crop.fits.image: Crop FITS Image

In AngusWright/LAMBDAR: Measure galaxy fluxes from an arbitrary FITS image using input aperture locations and dimensions

Crop FITS Image

Description

Crop a fits image to a sub-region determined by the input radius, RA, and Dec.

Usage

crop.fits.image(ra0 = -999, dec0 = -999, path.root = "./",
inpim = NA, crop.radius = 1,fitsoutname = NA, data.extn=1)

Arguments

ra0	numeric; RA of focus of crop (deg). If -999 is provided, the crop will centre around the central RA pixel of the provided FITS image (ie. NAXIS[1]/2).
dec0	numeric; Dec of focus of crop (deg). If -999 is provided, the crop will centre around the central DEC pixel of the provided FITS image (ie. NAXIS[2]/2).
path.root	string; Path to input FITS image. Default is "./", i.e. the current R working directory.
inpim	string; Filename of input FITS image
crop.radius	numeric; Radius of cropped region (deg). Default value is 1 degree.
fitsoutname	string; Filename for output cropped image
data.extn	numeric; FITS extension to crop from

Details

The inputs ra0, dec0, inpim, crop.radius, and fitsoutname can all be vectors of values if more than one crop is desired. Note that each cropped image _must_ have its own individual fitsoutname - the function will not create extended FITS files. For example, if you wish to crop one image in many places: you can provide a single inpim, but vectors of ‘n’ ra0s, dec0s, crop.radiuss, and fitsoutnames. If you wish to crop the same location out of many images, you can provide a single ra0, dec0, and crop.radius, but vectors of ‘n’ inpims and fitsoutnames.

Value

NULL; The cropped image(s) are output to file.

Author(s)

Angus H Wright ICRAR [e-mail]

See Also

measure.fluxes

Examples

#Load LAMBDAR
library(LAMBDAR)

#Load a Sample Image and Catalogue
data("SDSS.sample",envir=environment())
data("ApCat.sample",envir=environment())
#Write Sample Image to File
write.fits(file="SampleImage.fits",SDSS.sample)

#Crop a 40" (radius) cutout from the centre of the sample image:
crop.fits.image(inpim="SampleImage.fits",crop.radius=40/3600,
fitsoutname="SampleImage_cropped.fits")

#Read the cropped sample image
SDSS.sample.cropped<-read.fits("SampleImage_cropped.fits")

#Image the Uncropped and Cropped Images
layout(cbind(1,2))
#Full Image
image(x=1:length(SDSS.sample$dat[[1]][,1]),
y=1:length(SDSS.sample$dat[[1]][1,]),z=SDSS.sample$dat[[1]],
col=grey.colors(1E3),zlim=quantile(SDSS.sample$dat[[1]],
c(0,0.999)),asp=1,useRaster=TRUE,xlab='X (pix)',ylab="Y (pix)")
#Cropped Image
image(x=1:length(SDSS.sample.cropped$dat[[1]][,1]),
y=1:length(SDSS.sample.cropped$dat[[1]][1,]),
z=SDSS.sample.cropped$dat[[1]],col=grey.colors(1E3),
zlim=quantile(SDSS.sample.cropped$dat[[1]],c(0,0.99)),asp=1,
useRaster=TRUE,xlab='X (pix)',ylab="Y (pix)")

#The cropped image has been modified to reflect the new astrometry:
#Get Object Positions in the cropped and uncropped images
xy<-ad.to.xy(ApCat.sample$RAdeg,ApCat.sample$DECdeg,
read.astrometry("SampleImage.fits"))
xy.cropped<-ad.to.xy(ApCat.sample$RAdeg,ApCat.sample$DECdeg,
read.astrometry("SampleImage_cropped.fits"))
aspp<-abs(read.astrometry("SampleImage.fits")$CD[1,1])*3600
#Plot Full Image w/ Object positions
image(x=1:length(SDSS.sample$dat[[1]][,1]),
y=1:length(SDSS.sample$dat[[1]][1,]),z=SDSS.sample$dat[[1]],
col=grey.colors(1E3),zlim=quantile(SDSS.sample$dat[[1]],
c(0,0.999)),asp=1,useRaster=TRUE,xlab='X (pix)',ylab="Y (pix)")
points(xy,pch=3,col='red')
#Plot Cropped Image w/ Object positions
image(x=1:length(SDSS.sample.cropped$dat[[1]][,1]),
y=1:length(SDSS.sample.cropped$dat[[1]][1,]),
z=SDSS.sample.cropped$dat[[1]],col=grey.colors(1E3),
zlim=quantile(SDSS.sample.cropped$dat[[1]],c(0,0.99)),
asp=1,useRaster=TRUE,xlab='X (pix)',ylab="Y (pix)")
points(xy.cropped,pch=3,col='red')

AngusWright/LAMBDAR documentation built on May 12, 2022, 1:49 a.m.