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.
from openkm3.store import KM3Store
store = KM3Store()
INFO:root:Loaded catalog from data center.
Lookup table: Detector acceptance¶
The detector acceptance (here for the ANTARES 2007-2017 neutrino sample) is provided as lookup table.
acceptance = store.get("ana20_01_acc")
INFO:root:Loaded entry ana20_01_acc as <class 'openkm3.dataclasses.LookUpTable'>.
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 |
acceptance.lookup(xvalue = 100, yvalue = 10)
WARNING:root:x value 100 out of range. Range is [-90, 90]
df = acceptance.get_dataframe()
df.plot(kind = "line", logy=True, legend=False)
<AxesSubplot:>
Function: Number of background events estimate¶
This information (again for the ANTARES 2007-2017 sample) is provided as polynomial function.
bkg = store.get("ana20_01_bkg")
INFO:root:Loaded entry ana20_01_bkg as <class 'openkm3.dataclasses.Function'>.
bkg.functiontype
'polynomial'
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_{, bkg} |
bkg.evaluate(20) # returns function result for given value
7893.0656496
Download python script: example_datalevel4.py
Download Jupyter notebook: example_datalevel4.ipynb