+ +
About
+ +ctatools +are a set of ftools-like executables needed for the scientific analysis +of Cherenkov Telescope Array data. ctatools are based on GammaLib, a +versatile toolbox for the high-level analysis of +astronomical gamma-ray data.
+ +ctatools +are implemented in C++ and are fully scriptable using the +Python scripting language.
+ +The +ctatools development is led by the Insitut de Recherche en +Astrophysique et Planétologie +(IRAP), a mixed CNRS / Université Paul Sabatier laboratory +in Toulouse, France.
+ ++ + |
+
+
Documentation
+ +... +needs still to be written :-) +
+ +Download
+ ++The latest ctatools release is ctatools-00-01-00 (February 2, 2011).
+ +ctatools +are still internal to the CTA consortium. If you are part of the +consortium, you may obtained a copy by sending an e-mail to knodlseder@cesr.fr. +
+ +ctatools
+ +ctatools +are a set of ftools-like executables needed for the scientific analysis +of Cherenkov Telescope Array data. +
+ +Installation
+ + + + + + + + + + + ++Note: These installation instructions apply to +ctatools-00-01-00. ctatools-00-01-00 +require GammaLib-00-04-05 +to be installed on your system. +
+ +ctatools
+depends on GammaLib and thus GammaLib needs to be installed on your
+system prior to installing ctatools. If you do not have GammaLib
+installed, or if you need to upgrade GammaLib, fetch the latest copy
+from https://sourceforge.net/projects/gammalib/
+and
+follow the GammaLib installation instructions on
+http://gammalib.sourceforge.net/.
+
+
+
+
+
Before +using GammaLib (and ctatools use GammaLib) you have to setup some +environment variables. +This will be done automatically by an initialisation script that will +be installed in the bin +directory. Assuming that you have installed GammaLib in the default +directory +/usr/local/gamma +you need to add the following to your .bashrc +or $HOME/.profile +script on a Linux +machine: +
+ +export GAMMALIB=/usr/local/gamma
+
+source $GAMMALIB/bin/gammalib-init.sh
+
If +you use C shell or a variant then add the following to your +.cshrc +or .tcshrc +script: +
+ +setenv GAMMALIB /usr/local/gamma
+
+source $GAMMALIB/bin/gammalib-init.csh
After +downloading the ctatools tarball, save it in an appropriate location +(for example /usr/local/gamma/src), +and type
+ ++> tar xvfz ctatools-01-00-00.tar.gz +
+ +Step +in the created directory using +
+ ++> cd ctatools-01-00-00 +
+ ++and build and install ctatools by typing
+ +
+> ./configure
+
+> make
+
+> make install
+
+at the operating system prompt. +The ./configure +command customizes the Makefiles for the particular +system, +the make +command compiles the source files and builds the executables, and +the make +install command installs the executables in the bin +directory. +Type ./configure +and not simply configure +to ensure that the +configuration +script in the current directory is run and not some other system-wide +configuration +script.
+ +By +default, the install directory is set to +/usr/local/gamma. +To change the install directory, an optional --prefix +argument should be +given, +for example: +
+ ++> ./configure --prefix=/usr/local +
+ +A +full list of configuration options can be found using
+ ++> ./configure --help +
+ +
+Solaris
+
+
+ctatools has been compiled successfully on Solaris 2.10 using the Sun
+Studio compiler. However, GammaLib symbols are
+not globally exported due to a strage behaviour of the Sun Studio
+compiler. This prevents for example GammaLib library from catching
+its own exceptions and from registering models. Consequently, many
+functionnalities will not work.
Using
+gcc (version 3.4.3), ctatools and GammaLib works correctly on Solaris
+2.10, yet loading ctatools or GammaLib as a Python module fails.
