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Last modified: 15 Jan 2010
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Extracting a Spectrum of a Solar System Object

CIAO 4.2 Science Threads


Overview

Last Update: 15 Jan 2010 - updated for CIAO4.2: changes to the ds9 region menu

Synopsis:

The sso_freeze tool can reproject the event data to the reference frame of the solar system object, as well as creating an object-centered aspect solution file. Together these files can be used to extract an object-centered spectrum and create the corresponding Response Matrix Files (RMFs) and Ancillary Response Files (ARFs).

This procedure is identical to the basic spectral extraction explained in the Step-by-Step Guide to Creating ACIS Spectra for Pointlike Sources, except that an object-centered coordinate system (ocx,ocy) is used in place of the sky (x,y) coordinates.

Purpose:

To generate source and background PI (PHA) spectra of a moving solar system object and build the proper RMFs and ARFs.



Contents


Get Started

Sample ObsID used: 1463 (ACIS-S, Jupiter)

File types needed: evt2; asol1; eph1; pbk0


Creating Object-centered Event and Aspect Solution Files

There are separate threads which describe the sso_freeze tool and its uses in detail:

The following command was used to create the event and aspect solution files for this thread: 

unix% punlearn sso_freeze
unix% sso_freeze infile=acisf01463N002_evt2.fits asolfile=pcadf059968984N002_asol1.fits \
      scephemfile=orbitf059443264N002_eph1.fits ssoephemfile=jupiterf059875200N002_eph1.fits \
      ocsolfile=1463_oc_asol1.fits outfile=1463_oc_evt2.fits

In the new event file, the origin of the OC coordinate system is (0,0). The RA and Dec header keyword values are updated with dmhedit to reflect this, so that the correct reference point is used in the rest of the analysis: 

unix% cat edits.lis 
#add
RA_NOM = 0.0
DEC_NOM = 0.0
RA_PNT = 0.0
DEC_PNT = 0.0

unix% dmhedit 1463_oc_evt2.fits filelist=edits.lis

Downloading acis_fef_lookup

This thread uses the acis_fef_lookup script, which is part of the CIAO Scripts distribution. The CIAO scripts package should be the following version or newer: 

unix% cat $ASCDS_CONTRIB/VERSION.CIAO_scripts
14 Dec 2009

Please check that you have at least this version of the scripts package installed before continuing. If you do not have the scripts installed or need to update to a newer version, refer to the Scripts page.


Define the Source and Background Regions

We need to define two regions, one for the source and another for the background. To do this, first display the data in the object-centered coordinates (ocx,ocy): 

unix% ds9 "1463_oc_evt2.fits[bin=ocx,ocy]" &

In this example, the source (Jupiter) is defined by a circle with a radius of 60 pixels and the background is defined by three, 25-pixel-radius circles. Both regions are shown in Figure 1. The background region can also be selected from a different chip or different event file, if desired.

To save the regions, follow these steps:

  1. Region → Save Regions... → Save As "src.reg" (source) and "bg.reg" (background). To select multiple regions for saving, hold down the <SHIFT> key and click on each one.
  2. After choosing "OK" in the region filename dialog, a format dialog is opened. Set the format to "CIAO" and the coordinate system to "Physical".

Figure 1: Extraction regions on the event file

[Thumbnail image: The source region is shown as a white circle; the background region is comprised of the three green, dashed circles.]

[Version: full-size]

[Print media version: The source region is shown as a white circle; the background region is comprised of the three green, dashed circles.]

Figure 1: Extraction regions on the event file

The background was chosen from a from source-free area of the same chip for this example, but it may also be chosen from a different chip or different event file.

The resulting region files look like: 

unix% cat src.reg
# Region file format: CIAO version 1.0
circle(4116,4088,60)

unix% cat bg.reg
# Region file format: CIAO version 1.0
circle(3957,4182,25)
circle(3896,4106,25)
circle(3956,4036,25)

It is a good idea to check the image in sky(x,y) coordinates as well to be sure that there aren't any point sources which might contaminate the background region. These point sources show up as streaks in the object-centered image and may be difficult to see. A few sources to avoid are marked with white circles in Figure 2.

