Examples

Plotting

We have recipes for all our aperture types, so you can easily create overlays on your images.

using Photometry
using Plots

plot(CircularAperture(2, 3, 4), c=1, xlims=(-1, 12), ylims=(0, 9))
plot!(CircularAnnulus(5, 5, 2.1, 3), c=2)
plot!(EllipticalAperture(0, 0, 10, 1, 32), c=3)
plot!(EllipticalAnnulus(5, 5, 4, 5, 2, -32), c=4)
plot!(RectangularAperture(0, 0, 4, 4, 4), c=5)
plot!(RectangularAnnulus(5, 1, 3, 4, 4, 4), c=6)

Simple Stars

Here is an example where we will find aperture fluxes for stars from M67. The dataset is provided as part of the astropy/photutils-datasets repository.

Let's start by downloading and showing our image

using Photometry
using Plots
using FITSIO

# Load data in
url = "https://rawcdn.githack.com/astropy/photutils-datasets/8c97b4fa3a6c9e6ea072faeed2d49a20585658ba/data/M6707HH.fits"
hdu = FITS(download(url))
chunk = read(hdu[1], 81:155, 71:150)

# Plot
function imshow(image; kwargs...)
    xs, ys = axes(image)
    data = transpose(image)
    heatmap(xs, ys, data; aspect_ratio=1, xlim=extrema(xs), ylim=extrema(ys), kwargs...)
end

imshow(chunk)

Now let's add some apertures!

positions = [
    [47.5 , 67.5],
    [29.5 , 62.5],
    [23.5 , 48.5],
    [17.5 , 29.5],
    [13.25, 10.5],
    [65.5 , 14.0]
]

radii = [3, 3, 2.7, 2, 2.7, 3]

aps = CircularAperture.(positions, radii)

6-element Vector{CircularAperture{Float64}}:
 CircularAperture(47.5, 67.5, r=3.0)
 CircularAperture(29.5, 62.5, r=3.0)
 CircularAperture(23.5, 48.5, r=2.7)
 CircularAperture(17.5, 29.5, r=2.0)
 CircularAperture(13.25, 10.5, r=2.7)
 CircularAperture(65.5, 14.0, r=3.0)

now let's plot them up

imshow(chunk)
plot!(aps, c=:white)

and finally let's get our output table for the photometry

table = photometry(aps, chunk)

Table with 3 columns and 6 rows:
     xcenter  ycenter  aperture_sum
   ┌───────────────────────────────
 1 │ 47.5     67.5     2.48267e5
 2 │ 29.5     62.5     2.25989e5
 3 │ 23.5     48.5     1.49979e5
 4 │ 17.5     29.5     72189.4
 5 │ 13.25    10.5     1.48118e5
 6 │ 65.5     14.0     2.02803e5

Stars with Spatial Background Subtraction and PSF Fitting

This example will be the same as Simple Stars but will add background and PSF estimation using the tools in Background Estimation and PSFModels.jl.

clipped = sigma_clip(chunk, 1, fill=NaN)
# Estimate 2D spatial background using boxes of size (5, 5)
bkg, bkg_rms = estimate_background(clipped, 5)

plot(
    imshow(chunk, title="Original"),
    imshow(clipped, title="Sigma-Clipped"),
    imshow(bkg, title="Background"),
    imshow(bkg_rms, title="Background RMS");
    layout=(2, 2), size=(600, 600), ticks=false
)

Now, using the same apertures, let's find the output using the background-subtracted image

plot(
    imshow(chunk, title="Original"),
    imshow(chunk .- bkg, title="Subtracted");
    layout=2, size=(600, 260), ticks=false, colorbar=false
)
plot!(aps, c=:white, subplot=1)
plot!(aps, c=:white, subplot=2)

using PSFModels

function fit_psf(img_ap)
    # Normalize
    psf_data = collect(Float32, img_ap)
    psf_data ./= maximum(psf_data)

    # Set params
    y, x = Tuple(argmax(psf_data))
    fwhm = 5.0
    params = (; x, y, fwhm)

    # Fit
    psf_params, psf_model = PSFModels.fit(gaussian, params, psf_data; x_abstol = 2e-6)

    # Could also return a Tuple to display more information.
    # Just returning fitted FWHM here for simplicity.
    return psf_params.fwhm
end

table = photometry(aps, chunk .- bkg, bkg_rms; f = fit_psf)

Table with 5 columns and 6 rows:
     xcenter  ycenter  aperture_sum  aperture_sum_err  aperture_f
   ┌─────────────────────────────────────────────────────────────
 1 │ 47.5     67.5     2.13534e5     431.48            4.19789
 2 │ 29.5     62.5     114217.0      887.37            3.46587
 3 │ 23.5     48.5     59230.7       1061.28           2.58725
 4 │ 17.5     29.5     23159.6       697.556           2.32789
 5 │ 13.25    10.5     54638.1       1048.67           2.51242
 6 │ 65.5     14.0     91179.1       1168.71           3.09683