An adaptation of the statmorph Python code for calculating non-parametric morphological diagnostics of galaxy images. The changes are described in the publication "statmorph-lsst: quantifying and correcting morphological biases in galaxy surveys" (Sazonova et al., in prep.).
You can install the package by cloning/downloading this repository, navigating there, and running pip install .
The package will be uploaded to pip soon to make the installation simpler.
Full documentation describing the changes to the parent package is in preparation. Major changes as of now:
- isophote_asymmetry: similar to shape asymmetry of Pawlik et al. 2016, returns asymmetry of different flux isophotes given by asymmetry_isophotes argument. If None, isophotal asymmetry is not calculated. Ideally, isophotes should be defined by converting desired surface brightness limits to flux units.
- substructure: similar to Smoothness of Conselice et al. 2003, with an additional step of detecting contiguous clumps on the smoothed residual. This is the same procedure as what is commonly used to find high-redshift clumps (e.g., Shibuya 2016)
Please see the statmorph tutorial.
You can see the dependence of each parameter in this suite in the diagnostic_plots folder. Bias corrections are derived where possible with SymbolicRegression and are available in the paper (for now).
If you use this code for a scientific publication, please cite the following article:
- Rodriguez-Gomez et al. (2019)
- Sazonova et al. (in prep.)