Figure 2: Event file displayed in sky (x,y) coordinates

[Thumbnail image: The x-ray point sources are circled in white.]

[Version: full-size]

[Print media version: The x-ray point sources are circled in white.]

Figure 2: Event file displayed in sky (x,y) coordinates

When choosing the background regions, be sure to avoid areas where the x-ray point sources - circled in white - might contribute to the counts.


Extract Source and Background Spectra (dmextract)

In this example, we extract the spectra in pulse invariant (PI) space. This creates a histogram of number of counts vs. PI channel. The region filter is applied to the (ocx,ocy) columns in the event file: 

unix% punlearn dmextract
unix% pset dmextract infile="1463_oc_evt2.fits[(ocx,ocy)=region(src.reg)][bin pi]"
unix% pset dmextract outfile=jupiter.pi
unix% dmextract
Input event file  (1463_oc_evt2.fits[(ocx,ocy)=region(src.reg)][bin pi]):
Enter output file name (jupiter.pi):

And for the background spectrum: 

unix% pset dmextract infile="1463_oc_evt2.fits[(ocx,ocy)=region(bg.reg)][bin pi]"
unix% pset dmextract outfile=jupiter_bg.pi
unix% dmextract
Input event file  (1463_oc_evt2.fits[(ocx,ocy)=region(bg.reg)][bin pi]):
Enter output file name (jupiter_bg.pi):

You can check the parameter file that was used with plist dmextract.


Locate Centroids (dmstat)

Since the calibration varies across the chips, we need to locate the centroid (in chip coordinates) of the source and background regions. This information is needed to create the ARFs, as well as to select which FEF (FITS Embedded Function) to use in calculating the RMFs with mkrmf. For the source: 

unix% dmstat "1463_oc_evt2.fits[(ocx,ocy)=region(src.reg)][cols chipx,chipy,ccd_id,ocx,ocy]"
chip(chipx, chipy)[pixel]
    min:        ( 300 369 )           @:        ( 4137 674 )
    max:        ( 452 644 )           @:        ( 66982 70695 )
   mean:        ( 379.16560661 490.80174073 )
  sigma:        ( 28.377409253 46.738174943 )
    sum:        ( 27183899 35187540 )
   good:        ( 71694 71694 )
   null:        ( 0 0 )

ccd_id
    min:        7             @:        1 
    max:        7             @:        1 
   mean:        7 
  sigma:        0 
    sum:        501858 
   good:        71694 
   null:        0 

oc(ocx, ocy)[pixel]
    min:        ( 4056.2948414 4029.3782052 )         @:        ( 64442 15531 )
    max:        ( 4174.9612103 4147.9391422 )         @:        ( 56943 35070 )
   mean:        ( 4117.0205639 4089.8824481 )
  sigma:        ( 22.481838856 23.365494034 )
    sum:        ( 295165672.31 293220032.23 )
   good:        ( 71694 71694 )
   null:        ( 0 0 )

The centroid of the distribution is at (chipx,chipy) = (379.17,490.80). Note also that the mean position is (ocx,ocy) = (4117.02,4089.88) and is on CCD 7 (ACIS-S3).

And for the background: 

unix% dmstat "1463_oc_evt2.fits[(ocx,ocy)=region(bg.reg)][cols chipx,chipy,ccd_id,ocx,ocy]"
chip(chipx, chipy)[pixel]
    min:        ( 228 214 )           @:        ( 21 40 )
    max:        ( 439 489 )           @:        ( 325 449 )
   mean:        ( 326.7012987 332.93722944 )
  sigma:        ( 59.309752219 56.448520386 )
    sum:        ( 150936 153817 )
   good:        ( 462 462 )
   null:        ( 0 0 )

ccd_id
    min:        7             @:        1 
    max:        7             @:        1 
   mean:        7 
  sigma:        0 
    sum:        3234 
   good:        462 
   null:        0 

oc(ocx, ocy)[pixel]
    min:        ( 3871.0819593 4011.6378364 )         @:        ( 147 220 )
    max:        ( 3981.3509239 4205.2868584 )         @:        ( 358 219 )
   mean:        ( 3935.9608861 4110.4563662 )
  sigma:        ( 31.127925412 61.51227531 )
    sum:        ( 1818413.9294 1899030.8412 )
   good:        ( 462 462 )
   null:        ( 0 0 )

The centroid of the background distribution is at (chipx,chipy) = (326.70,332.94). Note also that the mean position is (ocx,ocy) = (3935.96,4110.46) and is also on CCD 7 (ACIS-S3). You can check the parameter file that was used with plist dmstat.


