import os
import pickle
import numpy as np
import sys
mother_ID=['Ds','Dplus','both']
meson_ID =['pi','X']
l_flv = ['e','mu']
data_type = ['MC','data']
mag_status =['Up','Down']
tree_name = 'Ds_OfflineTree/DecayTree'
def sel_eff(tp,threshold):
sig_eps = np.float(np.where(tp>threshold)[0].shape[0])/np.float(tp.shape[0])
return sig_eps
def load_datasets(l_index):
if sys.version_info[0]>2:
data_index=0
with open('/disk/lhcb_data/davide/Rphipi/BDT_training/'+l_flv[l_index]+l_flv[l_index]+'/'+data_type[data_index]+'_for_BDT_training_Ds_'+l_flv[l_index]+l_flv[l_index]+'.pickle', 'rb') as f:
MC_Ds_sig_dict=pickle.load(f, encoding='latin1')
data_index=0
with open('/disk/lhcb_data/davide/Rphipi/BDT_training/'+l_flv[l_index]+l_flv[l_index]+'/'+data_type[data_index]+'_for_BDT_training_Dplus_'+l_flv[l_index]+l_flv[l_index]+'.pickle', 'rb') as f:
MC_Dplus_sig_dict=pickle.load(f, encoding='latin1')
data_index=1
with open('/disk/lhcb_data/davide/Rphipi/BDT_training/'+l_flv[l_index]+l_flv[l_index]+'/'+data_type[data_index]+'_for_BDT_training_'+l_flv[l_index]+l_flv[l_index]+'.pickle', 'rb') as f:
data_bkg_dict=pickle.load(f, encoding='latin1')
else:
data_index=0
with open('/disk/lhcb_data/davide/Rphipi/BDT_training/'+l_flv[l_index]+l_flv[l_index]+'/'+data_type[data_index]+'_for_BDT_training_Ds_'+l_flv[l_index]+l_flv[l_index]+'.pickle', 'rb') as f:
MC_Ds_sig_dict=pickle.load(f)#, encoding='latin1')
data_index=0
with open('/disk/lhcb_data/davide/Rphipi/BDT_training/'+l_flv[l_index]+l_flv[l_index]+'/'+data_type[data_index]+'_for_BDT_training_Dplus_'+l_flv[l_index]+l_flv[l_index]+'.pickle', 'rb') as f:
MC_Dplus_sig_dict=pickle.load(f)#, encoding='latin1')
data_index=1
with open('/disk/lhcb_data/davide/Rphipi/BDT_training/'+l_flv[l_index]+l_flv[l_index]+'/'+data_type[data_index]+'_for_BDT_training_'+l_flv[l_index]+l_flv[l_index]+'.pickle', 'rb') as f:
data_bkg_dict=pickle.load(f)#, encoding='latin1')
return MC_Dplus_sig_dict, MC_Ds_sig_dict, data_bkg_dict
def extract_array(event_dict, branches_needed, features, examples):
extracted = np.array(
[np.zeros(shape=features) for i in range(examples)]
)
for event in range(examples):
for i, key in enumerate(branches_needed):
extracted[event][i]=event_dict[key][event]
return extracted
def add_labels(ndarray, signal=True):
if signal==True:
labeled_ndarray=np.concatenate((ndarray, np.ones(shape=(ndarray.shape[0],1))), axis =1)
elif signal==False:
labeled_ndarray=np.concatenate((ndarray, np.zeros(shape=(ndarray.shape[0],1))), axis =1)
return labeled_ndarray
def to_one_hot(labels):
temp = np.zeros(shape=(labels.shape[0],2))
for i in range(labels.shape[0]):
if labels[i]==0:
temp[i][0]=1
else:
temp[i][1]=1
return temp
def k_subsets(i, k, X, Y_labels):
train_size, dim=X.shape
#divide in k subsets and strip out the Ds_mass branch
k_batch_size = train_size//k
X_dict={}
Y_dict={}
for b in range(k):
X_dict[b]=X[k_batch_size*b:k_batch_size*(b+1)]
