  Despite image reconstruction becoming more widespread when interpreting
OIFITS Data, model fitting in u,v space often remains the best way to interpret
data, either because of the sparsity of the data, or because a quantitative
measurement needs to be done. PMOIRED, is a flexible Python library to
visualize, manipulate and model OIFITS data using simple geometric models. The
strength of PMOIRED resides in its capability to combine linearly various
simple components to create complex scenes, while linking, constraining, and
adding priors to fitted parameters. The code also enables grid search to find
global minima, as well as data resampling to better evaluate uncertainties. In
addition to analytical functions, arbitrary radial profiles, azimuthal
variations or sparse wavelet modelling of spectra are implemented.
