radec.to.xy | R Documentation |
Maps a provided array of RAs and Decs to pixel locations X and Y using the TAN Gnomonic projection, when provided with calibrating central RA/Dec, X/Y, and scales.
radec.to.xy(ra, dec, ra0 = 0, dec0 = 0, x0 = 0, y0 = 0, xscale = 1, yscale = 1)
ra |
numeric (n) vector; the (n) RAs to be converted (deg) |
dec |
numeric (n) vector; the (n) Decs to be converted (deg) |
ra0 |
numeric; the RA at the calibrating pixel (deg) |
dec0 |
numeric; the Dec at the calibrating pixel (deg) |
x0 |
numeric; x-coordinate of the calibrating pixel |
y0 |
numeric; x-coordinate of the calibrating pixel |
xscale |
numeric; RA-interval between successive x pixels (deg) |
yscale |
numeric; Dec-interval between successive y pixels (deg) |
numeric (n,2) array; two column bound vectors containing the desired x pixel locations [,'X'] and y pixel locations [,'Y']
This function is called by the ad.to.xy function, which extracts relevant information from an astrometry data.frame internally. It is therefore often more convenient to call ad.to.xy rather than to call radec.to.xy directly.
This function is designed to work with the TAN Gnomonic projection. However, due to degeneracy the procedure can also be used with a orthographic SIN projection *without rotation*.
Aaron Robotham ICRAR aaron.robotham@icrar.org
#Load LAMBDAR library(LAMBDAR) #Load sample image data(SDSS.sample) #Load sample catalogue data(ApCat.sample) #Save sample image to File write.fits(file="SampleImage.fits",SDSS.sample) #Read Astrometry astr<-read.astrometry("SampleImage.fits") #Get the relevent parameters from the Astrometry Header ### NB: This snippet is within the ad.to.xy function, which is a ### wrapper to the radec.to.xy function ra0<-astr$CRVAL[1] dec0<-astr$CRVAL[2] x0<-astr$CRPIX[1] y0<-astr$CRPIX[2] xscale<-astr$CD[1,1] yscale<-astr$CD[2,2] #Determine the pixel-locations of the aperture catalogue objects xy<-radec.to.xy(ra=ApCat.sample$RAdeg,dec=ApCat.sample$DECdeg, ra0=ra0, dec0=dec0, x0=x0, y0=y0, xscale=xscale, yscale=yscale) #Print sample print(head(xy)) #Show the positions on the image #Plot the 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(0,0.995)),useRaster=TRUE, xlab="X (pix)",ylab="Y (pix)",asp=1) #Overlay the points points(xy,pch=3,col='red')
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