Optical aberration evaluations to compute a list of Zernike coefficients for Zernike polynomials that correspond to various types of monochromatic aberration that arise when electromagnetic rays are focused by a system of lenses and mirrors. An Intersection Point 3D dataset (see IntersectionPoint2D, IntersectionPoint3D) pointing to a Ray (Dataset) dataset must be used.

When added to an evaluation group, replace numerical(<ftag>) with evaluationGroup(<ftag>).

model.result().numerical().create(<ftag>,"EvalAberration") creates a optical aberration evaluation feature with the name <ftag>.

model.result().numerical(<ftag>).getReal() returns the real-valued Zernike coefficients. Data is ordered so that there is one row with length equal to the number of Zernike polynomials up to the specified order.

model.result().numerical(<ftag>).getImag(<allocate>, <columnwise>) always returns null because the Zernike coefficients are always real-valued.

model.result().numerical(<ftag>).isComplex() always returns false because the Zernike coefficients are real-valued.

model.result().numerical(<ftag>).computeResult() returns the matrix of data containing the real and imaginary parts of the Zernike coefficients; the latter is always null.

model.result().numerical(<ftag>).setResult() and model.result().numerical(<ftag>).appendResult() evaluate the feature and set or append the result in the table indicated by the table property.