@begin(header)
author: Eric Mandel
show_author: ShowNone
author_organization: Smithsonian Astrophysical Observatory
node_expert: assist_xray@cfa.harvard.edu
expiration_date: 12/31/93
last_modifier: eric@foobar.mit.edu
last_mod_date: 12/05/92
mod_num: 11
@end(header)
@b<PROS Tutorials: Spectral>

This tutorial will lead you through some basic tasks in the PROS spectral
package. It assumes that you already are set up to run IRAF and that your
@b<imdir> directory exists.  

Load the @b<xray> package:
@button<xray, @dynamic[SendString,iraf,task,xray]>

Load the @b<xspectral> package:
@button<xspectral, @dynamic[SendString,iraf,task,xspectral]>

Extract a spectrum from a circle centered at at 6958,9356 with radius 120 pixels in image xdata$snr.  Background from annulus, same center, but with inner and outer radius of 130-200 pixels  The output file is arlac_obs.tab:
@button<qpspec xdata$rp110590n00.qp ..., @dynamic[SendString,iraf,task,qpspec xdata$rp110590n00.qp 'c 6958 9356 120' '' 'a 6958 9356 130 200' arlac clobber+]>


Load the @b<tables> package:
@button<tables, @dynamic[SendString,iraf,task,tables]>

Display the output table:
@button<tprint arlac_obs, @dynamic[SendString,iraf,task,tprint arlac_obs option='plain']>

Inspect counts vs. energy distribution to determine required channels.
This is done by plotting net counts vs. energy:
@button<counts_plot observed=arlac, @dynamic[SendString,iraf,task,counts_plot observed=arlac]>

(Note:Ignore warning, counts_plot looks for the fit which you have not yet run.)

While in cursor mode, you can do operations such as:

List the available cursor commands:
@button<:.help, @dynamic[SendString,iraf,task,:.help]>

(To get out of help mode, type 'q' or <CR>):
@button<q, @dynamic[SendString,iraf,task,q]>

Make a hardcopy and send it to the default IRAF printer:
@button<:.snap, @dynamic[SendString,iraf,task,:.snap]>

Quit cursor mode in plot_counts:
@button<q, @dynamic[SendString,iraf,task,q]>

Select channels 7:34 (=0.24-2.48keV):
@button<pkgpars.ros_pspc_chan='7:34', @dynamic[SendString,iraf,task,pkgpars.ros_pspc_chan='7:34']>

Run the spectral fitting program using a power-law spectrum:
@button<"fit model='abs(19:21)*pow(1:3)' ...", @dynamic[SendString,iraf,task,"fit model='abs(19:21)*pow(1:3)' observed='arlac'"]>

Plot the counts and model distribution. (Note that a power law is not a good fit to these data):
@button<counts_plot observed=arlac, @dynamic[SendString,iraf,task,counts_plot observed=arlac]>

Leave graphics window:
@button<q, @dynamic[SendString,iraf,task,q]>

List all parameters and counts for this fit:
@button<tprint arlac_prd prpar=yes, @dynamic[SendString,iraf,task,tprint arlac_prd prpar=yes option='plain']>

(THIS IS THE END OF THE TUTORIAL.)