Calculate the RMFs

The syntax for both mkacisrmf and mkrmf are given in this section. Users must choose the appropriate tool for the data and calibration. Refer to the Creating ACIS RMFs why topic for more information.

The observation used in this thread (ObsID 1463) was taken at the -109 C focal plane temperature, so mkrmf is used to create the RMF.

A. Using mkacisrmf (mkacisrmf)

The Creating ACIS RMFs with mkacisrmf thread has details on using the mkacisrmf tool. First determine which gain file was used in the data processing: 

unix% dmkeypar evt2.fits gainfile echo+
acisD2000-01-29gain_ctiN0006.fits

This event file has been reprocessed with the version 6 gain file. For this gain, use the acisD2000-01-29p2_respN0006.fits file as the infile parameter. The ccd_id value and (chipx,chipy) position from dmstat are also input. For the source: 

unix% punlearn mkacisrmf
unix% pset mkacisrmf infile=$CALDB/data/chandra/acis/p2_resp/acisD2000-01-29p2_respN0006.fits 
unix% pset mkacisrmf outfile=jupiter_mkacisrmf.rmf
unix% pset mkacisrmf energy=0.1:11.0:0.01
unix% pset mkacisrmf channel=1:1024:1
unix% pset mkacisrmf chantype=PI
unix% pset mkacisrmf wmap=none
unix% pset mkacisrmf ccd_id=7 chipx=379.17 chipy=490.80
unix% pset mkacisrmf gain=$CALDB/data/chandra/acis/det_gain/acisD2000-01-29gain_ctiN0006.fits

unix% mkacisrmf
scatter/rsp matrix file (/soft/ciao/CALDB/data/chandra/acis/p2_resp/acisD2000-01-29p2_respN0006.fits):
RMF output file (jupiter_mkacisrmf.rmf):
WMAP file (none):
energy grid in keV (lo:hi:bin) (0.1:11.0:0.01):
channel grids in pixel (min:max:bin) (1:1024:1):
channel type (PI|PHA) (PI):
filter CCD-ID (0:9) (7):
filter chipx in pixel (379):
filter chipy in pixel (490):
gain file (/soft/ciao/CALDB/data/chandra/acis/det_gain/acisD2000-01-29gain_ctiN0006.fits):

INFO: Effective user energy (keV) grids will be re-arranged in
     0.25000 - 11.00000


Single region, #1392 , processed.

For the background: 

unix% pset mkacisrmf outfile=jupiter_bg_mkacisrmf.rmf
unix% pset mkacisrmf ccd_id=7 chipx=326.70 chipy=332.94

unix% mkacisrmf
scatter/rsp matrix file (/soft/ciao/CALDB/data/chandra/acis/p2_resp/acisD2000-01-29p2_respN0006.fits):
RMF output file (jupiter_bg_mkacisrmf.rmf):
WMAP file (none):
energy grid in keV (lo:hi:bin) (0.1:11.0:0.01):
channel grids in pixel (min:max:bin) (1:1024:1):
channel type (PI|PHA) (PI):
filter CCD-ID (0:9) (7):
filter chipx in pixel (326):
filter chipy in pixel (332):
gain file (/soft/ciao/CALDB/data/chandra/acis/det_gain/acisD2000-01-29gain_ctiN0006.fits):

INFO: Effective user energy (keV) grids will be re-arranged in
     0.25000 - 11.00000


Single region, #1355 , processed.

You can check the parameter file that was used with plist mkacisrmf.

If you use mkacisrmf to create the RMFs, you can now continue to the Calculate the ARFs step.

