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()

INFO:root:Loaded catalog from cache.

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")

INFO:root:Loaded entry ana20_01_acc as <class 'openkm3.dataclasses.LookUpTable'>.

In [3]:

acceptance.show_paraminfo()

Parameter	Name	Description	Unit	Symbol	Range
xaxis	Declination	Source declination	deg	%delta	[-90, 90]
yaxis	Spectral index	Exponential of the energy power spectrum E^{-x}		%lambda	[1.5, 3.0]
returnvalue	Detector acceptance	Acceptance of the detector to a given neutrino point source flux	GeV^{-1} cm^{2} s	Acceptance

In [4]:

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

WARNING:root:x value 100 out of range. Range is [-90, 90]

In [5]:

df = acceptance.get_dataframe()

In [6]:

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

Out[6]:

<AxesSubplot:>

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")

INFO:root:Loading data from cache.
INFO:root:Loaded entry ana20_01_bkg as <class 'openkm3.dataclasses.Function'>.

In [8]:

bkg.functiontype

Out[8]:

'polynomial'

In [9]:

bkg.show_paraminfo()

Parameter	Name	Description	Unit	Symbol	Range
xvalue	Declination	Source declination	deg	%delta	[-90, 90]
returnvalue	Number of background events	Estimated number of muon background events		N_{\mu, bkg}

In [10]:

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

Out[10]:

7893.0656496