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The bi-symmetrized SAURON stellar kinematics of 6 Elliptical (left) and 6 S0 (right) fast-rotator early-type galaxies is compared to the predictions of the anisotropic Jeans models with JAM. Jeans Anisotropic Modelling of the dynamics, stellar kinematics or proper motions of axisymmetric or spherical galaxiesДЇigure 1: Examples of JAM data-model comparisons.

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NOTE: I would appreciate if you drop me an e-mail (address at the bottom) when you download the above procedures. Note that MgeFit uses the mpfit implementation instead of the _squares one, because of the ability of mpfit to tie parameters or keep them fixed. I modified the latter version to support Python 3 and fixed some numerical instabilities. The mpfit routine was translated into Python by Mark River and updated here for NumPy by Sergey Koposov. MgeFit requires the scientific core packages NumPy, SciPy and Matplotlib, and the examples use Astropy to read FITS images (it was tested with Python 3.10 using Numpy 1.22, SciPy 1.8 and Matplotlib 3.5).ДЄlso included in the MgeFit package is the mpfit implementation by Markwardt (2009) of the MINPACK (MorГ©, Garbow & Hillstrom, 1980) Levenberg-Marquardt nonlinear least-squares optimization algorithm. Usage examples: are in the directory 'examples' inside the main package folder inside site-packages.

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Without write access to the global site-packages directory, use ' pip install -user mgefit'.

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How to install: Use ' pip install mgefit'. It was last updated on the 24 June 2021 and the changes are documented in the CHANGELOG.

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The source code of the MgeFit package, including four test galaxy images, is on the Python Package Index (PyPI). The MGE parameterization is useful in the construction of realistic dynamical models of galaxies (see JAM modelling below), for PSF deconvolution of images, for the correction and estimation of dust absorption effects, or for galaxy photometry. (2012, Nature) for an application to the study of the stellar IMF.

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(2013) for a large scale application of this software to the study of the M/L ratio and the Fundamental Plane of early-type galaxies and Cappellari et al. Given that Gaussians are not orthogonal functions, MGE fits are in general strongly degenerate, with difficult global convergence, but the MGE_FIT_SECTORS method solves all problems, making MGE fitting an automated, reliable and robust process. 1994 Cappellari 2002) for a galaxy surface brightness with the fitting algorithm of Cappellari (2002, MNRAS, 333, 400). This software obtains an accurate Multi-Gaussian Expansion (MGE) parameterizations ( Emsellem et al. The MGE-Fit-Sectors method Robust technique to perform Multi-Gaussian Expansion (MGE) fits to galaxy images The figures were produced by the mge_fit_example.py script included in the Python distribution of the software.ДЎ. Illustration of the steps involved in the MGE fit to the S0 galaxy NGC 4342 using the MgeFit package. See my review on galaxy structure and evolution:

My packages above are on the Python Package Index (PyPI).

AdaMet: An Adaptive Metropolis package for Bayesian analisys.

LOESS: to uncover mean trends from noisy one-dimensional or two-dimensional data using the LOESS approach.

LtsFit: to robustly fit a plane or a line to data with intrinsic scatter.

PaFit: to measure the global galaxy kinematical axis from integral field observations.

pPXF: to extract the galaxy stellar or gas kinematics or stellar population from absorption-line spectra.

VorBin: to perform adaptive Voronoi spatial binning of Integral-Field Spectroscopy, X-ray or imaging data, to reach a chosen constant signal-to-noise ratio per bin.

JAM: to construct Jeans Anisotropic Models for the stellar kinematics of axisymmetric galaxies.

MgeFit: to fit Multi-Gaussian Expansion (MGE) models to galaxy images, to be used as a parametrization for galaxy photometry.

NOTE: an outdated version of my programs in the language is also available HERE, however I strongly recommend the Python version. You are not allowed to re-distribute any of these programs (modified or not) without explicit permission from the author. However, if you use it for published research, you are requested to cite the paper where the method is described, highlighted in red. The following software is freely available.