+
+
+
+
+
+Any questions, bug reports, or suggested enhancements related to +ctatools should be submitted to +knodlseder@cesr.fr. +
+ + + diff --git a/doc/html/menu.html b/doc/html/menu.html new file mode 100644 index 0000000..25849ab --- /dev/null +++ b/doc/html/menu.html @@ -0,0 +1,37 @@ + + + + + +| Home + Download + Installation + Getting Started + Documentation + About | + +
Getting started
+ +First steps with ctatools
+ ++This page gives provides a step-by-step description of the CTA data +analysis procedure implemented in ctatools. In this example we will +simulate data for the Crab nebula, observed on-axis, as a single source +in the CTA field of view.
+ +The +example consists of the following analysis steps:
+ + + + + + + + + +And +please read also: +
+ + + + + +CTA +data are simulated by the executable ctobssim. +To start the executable, type ctobssim +at the console prompt (which is denoted by >). +It will query for a number of parameters. The example shown below will +work on a system that has been installed in the default directory /usr/local/gamma. +If ctatools have been installed in another directory, please adjust the +parameter names accordingly. +
+ +
+> ctobssim
+
+Model [test/data/crab_alone.xml] /usr/local/gamma/share/models/crab.xml
+
+
+Output event data file [events.fits]
+
+Calibration database [test/irf] /usr/local/gamma/share/caldb/cta
+
+Instrument response function [kb_E_50h_v3]
+
+RA for ROI centre (degrees) (0-360) [83.63]
+
+Dec for ROI centre (degrees) (-90-90) [22.01]
+
+Radius of ROI (degrees) (0-180) [10.0]
+
+Start time (MET in s) (0) [0.0]
+
+End time (MET in s) (0) [1800.0]
+
+Lower energy limit (TeV) (0) [0.1]
+
+Upper energy limit (TeV) (0) [100.0]
+
+
Each +line represents a query for one parameter. The line starts with a short +description of the parameter, followed by the default parameter value +proposed by ctobssim +in squared brackets [ ]. +If no parameter is entered (which is the case for the majority of +parameters shown here), the default parameter will be used.
+ +The +CTA instrument properties (effective area, PSF width) are taken for the +moment from Konrad Bernlöhrs sensitivity files which are +stored in /usr/local/gamma/share/caldb/cta. +To test another CTA configuration you may adapt the instrument response +function name accordingly (see the final +remarks).
+ +Events +are simulated based on the instrument properties and based on a source +and background model. Only events that fall within the +specified region of interest (ROI), defined as a circle around a sky +position in Right Ascension and Declination (in degrees), will be +stored in the output event data file. The duration of the simulation is +taken here to 30 minutes (or 1800 seconds). Events are simulated for +energies between 0.1 and 100 TeV.
+ +The +source and background model is defined by the XML file /usr/local/gamma/share/models/crab.xml: +
+ +
+<?xml version="1.0" standalone="no"?>
+
+<source_library title="source library">
+
+ <source name="MAGIC Crab (Albert et al. 2008, ApJ,
+674, 1037)" type="PointSource">
+
+ <spectrum type="PowerLaw">
+
+
+<parameter name="Prefactor" scale="1e-16" value="5.7"
+min="1e-07" max="1000.0" free="1"/>
+
+
+<parameter name="Index"
+scale="-1" value="2.48"
+min="0.0" max="+5.0"
+free="1"/>
+
+
+<parameter name="Scale"
+scale="1e6" value="0.3"
+min="0.01" max="1000.0" free="0"/>
+
+ </spectrum>
+
+ <spatialModel
+type="SkyDirFunction">
+
+ <parameter
+name="RA" scale="1.0" value="83.6331" min="-360" max="360"
+free="0"/>
+
+ <parameter
+name="DEC" scale="1.0" value="22.0145" min="-90"
+max="90" free="0"/>
+
+ </spatialModel>
+
+ </source>
+
+ <source name="Background" type="RadialAcceptance"
+instrument="CTA">
+
+ <spectrum type="PowerLaw">
+
+
+<parameter name="Prefactor" scale="1e-6" value="61.8"
+min="0.0" max="1000.0" free="1"/>
+
+
+<parameter name="Index"
+scale="-1" value="1.85" min="0.0"
+max="+5.0" free="1"/>
+
+
+<parameter name="Scale"
+scale="1e6" value="1.0" min="0.01" max="1000.0"
+free="0"/>
+
+ </spectrum>
+
+ <radialModel
+type="Gaussian">
+
+
+<parameter name="Sigma" scale="1.0" value="3.0" min="0.01"
+max="10.0" free="1"/>
+
+ </radialModel>
+
+ </source>
+
+</source_library>
+
The +model consists of a source library that contains 2 +"sources": the Crab nebula and an instrumental background +model.
