Antonella Fruscione 20 May 2002 Introduction to...

Antonella Fruscione 20 May 2002

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Introduction to CIAO(Chandra Interactive Analysis of Obse

rom "ahelp ciao"....

A powerful data analysis system originally writtensers of the Chandra X-ray Observatory.

Built to handle N-dimensional data without concearticular axes are being analyzed: Chandra is the-dimensional data (2 spatial, time, energy) in whicon has many independent elements.

It is mission independent (a part from a few instruols).


project the 4-Dnvenient array:ation on the

‘regions’ syntax:t makes all this

and binnedtrack of this sub-

vious data pro-

f tools. For exam-can be fed into

an then be fit in

CXC

● Provides users with the ability to filter down and Chandra event data to manageable sizes and coall CIAO tools take a ‘filtering and binning’ specificcommand line, making use of a general purpose “ahelp dm” for information on the Data Model thapossible.

● To keep track of how the data had been filteredCIAO relies on the ‘data subspace’. The tools keepspace automatically and allow users to review precessing: see “ahelp subspace”.

● The CIAO design allows close interconnection ople, the output of any of source detection programdmextract to create a summed spectrum which cSherpa.


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● the CIAO sys-te ata in N-dimen-si h can be usedfo erpa results toth entification ofsp er fitting. See“

● e-existing tools,a ing FITS imagesa oe and imh files.

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The modeling and fitting tool Sherpa is central tom. Sherpa performs forward fitting of models to d

ons. Sherpa includes the “S-Lang” language whicr scripting and data manipulation. GUIDE links She APEC/APED plasma database, enabling the idectral lines and the use of their properties in furth

ahelp sherpa”, “ahelp slang”, “ahelp guide”.

In order to allow users of Chandra data to use prll CIAO tools read and write several formats, includnd tables (which includes event files) and IRAF qp


.. sherpa) and numer-ve their own help about 500 pages!)

ocumentation:

f subjects related to

y

CXC

CIAO help!

AHELP

CIAO comes with its own help system called ahelpTools (e.g. dmcopy, wavdetect), applications (e.gous concepts (e.g. regions, coords, dmsyntax) hatext. (The entire collection of ahelp files is currently

The ahelp command accesses the CIAO on-line d

% about <word> (e.g. about contour) gives a list othe query% ahelp <name> (e.g. ahelp tgextract) provides bdefault the ASCII version of the help file


version supplied

ntains HTML andte than the

o teach users by

ted” icons!). or will be made

CXC

% ahelp -w <name> loads into a browser the HTMLwith the CIAO distribution

NEW in CIAO 2.2:% ahelp -i <name> access the CIAO site which coPDF versions of the help files (often more up-to-dareleased ones).

DATA ANALYSIS THREADSMore than 90 CIAO processing recipes designed tleading step-by-step through a procedure.More added weekly (look for the “new” or “updaSeveral threads and groups of threads have beenmore automated in the form of scripts.PDF version available on-line.


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MC ed: majoru odel/DataM A CIAO-SLANGm

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ANUALSIAO manuals are currently being written or updatpdates for CIAO2.2 were done to the DM (Data Manipulation), Detect, Sherpa and Chips Manuals.anual is in progress.

IAO WEB PAGESead the Dictionary, FAQ, Bugs, Caveats

ELPDESKhen everything else fails....

ttp://cxc.harvard.edu/helpdesk/


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● d “complex”:

● n from a GUI.●● d:

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What is CIAO?

Collection of programs (both “atomic”: tools, anapplications).

Generally run from the shell; some part can be ruSource code is available.Available on several platforms; currently supporte

Solaris 2.6 (2.7, 2.8)Red Hat Linux 6.2, 7.1Slackware 7.1SuSE 7.2 (7.x)Alpha OSF4.0f


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● QPOE) andA● ta (keywords,su● . GTI, weightm● olumns can bev●

ThW start up the sys-te nd path assign-m●●

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hat formats does it work with?

Chandra data is stored in FITS format. IRAF (IMH &SCII files can be handled by many tools.Stores processing state/information along with dabspace).A single file can contain multiple “datasets” (e.gap, regions) stored in “blocks”.Blocks can contain image or table data. Table c

ectors.Use dmlist or prism to view file contents.

e CIAO Environmente recommend the use of an alias called “ciao” tom: it sets up a number of environment variables aents.ciao -v what version you are usingciao -h help on how to setup CIAO


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P nd line or, asw are stored in~ and are ASCIIfi d write to thesefi

P

● sing the GUIs)● ixel mask for ano

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arameter Files

arameters to programs can be set on the commaith IRAF and FTOOLS, using parameter files. These /cxcds_param/ by default, are called <tool>.par, les. A number of routines are provided to read anles (e.g. plist, pset, punlearn).

arameters:

provide a simple history mechanism (e.g. when uset parameters that rarely change (e.g. a bad-p

bservation)

e careful when analyzing more than one dataset


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F● tial part of X-raya or aspect solu-ti e

● stat“S

● at times periodso ata). They areg

● ground areas ofa anually orw (source.reg)]”).

