IRAF help page for package noao.twodspec.multispec, program msextract

• image
• output
• lower = -10
• upper = 10
• spectra = *
• lines = *
• ex_model = no
• integrated = yes
• unblend = no
• clean = yes
• nreplace = 1000.
• sigma_cut = 4.
• niterate = 1
• model = smooth
• naverage = 20
• fit_type = 2
• interpolator = spline3
• verbose = no

msextract image output

image

output

lower = -10

upper = 10

spectra = *

lines = *

ex_model = no

integrated = yes

unblend = no

clean = yes

sigma_cut = 4.

niterate = 1

model = smooth

naverage = 20

fit_type = 2

interpolator = spline3

verbose = no

The MULTISPEC database describing the spectra positions and shapes is used to guide the extraction of the spectra in the multi-spectra image. The user selects the spectra and image lines to be extracted and whether to extract integrated or strip spectra. In addition options are available to extract model spectra, replace bad pixels by model spectra values, and correct for blending of the spectra. The output_file three dimensional image consists of one band (the third dimension) per extracted spectrum, the extracted lines (the second dimension) and either one column for the integrated luminosity or the number of columns in the extracted strip.

Integrated spectra (integrated = yes) are extracted by summing the pixel or model values over the specified limits lower and upper measured relative to the spectra centers defined by the position functions in the database. Partial pixel sums are used at the endpoints.

Strip spectra (integrated = no) are extracted by image interpolation of the image line or model profiles to obtain a line of values for each spectrum and for each image line. The length of the strip is the smallest integer containing the interval between lower and upper. The strips for each spectrum are aligned so that the first column is a distance lower from the spectrum center as given by the position function in the database.

If ex_model = yes, unblend = yes, or clean = yes model spectra are fit to the spectra in the image. There are two models: a five parameter Gaussian profile called gauss5 and profiles obtained by averaging naverage image lines surrounding the image line being modeled called smooth. The model is selected either when the parameter unblend = yes or with the parameter model. If unblend = yes then the model is gauss5 regardless of the value of model.

When ex_model = yes the effect is to substitute model spectra for the image spectra in the output extraction image.

When clean = yes pixels with large residuals from the model are detected and removed from the model fit. The selected model is fit to the pixels which are not in the bad pixel list (not yet implemented) and which have not been removed from the model fit. The sigma of the fit is computed. Deviant pixels are detected by comparing them to the model to determine if they differ by more than sigma_cut times the sigma. The model fit is iterated, removing deviant pixels at each iteration, until no more pixels are found deviant or nreplace pixels have been found. The pixels removed or in the bad pixel list are then replaced with model values. (To clean an image with this algorithm see newimage.)

There are some technical differences in the model fitting and cleaning algorithms for the two models. In model smooth the fit for the profile scale factors is done independently for each spectrum and automatically corrected when a bad pixel is detected. This fitting process is fast and rigorous. The parameter nreplace in this model refers to the maximum number of pixels replaced per spectrum.

In model gauss5, however, the profile scale factors are fit to the entire image line (hence its ability to fit blended spectra). There are two fitting algorithms; a rigorous simultaneous fit and an approximate method. The simultaneous fit is selected when fit_type = 1. This step is relatively slow. The alternative method of fit_type = 2 sets the scale factor for each spectrum by taking the median scale, where scale = data / model profile, for the three pixels nearest the center of the profile. The median minimizes the chance of a large error due to a single bad pixel. This scale may be greatly in error in the case of extreme blending but is also quite fast; the extraction time is reduced by at least 40%. The steps of profile fitting and deviant pixel detection are alternated and the maximum number of iterations through these two steps is set by niterate. The default of 1 means that the model fitting is not repeated after detecting deviant pixels.

When unblend = yes the gauss5 model is fitted to the image spectra (including possible cleaning). The relative contributions to the total image pixel value from each of the blended spectra are determined from the model and applied toward either the integrated or strip spectra. If ex_model = yes then this option has no effect other than to force the selection of model gauss5.

The option verbose is used to print the image lines being extracted and the number of pixels replaced by the cleaning process.

To extract all the integrated spectra from all the image lines:

cl> msextract image image.ms

To extract model strip spectra:

cl> msextract image image.ms ex_model=yes int=no

To extract integrated spectra without any modeling:

cl> msextract image image.ms clean=no

newimage,