#!/usr/bin/env python
# coding: utf-8

# # rf513_wsfactory_tools
# Organization and simultaneous fits: illustration use of ROOT.RooCustomizer and
# ROOT.RooSimWSTool interface in factory workspace tool in a complex standalone B physics example
# 
# 
# 
# 
# **Author:**  Clemens Lange, Wouter Verkerke (C++ version)  
# <i><small>This notebook tutorial was automatically generated with <a href= "https://github.com/root-project/root/blob/master/documentation/doxygen/converttonotebook.py">ROOTBOOK-izer</a> from the macro found in the ROOT repository  on Wednesday, April 17, 2024 at 11:19 AM.</small></i>

# In[1]:


import ROOT


w = ROOT.RooWorkspace("w")


# Build a complex example pdf
# -----------------------------------------------------------

# Make signal model for CPV: A bmixing decay function in t (convoluted with a triple Gaussian resolution model)
# times a Gaussian function the reconstructed mass

# In[2]:


w.factory(
    "PROD::sig(  BMixDecay::sig_t( dt[-20,20], mixState[mixed=1,unmix=-1], tagFlav[B0=1,B0bar=-1], "
    "tau[1.54], dm[0.472], w[0.05], dw[0], "
    "AddModel::gm({GaussModel(dt,biasC[-10,10],sigmaC[0.1,3],dterr[0.01,0.2]), "
    "GaussModel(dt,0,sigmaT[3,10]), "
    "GaussModel(dt,0,20)},{fracC[0,1],fracT[0,1]}), "
    "DoubleSided ), "
    "Gaussian::sig_m( mes[5.20,5.30], mB0[5.20,5.30], sigmB0[0.01,0.05] ))"
)


# Make background component: A plain decay function in t times an Argus
# function in the reconstructed mass

# In[3]:


w.factory("PROD::bkg(  Decay::bkg_t( dt, tau, gm, DoubleSided), " "ArgusBG::bkg_m( mes, 5.291, k[-100,-10]))")


# Make composite model from the signal and background component

# In[4]:


w.factory("SUM::model( Nsig[5000,0,10000]*sig, NBkg[500,0,10000]*bkg )")


# Example of RooSimWSTool interface
# ------------------------------------------------------------------

# Introduce a flavour tagging category tagCat as observable with 4 states corresponding
# to 4 flavour tagging techniques with different performance that require different
# parameterizations of the fit model
# 
# ROOT.RooSimWSTool operation:
#     - Make 4 clones of model (for each tagCat) state, will gain an individual
#       copy of parameters w, and biasC. The other parameters remain common
#     - Make a simultaneous pdf of the 4 clones assigning each to the appropriate
#       state of the tagCat index category

# ROOT.RooSimWSTool is interfaced as meta-type SIMCLONE in the factory. The $SplitParam()
# argument maps to the SplitParam() named argument in the
# ROOT.RooSimWSTool constructor

# In[5]:


w.factory("SIMCLONE::model_sim( model, $SplitParam({w,dw,biasC},tagCat[Lep,Kao,NT1,NT2]))")


# Example of RooCustomizer interface
# -------------------------------------------------------------------
# 
# Class ROOT.RooCustomizer makes clones of existing pdfs with certain prescribed
# modifications (branch of leaf node replacements)
# 
# Here we take our model (the original before ROOT.RooSimWSTool modifications)
# and request that the parameter w (the mistag rate) is replaced with
# an expression-based function that calculates w in terms of the Dilution
# parameter D that is defined D = 1-2*w

# Make a clone model_D of original 'model' replacing 'w' with
# 'expr('0.5-D/2',D[0,1])'

# In[6]:


w.factory("EDIT::model_D(model, w=expr('0.5-D/2',D[0,1]) )")


# Print workspace contents

# In[7]:


w.Print()


# Make workspace visible on command line

# In[8]:


ROOT.gDirectory.Add(w)