● list can read thish

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ilters, Regions, and GTIsfiltering (removal of unwanted events) is an essen

nalysis - remove periods of high background or poon, or exclude uninteresting sources from an imag

the DataModel (DM) provides great flexibility: dmevt2.fits[EVENTS][energy>300][cols -grade]”ee: ahelp filtering

GTIs (Good Time Intervals) are used to define whf the observation can be used (i.e. contain valid denerally stored as a block in the event list.

Regions are used to define the source and backn image. They are text files that can be created mithin ds9, and are used as a filter (e.g. “[sky=region

Subspace records the filters applied to a file; dmistory using opt=subspace.


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DC ion, correctfo , createaRS ctTi src_regionC convolve,aPMS

(* bilities are nowp language.

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CIAO overviewatamodel:copy, filter, extraction, stats,...handra Specific Instrument tools: update calibratr instrumental effects, find & extract grating dataspect histogramsesponse tools: exposure map, PSF, RMF and ARFource Detection: celldetect, wavdetect, vtpdeteming & Background tools: lightcurve, axbary, get_onvolutions, Transforms, & Smoothing: csmooth, acrosscorr, apowerspectrumlotting: (*) ChIPSodeling/Fitting: (*) Sherpa

pectral Line Identification: GUIDE, ISIS

) powerful data manipulation and scripting capaossible with the inclusion of the S-Lang interpreted


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● ilt on aXC Data

● ata

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The “Data Model” and Data Manipulation Too

The CXC analysis and processing software is bucommon versatile interface library called the CModel (or just DM).

The DM provides users with a powerful built-in dfiltering and binning capability.

The name “Data Model” reflects the fact thatthe interface can be used on data files ofdifferent format (all described by a singleabstract description - the same “model”) in atransparent way.


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As of CIAO2.2, the format supported by the DMlibrary include: FITS, IRAF QPOE and IRAF IMH.

An important characteristic of the DM is that ANprogram that asks for a data file name as inputwill accept a virtual file string which will causethe program to see a filtered version of the file question.

The “virtual file” syntax is also commonly used tocreate on disk a filtered version of the input file.

Another important characteristic of the DM is thaall columns of event lists are treated “equally”:for example binning is allowed not only in spatiacoordinates but also in e.g. time, or energycoordinate, giving the ability of creatingmultidimensional images in space-energy, orspace-time, etc.


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PERTIES:

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SUMMARY OF MAIN DATA MODEL PRO

FORMAT INDEPENDENT

POWERFUL FILTERING AND BINNI

USAGE OF “VIRTUAL FILES”


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Data Manipulation Tooe four DM “core” tools are:

mlist: list contents or structure of a file

mcopy: filter and bin tables and images

mextract: make a histogram table file (e.g. PHA fiolumn. Generate count histogram on supplied regal table or image file.

mgti: create custom Good Time Intervals (GTIs)om a constraint expression

0+ “dmtools” are included in CIAO2.2


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DATA MODEL SYNTAX

ee ahelp dmsyntax)

All CIAO tools use the DM library and thereforeccept as input “virtual files” described using theM syntax.

In the DM context a “virtual file” in represented blename followed by a series of optional qualifiers in]:

lename[block][filter][columns/binning][options

here:


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c from a table tob n binning thed ge and binsize(m

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lock - is the “section” of the file to use

lter - is the filter to be applied

olumns/binning - specifies either the columns e included in an output table or the binning. Wheata to generate an n-dimensional image, the ran

in:max:bin) must be specified.

ptions - a sequence describing special options f

name - specifies a name for the new block

ote that:the order of the qualifiers generally matters, hownot all qualifiers need to be present always


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● by number:a 0][cols #1,#2,#3]

oa d_id,node_id]

a

● ecified region(ia in pi=1:1024:1]

oa 4,y=320:480:4]

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imple examples of “virtual files”:

Select the first three columns of the EVENTS blockcisf01843N001_evt2.fits[EVENTS][time=84245787:8424700

r by name:cisf01843N001_evt2.fits[EVENTS][grade=0,2,3][cols time,cc

fter filtering in time or grade

Bin an events file to create a PI spectrum for a spnput of dmextract):cisf01843N001_evt2.fits[sky=region(mysrc.reg)][EVENTS][b

r an image (input of dmcopy):cisf01843N001_evt2.fits[EVENTS][pha<100][bin x=320:480:


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the examples above:

lock: [EVENTS]

lter: [time=84245787:84247000][grade=0,2,3][sky=region(mysource.reg)][pha<1000]

olumns/binning:[cols time,ccd_id,node_id][cols #1,#2,#3][bin pi=1:1024:1][bin x=320:480:4,y=320:480:4]

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Antonella Fruscione 20 May 2002 Introduction to...

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