SpectrumObservationStacker

class gammapy.spectrum.SpectrumObservationStacker(obs_list)

Bases: object

Stack observations in a SpectrumObservationList.

The stacking of \(j\) observations is implemented as follows. \(k\) and \(l\) denote a bin in reconstructed and true energy, respectively.

\[ \begin{align}\begin{aligned}\begin{split}\epsilon_{jk} =\left\{\begin{array}{cl} 1, & \mbox{if bin k is inside the energy thresholds}\\ 0, & \mbox{otherwise} \end{array}\right.\end{split}\\\overline{\mathrm{n_{on}}}_k = \sum_{j} \mathrm{n_{on}}_{jk} \cdot \epsilon_{jk}\\\overline{\mathrm{n_{off}}}_k = \sum_{j} \mathrm{n_{off}}_{jk} \cdot \epsilon_{jk}\\\overline{\alpha}_k = \frac{\overline{{b_{on}}}_k}{\overline{{b_{off}}}_k}\\\overline{{b}_{on}}_k = 1\\\overline{{b}_{off}}_k = \frac{1}{\sum_{j}\alpha_{jk} \cdot \mathrm{n_{off}}_{jk} \cdot \epsilon_{jk}} \cdot \overline{\mathrm {n_{off}}}\end{aligned}\end{align} \]

Please refer to the IRFStacker for the description of how the IRFs are stacked.

Parameters:

obs_list : SpectrumObservationList

Observations to stack

Examples

>>> from gammapy.spectrum import SpectrumObservationList, SpectrumObservationStacker
>>> obs_list = SpectrumObservationList.read('$GAMMAPY_EXTRA/datasets/hess-crab4_pha')
>>> obs_stacker = SpectrumObservationStacker(obs_list)
>>> obs_stacker.run()
>>> print(obs_stacker.stacked_obs)
*** Observation summary report ***
Observation Id: [23523-23592]
Livetime: 0.879 h
On events: 279
Off events: 108
Alpha: 0.037
Bkg events in On region: 3.96
Excess: 275.04
Excess / Background: 69.40
Gamma rate: 0.14 1 / min
Bkg rate: 0.00 1 / min
Sigma: 37.60
energy range: 681292069.06 keV - 87992254356.91 keV

Methods Summary

run()	Run all steps in the correct order.
setup_counts_vectors()	Add correct attributes to stacked counts vectors.
stack_aeff()	Stack effective areas (weighted by livetime).
stack_backscal()	Stack backscal for on and off vector.
stack_counts_spectrum(counts_spectrum_list)	Stack PHACountsSpectrum.
stack_counts_vectors()	Stack on and off vectors.
stack_edisp()	Stack energy dispersion (weighted by exposure).
stack_obs()	Create stacked SpectrumObservation
stack_off_vector()	Stack the off count vector.
stack_on_vector()	Stack the on count vector.

Methods Documentation

run()

Run all steps in the correct order.

setup_counts_vectors()

Add correct attributes to stacked counts vectors.

stack_aeff()

Stack effective areas (weighted by livetime).

Calls gammapy.irf.IRFStacker.stack_aeff.

stack_backscal()

Stack backscal for on and off vector.

static stack_counts_spectrum(counts_spectrum_list)

Stack PHACountsSpectrum.

• Bins outside the safe energy range are set to 0
• Attributes are set to None.
• The quality vector of the observations are combined with a logical or, such that the low (high) threshold of the stacked obs is the minimum low (maximum high) threshold of the observation list to be stacked.

stack_counts_vectors()

Stack on and off vectors.

stack_edisp()

Stack energy dispersion (weighted by exposure).

Calls stack_edisp

stack_obs()

Create stacked SpectrumObservation

stack_off_vector()

Stack the off count vector.

stack_on_vector()

Stack the on count vector.