Ejemplo n.º 1
0
def mres(pion_gv, etas_gv):
    prior = dict()
    prior['mres'] = gv.gvar(0.0, 1.0)
    x = np.arange(len(pion_gv))

    c51.scatter_plot(x, pion_gv)
    trange = dict()
    T = len(pion_gv) - 2
    trange['tmin'] = [2, 2]
    trange['tmax'] = [T, T]
    pionfit = c51.fitscript(trange,
                            pion_gv,
                            prior,
                            c51.mres_fitfcn,
                            result_flag='off')
    print "Pion"
    c51.stability_plot(pionfit, 'mres', 'pion')

    c51.scatter_plot(x, etas_gv)
    etasfit = c51.fitscript(trange,
                            etas_gv,
                            prior,
                            c51.mres_fitfcn,
                            result_flag='off')
    print "Etas"
    c51.stability_plot(etasfit, 'mres', 'kaon')
    #print kaonfit['post']
    return 0
Ejemplo n.º 2
0
def decay(pion_ss_ps_gv, kaon_ss_ps_gv):
    prior = dict()
    prior['Z0_s'] = gv.gvar(0.025, 0.01)
    prior['Z1_s'] = gv.gvar(0.025, 0.035)
    prior['Z2_s'] = gv.gvar(0.025, 0.035)
    prior['Z0_p'] = gv.gvar(0.27, 0.15)
    prior['Z1_p'] = gv.gvar(0.27, 0.35)
    prior['Z2_p'] = gv.gvar(0.27, 0.35)
    prior['E0'] = gv.gvar(0.23, 0.2)
    prior['E1'] = gv.gvar(0.0, 1.0)
    prior['E2'] = gv.gvar(0.0, 1.0)
    trange = dict()
    trange['tmin'] = [6, 6]
    trange['tmax'] = [20, 20]
    T = len(pion_ss_ps_gv)
    fitfcn = c51.fit_function(T=T, nstates=2)
    fit = c51.fitscript(trange,
                        pion_ss_ps_gv,
                        prior,
                        fitfcn.twopt_fitfcn_ss_ps,
                        sets=2,
                        result_flag='off')
    print "pion"
    c51.stability_plot(fit, 'Z0_p')
    c51.stability_plot(fit, 'E0')
    ml = 0.0158
    ms = 0.0902
    mres_pi = gv.gvar(0.0009633, 0.0000065)
    Z0_p = fit['post'][0]['Z0_p']
    E0 = fit['post'][0]['E0']
    fpi = Z0_p * np.sqrt(2.) * (2. * ml + 2. * mres_pi) / E0**(3. / 2.)
    print 'fpi:', fpi

