23.04.2015 Views

ISOCAM Interactive Analysis User's Manual Version 5.0 - ISO - ESA

ISOCAM Interactive Analysis User's Manual Version 5.0 - ISO - ESA

ISOCAM Interactive Analysis User's Manual Version 5.0 - ISO - ESA

SHOW MORE
SHOW LESS

Create successful ePaper yourself

Turn your PDF publications into a flip-book with our unique Google optimized e-Paper software.

266 CHAPTER 20. ADVANCED DATA CALIBRATION<br />

20.16 Faint source data reduction with PRETI<br />

Several methods for <strong><strong>ISO</strong>CAM</strong> faint source data reduction exist:<br />

triple-beam-method (Désert, et al., 1999)<br />

Lari method (Lari, et al., 2001)<br />

This method is coded in IDL, and available as add-on package to CIA. For more informatation,<br />

please contact Carlo Lari (lari@ira.bo.cnr.it)<br />

Metcalfe method (Blommaert, et al., 2002)<br />

This method is coded in IDL, and completely based on CIA routines. For more information,<br />

please contact the <strong>ISO</strong> helpdesk (helpdesk@iso.vilspa.esa.es)<br />

PRETI method (Starck, et al., 1999)<br />

This method is based on the multiresolution package MR/2. The corresponding C++<br />

executable for Sun/Solaris is provide is with CIA, together with its IDL interface reduce<br />

faint source, which performs the following data-reduction steps:<br />

1. Slice the CISP file and create a raster pds<br />

2. Dark correction<br />

3. Calling the PRETI C++ executable which corrects glitches and performs a median<br />

flat-fielding<br />

4. Optional: Transient correction<br />

5. Conversion to milli-Jansky<br />

6. Averaging the CUBE into EXPOSURES<br />

7. Projection of the IMAGETTES into the MOSAIC<br />

Calling syntax is:<br />

CIA> reduce_faint_source, ’cisp_file.fits’, raster<br />

20.17 Error handling in CIA<br />

In this section we discuss the error calculated by CIA during the calibration and data reduction<br />

stages. We use the standard definitions:<br />

Mean = ¯x = 1 N<br />

N−1<br />

∑<br />

j=0<br />

x j (20.2)<br />

Variance = σ 2 = 1 N−1<br />

∑<br />

(x j − ¯x) 2 (20.3)<br />

N − 1<br />

j=0<br />

Standard Deviation = σ = √ Variance (20.4)<br />

σ<br />

Standard Error = √<br />

N − 1<br />

(20.5)

Hooray! Your file is uploaded and ready to be published.

Saved successfully!

Ooh no, something went wrong!