Statmorph

Latest version: v0.5.5

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0.5.5

- More robust search for asymmetry center.
- Attempt Sersic fit even when basic measurements were not successful (flag >= 2).

0.5.4

- Make statmorph slightly more memory efficient.

0.5.3

- An improved initial guess for the double Sersic fit is now obtained by performing single Sersic fits to to the inner and outer regions of the source of interest, which are assumed to be separated by an ellipse of a given size.
- The separating ellipse is by default twice the half-light ellipse, but this can be controlled by the user with the argument `doublesersic_rsep_over_rhalf`
- The Akaike Information Criterion (AIC) and Bayesian Information Criterion (BIC) are now calculated for the single and double Sersic fits.

0.5.2

- Users can now perform _double_ 2D Sersic fits by including the option `include_doublesersic = True`.
- Users can (optionally) customize the fits via the arguments `doublesersic_model_args` and `doublesersic_fitting_args`.
- Furthermore, the option `doublesersic_tied_ellip = True` can be used to ensure that both components have the same ellipticity and position angle, if desired.
- The quality flags `flag_sersic` and `flag_doublesersic` now take values 0-4, just like `flag` (see v0.5.0 release notes).
- Added reduced chi^2 statistics (`sersic_chi2_dof` and `doublesersic_chi2_dof`) to measure goodness of fit.
- Added an example notebook about double Sersic fitting to the documentation.
- Updated tutorial.

0.5.1

- Added support for constrained Sersic fits via the `sersic_model_args` keyword.
- The input argument `sersic_maxiter` is deprecated. Please use `sersic_fitting_args` instead.
- Default value of `cutout_extent` increased from 1.5 to 2.5 (more "space" to make measurements by default, although this also depends on the input segmap).

0.5.0

The "bad measurement" flag now takes values between 0 and 4 (formerly 0 and 1), as explained in the [documentation](https://statmorph.readthedocs.io/en/latest/description.html#output). In summary, a flag of 1 now indicates mild issues with the measurements, while a flag of 2 is reserved for more serious problems. In practice, users of previous versions of statmorph need to know the following when upgrading to v0.5.0:

- The statement `flag == 0` has the same effect as before, since a flag of 0 indicates good measurements.
- The statement `flag != 1` should be replaced with `flag == 0` (to avoid erroneously selecting `flag == 2` cases).
- The statement `flag == 1` (or `flag != 0`) should be replaced with either `flag >= 1` (to restore the functionality of previous versions) or with `flag == 2`, which should result in a smaller fraction of "bad" measurements.
- Users who are dealing with a high fraction of "bad" measurements should consider replacing `flag == 0` with the less strict `flag <= 1` condition.
- The `flag_catastrophic` property was removed and is now represented by `flag == 4` (note that all calculations are aborted when this happens).

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