps)[1:], 1, 'cosh')
xlim = [1, len(meff_ss)] #*2/5]
#ylim = [0.7, 1.1]
ylim = [0.3, 0.9]
#ylim = c51.find_yrange(meff_ss, xlim[0], xlim[1])
c51.scatter_plot(np.arange(len(meff_ss))+1, meff_ss, 'proton ss effective mass', xlim = xlim, ylim = ylim)
#ylim = c51.find_yrange(meff_ps, xlim[0], xlim[1])
c51.scatter_plot(np.arange(len(meff_ps))+1, meff_ps, 'proton ps effective mass', xlim = xlim, ylim = ylim)
# scaled correlator
E0 = pr.priors['proton']['E0'][0]
scaled_ss = eff.scaled_correlator(c51.make_gvars(p_ss), E0, phase=1.0)
scaled_ps = eff.scaled_correlator(c51.make_gvars(p_ps), E0, phase=1.0)
ylim = c51.find_yrange(scaled_ss, xlim[0], xlim[1]/2)
c51.scatter_plot(np.arange(len(scaled_ss)), scaled_ss, 'proton ss scaled correlator (take sqrt to get Z0_s)', xlim = xlim, ylim = ylim)
ylim = c51.find_yrange(scaled_ps, xlim[0], xlim[1]/2)
c51.scatter_plot(np.arange(len(scaled_ps)), scaled_ps, 'proton ps scaled correlator (divide by Z0_s to get Z0_p)', xlim = xlim, ylim = ylim)
plt.show()
return p_avg, T
def read_proton(pr):
# read data
p_up = c51.open_data(pr.data_loc['file_loc'], pr.data_loc['proton_spin_up'])
p_dn = c51.open_data(pr.data_loc['file_loc'], pr.data_loc['proton_spin_dn'])
pnp_up = c51.open_data(pr.data_loc['file_loc'], pr.data_loc['proton_np_spin_up'])
pnp_dn = c51.open_data(pr.data_loc['file_loc'], pr.data_loc['proton_np_spin_dn'])
p_savg = c51.ispin_avg(p_up, p_dn)
pnp_savg = c51.ispin_avg(pnp_up, pnp_dn)
p_avg = c51.parity_avg(p_savg, pnp_savg, phase=-1.0)
T = len(p_avg[0])
p_avg = p_avg[:, :T/2] # keep only first half of data ('folded' length)
if pr.plot_data_flag == 'on':
# folded correlator data
p_ss = p_avg[:,:,0,0]
p_ps = p_avg[:,:,3,0]
c51.scatter_plot(np.arange(len(p_ss[0])), c51.make_gvars(p_ss), 'proton ss folded')
c51.scatter_plot(np.arange(len(p_ps[0])), c51.make_gvars(p_ps), 'proton ps folded')
# effective mass
eff = c51.effective_plots(T)
meff_ss = eff.effective_mass(c51.make_gvars(p_ss)[1:], 1, 'cosh')
meff_ps = eff.effective_mass(c51.make_gvars(p_ps)[1:], 1, 'cosh')
xlim = [1, len(meff_ss)] #*2/5]
ylim = [0.6, 1.2]
#ylim = c51.find_yrange(meff_ss, xlim[0], xlim[1])
c51.scatter_plot(np.arange(len(meff_ss))+1, meff_ss, 'proton ss effective mass', xlim = xlim, ylim = ylim)
#ylim = c51.find_yrange(meff_ps, xlim[0], xlim[1])
c51.scatter_plot(np.arange(len(meff_ps))+1, meff_ps, 'proton ps effective mass', xlim = xlim, ylim = ylim)
# scaled correlator
E0 = pr.priors['proton']['E0'][0]
scaled_ss = eff.scaled_correlator(c51.make_gvars(p_ss), E0, phase=1.0)
scaled_ps = eff.scaled_correlator(c51.make_gvars(p_ps), E0, phase=1.0)
ylim = c51.find_yrange(scaled_ss, xlim[0], xlim[1])
c51.scatter_plot(np.arange(len(scaled_ss)), scaled_ss, 'proton ss scaled correlator (take sqrt to get Z0_s)', xlim = xlim, ylim = ylim)
ylim = c51.find_yrange(scaled_ps, xlim[0], xlim[1])
c51.scatter_plot(np.arange(len(scaled_ps)), scaled_ps, 'proton ps scaled correlator (divide by Z0_s to get Z0_p)', xlim = xlim, ylim = ylim)
return p_avg, T
def read_baryon(pr):
# read data
baryon = pr.baryon2pt
if baryon in ['proton', 'sigma', 'xi', 'lambda']:
corr_up = c51.open_data(pr.data_loc['file_loc'],
pr.data_loc[baryon + '_spin_up'])
corr_dn = c51.open_data(pr.data_loc['file_loc'],
pr.data_loc[baryon + '_spin_dn'])
corrnp_up = c51.open_data(pr.data_loc['file_loc'],
pr.data_loc[baryon + '_np_spin_up'])
corrnp_dn = c51.open_data(pr.data_loc['file_loc'],
pr.data_loc[baryon + '_np_spin_dn'])
# spin avg
corr = 0.5 * (corr_up + corr_dn)
corrnp = 0.5 * (corrnp_up + corrnp_dn)
elif baryon in ['delta', 'sigma_st', 'xi_st', 'omega']:
corr_upup = c51.open_data(pr.data_loc['file_loc'],
pr.data_loc[baryon + '_spin_upup'])
corr_up = c51.open_data(pr.data_loc['file_loc'],
pr.data_loc[baryon + '_spin_up'])
corr_dn = c51.open_data(pr.data_loc['file_loc'],
pr.data_loc[baryon + '_spin_dn'])
corr_dndn = c51.open_data(pr.data_loc['file_loc'],
pr.data_loc[baryon + '_spin_dndn'])
corrnp_upup = c51.open_data(pr.data_loc['file_loc'],
pr.data_loc[baryon + '_np_spin_upup'])
corrnp_up = c51.open_data(pr.data_loc['file_loc'],