B. Using mkrmf (acis_fef_lookup, mkrmf)

First acis_fef_lookup is needed to determine the correct FEFs. The ccd_id value and (chipx,chipy) position from dmstat are input. For the source: 

unix% punlearn acis_fef_lookup
unix% acis_fef_lookup 1463_oc_evt2.fits 7 379.17 490.80 
/soft/ciao/CALDB/data/chandra/acis/fef_pha/acisD1999-09-16fef_phaN0002.fits[2][ccd_id=7,chipx=353:384,chipy=481:512]

and for the background: 

unix% acis_fef_lookup 1463_oc_evt2.fits 7 326.70 332.94
/soft/ciao/CALDB/data/chandra/acis/fef_pha/acisD1999-09-16fef_phaN0002.fits[2][ccd_id=7,chipx=321:352,chipy=321:352]

You can check the parameter file that was used with plist acis_fef_lookup.

Now that we have the FEFs, we can compute the RMFs with mkrmf. The energy range (keV) for axis1 should cover the detector response range, which is ~0.2-10 keV for ACIS-S. The default for extraction in PI space is axis2=1:1024:1.

For the source: 

unix% punlearn mkrmf
unix% pset mkrmf infile="/soft/ciao/CALDB/data/chandra/acis/fef_pha/acisD1999-09-16fef_phaN0002.fits[2][ccd_id=7,chipx=353:384,chipy=481:512]"
unix% pset mkrmf outfile=jupiter.rmf
unix% pset mkrmf axis1="energy=0.1:11.0:0.01"
unix% pset mkrmf axis2="pi=1:1024:1"

unix% mkrmf
name of FEF input file (/soft/ciao/CALDB/data/chandra/acis/fef_pha/acisD1999-09-16fef_phaN0002.fits[2][ccd_id=7,chipx=353:384,chipy=481:512]):
name of RMF output file (jupiter.rmf):
axis-1(name=lo:hi:btype) (energy=0.1:11.0:0.01):
axis-2(name=lo:hi:btype) (pi=1:1024:1):

and for the background: 

unix% pset mkrmf infile="/soft/ciao/CALDB/data/chandra/acis/fef_pha/acisD1999-09-16fef_phaN0002.fits[2][ccd_id=7,chipx=321:352,chipy=321:352]"
unix% pset mkrmf outfile=jupiter_bg.rmf

unix% mkrmf
name of FEF input file (/soft/ciao/CALDB/data/chandra/acis/fef_pha/acisD1999-09-16fef_phaN0002.fits[2][ccd_id=7,chipx=321:352,chipy=321:352]):
name of RMF output file (jupiter_bg.rmf):
axis-1(name=lo:hi:btype) (energy=0.1:11.0:0.01):
axis-2(name=lo:hi:btype) (pi=1:1024:1):

You can check the parameter file that was used with plist mkrmf.


Calculate the ARFs

1. Compute the Aspect Histogram (asphist)

With the OC aspect solution file we can create a binned histogram detailing the aspect history of the observation.

Data Model syntax is used in the infile parameter to rename the "OCSOL" block to "ASPSOL". The "ocra" and "ocdec" columns are also renamed on-the-fly to "ra" and "dec", respectively. The changes are required because asphist expects the block and columns to have those names. 

unix% punlearn asphist
unix% pset asphist infile=1463_oc_asol1.fits"[ocsol][ASPSOL][cols time,ra=ocra,dec=ocdec,roll,dy,dz,dtheta]"
unix% pset asphist outfile=jupiter.asphist
unix% pset asphist evtfile="1463_oc_evt2.fits[ccd_id=7]"

unix% asphist
Aspect Solution List Files (1463_oc_asol1.fits[ocsol][ASPSOL][cols time,ra=ocra,dec=ocdec,roll,dy,dz,dtheta]):
Aspect Histogram Output File (jupiter.asphist):
Event List Files (1463_oc_evt2.fits[ccd_id=7]):

You can check the parameter file that was used with plist asphist.

2. Compute the ARFs (mkarf)

In addition to the aspect histogram file, the mean position in (ocx,ocy) calculated by dmstat is input to mkarf. The RMF file is used to define the energy grid (engrid) to ensure that the ARF is made on the same grid.