Y_dict[b]=Y_labels[k_batch_size*b:k_batch_size*(b+1)]
k_range=np.arange(k)
X_test = X_dict[i][:,0:dim-1]
Y_test = Y_dict[i][:,0:dim-1]
k_subset=np.delete(k_range, i)
X_train = np.concatenate([X_dict[j][:,0:dim-1] for j in k_subset],axis=0)
Y_train = np.concatenate([Y_dict[j][:,0:dim-1] for j in k_subset],axis=0)
return X_train, Y_train, X_test, Y_test, X_dict, Y_dict
def return_branches(data_index=None, mother_index=None, l_index=None, meson_index=None):
if data_index==0:
if l_index==1:
branches_needed = [
#________________________________________
#D MC true info
mother_ID[mother_index]+'_MC_MOTHER_ID',
mother_ID[mother_index]+'_BKGCAT',
mother_ID[mother_index]+'_TRUEID',
#________________________________________
#D Geometric variables, pT and FD
mother_ID[mother_index]+"_ENDVERTEX_CHI2",
mother_ID[mother_index]+"_ENDVERTEX_NDOF",
mother_ID[mother_index]+"_IPCHI2_OWNPV",
mother_ID[mother_index]+"_OWNPV_CHI2",
mother_ID[mother_index]+"_OWNPV_NDOF",
mother_ID[mother_index]+"_IP_OWNPV",
mother_ID[mother_index]+"_DIRA_OWNPV",
mother_ID[mother_index]+"_PX",
mother_ID[mother_index]+"_PY",
mother_ID[mother_index]+"_PZ",
mother_ID[mother_index]+"_PT",
mother_ID[mother_index]+"_FD_OWNPV",
mother_ID[mother_index]+"_FDCHI2_OWNPV",
#D Reconstructed mass
mother_ID[mother_index]+"_ConsD_M",
#D Trigger variables
mother_ID[mother_index]+"_Hlt1TrackMVADecision_TOS",
mother_ID[mother_index]+"_Hlt2RareCharmD2Pi"+l_flv[l_index].capitalize()+l_flv[l_index].capitalize()+"OSDecision_TOS",
mother_ID[mother_index]+"_Hlt2Phys_TOS",
#________________________________________
#PHI MC TRUE INFO
'phi_MC_MOTHER_ID',
'phi_BKGCAT',
'phi_TRUEID',
#________________________________________
#phi geometric variables, pT and FD
"phi_ENDVERTEX_CHI2",
"phi_ENDVERTEX_NDOF",
"phi_IPCHI2_OWNPV",
#"phi_OWNPV_CHI2",
#"phi_OWNPV_NDOF",
#"phi_IP_OWNPV",
#"phi_DIRA_OWNPV",
"phi_PT",
#phi Reconstructed mass
"phi_M",
#________________________________________
#PION
#Pion mother ID and bkg cat
meson_ID[meson_index]+'_MC_MOTHER_ID',
meson_ID[meson_index]+'_TRUEID',
#_____________________________________
#pi Geometric variables and pT
#"pi_OWNPV_CHI2",
#"pi_OWNPV_NDOF",
#'pi_IP_OWNPV',
meson_ID[meson_index]+"_PX",
meson_ID[meson_index]+"_PY",
meson_ID[meson_index]+"_PZ",
meson_ID[meson_index]+'_PT',
#pi PID variables
"pi_MC15TuneV1_ProbNNpi",
#________________________________________
#LEPTONS
l_flv[l_index]+'_plus_MC_MOTHER_ID',
l_flv[l_index]+'_plus_TRUEID',
l_flv[l_index]+'_minus_MC_MOTHER_ID',
l_flv[l_index]+'_minus_TRUEID',
#________________________________________
#leptons Geometric variables and pT
l_flv[l_index]+"_plus_OWNPV_CHI2",
#l_flv[l_index]+"_plus_OWNPV_NDOF",
l_flv[l_index]+"_minus_OWNPV_CHI2",
#l_flv[l_index]+"_minus_OWNPV_NDOF",
#
#l_flv[l_index]+"_plus_IP_OWNPV",
#l_flv[l_index]+"_minus_IP_OWNPV",
l_flv[l_index]+"_plus_PX",
l_flv[l_index]+"_plus_PY",
l_flv[l_index]+"_plus_PZ",
l_flv[l_index]+"_minus_PX",
