for s in ms: decay_params['decay_ward_fit']['ms'] = s ss, ps = decay.read_decay_bs(psql,decay_params,'kaon') x_list['ss_%s_%s' %(str(m),str(s))] = len(data[0]) + np.arange(len(ss[0])) data = np.concatenate((data,ss), axis=1) x_list['ps_%s_%s' %(str(m),str(s))] = len(data[0]) + np.arange(len(ps[0])) data = np.concatenate((data,ps), axis=1) # make gvars data_gv = c51.make_gvars(data) ### fit ### result = dict() # mres for m in ml: gv_mp = data_gv[x_list['mp_%s' %str(m)]] gv_pp = data_gv[x_list['pp_%s' %str(m)]] fit = decay.fit_mres_bs(psql,decay_params,m,gv_mp,gv_pp)['mres_fit'] result['mres_%s' %str(m)] = fit for s in ms: gv_mp = data_gv[x_list['mp_%s' %str(s)]] gv_pp = data_gv[x_list['pp_%s' %str(s)]] fit = decay.fit_mres_bs(psql,decay_params,s,gv_mp,gv_pp)['mres_fit'] result['mres_%s' %str(s)] = fit # mesons for m in ml: decay_params['decay_ward_fit']['ml'] = m gv_SS = data_gv[x_list['ss_%s_%s' %(str(m),str(m))]] gv_PS = data_gv[x_list['ps_%s_%s' %(str(m),str(m))]] fit = decay.fit_decay_bs(psql,decay_params,'pion', gv_SS, gv_PS)['meson_fit'] result['meson_%s_%s' %(str(m),str(m))] = fit for s in ms: decay_params['decay_ward_fit']['ms'] = s
(mpl, ppl, mps, pps, ss_pion, ps_pion, ss_kaon, ps_kaon), axis=1) # correlated covariance gvboot0 = c51.make_gvars(boot0) # split for projects gvmpl = gvboot0[x_mpl] gvppl = gvboot0[x_ppl] gvmps = gvboot0[x_mps] gvpps = gvboot0[x_pps] gvss_pion = gvboot0[x_ss_pion] gvps_pion = gvboot0[x_ps_pion] gvss_kaon = gvboot0[x_ss_kaon] gvps_kaon = gvboot0[x_ps_kaon] # fit # # mres mresl = decay.fit_mres_bs(psql, decay_params, decay_params['decay_ward_fit']['ml'], gvmpl, gvppl) mress = decay.fit_mres_bs(psql, decay_params, decay_params['decay_ward_fit']['ms'], gvmps, gvpps) # meson pionfit = decay.fit_decay_bs(psql, decay_params, 'pion', gvss_pion, gvps_pion, flow=True) kaonfit = decay.fit_decay_bs(psql, decay_params, 'kaon', gvss_kaon,
# split to different project subsets gvlmp = gvboot0[x_lmp] gvlpp = gvboot0[x_lpp] gvsmp = gvboot0[x_smp] gvspp = gvboot0[x_spp] gvss_pion = gvboot0[x_ss_pion] gvps_pion = gvboot0[x_ps_pion] gvss_kaon = gvboot0[x_ss_kaon] gvps_kaon = gvboot0[x_ps_kaon] gvll = gvboot0[x_ll] gvls = gvboot0[x_ls] gvgAboot0 = gvboot0[x_gAboot0] # fit # # mres mresl = decay.fit_mres_bs(psql, decay_params, decay_params['decay_ward_fit']['ml'], gvlmp, gvlpp) mress = decay.fit_mres_bs(psql, decay_params, decay_params['decay_ward_fit']['ml'], gvsmp, gvspp) # meson #pifit = decay.fit_decay_bs(psql,decay_params,'pion',gvss_pion,gvps_pion) #kafit = decay.fit_decay_bs(psql,decay_params,'kaon',gvss_kaon,gvps_kaon) # axial aldata = np.concatenate((gvss_pion, gvps_pion, gvll)) alfit = axial.fit_axial(psql, axial_params, decay_params, 'axial_ll', aldata, flow=True) #,pifit['meson_fit'].p)
print "len ss_pion:", np.shape(ss_pion) print "len ps_pion:", np.shape(ps_pion) print "len gAboot0:", np.shape(gAboot0) # concatenate boot0 = np.concatenate((mp,pp,ss_pion,ps_pion,gAboot0),axis=1) # correlated covariance gvboot0 = c51.make_gvars(boot0) # split to different project subsets gvmp = gvboot0[x_mp] gvpp = gvboot0[x_pp] gvss_pion = gvboot0[x_ss_pion] gvps_pion = gvboot0[x_ps_pion] gvgAboot0 = gvboot0[x_gAboot0] # fit # # mres mresl = decay.fit_mres_bs(psql,decay_params,decay_params['decay_ward_fit']['ml'],gvmp,gvpp) # meson pifit = decay.fit_decay_bs(psql,decay_params,'pion',gvss_pion,gvps_pion) # mN and gA #gAfit = gA.fit_gA(psql,gA_params,gvgAboot0) gAfit = gA.fit_proton(psql,gA_params,gvgAboot0) # chipt parameters priors = gv.BufferDict() priors['mpi'] = pifit['meson_fit'].p['E0'] priors['fpi'] = decay.decay_constant(decay_params,pifit['meson_fit'].p['Z0_p'],pifit['meson_fit'].p['E0'],mresl['mres_fit'].p['mres']) #priors['mN'] = gAfit['gA_fit'].p['E0'] priors['mN'] = gAfit['nucleon_fit'].p['E0'] print priors #print gv.evalcorr([pifit['meson_fit'].p['E0'],decay.decay_constant(decay_params,pifit['meson_fit'].p['Z0_p'],pifit['meson_fit'].p['E0'],mresl['mres_fit'].p['mres']),gAfit['gA_fit'].p['E0'],gAfit['gA_fit'].p['gA00']]) print priors['mN']/priors['fpi'] data = gv.BufferDict()