For the source, (ocx,ocy) = (4117.02,4089.88): 

unix% punlearn mkarf
unix% pset mkarf outfile=jupiter.arf
unix% pset mkarf asphistfile="jupiter.asphist[ASPHIST]"
unix% pset mkarf obsfile="1463_oc_evt2.fits[EVENTS]"
unix% pset mkarf pbkfile=acisf059969672N002_pbk0.fits
unix% pset mkarf dafile=CALDB
unix% pset mkarf detsubsys=ACIS-S3
unix% pset mkarf engrid="grid(jupiter.rmf[cols ENERG_LO,ENERG_HI])"
unix% pset mkarf sourcepixelx=4117.02 sourcepixely=4089.88

unix% mkarf 
Aspect Histogram File (jupiter.asphist[ASPHIST]): 
Output File Name (jupiter.arf): 
Source X Pixel (4146.05): 
Source Y Pixel (4045.95): 
Energy grid spec (grid(jupiter.rmf[cols ENERG_LO,ENERG_HI])): 
Name of fits file with obs info (evt file -- include extension) (1463_oc_evt2.fits[EVENTS]): 
Verbosity (0:5) (0): 
Detector Name (ACIS-S3): 
Grating for zeroth order ARF (NONE|LETG|HETG) (HETG): 
NONE, or name of ACIS window mask file (): 
NONE, or the name of the parameter block file (acisf059969672N002_pbk0.fits):

and for the background, (ocx,ocy) = (3935.96,4110.46): 

unix% pset mkarf outfile=jupiter_bg.arf
unix% pset mkarf engrid="grid(jupiter_bg.rmf[cols ENERG_LO,ENERG_HI])"
unix% pset mkarf sourcepixelx=3935.96 sourcepixely=4110.46
unix% mkarf 
Aspect Histogram File (jupiter.asphist[ASPHIST]):
Output File Name (jupiter_bg.arf):
Source X Pixel (3935.96):
Source Y Pixel (4110.46):
Energy grid spec (grid(jupiter_bg.rmf[cols ENERG_LO,ENERG_HI])):
Name of fits file with obs info (evt file -- include extension) (1463_oc_evt2.fits[EVENTS]):
Verbosity (0:5) (0):
Detector Name (ACIS-S3):
Grating for zeroth order ARF (NONE|LETG|HETG) (NONE):
NONE, or name of ACIS window mask file (NONE):
NONE, or the name of the parameter block file (acisf059969672N002_pbk0.fits):

You can check the parameter file that was used with plist mkarf.


Update File Headers (dmhedit)

Finally, add the background and response filenames to the header of the streak spectrum file. 

unix% dmhedit infile=jupiter.pi filelist="" operation=add key=BACKFILE value=jupiter_bg.pi
unix% dmhedit infile=jupiter.pi filelist="" operation=add key=RESPFILE value=jupiter.rmf
unix% dmhedit infile=jupiter.pi filelist="" operation=add key=ANCRFILE value=jupiter.arf

Fitting

To fit the streak spectrum using the RMF and ARF, simply read the source spectrum FITS file into Sherpa, subtract the background, and fit it. See the Introduction to Fitting PHA Spectra thread for details.


Analysis Caveats

Users should be cautious about analyzing the data for sources near the edges of the ACIS CCDs.

  1. For X-rays passing through the mirrors, the very bottom of each CCD is obscured by the frame store. As a result, some of the events in rows with CHIPY <= 8 are not detected. (The set of rows affected varies from CCD to CCD.) Since the CIAO tools do not compensate for this effect, the ARFs and exposure maps for sources in these regions may be inaccurate.

  2. For sources within about thirty-two pixels of any edge of a CCD, the source may be dithered off the CCD during part of an observation. The aspect histogram, which is used to create ARFs and exposure maps, is designed to compensate for this effect.

  3. An ARF calculated at the edge of a chip will not be accurate. The response tools for spectral extraction (specifically the ARF) assume that 100% of the PSF is enclosed - i.e. on the chip - all the time, which may not be the case. The amount of error introduced depends on how close the source is to the edge, the morphology of the source, and the characteristics of the PSF, which depends on the source spectrum.

  4. A contaminant has accumulated on the optical-blocking filters of the ACIS detectors, as described in the ACIS QE Contamination why topic. Since there is a gradient in the temperature across the filters (the edges are colder), there is a gradient in the amount of material on the filters. (The contaminant is thicker at the edges.) Within about 100 pixels of the outer edges of the ACIS-I and ACIS-S arrays, the gradient is relatively steep. Therefore, the effective low-energy (' 1 keV) detection efficiency may vary within the dither pattern in this region. The ARF and instrument map tools are designed to read a calibration file which describes this spatial dependence. 