l_flv[l_index]+"_minus_PY",
l_flv[l_index]+"_minus_PZ",
l_flv[l_index]+"_plus_PT",
l_flv[l_index]+"_minus_PT",
#leptons PID variables
l_flv[l_index]+"_plus_MC15TuneV1_ProbNN"+l_flv[l_index],
l_flv[l_index]+"_minus_MC15TuneV1_ProbNN"+l_flv[l_index],
]
if l_index==0:
branches_needed = [
#________________________________________
#D MC true info
mother_ID[mother_index]+'_MC_MOTHER_ID',
mother_ID[mother_index]+'_BKGCAT',
mother_ID[mother_index]+'_TRUEID',
#________________________________________
#D Geometric variables, pT and FD
mother_ID[mother_index]+"_ENDVERTEX_CHI2",
mother_ID[mother_index]+"_ENDVERTEX_NDOF",
mother_ID[mother_index]+"_IPCHI2_OWNPV",
mother_ID[mother_index]+"_OWNPV_CHI2",
mother_ID[mother_index]+"_OWNPV_NDOF",
mother_ID[mother_index]+"_IP_OWNPV",
mother_ID[mother_index]+"_DIRA_OWNPV",
mother_ID[mother_index]+"_PX",
mother_ID[mother_index]+"_PY",
mother_ID[mother_index]+"_PZ",
mother_ID[mother_index]+"_PT",
mother_ID[mother_index]+"_FD_OWNPV",
mother_ID[mother_index]+"_FDCHI2_OWNPV",
#D Reconstructed mass
mother_ID[mother_index]+"_ConsD_M",
#D Trigger variables
mother_ID[mother_index]+"_Hlt1TrackMVADecision_TOS",
mother_ID[mother_index]+"_Hlt2RareCharmD2Pi"+l_flv[l_index].capitalize()+l_flv[l_index].capitalize()+"OSDecision_TOS",
mother_ID[mother_index]+"_Hlt2Phys_TOS",
#________________________________________
#PHI MC TRUE INFO
'phi_MC_MOTHER_ID',
'phi_BKGCAT',
'phi_TRUEID',
#________________________________________
#phi geometric variables, pT and FD
"phi_ENDVERTEX_CHI2",
"phi_ENDVERTEX_NDOF",
"phi_IPCHI2_OWNPV",
#"phi_OWNPV_CHI2",
#"phi_OWNPV_NDOF",
#"phi_IP_OWNPV",
#"phi_DIRA_OWNPV",
"phi_PT",
#phi Reconstructed mass
"phi_M",
#________________________________________
#PION
#Pion mother ID and bkg cat
meson_ID[meson_index]+'_MC_MOTHER_ID',
meson_ID[meson_index]+'_TRUEID',
#_____________________________________
#pi Geometric variables and pT
#"pi_OWNPV_CHI2",
#"pi_OWNPV_NDOF",
#'pi_IP_OWNPV',
meson_ID[meson_index]+"_PX",
meson_ID[meson_index]+"_PY",
meson_ID[meson_index]+"_PZ",
meson_ID[meson_index]+'_PT',
#pi PID variables
"pi_MC15TuneV1_ProbNNpi",
#________________________________________
#LEPTONS
l_flv[l_index]+'_plus_MC_MOTHER_ID',
l_flv[l_index]+'_plus_TRUEID',
l_flv[l_index]+'_minus_MC_MOTHER_ID',
l_flv[l_index]+'_minus_TRUEID',
#________________________________________
#leptons Geometric variables and pT
l_flv[l_index]+"_plus_OWNPV_CHI2",
#l_flv[l_index]+"_plus_OWNPV_NDOF",
l_flv[l_index]+"_minus_OWNPV_CHI2",
#l_flv[l_index]+"_minus_OWNPV_NDOF",
#
#l_flv[l_index]+"_plus_IP_OWNPV",
#l_flv[l_index]+"_minus_IP_OWNPV",
l_flv[l_index]+"_plus_PX",
l_flv[l_index]+"_plus_PY",
l_flv[l_index]+"_plus_PZ",
l_flv[l_index]+"_plus_PT",
l_flv[l_index]+"_minus_PX",
l_flv[l_index]+"_minus_PY",
l_flv[l_index]+"_minus_PZ",
l_flv[l_index]+"_minus_PT",
#leptons PID variables
l_flv[l_index]+"_plus_MC15TuneV1_ProbNN"+l_flv[l_index],
