  The two most successful methods for exoplanet detection rely on the detection
of planetary signals in photometric and radial velocity time-series. This
depends on numerical techniques that exploit the synergy between data and
theory to estimate planetary, orbital, and/or stellar parameters. In this work,
we present a new version of the exoplanet modelling code pyaneti. This new
release has a special emphasis on the modelling of stellar signals in radial
velocity time-series. The code has a built-in multidimensional Gaussian process
approach to modelling radial velocity and activity indicator time-series with
different underlying covariance functions. This new version of the code also
allows multi-band and single transit modelling; it runs on Python 3, and
features overall improvements in performance. We describe the new
implementation and provide tests to validate the new routines that have direct
application to validate the new routines that have direct application to
exoplanet detection and characterisation. We have made the code public and
freely available at https://github.com/oscaribv/pyaneti. We also present the
codes citlalicue and citlalatonac that allow one to create synthetic
photometric and spectroscopic time-series, respectively, with planetary and
stellar-like signals.

Earth and Planetary Astrophysics;Instrumentation and Methods for Astrophysics