SPARCO reconstruction

For targets with a spectrally-variable environment (e.g. T Tauri discs), the SPARCO framework separates a grey circumstellar component from an unresolved stellar point source. The high-level reconstruct_sparco takes physical parameters directly:

using OITOOLS
data = readoifits("data/2019_v1295Aql.WL_SMOOTH.A.oifits";
                  polychromatic=true, filter_bad_data=true)
nx      = 64
pixsize = 0.25
ft      = setup_ft(data, nx, pixsize)
x0      = gaussian2d(nx, nx, nx / 6)

result = reconstruct_sparco(x0, data[1,1], ft;
    lambda_ref  = 1.6e-6,
    star_flux   = 0.48,
    bg_flux     = 0.0,
    d_env       = -0.1,
    weights     = [1.0, 0.0, 1.0],
    regularizers = [["tv", 1e2]],
    maxiter     = 200,
    rounds      = 3,
    verb        = true)

imdisp(result.image; pixsize)
println("Final params: ", result.params)
println("χ²/ν = ", result.chi2)

The result is a named tuple with fields params, image, model, free_params, chi2, and param_names.

Keyword reference

Keyword	Default	Description
`lambda_ref`	`1.6e-6`	Reference wavelength (m)
`star_flux`	`0.5`	Stellar flux fraction at `lambda_ref`
`bg_flux`	`0.0`	Background flux fraction at `lambda_ref`
`d_env`	`0.0`	Environment spectral index
`star_di`	`4.0`	Stellar spectral index (Rayleigh–Jeans default)
`star_spectral_index_fixed`	`true`	If `false`, fit the stellar spectral index too
`fit_model_first`	`true`	Run a model-only fit before image reconstruction
`rounds`	`3`	Number of alternating image/parameter rounds
`regularizers`	`[["centering", 1e4]]`	Image regularizers
`weights`	`[1,1,1,0,0,0,0]`	Observable weights `[V², T3amp, T3φ, ...]`

See example_image_reconstruction_sparco_grey_v1295_newAPI.jl.

See the Imaging (SPARCO) API reference for full docstrings.