l_flv[l_index]+"_minus_MC15TuneV1_ProbNN"+l_flv[l_index],
]
if data_index==1:
branches_needed = [
#________________________________
#D Geometric variables, pT and FD
mother_ID[mother_index]+"_ENDVERTEX_CHI2",
mother_ID[mother_index]+"_ENDVERTEX_NDOF",
mother_ID[mother_index]+"_IPCHI2_OWNPV",
mother_ID[mother_index]+"_OWNPV_CHI2",
mother_ID[mother_index]+"_OWNPV_NDOF",
mother_ID[mother_index]+"_IP_OWNPV",
mother_ID[mother_index]+"_DIRA_OWNPV",
mother_ID[mother_index]+"_PX",
mother_ID[mother_index]+"_PY",
mother_ID[mother_index]+"_PZ",
mother_ID[mother_index]+"_PT",
mother_ID[mother_index]+"_FD_OWNPV",
mother_ID[mother_index]+"_FDCHI2_OWNPV",
#D Reconstructed mass
mother_ID[mother_index]+"_ConsD_M",
#D Trigger variables
mother_ID[mother_index]+"_Hlt1TrackMVADecision_TOS",
mother_ID[mother_index]+"_Hlt2RareCharmD2Pi"+l_flv[l_index].capitalize()+l_flv[l_index].capitalize()+"OSDecision_TOS",
mother_ID[mother_index]+"_Hlt2Phys_TOS",
#________________________________________
#phi geometric variables, pT and FD
"phi_ENDVERTEX_CHI2",
"phi_ENDVERTEX_NDOF",
"phi_IPCHI2_OWNPV",
#"phi_OWNPV_CHI2",
#"phi_OWNPV_NDOF",
#"phi_IP_OWNPV",
#"phi_DIRA_OWNPV",
"phi_PT",
#phi Reconstructed mass
"phi_M",
#________________________________________
#PION
#_____________________________________
#pi Geometric variables and pT
#"pi_OWNPV_CHI2",
#"pi_OWNPV_NDOF",
#'pi_IP_OWNPV',
meson_ID[meson_index]+"_PX",
meson_ID[meson_index]+"_PY",
meson_ID[meson_index]+"_PZ",
meson_ID[meson_index]+'_PT',
#pi PID variables
"pi_MC15TuneV1_ProbNNpi",
#________________________________________
#LEPTONS
#________________________________________
#leptons Geometric variables and pT
l_flv[l_index]+"_plus_OWNPV_CHI2",
#l_flv[l_index]+"_plus_OWNPV_NDOF",
l_flv[l_index]+"_minus_OWNPV_CHI2",
#l_flv[l_index]+"_minus_OWNPV_NDOF",
#
#l_flv[l_index]+"_plus_IP_OWNPV",
#l_flv[l_index]+"_minus_IP_OWNPV",
l_flv[l_index]+"_plus_PX",
l_flv[l_index]+"_plus_PY",
l_flv[l_index]+"_plus_PZ",
l_flv[l_index]+"_plus_PT",
l_flv[l_index]+"_minus_PX",
l_flv[l_index]+"_minus_PY",
l_flv[l_index]+"_minus_PZ",
l_flv[l_index]+"_minus_PT",
#leptons PID variables
l_flv[l_index]+"_plus_MC15TuneV1_ProbNN"+l_flv[l_index],
l_flv[l_index]+"_minus_MC15TuneV1_ProbNN"+l_flv[l_index],
]
return branches_needed
def return_branches_BDT(mother_index=None, l_index=None, meson_index=None):
if l_index==1:
branches_needed = [
#________________________________
#D Geometric variables, pT and FD
mother_ID[mother_index]+"_ENDVERTEX_CHI2",
mother_ID[mother_index]+"_IPCHI2_OWNPV",
#mother_ID[mother_index]+"_OWNPV_CHI2",
#mother_ID[mother_index]+"_IP_OWNPV",
mother_ID[mother_index]+"_DIRA_OWNPV",
mother_ID[mother_index]+"_PT",
#mother_ID[mother_index]+"_FD_OWNPV",
mother_ID[mother_index]+"_FDCHI2_OWNPV",
#________________________________________
#phi geometric variables, pT and FD
#"phi_ENDVERTEX_CHI2",
"phi_IPCHI2_OWNPV",
#"phi_OWNPV_CHI2",
#"phi_OWNPV_NDOF",
#"phi_IP_OWNPV",
