Perform source extraction¶

After simulating the image, it is possible to run SExtractor on the image. You then receive a catalog of intrinisic and measured quantities similar to the emulator case alongside the image and the background and segmentation map by SExtractor.

model = GalSBI("Fischbacher+24")
model(mode="image+SE")

images = model.load_images()
image = images["image i"]
bkg = images["background i"]
seg = images["segmentation i"]

interval = PercentileInterval(95)
vmin, vmax = interval.get_limits(image)
norm = ImageNormalize(vmin=vmin, vmax=vmax)

fig, axs = plt.subplots(1, 3, figsize=(9,3))
axs[0].imshow(image, cmap='gray', norm=norm)
axs[1].imshow(bkg)
axs[2].imshow(seg!=0, cmap="Blues")

cats = model.load_catalogs()
cat_ucat = cats["ucat galaxies i"]
cat_sextractor = cats["sextractor i"]

de_kwargs = {
    "smoothing_parameter1D": 0.5,
    "smoothing_parameter2D": 0.5,
}

ranges = {
    "mag": [18, 28],
    "r50": [0, 4],
    "sersic_n": [0, 5],
    "z": [0, 6],
    "MAG_AUTO": [18, 28],
    "FLUX_RADIUS": [0, 10],
}
tri = TriangleChain(ranges=ranges, params=list(ranges.keys()), fill=True, histograms_1D_density=False, de_kwargs=de_kwargs)
tri.contour_cl(cat_ucat, label="intrinsic");
tri.contour_cl(cat_sextractor, label="measured", show_legend=True);