+ +The +Crab nebula is modelled by a factorized sky model that has a spectral +and a spatial component (tags <spectrum> +and <spatialModel>, +respectively). The spectrum is modelled by a power law, which is +defined by 3 parameters: the Prefactor, +the Index +and the Scale. +The spatial model has 2 parameters: Right Ascension in degrees (RA), +and Declination in degrees (DEC). +Each parameter has a value +and a scale +factor, the real value of the parameter being the product value * +scale. Typically, scale +is chosen so that value +is of the order of 1 (this is relevant for model fitting later). In +addition, value +is bound by a minimum (min) +and maximum (max) +value, and a parameter may be free (free="1") +or fixed (free="0"). +The min, +max, +and free +attributes are not relevant here for the simulations, but they will be +important for the model fitting later.
+ +The +spectral intensity I(E) +(in units of photons/cm2/s/MeV) of the power law is given by
+ +I(E) = Prefactor * (E/Scale)^Index
+ +where +the E +and Scale +are given in MeV.
+ +The +instrumental background of CTA is modelled by a factorized data model +that has a spectral and a radial component (tags <spectrum> +and <radialModel>, +respectively). The spectral component describes the on-axis background +counting rate of CTA as function of energy in units of +counts/s/sr/TeV. +The radial component describes the variation of the background rate +with offset angle squared, +(i.e. square of the offset angle with respect to the pointing +direction) which is modelled here by a Gaussian. The only parameter of +the radial component is the width of the Gaussian Sigma, +which is here set to 3 degrees squared.
+ +ctobssim +has a couple of hidden parameters, the most important one being +certainly seed. +seed +is an integer that specifies the seed value for the random number +generator, and changing this parameter will allow to generate +statistically independent Monte Carlo samples of CTA event data. To +use for example a seed value of 41 one should type: +
+ +> ctobssim seed=41
+
+
+ctobssim +will write 2 files in the working directory: events.fits +and ctobssim.log. +The first file contains the simulated events in FITS format and can be +inspected using fv +or ds9. +The FITS file will contain 3 extensions: an empty primary image, a +binary table named EVENTS +that holds the events (one row per event), and a binary table named GTI +holding the Good Time Interval (for the moment a single row with 2 +columns providing the start and the stop time of the simulated time +interval).
+ +The +second file produced by ctobssim +is a human readable log file that contains information about +the job execution. As example, the last lines from this file are shown +here:
+ +2011-01-31T23:50:39: +==================+
+
+2011-01-31T23:50:39: | Simulate photons |
+
+2011-01-31T23:50:39: +==================+
+
+2011-01-31T23:50:39: Simulated photons .........: 33943
+
+2011-01-31T23:50:39: Simulation area ...........: 3.2e+10 cm2
+
+2011-01-31T23:50:39: Simulation cone ...........: RA=83.63
+deg, Dec=22.01deg, r=10 deg
+
+2011-01-31T23:50:39: Time interval .............: 0 s - 1800 s
+
+2011-01-31T23:50:39: Energy range ..............: 100 GeV -
+100 TeV
+
+2011-01-31T23:50:39: Random number seed ........: 1
+
+2011-01-31T23:50:39:
+
+2011-01-31T23:50:39: +=================+
+
+2011-01-31T23:50:39: | Simulate events |
+
+2011-01-31T23:50:39: +=================+
+
+2011-01-31T23:50:39: MC source events ..........: 649
+
+2011-01-31T23:50:39: MC background events ......: 3407
+
+2011-01-31T23:50:39:
+
+2011-01-31T23:50:39: +==========================+
+
+2011-01-31T23:50:39: | Save events in FITS file |
+
+2011-01-31T23:50:39: +==========================+
+
+2011-01-31T23:50:39:
+
+2011-01-31T23:50:39: Application "ctobssim" terminated after consuming
+14 seconds of CPU time.
