profitMakePointSource: Create an image of a point source (PS) with an analytical or empirical point spread function (PSF).

Description

Create an image of a point source at an arbitrary location (can be fractional pixels) based on a user-defined point spread function (PSF) model, or by interpolating a user-defined empirical PSF image. Defaults to creating an empirical image of a Gaussian PSF.

Usage

profitMakePointSource(xcen, ycen, mag = 0, magzero = 0,
  modellist = list(sersic = list(mag = 0, re = 1, nser = 0.5, axrat=1, ang=0)),
  psf=NULL, image=matrix(0, 25, 25), finesample=1L, add=FALSE, plot = FALSE,
  returnfine=FALSE, ...)

Arguments

xcen

The x-axis centre of the point source in image coordinates. If missing it will be the mid-x location on the specified image.

ycen

The y-axis centre of the point source in image coordinates. If missing it will be the mid-y location on the specified image.

modellist

An optional list containing a valid model as described in profitMakeModel, which must be defined such that the integral of the model is unity (mag=0). One of modellist or psf (but not both) must be supplied.

mag

The magnitude of the point source, defined such that (mag-magzero)=-2.5(log10(flux)).

magzero

The magnitude zero point, where values become scaled by the standard scale=10^(-0.4*(mag-magzero)).

psf

An optional image matrix containing an empirical PSF to be interpolated and rescaled. One of model or psf (but not both) must be supplied.

image

An optional image matrix defining the dimensions of the output image, and optionally containing some data to be added to if add is TRUE.

finesample

An integer factor (>=1L) to oversample the model grid by; see profitMakeModel.

add

Logical flag to determine if the output should return the sum of this pointsource and the data in image.

plot

Logical; should a magimage plot of the output be generated?

returnfine

Logical; should an oversampled imaged be returned? Relevant only if finesample>1L.

…

Further arguments to be passed to magimage. Only relevant is plot=TRUE.

Value

Matrix; image containing the PS as specified above.

Details

By ProFit convention the bottom-left part of the bottom-left pixel when plotting the image matrix is c(0,0) and the top-right part of the bottom-left pixel is c(1,1), i.e. the mid-point of pixels are half integer values in x and y.

To confuse things a bit, when R plots an image of a matrix it is transposed and re-ordered vertically to how it appears if you print the matrix directly to screen, i.e. compare print(matrix(1:4,2,2)) and image(matrix(1:4,2,2)). The lowest value (1) is top-left when printed but bottom-left when displayed using image (the red pixel). Both are "correct": the issue is whether you consider the first element of a matrix to be the Cartesian x position (movement in x) or a row element (movement in y). Matrices in maths are always written top-left first where the first argument refers to row number, but images by convention are accessed in a Cartesian sense. Hence [3,4] in a maths matrix means 3 down and 4 right from the top-left, but 3 right and 4 up from the bottom-left in an image.

Examples

Run this code

# NOT RUN {
# Create a PSF with a suitable width:
profitMakePointSource(plot=TRUE)
  
# We can create a point source in a larger image:
psf = profitMakePointSource(xcen=100,ycen=50,mag=15,modellist=list(
  sersic=list(re=2,nser=0.5,mag=0,axrat=0.2, ang=0.5)),
  magzero=0,image=matrix(0,200,200), finesample=1L)
magimage(psf)

# Note that Gaussian PSFs are very accurate but subject to roundoff errors below ~1e-30. 
# Try rotating an elliptical PSF:
angles = seq(0,180,by=90/4)
par(mfrow=c(3,3))
for(ang in angles) {
  psf = round(profitMakePointSource(mag=0,modellist=list(
    sersic=list(re=2,nser=0.5,mag=0,axrat=0.5,ang=ang)), 
    image=matrix(0,15,15)),20)
  print(max(psf))
  magimage(psf)
}
par(mfrow=c(1,1))

# Now interpolate the last empirical PSF (less accurate than creating it from scratch):

profitMakePointSource(xcen=7,ycen=7,mag=0,psf=psf,image=image,modellist=NULL, plot=TRUE)

# }