#"phi_DIRA_OWNPV",
#"phi_PT",
#________________________________________
#PION
#_____________________________________
#pi Geometric variables and pT
#"pi_OWNPV_CHI2",
#"pi_OWNPV_NDOF",
#'pi_IP_OWNPV',
meson_ID[meson_index]+'_PT',
#________________________________________
#LEPTONS
#________________________________________
#leptons Geometric variables and pT
#l_flv[l_index]+"_plus_OWNPV_CHI2",
#l_flv[l_index]+"_plus_OWNPV_NDOF",
#l_flv[l_index]+"_minus_OWNPV_CHI2",
#l_flv[l_index]+"_minus_OWNPV_NDOF",
#
#l_flv[l_index]+"_plus_IP_OWNPV",
#l_flv[l_index]+"_minus_IP_OWNPV",
l_flv[l_index]+"_plus_PT",
l_flv[l_index]+"_minus_PT",
#D Reconstructed mass
mother_ID[mother_index]+"_ConsD_M",
]
if l_index==0:
branches_needed = [
#________________________________
#D Geometric variables, pT and FD
mother_ID[mother_index]+"_ENDVERTEX_CHI2",
mother_ID[mother_index]+"_IPCHI2_OWNPV",
mother_ID[mother_index]+"_OWNPV_CHI2",
#mother_ID[mother_index]+"_IP_OWNPV",
mother_ID[mother_index]+"_DIRA_OWNPV",
mother_ID[mother_index]+"_PT",
mother_ID[mother_index]+"_FD_OWNPV",
mother_ID[mother_index]+"_FDCHI2_OWNPV",
#________________________________________
#phi geometric variables, pT and FD
#"phi_ENDVERTEX_CHI2",
#"phi_IPCHI2_OWNPV",
#"phi_OWNPV_CHI2",
#"phi_OWNPV_NDOF",
#"phi_IP_OWNPV",
#"phi_DIRA_OWNPV",
#"phi_PT",
#________________________________________
#PION
#_____________________________________
#pi Geometric variables and pT
#"pi_OWNPV_CHI2",
#"pi_OWNPV_NDOF",
#'pi_IP_OWNPV',
meson_ID[meson_index]+'_PT',
#________________________________________
#LEPTONS
#________________________________________
#leptons Geometric variables and pT
#l_flv[l_index]+"_plus_OWNPV_CHI2",
#l_flv[l_index]+"_plus_OWNPV_NDOF",
#l_flv[l_index]+"_minus_OWNPV_CHI2",
#l_flv[l_index]+"_minus_OWNPV_NDOF",
#
#l_flv[l_index]+"_plus_IP_OWNPV",
#l_flv[l_index]+"_minus_IP_OWNPV",
l_flv[l_index]+"_plus_PT",
l_flv[l_index]+"_minus_PT",
#D Reconstructed mass
mother_ID[mother_index]+"_ConsD_M",
]
return branches_needed
def norm_chi2(MC_Dplus_sig_dict, MC_Ds_sig_dict, data_dict):
MC_Ds_sig_dict["Ds_ENDVERTEX_CHI2"]=MC_Ds_sig_dict["Ds_ENDVERTEX_CHI2"]/MC_Ds_sig_dict["Ds_ENDVERTEX_NDOF"]
MC_Ds_sig_dict["Ds_IPCHI2_OWNPV"]=MC_Ds_sig_dict["Ds_IPCHI2_OWNPV"]/MC_Ds_sig_dict["Ds_ENDVERTEX_NDOF"]
MC_Ds_sig_dict["Ds_FDCHI2_OWNPV"]=MC_Ds_sig_dict["Ds_FDCHI2_OWNPV"]/MC_Ds_sig_dict["Ds_OWNPV_NDOF"]
MC_Ds_sig_dict["Ds_OWNPV_CHI2"]=MC_Ds_sig_dict["Ds_OWNPV_CHI2"]/MC_Ds_sig_dict["Ds_OWNPV_NDOF"]
del MC_Ds_sig_dict["Ds_OWNPV_NDOF"]
del MC_Ds_sig_dict["Ds_ENDVERTEX_NDOF"]
MC_Dplus_sig_dict["Dplus_ENDVERTEX_CHI2"]=MC_Dplus_sig_dict["Dplus_ENDVERTEX_CHI2"]/MC_Dplus_sig_dict["Dplus_ENDVERTEX_NDOF"]
MC_Dplus_sig_dict["Dplus_IPCHI2_OWNPV"]=MC_Dplus_sig_dict["Dplus_IPCHI2_OWNPV"]/MC_Dplus_sig_dict["Dplus_ENDVERTEX_NDOF"]
MC_Dplus_sig_dict["Dplus_FDCHI2_OWNPV"]=MC_Dplus_sig_dict["Dplus_FDCHI2_OWNPV"]/MC_Dplus_sig_dict["Dplus_OWNPV_NDOF"]
