# ZernikePolynomials.jl

ZernikePolynomials.jl is a package for working with Zernike polynomials in Julia. I give a short introduction to the package. The software can be found here.

Zernike polynomials are often used to describe optical aberrations in a circular pupil. To aid working with these polynomials, I released ZernikePolynomials.jl. This Julia package has three purposes:

• Helping with conversion of the indices used to describe the polynomials into different sequential orderings;
• Generating these polynomials as functions and evaluating them;
• Estimating the coefficients from data when an optical aberration can be described as a linear combination of these polynomials.

I’ve plotted the first 21 Zernike polynomials below together with the tuple of integers that specify them.

## Package functions

There are several ways to label the polynomials (see the Wikipedia page). The following ways are supported:

• a tuple of integers $(m,n)$,
• a sequential index called Noll’s index,
• the sequential OSA/ANSI index.

The standard way is to use the tuple $(m,n)$. When a sequential index is provided to a function, this package defaults to the OSA/ANSI indexing.

The conversion functions are:

• mn2OSA, OSA2mn
• mn2Noll, Noll2mn
• Noll2OSA, OSA2NOll

By default the polynomials are normalized according to (Thibos, Applegate, Schwiegerling, & Webb, 2002). The normalization constants can be obtained with the function normalization(m,n). Note that the Wikipedia page uses a different normalization.

A specific polynomial can be obtained as a function using Zernike(). The returned function can be evaluated on polar coordinates or cartesian coordinates depending on the keyword argument coord supplied to Zernike (defaults to polar coordinates). See ?Zernike for further documentation.

The Zernike polynomials can easily be evaluated on a grid using the function evaluateZernike by supplying a range of x coordinates (the polynomial is evaluated on a square grid), a vector of indices (OSA indices by default) of the polynomials and a vector of coefficients. See ?evaluateZernike for further documentation.

Given a (measured or estimated) phase, the function Zernikecoefficients can be used to estimate the optimal coefficients in a least squares sense of the weighted sum of Zernike polynomials that optimally approximate this phase. See ?Zernikecoefficients for further documentation.

## Further documentation

Documentation can be found using ?functionname in the Julia REPL and over at the GitHub repository page.

## Bibliography

1. Thibos, L. N., Applegate, R. A., Schwiegerling, J. T., & Webb, R. (2002). Standards for reporting the optical aberrations of eyes. Journal of Refractive Surgery, 18(5), S652–S660.