FORSTAND constructs dynamical models of galaxies using the Schwarzschild orbit-superposition method; the method is available as part of the AGAMA (ascl:1805.008) framework. The models created are constrained by line-of-sight kinematic observations and are applicable to galaxies of all morphological types, including disks and triaxial rotating bars.

NIMBLE (Non-parametrIc jeans Modeling with B-spLinEs) inferrs the cumulative mass distribution of a gravitating system from full 6D phase space coordinates of its tracers via spherical Jeans modeling. It models the Milky Way's dark matter halo using Gaia and Dark Energy Spectroscopic Instrument Milky Way Survey (DESI MWS) data. NIMBLE includes a basic inverse modeling Jeans routine that assumes perfect and complete data is available and a more complex forward modeling Jeans routine that deconvolves observational effects (uncertainties and limited survey volume) characteristic of Gaia and the DESI-MWS. It also includes tools for generating simple equilibrium model galaxies using Agama (ascl:1805.008) and imposing mock Gaia+DESI errors on 6D phase space input data.

naif is a pure-python package based on the Numerical Analysis of Fundamental Frequencies (NAFF) algorithm, first proposed by Laskar (1990) and further developed by Valluri & Merritt (1998). Given a time-series, particularly that of an orbital coordinate, it extracts from its power-spectrum as many frequencies and respective amplitudes as required. In comparison to the original NAFF algorithm, it has some improvements, particularly in the performance (computation time). It also offers functions to plot the power-spectrum before extraction of each frequency, which can be useful for debugging particular orbits. The code is fully documented and the documentation page has several tutorials. In the future, the code will be expanded with other tools for frequency analysis.