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Description
Section starts with this text by Mireille (first sentence), and then Mattia
uv_distance_min and uv_distance_max are evaluated by fitting an ellipse on the visibilities present in the uv plane.
To compute the ellipse's eccentricity of the UV distribution a principal component analysis (PCA) with 2 components is performed over the data points sampling the UV plane to select the main axis of data scattering.
The first component is used to rotate the distribution of UV in a way that the major variation of the distribution is leaning towards the$x$ axis of a bi dimensional$xy$ Cartesian plane. The major axis length and the minor axis length of the ellipse are therefore defined as the semi distance between the most positive point along the$x$ /$y$ axis and the most negative point among the$y$ axis. For instance, if the range of the rotated UV will cover on the$x \in [-10, 10]$ the major axis distance would be 10, a similar procedure is done on the y axis. This procedure allows the definition of the UV distribution eccentricity:
I understand that the absolute farthest point from the center in the uv plane and the closest are not significant for estimation of uv_distance_min and uv_distance_max. But if we fit an outer ellipse to the distribution should we use the same PCA results used in the ellipse's ellepticity estimation and retain the semi major axis for uv_distance_max (significant) ???
Alternatively should we use some criterium estimated on the visibility amplitude (or number of visibilities) versus uv distance ?
This will probably solve easier the estimation of the minimal uv_distance.
Thoughts ?