Parameters for /home/username/cxcds_param/dmextract.par


        infile = 1463_oc_evt2.fits[(ocx,ocy)=region(bg.reg)][bin pi] Input event file
       outfile = jupiter_bg.pi    Enter output file name
          (bkg = )                Background region file or fixed background (counts/pixel/s) subtraction
        (error = gaussian)        Method for error determination(gaussian|gehrels|<variance file>)
     (bkgerror = gaussian)        Method for background error determination(gaussian|gehrels|<variance file>)
      (bkgnorm = 1.0)             Background normalization
          (exp = )                Exposure map image file
       (bkgexp = )                Background exposure map image file
      (sys_err = 0)               Fixed systematic error value for SYS_ERR keyword
          (opt = pha1)            Output file type
     (defaults = ${ASCDS_CALIB}/cxo.mdb -> /soft/ciao/data/cxo.mdb) Instrument defaults file
         (wmap = )                WMAP filter/binning (e.g. det=8 or default)
      (clobber = no)              OK to overwrite existing output file(s)?
      (verbose = 0)               Verbosity level
         (mode = ql)
    

Parameters for /home/username/cxcds_param/dmstat.par


        infile = 1463_oc_evt2.fits[(ocx,ocy)=region(bg.reg)][cols chipx,chipy,ccd_id,ocx,ocy] Input file specification
   out_columns = chipx,chipy,ccd_id,ocx,ocy Output Column Label
       out_min = 228,214,7,3871.0819593,4011.6378364 Output Minimum Value
   out_min_loc = 21,40,1,147,220  Output Minimum Location Value
       out_max = 439,489,7,3981.3509239,4205.2868584 Output Maximum Value
   out_max_loc = 325,449,1,358,219 Output Maxiumum Location Value
      out_mean = 326.7012987,332.93722944,7,3935.9608861,4110.4563662 Output Mean Value
    out_median =                  Output Median Value
     out_sigma = 59.309752219,56.448520386,0,31.127925412,61.51227531 Output Sigma Value
       out_sum = 150936,153817,3234,1818413.9294,1899030.8412 Output Sum of Values
      out_good = 462,462,462,462,462 Output Number Good Values
      out_null = 0,0,0,0,0        Output Number Null Values
    out_cnvrgd =                  Converged?
 out_cntrd_log =                  Output Centroid Log Value
out_cntrd_phys =                  Output Centriod Phys Value
out_sigma_cntrd =                  Output Sigma Centriod Value
     (centroid = yes)             Calculate centroid if image?
       (median = no)              Calculate median value?
        (sigma = yes)             Calculate the population standard deviation?
         (clip = no)              Calculate stats using sigma clipping?
       (nsigma = 3)               Number of sigma to clip
      (maxiter = 20)              Maximum number of iterations
      (verbose = 1)               Verbosity level
         (mode = ql)
    

Parameters for /home/username/cxcds_param/mkacisrmf.par


        infile = /soft/ciao/CALDB/data/chandra/acis/p2_resp/acisD2000-01-29p2_respN0006.fits scatter/rsp matrix file
       outfile = jupiter_bg_mkacisrmf.rmf RMF output file
          wmap = none             WMAP file
        energy = 0.1:11.0:0.01    energy grid in keV (lo:hi:bin)
       channel = 1:1024:1         channel grids in pixel (min:max:bin)
      chantype = PI               channel type
        ccd_id = 7                filter CCD-ID
         chipx = 326              filter chipx in pixel
         chipy = 332              filter chipy in pixel
          gain = /soft/ciao/CALDB/data/chandra/acis/det_gain/acisD2000-01-29gain_ctiN0006.fits gain file
     (asolfile = )                aspect solution file or a stack of asol files
      (obsfile = )wmap -> none)   obs file
      (logfile = )                log file
      (contlvl = 100)             # contour level
      (geompar = geom)            pixlib geometry parameter file
       (thresh = 1e-06)           low threshold of energy cut-off probability
      (clobber = no)              overwrite existing output file (yes|no)?
      (verbose = 0)               verbosity level (0 = no display)
         (mode = ql)
    

