  The Cherenkov Telescope Array (CTA) will be the next generation ground-based
very-high-energy gamma-ray observatory, constituted by tens of Imaging
Atmospheric Cherenkov Telescopes at two sites once its construction and
commissioning are finished. Like its predecessors, CTA relies on Instrument
Response Functions (IRFs) to relate the observed and reconstructed properties
to the true ones of the primary gamma-ray photons. IRFs are needed for the
proper reconstruction of spectral and spatial information of the observed
sources and are thus among the data products issued to the observatory users.
They are derived from Monte Carlo simulations, depend on observation conditions
like the telescope pointing direction or the atmospheric transparency and can
evolve with time as hardware ages or is replaced. Producing a complete set of
IRFs from simulations for every observation taken is a time-consuming task and
not feasible when releasing data products on short timescales. Consequently,
interpolation techniques on simulated IRFs are investigated to quickly estimate
IRFs for specific observation conditions. However, as some of the IRFs
constituents are given as probability distributions, specialized methods are
needed. This contribution summarizes and compares the feasibility of multiple
approaches to interpolate IRF components in the context of the pyirf python
software package and IRFs simulated for the Large-Sized Telescope prototype
(LST-1). We will also give an overview of the current functionalities
implemented in pyirf.
