Spitzer Documentation & Tools
Spitzer Data Analysis Cookbook

 

Recipe 20.                                    SMART screen shot recipe

This example includes a step by step extraction of the source SMPLMC36 (AORkey=4949348), a planetary nebulae in the LMC. For simplicity this example includes only the extraction of the SL module. It includes snapshots of the GUI at every step. It does not explain the purposes of the different steps as this is explain in the previous recipe.  Remember that we recommend to save the project at each step.

20.1            Start SMART

Type smart in the terminal.

20.2            Data preparation

In the initial GUI create a new project and new data set by clicking on New under the Project menu. In this case we shall call it smplmc36. Click Ok.

 

 

 

Highlight the Data set and either double click on it or click Edit button. A new GUI appears.

 

 

Click on Add to add data sets to import the data ({bcd, func, bmask}.fits) into the dataset. The new Gui will show the files imported.

 

 

 

Select all the imported files and click on Image operations -> 3-plane data -> Make 3-plane data. This creates *_bcd3p records.

 

 

Select the bcd3p records and click on Image operations -> Clean using IRSCLEAN -> Clean!. Leave the default values and click on Proceed. This creates cl*_filename.fits records.

 

 

 

Select all the cleaned records (cl_*bcd3p) and click on Image operations -> Automatically combine DCEs for a given ExpID.  This will combine the individual exposures and creates the com_cl*_filename.fits records.

 

20.3            Background subtraction (and low-level rogue pixels removal)

In this example we shall subtract the background from the correspondent nod position.

 

For each module and order (in this case SL1, and SL2), we select the 2 nods and click on Image operations -> Image combinations & arithmetics -> Arithmetics. Then type the appropriate subtraction equation: Input the operation im1-im2 and call that SL1_nod1.fits. Using the same selected files do the operation im2-im1, that will contain SL1_nod2.fits. Repeat for SL1.

 

20.4            Spectral extraction

In this case this is a point like source and we are going to performed an automatic optimal extraction. While not shown here, it is advised to run the AdOpt algorithm on at least one exposure of each module in order to check the actual extent of the source, the possible presence of multiple sources, and/or the presence of a significant extended background emission.

 

Select all the data. And click on Extract. As mentioned before in this case we select automatic optimal extraction. One could select automatic tapered or any other option.

 

20.5            Spectra visualiation and analysis

Once the extraction is completed, the spectra is displayed in IDEA automatically. By default only the first spectrum is shown. To display another spectrum, click on the corresponding checkbox in the Stored datasets window, click on Choose an apply a function, and click on Make prime dataset.

 

 

 

 

To overplot all the spectra, click on Merge/overplot all data sets (shown in figure). In order to store the file containing the merged modules/orders click on Merge/Overplot all data sets. Click on Store Prime (the Store data sets disappears). Then click on Stored Spectra (the updated Store data sets appears). The name of this file is long but we can modify it in the Store data sets window by choosing Apply function*->*Change Name.

 

 

 

20.6            Saving the data

Click the Copy Spectra to Project Manager as shown in the figure (option2) so that the spectra is saved in the project manager. There are several options to store the data in a given directory and format. The data can be written in a given directory (and format) using the store buttom in the IDEA GUI (option 1 first figure below). Also, the data can be exported form the Project Manager GUI as in the second figure below.

 

 

 

 

*Finally and very important, save the project! and exit.