def make_2d_histo(self, tmin = None, tmax = None):
# get data
a_data = analysis_data(self)
# time slice the data
dt = self.par['time_slice_width']*us # step width
# good data
tg = a_data.tg
Ag = a_data.Ag
# all pos. data
tp = a_data.tp
Ap = a_data.Ap
# 2d histogram setup
# y - aaxis
hy_min = self.par['h_min']
hy_max = self.par['h_max']
hy_bins = self.par['h_bins']
# x - axis
if tmin is None:
tmin = tp.min()
if tmax is None:
tmax = tp.max()
hx_bins = int((tmax - tmin)/dt) + 1
h_title = f'shot {self.par["shot"]}, channel = {self.par["channel"]}'
self.h2 = B.histo2d(tg, Ag, range = [[tmin,tmax],[hy_min,hy_max]], bins = [hx_bins, hy_bins],
title = h_title, xlabel = r't[$\mu$ s]', ylabel = 'fitted PH [V]')
self.h2p = B.histo2d(tp, Ap, range = [[tmin,tmax],[hy_min,hy_max]], bins = [hx_bins, hy_bins],
title = h_title, xlabel = r't[$\mu$ s]', ylabel = 'raw PH [V]')
#%%
cost_min = -1.0
cost_max = 1.0
bins_cost = 20
metappi0_min = 1.0
metappi0_max = 2.5
metappi0_binwidth = 50e-3 # bin width in GeV
bins_metappi0 = int((metappi0_max - metappi0_min) / metappi0_binwidth)
h2_ep_cost_weighted = B.histo2d(metappi0[sel][:],
cos_theta_etap_gj[sel][:],
bins=(bins_metappi0, bins_cost),
range=[[metappi0_min, metappi0_max],
[cost_min, cost_max]],
title="Angular distribution in GJ Frame",
weights=qf)
#%%
np.savez(
'/Users/rupeshdotel/analysis/work/pi0pippimeta/data/qfactor_data/qweights.npz',
qf=qf)
#%%
np.savez(
'/Users/rupeshdotel/analysis/work/pi0pippimeta/data/qfactor_data/qweights_2d.npz',
qf=qf)
#cost_pi0 = d['cost_pi0']
#pi0phiGJ = d['pi0phiGJ']
#etaprimephiGJ = d['etaprimephiGJ']
#%%
mep_bins = 18 # bins etaprime invariant mass
mp_bins = 12 # bins pi0 invariant mass
mep_min = 0.86 # left edge of etaprime invariant mass
mep_max = 1.05 # right edge of etaprime invariant mass
mp_min = 0.12 # left edge of pi0 invariant mass
mp_max = 0.15 # right edge of pi0 invariant mass
h_epi0 = B.histo2d(metap,
mpi0,
bins=(mep_bins, mp_bins),
range=np.array([(mep_min, mep_max), (mp_min, mp_max)]),
title='2D_prompt',
xlabel="$M(\pi^{+}\pi^{-}\eta)$",
ylabel="$M(\gamma\gamma)$")
epm = h_epi0.x_bin_center
pi0m = h_epi0.y_bin_center
def fit_histo(h2d):
#define empty lists for parameters and their errors from fits
A_a, x0_a, sigma_a, c0_a, b0_a = [], [], [], [], []
for i in range(h2d.nbins_y): # looping over pi0mass bins
h = h2d.project_x(bins=[i])
m_etappi0_gen = d['metaprimepi0']
cost_etap_gen = d['cos_theta']
#%%
cost_min = -1.0
cost_max = 1.0
bins_cost = 20
metappi0_min = 1.0
metappi0_max = 2.0
metappi0_binwidth = 50e-3 # bin width in GeV
bins_metappi0 = int((metappi0_max - metappi0_min) / metappi0_binwidth)
h2_ep_cost_ac = B.histo2d(m_etappi0_ac,
cost_etap_ac,
bins=(bins_metappi0, bins_cost),
range=[[metappi0_min, metappi0_max],
[cost_min, cost_max]],
title="Angular distribution in GJ Frame")
h2_ep_cost_gen = B.histo2d(m_etappi0_gen,
cost_etap_gen,
bins=(bins_metappi0, bins_cost),
range=[[metappi0_min, metappi0_max],
[cost_min, cost_max]],
title="Angular distribution in GJ Frame")
#%%
m_gen = B.histo(m_etappi0_gen, bins=100)
m_ac = B.histo(m_etappi0_ac, bins=100)
m_acceptance = m_ac / m_gen
selm = sel_winm & vetom
"""
#%%
h_mm2m = B.histo(mm2m, bins=30, title="missing mass squared")
h_etap = B.histo(metap[sel],
bins=24,
title="$\eta^{'}$",
xlabel="$M(\pi^{+}\pi^{-}\eta)")
h_etap_pi0 = B.histo2d(metap[sel],
mpi0[sel],
bins=24,
title=" pi0 vs etaprime Kinfit variables",
xlabel="$M(\pi^{+}\pi^{-}\eta)$",
ylabel="$M(\gamma\gamma)$")
h_etappi0 = B.histo(metappi0[sel],
bins=40,
title="$\eta'\pi^{0}$",
xlabel="$M(\eta^{'}\pi^{0})$")
h2_ep_cost = B.histo2d(metappi0[sel],
cost_etap[sel],
bins=(25, 25),
title="Angular distribution in GJ Frame",