MC_Dplus_sig_dict["Dplus_OWNPV_CHI2"]=MC_Dplus_sig_dict["Dplus_OWNPV_CHI2"]/MC_Dplus_sig_dict["Dplus_OWNPV_NDOF"]
del MC_Dplus_sig_dict["Dplus_OWNPV_NDOF"]
del MC_Dplus_sig_dict["Dplus_ENDVERTEX_NDOF"]
data_dict["Ds_ENDVERTEX_CHI2"]=data_dict["Ds_ENDVERTEX_CHI2"]/data_dict["Ds_ENDVERTEX_NDOF"]
data_dict["Ds_IPCHI2_OWNPV"]=data_dict["Ds_IPCHI2_OWNPV"]/data_dict["Ds_ENDVERTEX_NDOF"]
data_dict["Ds_FDCHI2_OWNPV"]=data_dict["Ds_FDCHI2_OWNPV"]/data_dict["Ds_OWNPV_NDOF"]
data_dict["Ds_OWNPV_CHI2"]=data_dict["Ds_OWNPV_CHI2"]/data_dict["Ds_OWNPV_NDOF"]
del data_dict["Ds_OWNPV_NDOF"]
del data_dict["Ds_ENDVERTEX_NDOF"]
return MC_Dplus_sig_dict, MC_Ds_sig_dict, data_dict
def mass_cut_for_fit(lower_cut, upper_cut, mother_index_fit=None, l_index=None,
branches_needed=None, data_dict=None,
MC_Dplus_dict=None, MC_Ds_dict=None):
#applying needed mass cuts on data
#Applies needed mass cuts on data and
#returns arrays of mass distr for MC and data
data_indices=[]
for i in range(len(data_dict["Ds_ConsD_M"])):
D_m = data_dict["Ds_ConsD_M"][i]
#fixing a window on the phi mass
if lower_cut<D_m<upper_cut:
data_indices.append(i)
for label in branches_needed:
data_dict[label] = data_dict[label][data_indices]
m_plus=MC_Dplus_dict["Dplus_ConsD_M"].shape[0]
m_s=MC_Ds_dict["Ds_ConsD_M"].shape[0]
m=data_dict["Ds_ConsD_M"].shape[0]
mc_Dplus_mass=np.array([MC_Dplus_dict["Dplus_ConsD_M"][i][0] for i in range(m_plus)])
mc_Ds_mass=np.array([MC_Ds_dict["Ds_ConsD_M"][i][0] for i in range(m_s)])
#mc_D_mass=np.concatenate((mc_Ds_mass,mc_Dplus_mass),axis=0)
data_mass=np.array([data_dict["Ds_ConsD_M"][i][0] for i in range(m)])
# if mother_index_fit==0:
# mc_mass=mc_Ds_mass
# if mother_index_fit==1:
# mc_mass=mc_Dplus_mass
# if mother_index_fit==2:
# mc_mass=mc_D_mass
return data_mass, mc_Dplus_mass, mc_Ds_mass, data_dict
def preprocess_for_XGBoost(MC_Dplus_dict, MC_Ds_dict, data_dict, branches_needed, mother_index_fit=None):
m_plus=MC_Dplus_dict["Dplus_ConsD_M"].shape[0]
m_s=MC_Ds_dict["Ds_ConsD_M"].shape[0]
m=data_dict["Ds_ConsD_M"].shape[0]
print(m, m_plus, m_s)
branches_needed.pop()
dim=len(branches_needed)
branches_needed_Dplus=[]
for branch in branches_needed:
if 'Ds' in branch:
branches_needed_Dplus.append(branch.replace("Ds", "Dplus"))
else:
branches_needed_Dplus.append(branch)
data = extract_array(data_dict, branches_needed, dim, m)
mc_Ds_sig = extract_array(MC_Ds_dict, branches_needed, dim, m_s)
mc_Dplus_sig = extract_array(MC_Dplus_dict, branches_needed_Dplus, dim, m_plus)
mc_Ds_mean=mc_Ds_sig.mean(axis=0)
mc_Ds_1=mc_Ds_sig-mc_Ds_mean
mc_Ds_std=mc_Ds_1.std(axis=0)
mc_Ds_2=mc_Ds_1/mc_Ds_std
mc_Dplus_mean=mc_Dplus_sig.mean(axis=0)
mc_Dplus_1=mc_Dplus_sig-mc_Dplus_mean
mc_Dplus_std=mc_Dplus_1.std(axis=0)
mc_Dplus_2=mc_Dplus_1/mc_Dplus_std
data_mean=data.mean(axis=0)
data_1=data-data_mean
data_std=data_1.std(axis=0)
data_2=data_1/data_std
return data_2, mc_Dplus_2, mc_Ds_2
Davide Lancierini