FitPDF fits complex mixture models of various distributions to observational data. This is useful, for instance, for characterizing the observed pulse energy distributions of radio pulsars and repeating fast radio bursts (FRBs). However, FitPDF is data-agnostic and can, in principle, fit any distribution data and determine its underlying probability density function (PDF). The FitPDF software suite includes tools for simulating distribution data, fitting complex mixture distributions to data, and comparing the resulting fits in an information-theoretical sense. The code supports several model distributions, which are homogeneous or heterogeneous mixtures of individual component distributions (e.g. normal, lognormal, power law). FitPDF, based on PyMC (ascl:1610.016), operates in a Bayesian and unbinned manner, thereby maximizing the information extracted from the data and robustly determining the model parameters and their uncertainties.

Scatfit models observed burst signals of impulsive time domain radio signals ( e.g., Fast Radio Bursts (FRBs) or pulsars pulses), which usually are convolution products of various effects, and fits them to the experimental data. It includes several models for scattering and instrumental effects. The code loads the experimental time domain radio data, cleans them, fits an aggregate scattering model to the data, and robustly estimates the model parameters and their uncertainties. Additionally, scatfit determines the scaling of the scattering time with frequency, i.e. the scattering index, and the scattering-corrected dispersion measure of the burst or pulse.

Molsoft operates, monitors and schedules observations, both through predetermined schedule files and fully dynamically, at the refurbished Molonglo Observatory Synthesis Radio Telescope (MOST). It was developed as part of the UTMOST upgrade of the facility. The software runs a large-scale pulsar timing program; the autonomous observing system and the dynamic scheduler have increased the observing efficiency by a factor of 2-3 in comparison with static scheduling.