LAMBDAR

LAMBDAR (Lambda Adaptive Multi-Band Deblending Algorithm in R) measures matched-aperture galaxy fluxes from FITS images. Given an aperture catalogue and image data, it creates apertures, optionally convolves and deblends them, and writes photometric fluxes and uncertainties.

The main entry point is measure.fluxes(). The package also provides helpers for aperture construction, point-spread-function handling, astrometry, FITS I/O, and creating simulated images.

Installation

Install from GitHub with remotes:

install.packages(c("remotes", "FITSio"))
remotes::install_github("AngusWright/LAMBDAR", dependencies = TRUE)
library(LAMBDAR)

LAMBDAR depends on doParallel, foreach, magicaxis, nortest, seqinr, iterators, plotrix, RANN, matrixStats, data.table, FITSio, and astro. astro is declared as a GitHub remote and is installed by install_github(). Optional functionality uses EBImage and reticulate.

To install a local clone instead:

R CMD INSTALL LAMBDAR

Run this command from the directory that contains the clone.

Quick start

The package includes an SDSS r-band FITS image and a matching aperture catalogue (SDSS.sample and ApCat.sample). The catalogue has 274 rows and the columns CATAID, RAdeg, DECdeg, rotW2N, radminasec, radmajasec, and rotN2E.

The following reproduces the package's basic measurement workflow:

library(LAMBDAR)

data("SDSS.sample", envir = environment())
data("ApCat.sample", envir = environment())

write.fits(file = "SampleImage.fits", SDSS.sample)
write.csv(
  ApCat.sample, "SampleCat.csv",
  row.names = FALSE, quote = FALSE
)

create.par.file(
  filename = "Lambdar_Sample.par",
  DataMap = "SampleImage.fits",
  Catalogue = "SampleCat.csv"
)
measure.fluxes("Lambdar_Sample.par")

results <- read.csv("LAMBDAR_Results.csv", stringsAsFactors = FALSE)
summary(results$DFAFlux_Jy)

Lambdar_Sample.par contains all run settings. Generate a fully annotated default parameter file with:

measure.fluxes("--makepar")

The principal result is LAMBDAR_Results.csv; with do.return = TRUE, measure.fluxes() also returns a list including SFAflux, SFAerror, DFAflux, and DFAerror.

Function examples

The outputs below were produced by running the shown calls against this checkout.

Spherical coordinates to Cartesian coordinates

sph.to.car(c(0, 90), c(0, 0))

                x y z
[1,] 1.000000e+00 0 0
[2,] 6.123234e-17 1 0

Pixel coordinates to right ascension and declination

xy.to.radec(
  c(100, 110), c(200, 205),
  ra0 = 150, dec0 = 2, x0 = 100, y0 = 200,
  xscale = 0.001, yscale = 0.001
)

         RA   DEC
[1,] 150.00 2.000
[2,] 150.01 2.005

Gaussian FWHM estimate

sd <- 5
x <- matrix(-10:10, 21, 21, byrow = TRUE)
zdist <- matrix(
  exp(-1 * (t(x)^2 / (2 * sd^2) + x^2 / (2 * sd^2))),
  21, 21
)
paste(2 * sqrt(2 * log(2)) * sd, "~", get.fwhm(zdist))

[1] "11.7741002251547 ~ 12"

The analytic FWHM is approximately 11.77 pixels; get.fwhm() returns the integer pixel estimate, 12.

Sub-pixel elliptical aperture

grid <- expand.grid(-2:2, -2:2)
aperture <- generate.aperture(
  grid[, 1], grid[, 2],
  xstep = 1, ystep = 1,
  axrat = 0.5, axang = 0, majax = 2,
  resample.iterations = 0, pixscale = TRUE
)

matrix(aperture[, 3], nrow = 5)
sum(aperture[, 3])

     [,1] [,2] [,3] [,4] [,5]
[1,] 0.00  0.0  0.0  0.0 0.00
[2,] 0.25  0.5  0.5  0.5 0.25
[3,] 0.50  1.0  1.0  1.0 0.50
[4,] 0.25  0.5  0.5  0.5 0.25
[5,] 0.00  0.0  0.0  0.0 0.00
[1] 8

Simulation

create.sim() produces a simulated FITS image and catalogue from a LAMBDAR parameter file. It accepts observing parameters such as exposure time, collecting area, effective wavelength, and filter width:

create.sim(
  "Lambdar_Simulation.par",
  ObsParm = data.frame(exp = 53.9, area = 4.91, lamEff = 1111.2, Weff = 6165)
)

See ?measure.fluxes, ?create.par.file, and ?create.sim for the full parameter reference and complete examples.

License

GPL-2. See DESCRIPTION.