v0.7.2

• Bugfix: statmorph was trying to measure the Petrosian radius even when it was beyond the boundaries of the image cutout, which was causing a crash with the error message "ValueError: f(a) and f(b) must have different signs".
• In this new version, when the Petrosian radius cannot be measured, an arbitrary value is returned and the flag property is set to a value of 2, which indicates a "bad" measurement.

v0.7.1

• Fix bug where the weightmap input by the user was being modified.

v0.7.0

Bugfix: properly account for masked regions during the Petrosian radius calculations.

This change directly affects measurements of the Petrosian radius in masked images (usually resulting in slightly larger radii), and indirectly affects other quantities that depend on the Petrosian radius, such as the Gini-M20 and CAS parameters.

However, the effect is very small in most cases. For example, even in the extreme case of the heavily masked BCG+ICL synthetic images presented in Montenegro-Taborda et al. (2025b), the Petrosian radii increased by 6%, on average, after this change. The impact should be smaller than this in most situations, especially for "normal" galaxies with a moderate amount of masking. Unmasked images are unaffected by this change.

v0.6.1

• Use optimized version of skimage.feature.peak_local_max (see scikit-image/scikit-image#7548). This slightly changes the intensity measurements.

v0.6.0

• Update to photutils v2.0.

v0.5.7

• Change rms_asymmetry to rms_asymmetry2, since this quantity actually represents the square of A_rms.

v0.5.6

• Implement RMS asymmetry (Sazonova et al. 2024).

v0.5.5

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

v0.5.4

• Make statmorph slightly more memory efficient.

v0.5.3

• 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.