pr.data_loc[baryon + '_np_spin_up'])
corrnp_dn = c51.open_data(pr.data_loc['file_loc'],
pr.data_loc[baryon + '_np_spin_dn'])
corrnp_dndn = c51.open_data(pr.data_loc['file_loc'],
pr.data_loc[baryon + '_np_spin_dndn'])
# spin avg
corr = 0.25 * (corr_upup + corr_up + corr_dn + corr_dndn)
corrnp = 0.25 * (corrnp_upup + corrnp_up + corrnp_dn + corrnp_dndn)
# parity avg
corr_avg = c51.parity_avg(corr, corrnp, phase=-1.0)
T = len(corr_avg[0])
corr_avg = corr_avg[:, :T /
2] # keep only first half of data ('folded' length)
if pr.plot_data_flag == 'on':
for src in range(len(corr_avg[0, 0, 0])):
for snk in range(len(corr_avg[0, 0])):
# folded correlator data
corr_i = corr_avg[:, :, snk, src]
#c51.scatter_plot(np.arange(len(corr_i[0])), c51.make_gvars(corr_i), '%s snk_%s src_%s folded' %(baryon,str(snk),str(src)))
# effective mass
eff = c51.effective_plots(T)
meff = eff.effective_mass(
c51.make_gvars(corr_i)[1:], 1, 'cosh')
xlim = [1, len(meff)]
ylim = c51.find_yrange(meff, xlim[0], xlim[1] * 2 / 5)
c51.scatter_plot(np.arange(len(meff)) + 1,
meff,
'%s snk_%s src_%s effective mass' %
(baryon, str(snk), str(src)),
xlim=xlim,
ylim=ylim)
# scaled correlator
E0 = pr.priors[baryon]['E0'][0]
scaled = eff.scaled_correlator(c51.make_gvars(corr_i),
E0,
phase=1.0)
ylim = c51.find_yrange(scaled, xlim[0], xlim[1] * 2 / 5)
c51.scatter_plot(
np.arange(len(scaled)),
scaled,
'%s snk_%s src_%s scaled correlator (take sqrt to get Z0_s)'
% (baryon, str(snk), str(src)),
xlim=xlim,
ylim=ylim)
plt.show()
return corr_avg, T
filename = 'l3248f211b580m00235m0647m831a_avg.h5' path = 'l3248f211b580m00235m0647m831/wf1p0_m51p3_l524_a53p5_smrw4p5_n60/spectrum/ml0p00211_ms0p0902/' datapath = path + 'proton/spin_up' data_up = c51.read_data(filename, datapath, 0, 0) datapath = path + 'proton/spin_dn' data_dn = c51.read_data(filename, datapath, 0, 0) data_pos = c51.ispin_avg(data_up, data_dn) #Read spin averaged negative parity proton datapath = path + 'proton_np/spin_up' data_up = c51.read_data(filename, datapath, 0, 0) datapath = path + 'proton_np/spin_dn' data_dn = c51.read_data(filename, datapath, 0, 0) data_neg = c51.ispin_avg(data_up, data_dn) #Parity average data_ss = c51.parity_avg(data_pos, data_neg, -1) datapath = path + 'proton/spin_up' data_up = c51.read_data(filename, datapath, 3, 0) datapath = path + 'proton/spin_dn' data_dn = c51.read_data(filename, datapath, 3, 0) data_pos = c51.ispin_avg(data_up, data_dn) #Read spin averaged negative parity proton datapath = path + 'proton_np/spin_up' data_up = c51.read_data(filename, datapath, 3, 0) datapath = path + 'proton_np/spin_dn' data_dn = c51.read_data(filename, datapath, 3, 0) data_neg = c51.ispin_avg(data_up, data_dn) #Parity average data_ps = c51.parity_avg(data_pos, data_neg, -1) ##READ SPIN AND PARITY AVG'D DATA
filename = 'l3248f211b580m00235m0647m831a_avg.h5' path = 'l3248f211b580m00235m0647m831/wf1p0_m51p3_l524_a53p5_smrw4p5_n60/spectrum/ml0p00211_ms0p0902/' datapath = path+'proton/spin_up' data_up = c51.read_data(filename, datapath, 0, 0) datapath = path+'proton/spin_dn' data_dn = c51.read_data(filename, datapath, 0, 0) data_pos = c51.ispin_avg(data_up, data_dn) #Read spin averaged negative parity proton datapath = path+'proton_np/spin_up' data_up = c51.read_data(filename, datapath, 0, 0) datapath = path+'proton_np/spin_dn' data_dn = c51.read_data(filename, datapath, 0, 0) data_neg = c51.ispin_avg(data_up, data_dn) #Parity average data_ss = c51.parity_avg(data_pos, data_neg, -1) datapath = path+'proton/spin_up' data_up = c51.read_data(filename, datapath, 3, 0) datapath = path+'proton/spin_dn' data_dn = c51.read_data(filename, datapath, 3, 0) data_pos = c51.ispin_avg(data_up, data_dn) #Read spin averaged negative parity proton datapath = path+'proton_np/spin_up' data_up = c51.read_data(filename, datapath, 3, 0) datapath = path+'proton_np/spin_dn' data_dn = c51.read_data(filename, datapath, 3, 0) data_neg = c51.ispin_avg(data_up, data_dn) #Parity average data_ps = c51.parity_avg(data_pos, data_neg, -1) ##READ SPIN AND PARITY AVG'D DATA