Parameters for /home/username/cxcds_param/acis_fef_lookup.par


        infile = 1463_oc_evt2.fits Source file (event or spectrum)
        chipid = 7                ACIS chip number
         chipx = 326              ACIS chip x coordinate
         chipy = 332              ACIS chip y coordinate
       outfile = /soft/ciao/CALDB/data/chandra/acis/fef_pha/acisD1999-09-16fef_phaN0002.fits[2][ccd_id=7,chipx=321:352,chipy=321:352] FEF file to use
      (quality = yes)             Should you use the FEF file (if no use mkacisrmf)?
      (verbose = 0)               Verbose level
         (mode = ql)
    

Parameters for /home/username/cxcds_param/mkrmf.par


        infile = /soft/ciao/CALDB/data/chandra/acis/fef_pha/acisD1999-09-16fef_phaN0002.fits[2][ccd_id=7,chipx=321:352,chipy=321:352] name of FEF input file
       outfile = jupiter_bg.rmf   name of RMF output file
         axis1 = energy=0.1:11.0:0.01 axis-1(name=lo:hi:btype)
         axis2 = pi=1:1024:1      axis-2(name=lo:hi:btype)
      (logfile = STDOUT)          name of log file
      (weights = )                name of weight file
       (thresh = 1e-5)            low threshold of energy cut-off probability
       (outfmt = legacy)          RMF output format (legacy|cxc)
      (clobber = no)              overwrite existing output file (yes|no)?
      (verbose = 0)               verbosity level (0 = no display)
        (axis3 = none)            axis-3(name=lo:hi:btype)
        (axis4 = none)            axis-4(name=lo:hi:btype)
        (axis5 = none)            axis-5(name=lo:hi:btype)
         (mode = ql)
    

Parameters for /home/username/cxcds_param/asphist.par


        infile = 1463_oc_asol1.fits[ocsol][ASPSOL][cols time,ra=ocra,dec=ocdec,roll,dy,dz,dtheta] Aspect Solution List Files
       outfile = jupiter.asphist  Aspect Histogram Output File
       evtfile = 1463_oc_evt2.fits[ccd_id=7] Event List Files
       dtffile =                  Live Time Correction List Files for HRC
      (geompar = geom)            Parameter file for Pixlib Geometry files
       (res_xy = 0.5)             Aspect Resolution x and y in arcsec
     (res_roll = 600.)            Aspect Resolution roll in arcsec
      (max_bin = 10000.)          Maximal number of bins
      (clobber = no)              Clobber output
      (verbose = 0)               Verbose
         (mode = ql)
    

Parameters for /home/username/cxcds_param/mkarf.par


   asphistfile = jupiter.asphist[ASPHIST] Aspect Histogram File
       outfile = jupiter_bg.arf   Output File Name
  sourcepixelx = 3935.96          Source X Pixel
  sourcepixely = 4110.46          Source Y Pixel
        engrid = grid(jupiter_bg.rmf[cols ENERG_LO,ENERG_HI]) Energy grid spec
       obsfile = 1463_oc_evt2.fits[EVENTS] Name of fits file with obs info (evt file -- include extension)
       pbkfile = acisf059969672N002_pbk0.fits NONE, or the name of the parameter block file
     detsubsys = ACIS-S3          Detector Name
       grating = NONE             Grating for zeroth order ARF
      maskfile = NONE             NONE, or name of ACIS window mask file
       verbose = 0                Verbosity
       (dafile = CALDB)           NONE, CALDB, or name of ACIS dead-area calibration file
       (mirror = HRMA)            Mirror Name
(ardlibparfile = ardlib.par)      name of ardlib parameter file
      (geompar = geom)            Parameter file for Pixlib Geometry files
      (clobber = no)              Overwrite existing files?
         (mode = ql)              Enter mode for parameter file.

History

24 Jul 2009 new for CIAO 4.1
15 Jan 2010 updated for CIAO4.2: changes to the ds9 region menu
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Where are the PDFs?
Last modified: 15 Jan 2010