xlabel="$M(\eta^{'}\pi^{0})$",
ylabel="$\cos\\theta_{GJ}$")
t_max = 0.7
bins_t = 15
be_min = 8.2
be_max = 8.8
bins_be = 15
metap_min = 0.85
metap_max = 1.05
metap_binwidth = 7e-3 # bin width in GeV
bins_metap = int((metap_max - metap_min) / metap_binwidth)
h2_etap_cost = B.histo2d(metap,
cost_etap_gj,
bins=(bins_metap, bins_cost),
range=[[metap_min, metap_max], [cost_min, cost_max]],
title="Angular dependence of etaprime signal",
xlabel="$M(\pi^{+}\pi^{-}\eta)$",
ylabel="$\cos\\theta_{GJ}$")
h2_etap_phi = B.histo2d(metap,
phi_etap_gj,
bins=(bins_metap, bins_phi),
range=[[metap_min, metap_max], [phi_min, phi_max]],
title="Angular dependence of etaprime signal",
xlabel="$M(\pi^{+}\pi^{-}\eta)$",
ylabel="$\\phi_{GJ}$")
h2_etap_mant = B.histo2d(metap,
mant,
bins=(bins_metap, bins_t),
mpi0p = d['pi0p_unique']
mpipp = d['pipp_unique']
num_combos = d['num_combos_unique']
combo_num = d['combo_number_unique']
dt = d['dt_unique']
event_num = d['event_num_unique']
kinfit_CL = d['kinfit_CL_unique']
chisq_ndf = d['chisq_ndf_unique']
#%%
xbin = 30
ybin = 18
h_epi0 = B.histo2d(metap,
mpi0,
bins=(xbin, ybin),
range=np.array([(0.86, 1.06), (0.12, 0.15)]),
title='2D_prompt',
xlabel="$M(\pi^{+}\pi^{-}\eta)$",
ylabel="$M(\gamma\gamma)$")
epm = h_epi0.x_bin_center
pi0m = h_epi0.y_bin_center
def fit_histo(epm=True):
#define empty lists for parameters and their errors from fits
Aa = []
Aa_err = []
X0 = []
X0_err = []
#%%
metap = d['metap']
metappi0 = d['metappi0']
cost_etap = d['cost_etap']
h_etap = B.histo(metap, bins = 32, title = "$M(\pi^{+}\pi^{-}\eta)$ Kinfit Variables (Mass constrained trees)")
h_etappi0 = B.histo(metappi0, bins = 40,
title = "$M(\eta^{'}\pi^{0})$ Kinfit Variables (Mass constrianed trees) ")
h2_ep_cost = B.histo2d(metappi0, cost_etap, bins = ( 25, 25 ),
title = "Angular distribution in GJ Frame",
xlabel = "$M(\eta^{'}\pi^{0})$", ylabel = "$\cos\\theta_{GJ}$" )
#%%
#read the ASCII data file
par = B.LT.parameterfile.pfile('/Users/rupeshdotel/analysis/work/gluexgit/data_files/data/sideband.data')
# load the parameters values
la = par.get_value('la'); lb = par.get_value('lb') # left sideband edges
ma = par.get_value('ma'); mb = par.get_value('mb') # edges for middle region
ra = par.get_value('ra'); rb = par.get_value('rb') # right sideband edges
#left band center
xlabel = "$M(\gamma\gamma)$")
# for etamass
hb_eta = B.histo(meta[sel], range = (0.48, 0.60), bins = 50, weights = qbe, title = 'bkg',
xlabel = "$M(\gamma\gamma)$")
hs_eta = B.histo(meta[sel], range = (0.48, 0.60), bins = 50, weights = qse, title = 'sig',
xlabel = "$M(\gamma\gamma)$")
ht_eta = B.histo(meta[sel], range = (0.48, 0.60), bins = 50, title = 'All',
xlabel = "$M(\gamma\gamma)$")
hs2 = B.histo2d(metap[sel], mpi0[sel], range = [[0.86, 1.06], [0.12, 0.15]],
bins = (20, 10), title = '2d_sig', weights = qsep*qsp*qse,
xlabel = "$M(\pi^{+}\pi^{-}\eta)$", ylabel = "$M(\gamma\gamma)$")
hb2 = B.histo2d(metap[sel], mpi0[sel], range = [[0.86, 1.06], [0.12, 0.15]],
bins = (20, 10), title = '2d_bkg', weights = qbep*qbp,
xlabel = "$M(\pi^{+}\pi^{-}\eta)$", ylabel = "$M(\gamma\gamma)$")
ht2 = B.histo2d(metap[sel], mpi0[sel], range = [[0.86, 1.06], [0.12, 0.15]], bins = (20, 10),
title = '2d_total', xlabel = "$M(\pi^{+}\pi^{-}\eta)$", ylabel = "$M(\gamma\gamma)$")
hs2_X_GJ = B.histo2d(metap_pi0[sel], cos_GJ_etap[sel], range = [[1.3, 3], [-1, 1]],
bins = (50, 40), title = '2d_sig_X_GJ', weights = qsep*qsp*qse,
xlabel = "$M(\eta^{'}\pi^{0})$", ylabel = "$cos\\theta_{GJ}$")
hb2_X_GJ = B.histo2d(metap_pi0[sel], cos_GJ_etap[sel], range = [[1.3, 3], [-1, 1]],
bins = (50, 40), title = '2d_bkg_X_GJ', weights = qbep*qbp,
xlabel = "$M(\eta^{'}\pi^{0})$", ylabel = "$cos\\theta_{GJ}$")
