ProFit (Profile Fit)

ProFit is a new publicly available code for Bayesian^{[disambiguation needed]} two-dimensional photometric galaxy profile modelling and decomposition. ProFit uses a fast C++ image generation library (libprofit) and a flexible interface to a large number of likelihood samplers. libprofit offers fast and accurate 2D integration for a useful number of profiles, including Sersic, Core-Sersic, broken-exponential, Ferrer, Moffat, empirical King, point-source and sky, with a simple mechanism for adding new profiles.

Initially ProFit comes in three varieties: a fully featured R package (ProFit), a basic PYTHON wrapper (pyprofit) and a command line terminal interface (profit-cli). However, the R package is the most advanced in terms of features and the most up to dated version.

The core libprofit library is designed to be fast and accurate at integrating and convolving target model images, where the likelihood function to compute, and optimization engine to use, are largely choices for the user via higher level interfaces. The R package version of ProFit contains a large number of examples using simple down-hill gradient schemes, more complex genetic algorithms and more computationally expensive MCMC techniques.

The core advances that ProFit offers over currently available software are that it:

is fully open-source with multiple active developers,
offers a standalone library (libprofit) for accurate and fast pixel integrations when generating a model,
can be extended with new profiles in a simple well- documented manner,
allows for simple or complex priors on parameters (an important aspect of Bayesian analysis),
offers a range of likelihood calculations,
is untied to any specific optimizers but has easy access to downhill minimization, genetic algorithm, and MCMC routines,
can fit parameters in log or linear space,
allows for simple or complex additional constraints be- tween parameters,
offers brute-force and FFT PSF convolution options, with automatic benchmarking to select the fastest strategy.

ProFound

The ProFit R package comes with the ProFound source finding and image utilites suite. In brief, in fully automatic mode using default option, it does the following things:

Makes a rough sky map
Using this rough sky map, makes an initial segmentation image
Using this segmentation image, makes a better sky map
Using this better sky map, extracts basic photometric properties
Using the current segmentation image it starts to dilate a re-measure photometric properties for the image segments (this stage iterates for 6 times by default)
Using the iterative dilation statistics, every object is checked for flux convergence
A final segmentation image is made, combining the segments when each source has converged in flux
Using this final segmentation image, make a final sky map
Using the final segmentation image and final sky map, computes final photometric properties
Returns a list containing input image pixel matched segim, objects, sky and skyRMS, as well as the segstats data-frame of photometric properties for every detected source

For more details and the ProFound user manual see the vignette at: https://rpubs.com/asgr/280146

References[edit]

Robotham, A. S. G., Taranu, D. S., Tobar, R., Moffett, A., & Driver, S. P. (2016). ProFit: Bayesian profile fitting of galaxy images. Monthly Notices of the Royal Astronomical Society, 466(2), 1513-1541. (http://adsabs.harvard.edu/abs/2017MNRAS.466.1513R)

External links[edit]