Source code for gammapy.irf.irf_stack

# Licensed under a 3-clause BSD style license - see LICENSE.rst
import logging
import numpy as np
from astropy.units import Quantity
from .effective_area import EffectiveAreaTable
from .energy_dispersion import EnergyDispersion

__all__ = ["IRFStacker"]

log = logging.getLogger(__name__)

[docs]class IRFStacker: r""" Stack instrument response functions. Compute mean effective area and the mean energy dispersion for a given for a given list of instrument response functions. Results are stored as attributes. The stacking of :math:`j` elements is implemented as follows. :math:`k` and :math:`l` denote a bin in reconstructed and true energy, respectively. .. math:: \epsilon_{jk} =\left\{\begin{array}{cl} 1, & \mbox{if bin k is inside the energy thresholds}\\ 0, & \mbox{otherwise} \end{array}\right. \overline{t} = \sum_{j} t_i \overline{\mathrm{aeff}}_l = \frac{\sum_{j}\mathrm{aeff}_{jl} \cdot t_j}{\overline{t}} \overline{\mathrm{edisp}}_{kl} = \frac{\sum_{j} \mathrm{edisp}_{jkl} \cdot \mathrm{aeff}_{jl} \cdot t_j \cdot \epsilon_{jk}}{\sum_{j} \mathrm{aeff}_{jl} \cdot t_j} Parameters ---------- list_aeff : list list of `~gammapy.irf.EffectiveAreaTable` list_livetime : list list of `~astropy.units.Quantity` (livetime) list_edisp : list list of `~gammapy.irf.EnergyDispersion` list_low_threshold : list list of low energy threshold, optional for effective area mean computation list_high_threshold : list list of high energy threshold, optional for effective area mean computation """ def __init__( self, list_aeff, list_livetime, list_edisp=None, list_low_threshold=None, list_high_threshold=None, ): self.list_aeff = list_aeff self.list_livetime = Quantity(list_livetime) self.list_edisp = list_edisp self.list_low_threshold = list_low_threshold self.list_high_threshold = list_high_threshold self.stacked_aeff = None self.stacked_edisp = None
[docs] def stack_aeff(self): """ Compute mean effective area (`~gammapy.irf.EffectiveAreaTable`). """ nbins = self.list_aeff[0].energy.nbin aefft = Quantity(np.zeros(nbins), "cm2 s") livetime_tot = np.sum(self.list_livetime) for i, aeff in enumerate(self.list_aeff): aeff_data = aeff.evaluate_fill_nan() aefft_current = aeff_data * self.list_livetime[i] aefft += aefft_current stacked_data = aefft / livetime_tot energy = self.list_aeff[0].energy.edges self.stacked_aeff = EffectiveAreaTable( energy_lo=energy[:-1], energy_hi=energy[1:],"cm2") )
[docs] def stack_edisp(self): """ Compute mean energy dispersion (`~gammapy.irf.EnergyDispersion`). """ reco_bins = self.list_edisp[0].e_reco.nbin true_bins = self.list_edisp[0].e_true.nbin aefft = Quantity(np.zeros(true_bins), "cm2 s") temp = np.zeros(shape=(reco_bins, true_bins)) aefftedisp = Quantity(temp, "cm2 s") for i, edisp in enumerate(self.list_edisp): aeff_data = self.list_aeff[i].evaluate_fill_nan() aefft_current = aeff_data * self.list_livetime[i] aefft += aefft_current edisp_data = edisp.pdf_in_safe_range( self.list_low_threshold[i], self.list_high_threshold[i] ) aefftedisp += edisp_data.transpose() * aefft_current with np.errstate(divide="ignore", invalid="ignore"): stacked_edisp = np.nan_to_num(aefftedisp / aefft) e_true = self.list_edisp[0].e_true.edges e_reco = self.list_edisp[0].e_reco.edges self.stacked_edisp = EnergyDispersion( e_true_lo=e_true[:-1], e_true_hi=e_true[1:], e_reco_lo=e_reco[:-1], e_reco_hi=e_reco[1:], data=stacked_edisp.transpose(), )