+
+
+
+
Each +line starts with the UTC time at which the line has been written. In +this +run, 33943 Crab photons have been thrown over an area of 3.2 square +kilometres during a time interval of 1800 seconds. 649 of these photons +have been registered by CTA as events. In the same time +interval, 3407 background events have been registred by CTA.
+ ++As next analysis step the data are binned in a counts map using the +executable ctbin. +A counts map is a 3 dimensional data cube, spanned by Right Ascension +(or Galactic longitude), Declination (or Galactic latitude), and the +logarithm (base 10) of energy.
+ +ctbin +is executed by typing:
+ +
+> ctbin
+
+Event data file name [test/data/crab_events.fits.gz] events.fits
+
+Output file name [cntmap.fits]
+
+Start value for first energy bin in TeV [0.1]
+
+Stop value for last energy bin in TeV [100.0]
+
+Number of energy bins [20]
+
+Projection method e.g. AIT|ARC|CAR|GLS|MER|NCP|SIN|STG|TAN [CAR]
+
+Coordinate system (CEL - celestial, GAL - galactic) (CEL|GAL) [CEL]
+
+First coordinate of image center in degrees (RA or galactic l) [83.63]
+
+Second coordinate of image center in degrees (DEC or galactic b)
+[22.01]
+
+Image scale (in degrees/pixel) [0.02]
+
+Size of the X axis in pixels [200]
+
+Size of the Y axis in pixels [200]
+In this example we adjust the event data file name and accept all the +remaining parameter defaults as they perfectly +satisfy our needs. The counts map will be centred on the location of +the Crab (Right Ascension 83.63 degrees, Declination 22.01 degrees) and +will be aligned in celestial coordinates. A cartesian projection has +been selected (note that +the cartesian projection is the only valid project available for the +moment). The counts map has 200 x 200 +spatial pixels of 0.02 x 0.02 degrees in size, hence it covers a total +area of 4 x 4 degrees.
+ +A +set of 20 counts maps will be created, which are logarithmically spaced +in energy, and which cover the energy range from 0.1 TeV to 100 TeV. In +this example, the counts map will be saved as cntmap.fits +in the +working directory. +In addition to the counts map, that is stored as the primary image extension, the FITS +file also contains an extension named EBOUNDS +that defines the energy boundaries that were used, and an extension GTI +that defines the Good Time Intervals that have been used. The following +image shows the resulting FITS file. The EBOUNDS table has 20 rows, one for each energy bin, while the GTI table has jusr a single row, indicating the start and stop time of the simulated data.
