Brief description

The main interface between the user and the code is the source_morphology function, which calculates the morphological parameters of a set of sources. Below we briefly describe the input and output of this function.

A more detailed description of the input parameters and the measurements performed by statmorph can be found in the API reference, as well as in Rodriguez-Gomez et al. (2019). We also refer the user to the tutorial, which contains a more concrete (albeit simplified) usage example.

Input

The main two required input parameters are the following:

  • image : A background-subtracted image (2D array) containing the source(s) of interest.
  • segmap : A segmentation map (2D array) of the same size as the image with different sources labeled by different positive integer numbers. A value of zero is reserved for the background.

In addition, one of the following two parameters is also required:

  • weightmap : A 2D array (of the same size as the image) representing one standard deviation of each pixel value. This is also known as the “sigma” image and is related to the Poisson noise. If the weight map is not provided by the user, then it is computed internally using the gain keyword argument.
  • gain : A scalar that, when multiplied by the image, converts the image units into electrons/pixel. This parameter is required when weightmap is not provided by the user.

Optionally, the function can also accept:

  • mask : A 2D array (of the same size as the image) indicating the pixels that should be masked (e.g., to remove contamination from foreground stars).
  • psf : A 2D array (usually smaller than the image) representing the point spread function (PSF). This is used when fitting Sersic profiles.

In addition, almost all of the parameters used in the calculation of the morphological diagnostics can be specified by the user as keyword arguments, although it is recommended to leave the default values alone. For a complete list of keyword arguments, please see the API Reference.

Output

The output of the source_morphology function is a list of SourceMorphology objects, one for each labeled source, in which the different morphological measurements can be accessed as keys or attributes.

Apart from the morphological parameters, statmorph also produces two different “bad measurement” flags (where values of 0 and 1 indicate good and bad measurements, respectively):

  1. flag : indicates a problem with the basic morphological measurements (e.g., a discontinuous Gini segmentation map).
  2. flag_sersic : indicates if there was a problem during the Sersic profile fitting.

In general, users should enforce flag == 0, while flag_sersic == 0 should be applied only when actually interested in Sersic fits (which can fail for merging galaxies and other “irregular” objects).

In addition to the flags described above, the output should not be trusted when any of the measured distance scales (Petrosian radii, half-light radii, etc.) is smaller than the radius at half-maximum of the PSF, or when the signal-to-noise per pixel (sn_per_pixel) is lower than 2.5 (Lotz et al. 2006).