    print "kaon"
    prior['Z0_s'] = gv.gvar(0.02, 0.01)
    prior['Z1_s'] = gv.gvar(0.02, 0.03)
    prior['Z2_s'] = gv.gvar(0.02, 0.03)
    prior['Z0_p'] = gv.gvar(0.2, 0.1)
    prior['Z1_p'] = gv.gvar(0.2, 0.3)
    prior['Z2_p'] = gv.gvar(0.2, 0.3)
    prior['E0'] = gv.gvar(0.404, 0.2)
    prior['E1'] = gv.gvar(0.0, 1.0)
    prior['E2'] = gv.gvar(0.0, 1.0)
    fit = c51.fitscript(trange,
                        kaon_ss_ps_gv,
                        prior,
                        fitfcn.twopt_fitfcn_ss_ps,
                        sets=2,
                        result_flag='off')
    c51.stability_plot(fit, 'Z0_p')
    c51.stability_plot(fit, 'E0')
    mres_kaon = gv.gvar(0.0006685, 0.0000044)
    Z0_p = fit['post'][0]['Z0_p']
    E0 = fit['post'][0]['E0']
    fk = Z0_p * np.sqrt(2.) * (ml + ms + mres_pi + mres_kaon) / E0**(3. / 2.)
    print 'fk:', fk
    fkfpi = fk / fpi
    print 'fk/fpi:', fkfpi
Ejemplo n.º 3
0
def decay(pion_ss_ps_gv, kaon_ss_ps_gv):
    prior = dict()
    prior['Z0_s'] = gv.gvar(0.025, 0.01)
    prior['Z1_s'] = gv.gvar(0.025, 0.035)
    prior['Z2_s'] = gv.gvar(0.025, 0.035)
    prior['Z0_p'] = gv.gvar(0.27, 0.15)
    prior['Z1_p'] = gv.gvar(0.27, 0.35)
    prior['Z2_p'] = gv.gvar(0.27, 0.35)
    prior['E0'] = gv.gvar(0.23, 0.2)
    prior['E1'] = gv.gvar(0.0, 1.0)
    prior['E2'] = gv.gvar(0.0, 1.0)
    trange = dict()
    trange['tmin'] = [6,6]
    trange['tmax'] = [20,20]
    T = len(pion_ss_ps_gv)
    fitfcn = c51.fit_function(T=T, nstates=2)
    fit = c51.fitscript(trange, pion_ss_ps_gv, prior, fitfcn.twopt_fitfcn_ss_ps, sets=2, result_flag='off')
    print "pion"
    c51.stability_plot(fit, 'Z0_p')
    c51.stability_plot(fit, 'E0')
    ml = 0.0158
    ms = 0.0902
    mres_pi = gv.gvar(0.0009633, 0.0000065)
    Z0_p = fit['post'][0]['Z0_p']
    E0 = fit['post'][0]['E0']
    fpi = Z0_p*np.sqrt(2.)*(2.*ml+2.*mres_pi)/E0**(3./2.)
    print 'fpi:', fpi

    print "kaon"
    prior['Z0_s'] = gv.gvar(0.02, 0.01)
    prior['Z1_s'] = gv.gvar(0.02, 0.03)
    prior['Z2_s'] = gv.gvar(0.02, 0.03)
    prior['Z0_p'] = gv.gvar(0.2, 0.1)
    prior['Z1_p'] = gv.gvar(0.2, 0.3)
    prior['Z2_p'] = gv.gvar(0.2, 0.3)
    prior['E0'] = gv.gvar(0.404, 0.2)
    prior['E1'] = gv.gvar(0.0, 1.0)
    prior['E2'] = gv.gvar(0.0, 1.0)
    fit = c51.fitscript(trange, kaon_ss_ps_gv, prior, fitfcn.twopt_fitfcn_ss_ps, sets=2, result_flag='off')
    c51.stability_plot(fit, 'Z0_p')
    c51.stability_plot(fit, 'E0')
    mres_kaon = gv.gvar(0.0006685, 0.0000044)
    Z0_p = fit['post'][0]['Z0_p']
    E0 = fit['post'][0]['E0']
    fk = Z0_p*np.sqrt(2.)*(ml+ms+mres_pi+mres_kaon)/E0**(3./2.)
    print 'fk:', fk
    fkfpi = fk/fpi
    print 'fk/fpi:', fkfpi
Ejemplo n.º 4
0
def mres(pion_gv, etas_gv):
    prior = dict()
    prior['mres'] = gv.gvar(0.0, 1.0)
    x = np.arange(len(pion_gv))
    
    c51.scatter_plot(x,pion_gv)
    trange = dict()
    T = len(pion_gv)-2
    trange['tmin'] = [2, 2]
    trange['tmax'] = [T, T]
    pionfit = c51.fitscript(trange, pion_gv, prior, c51.mres_fitfcn, result_flag='off')
    print "Pion"
    c51.stability_plot(pionfit,'mres','pion')

    c51.scatter_plot(x,etas_gv)
    etasfit = c51.fitscript(trange, etas_gv, prior, c51.mres_fitfcn, result_flag='off')
    print "Etas"
    c51.stability_plot(etasfit,'mres','kaon')
    #print kaonfit['post']
    return 0
Ejemplo n.º 5
0
#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')
c51.stability_plot(fit, 'Z0_s')
c51.stability_plot(fit, 'Z0_p')
plt.show()
Ejemplo n.º 6
0
#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')
c51.stability_plot(fit, 'Z0_s')
plt.show()