+
An +image +of the first bin, covering the energy range 100 - 141 GeV, is +shown below: +
+ +
For +illustrating, the last few lines of the log file ctbin.log +are shown below: +
+ +2011-02-01T09:28:05: +=========+
+
+2011-02-01T09:28:05: | Binning |
+
+2011-02-01T09:28:05: +=========+
+
+2011-02-01T09:28:05: Events in list ............: 4056
+
+2011-02-01T09:28:05: Events in map .............: 3683
+
+2011-02-01T09:28:05: Events outside map area ...: 373
+
+2011-02-01T09:28:05: Events outside energy bins : 0
+
+2011-02-01T09:28:05:
+
+2011-02-01T09:28:05: +============+
+
+2011-02-01T09:28:05: | Counts map |
+
+2011-02-01T09:28:05: +============+
+
+2011-02-01T09:28:05: === GSkymap ===
+
+2011-02-01T09:28:05: Number of pixels ..........: 40000
+
+2011-02-01T09:28:05: Number of maps ............: 20
+
+2011-02-01T09:28:05: X axis dimension ..........: 200
+
+2011-02-01T09:28:05: Y axis dimension ..........: 200
+
+2011-02-01T09:28:05: === GWcsCAR ===
+
+2011-02-01T09:28:05: Coordinate system .........: EQU
+
+2011-02-01T09:28:05: Reference coordinate ......: (83.63,
+22.01) deg
+
+2011-02-01T09:28:05: Reference pixel ...........: (100.5,
+100.5)
+
+2011-02-01T09:28:05: Increment at reference ....: (0.02,
+0.02) deg
+
+2011-02-01T09:28:05: Coordinate of North Pole ..: (180, 0) deg
+
+2011-02-01T09:28:05: CD matrix .................: [0.02 0][0
+0.02]
+
+2011-02-01T09:28:05: Inverse CD matrix .........: [50 -0][-0
+50]
+
+2011-02-01T09:28:05: Coordinate of native pole .: (83.63,
+112.01)
+
+2011-02-01T09:28:05:
+
+2011-02-01T09:28:05: Application "ctbin" terminated after consuming 10
+seconds of CPU time.
+
From +the 4056 events that have been simulated and stored in the events.fits +file, 3683 lie within the map boundaries and are thus put into the +resulting counts map. The counts map is stored in a cartesian +projection in a World Coordinate System (WCS) +compliant format. +
+ ++Now we are ready to fit the simulated data with a model. For simplicity +we use in this example the same model that we used to simulate the data +with ctobssim. +Model fitting is done using the executable ctlike, +and we do the fit by typing: +
+ +
+> ctlike
+
+Maximum likelihood method [BINNED]
+
+Calibration database [test/irf] /usr/local/gamma/share/caldb/cta
+
+Instrument response function [kb_E_50h_v3]
+
+Source model [test/data/crab.xml] /usr/local/gamma/share/models/crab.xml
+
+Source model output file [crab_results.xml]
+
+Counts map [test/data/crab_cntmap.fits.gz] cntmap.fits
+
Fitting +of the data is done in BINNED +mode, which means that the events have been binned into a counts map +and the fit computes the log-likelihood function by summing over all +200 x 200 x 20 bins of the counts map. There is an alternative method, +the so called UNBINNED +mode, where the events are not binned into a counts map and the +log-likelihood is computed directly by summing over all events. We will +explore +the UNBINNED +mode later.
+ ++One of the parameters given to ctlike +is a source model output file (we specified crab_results.xml +in the example), and this file will be a copy of the model XML file +where the parameter values have been replaced by the fit results. In +addition, the statistical uncertainties are added for each fitted +parameter using the attribute error. +Below we show the XML result file that has been produced by the run: +
+ +<?xml version="1.0"
+encoding="UTF-8" standalone="no"?>
+
+<source_library title="source library">
+
+ <source name="MAGIC Crab (Albert et al. 2008, ApJ,
+674, 1037)" type="DiffuseSource">
+
+ <spectrum type="PowerLaw">
+
+ <parameter
+name="Prefactor" value="5.7765" error="0.243328" scale="1e-16"
+min="1e-07" max="1000" free="1" />
