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

# # Using high-level science data
# 
# High-level science data includes information provided as functions, histograms, tables etc. containing data derived from e.g. simulations like detector acceptance, background expectations etc. 

# In[1]:


from openkm3.store import KM3Store
store = KM3Store()


# ## Lookup table: Detector acceptance
# The detector acceptance (here for the ANTARES 2007-2017 neutrino sample) is provided as lookup table.

# In[2]:


acceptance = store.get("ana20_01_acc")


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acceptance.show_paraminfo()


# In[4]:


acceptance.lookup(xvalue = 100, yvalue = 10)


# In[5]:


df = acceptance.get_dataframe()


# In[6]:


df.plot(kind = "line", logy=True, legend=False)


# ## Function: Number of background events estimate
# 
# This information (again for the ANTARES 2007-2017 sample) is provided as polynomial function.

# In[7]:


bkg = store.get("ana20_01_bkg")


# In[8]:


bkg.functiontype


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bkg.show_paraminfo()


# In[10]:


bkg.evaluate(20) # returns function result for given value