giant.point_spread_functions.gaussiansΒΆ
Defines PSF subclasses for representing/fitting various forms of 2D Gaussian functions.
Note that in this module we assume that the resulting illumination profile for a point source as captured by a detector is Gaussian, which is not strictly true. In actuality, if the PSF is well modelled by a Gaussian function then the captured profile will be integrals of the portions of the Gaussian contained within each pixel. These integrals are not easily defined which makes fitting much more cumbersome and cost intensive (requiring numeric approximations for the Jacobians). In general, however, particularly for a well sampled PSF (where the FWHM is larger than the pixel pitch of the detector), this distinction is negligible, particularly when it comes to estimating the centroid of the PSF, which is typically our primary goal. Providing integrated Gaussian PSFs for extra precise estimation is something that is currently under development.
Classes
A class for representing and fitting a standard (non-rotated) 2D gaussian point spread function. |
|
A class for representing and fitting a standard (non-rotated) 2D Gaussian point spread function using iterative non-linear least squares. |
|
A class for representing and fitting the superposition of a standard (non-rotated) 2D Gaussian point spread function and a linear background gradiant using iterative non-linear least squares. |
|
A class for representing and fitting a generalized (rotated) 2D gaussian point spread function. |
|
A class for representing and fitting a generalized (rotated) 2D Gaussian point spread function using iterative non-linear least squares. |
|
A class for representing and fitting the superposition of a standard (non-rotated) 2D Gaussian point spread function and a linear background gradiant using iterative non-linear least squares. |