Kinemetry analyses 2D maps of the moments of the line-of-sight velocity distribution (LOSVD), such as the mean velocity and the velocity dispersion. The method is a generalisation of surface photometry (e.g. Jedrzejewski 1987) to all moments of the LOSVD. It performs harmonic expansion of 2D maps of observed moments (surface brightness, velocity, velocity dispersion, h3, h4...) along the best fitting ellipses (either fixed or free to change along the radii). Its purpose is to robustly quantify maps of the LOSVD moments, describe trends in structures and detect morphological and kinematic sub-components. Kinemetry can also be used for analysis of gas kinematics, in a similar way as classical tilted-ring analysis. This is because kinemetry, in the case of the velocity moment, assumes that motion is along circular orbits within a thin disk. More details about the method can be found in this paper Krajnović et al. (2006, MNRAS, 366, 787).

The software was original written in IDL programming language, which you can download from here. There is also a python version of the code, which is distributed via this link. See below for its contents.

The python kinemetry distribution consists of (this link): 
- -- the main programme

- run_kinemetry_examples -- a set of python functions which can help you run kinemetry

- - slight modification of the Michele Cappellari's python mpfit routine

- NGC2974_*_.txt -- velocity and velocity dispersion values (for the examples)

- NGC4473r.fits - an image, also for the examples, for photometry

You will also need python scripts for plotting maps. I use Michele Cappellari's plotbin (available here:, as well as the usual set of python stuff: astropy, matplotlin, numpy, scipy.  Finally, to run run_kinemetry_examples, you might need to set the path to the data files manually.

Last update: 28. March 2022