Updated completeness curves/maps description
@@ -517,12 +517,12 @@ def completeness_map(cube, angle_list, psf, fwhm, algo, an_dist, ini_contrast,
starphot=1, n_fc=20, snr_approximation=True, nproc=1,
algo_dict={'ncomp': 20}, verbose=True):
"""
- Function allowing the computation of two dimensional (radius and azimuth)
- completeness-basedcontrast with any psf-subtraction algorithm provided by
- VIP. The code
- relies on the approach proposed by Dahlqvist et al. (2021), itself inspired
- by the framework developped by Jensen-Clem et al. (2018). It relies on the
- computation of the contrast associated to a completeness level achieved at
+ Function allowing the computation of two dimensional (radius and
+ completeness) contrast curves with any psf-subtraction algorithm provided by
+ VIP. The code relies on the approach proposed by Dahlqvist et al. (2021),
+ itself inspired by the framework developped by Jensen-Clem et al. (2018).
+ It relies on the computation of the contrast associated to a completeness
+ level achieved at
a level defined as the first false positive in the original SNR map
(brightest speckle observed in the empty map). The computation of the
completeness level associated to a contrast is done via the sequential
@@ -532,7 +532,7 @@ def completeness_map(cube, angle_list, psf, fwhm, algo, an_dist, ini_contrast,
of three dimensional completeness map, with contrasts computed for multiple
completeness level, allowing the reconstruction of the
contrast/completeness distribution for every considered angular
- separations.(for more details see Dahlqvist et al. 2021)
+ separations (for more details see Dahlqvist et al. 2021).
Parameters
----------
