wf_net: Wavefront smoothing

In mlpeck/zernike: Zernike Polynomials

Wavefront smoothing

Description

Calculate net and smoothed wavefronts from a raw wavefront containing low order nuisance aberrations.

Usage

wf_net(wf.raw, cp, options)

Arguments

wf.raw	Raw wavefront to be processed
cp	a list describing the pupil boundary
options	a list of options. See psfit_options

Details

Called by psifit

Value

A list with the following components:

wf.net	Net unsmoothed wavefront; a matrix of class "pupil"
wf.smooth	Net smoothed wavefront
wf.residual	Difference between net wavefront and polynomial fit
fit	Return value from fitzernikes
zcoef.net	Net Zernike coefficients from fit

Note

As of ver. 3.7.2 the values of options$isoseq and cp$obstruct determine what is called to fit Zernikes. If isoseq is TRUE it's either zpm_cart or zapm_cart, with the latter called automatically if cp$obstruct > 0. Otherwise the calls are made to zpm or zapmC.

Author(s)

M.L. Peck [e-mail]

Examples

## illustrates effect of incremental addition of an obstruction
## and standalone use of wf_net
  
require(zernike)
fpath <- file.path(find.package(package="zernike"), "psidata")
files <- scan(file.path(fpath, "files.txt"), what="character")
for (i in 1:length(files)) files[i] <- file.path(fpath, files[i])

# load the images into an array

images <- load.images(files)

# parameters for this run

source(file.path(fpath, "parameters.txt"))

# phase shifts

phases <- wrap((0:(dim(images)[3]-1))/frames.per.cycle*2*pi)
phases <- switch(ps.dir, ccw = -phases, cw = phases, phases)

# target SA coefficients for numerical null.

sa.t <- sconic(diam,roc,lambda=wavelength)
zopt <- psfit_options()
zopt$satarget <- sa.t
psfit <- psifit(images, phases, psialg="ls", options=zopt)

# get back the raw wavefront

wf.raw <- qpuw(psfit$phi, psfit$mod)
cp <- psfit$cp

eps <- seq(0.1, 0.5, by=0.1)
ne <- length(eps)
pad0 <- rep(0, ne)

## collect some basic data

df.annfits <- data.frame(eps=c(0, eps), sa.null = c(sa.t[1], pad0), sa.obs = c(psfit$fit[9], pad0), sa.net = c(psfit$zcoef.net[8], pad0),
                         rms.net = c(sqrt(crossprod(psfit$zcoef.net)), pad0), defocus=c(psfit$fit[4], pad0))
for (i in seq_along(eps)) {
  cp$obstruct <- eps[i]
  sa.t <- sconic(diam, roc, eps=eps[i], lambda=wavelength)
  zopt$satarget <- sa.t
  fiti <- wf_net(wf.raw, cp=cp, options=zopt)
  df.annfits[i+1, 2:ncol(df.annfits)] <- c(sa.t[1], fiti$fit[9], fiti$zcoef.net[8], sqrt(crossprod(fiti$zcoef.net)), fiti$fit[4])
}

rm(eps)
attach(df.annfits)

X11()
plot(eps, sa.null, type="b", ylim=range(df.annfits[,2:ncol(df.annfits)]), xlim=c(0, 0.8), main="Trends with obstruction fraction")
points(eps, sa.obs, type="b", pch=2, col=2, lty=2)
points(eps, sa.net, type="b", pch=3, col=3, lty=3)
points(eps, rms.net, type="b", pch=4, col=4, lty=4)
points(eps, defocus, type="b", pch=5, col=5, lty=5)
grid()
legend(x=0.6, y=0, legend=names(df.annfits)[-1], col=1:5, lty=1:5, pch=1:5)

## plot the first and last smoothed wavefronts to show difference is completely symmetrical

plotn(psfit, fiti, wftype="smooth", qt=c(0,1))
detach(df.annfits)
print(df.annfits, digits=2)

mlpeck/zernike documentation built on April 19, 2024, 3:16 p.m.