+
+ <parameter
+name="Index" value="2.49937" error="0.0330191" scale="-1" min="0"
+max="5" free="1" />
+
+ <parameter
+name="Scale" value="0.3" scale="1e+06" min="0.01" max="1000" free="0"
+/>
+
+ </spectrum>
+
+ <spatialModel
+type="SkyDirFunction">
+
+ <parameter
+name="RA" value="83.6331" scale="1" min="-360" max="360" free="0"
+/>
+
+ <parameter
+name="DEC" value="22.0145" scale="1" min="-90" max="90" free="0"
+/>
+
+ </spatialModel>
+
+ </source>
+
+ <source name="Background" type="RadialAcceptance"
+instrument="CTA">
+
+ <spectrum type="PowerLaw">
+
+ <parameter
+name="Prefactor" value="61.7696" error="1.89829" scale="1e-06" min="0"
+max="1000" free="1" />
+
+ <parameter
+name="Index" value="1.87195" error="0.0166039" scale="-1" min="0"
+max="5" free="1" />
+
+ <parameter
+name="Scale" value="1" scale="1e+06" min="0.01" max="1000" free="0"
+/>
+
+ </spectrum>
+
+ <radialModel
+type="Gaussian">
+
+ <parameter
+name="Sigma" value="3.00467" error="0.071261" scale="1" min="0.01"
+max="10" free="1" />
+
+ </radialModel>
+
+ </source>
+
+</source_library>
+
+In this example, the Prefactor +and Index +of the spectral model for the Crab as well as the Prefactor, +Index +and Sigma +parameter of the radial acceptance model have been fitted (all +parameters having the attribute free="1" +are fitted). One could +be tempted to try fitting also the location of the Crab point source, +yet this feature is not yet implemented. +
+ +To +get more details about the model fitting one can inspect the log file. +Below +we show the last lines of the ctlike.log +log file that has been produced by this run: +
+ +2011-02-01T09:53:17:
++=================================+
+
+2011-02-01T09:53:17: | Maximum likelihood optimisation |
+
+2011-02-01T09:53:17: +=================================+
+
+2011-02-01T09:53:20: Initial iteration: func=18092.1,
+Lambda=0.001
+
+2011-02-01T09:53:24: Iteration 1: func=18090, Lambda=0.0001,
+delta=2.08792
+
+2011-02-01T09:53:27: Iteration 2: func=18090, Lambda=1e-05,
+delta=0.0021398
+
+2011-02-01T09:53:30: Iteration 3: func=18090, Lambda=1e-06,
+delta=4.80215e-06
+
+2011-02-01T09:53:34: Iteration 4: func=18090, Lambda=1e-07,
+delta=1.7495e-08
+
+2011-02-01T09:53:37:
+
+2011-02-01T09:53:37: +=========================================+
+
+2011-02-01T09:53:37: | Maximum likelihood optimisation results |
+
+2011-02-01T09:53:37: +=========================================+
+
+2011-02-01T09:53:37: === GOptimizerLM ===
+
+2011-02-01T09:53:37: Optimized function value ..: 18090
+
+2011-02-01T09:53:37: Absolute precision ........: 1e-06
+
+2011-02-01T09:53:37: Optimization status .......: converged
+
+2011-02-01T09:53:37: Number of parameters ......: 11
+
+2011-02-01T09:53:37: Number of free parameters .: 5
+
+2011-02-01T09:53:37: Number of iterations ......: 4
+
+2011-02-01T09:53:37: Lambda ....................: 1e-07
+
+2011-02-01T09:53:37: Maximum log likelihood ....: -18090
+
+2011-02-01T09:53:37: Npred .....................: 3683
+
+2011-02-01T09:53:37: === GModels ===
+
+2011-02-01T09:53:37: Number of models ..........: 2
+
+2011-02-01T09:53:37: Number of parameters ......: 11
+
+2011-02-01T09:53:37: === GModelPointSource ===
+
+2011-02-01T09:53:37: Name ......................: MAGIC Crab
+(Albert et al. 2008, ApJ, 674, 1037)
+
+2011-02-01T09:53:37: Instruments ...............: all
+
+2011-02-01T09:53:37: Number of parameters ......: 6
+
+2011-02-01T09:53:37: Number of spatial par's ...: 2
+
+2011-02-01T09:53:37: RA .......................:
+83.6331 [-360,360] deg (fixed,scale=1)
+
+2011-02-01T09:53:37: DEC ......................:
+22.0145 [-90,90] deg (fixed,scale=1)
+
+2011-02-01T09:53:37: Number of spectral par's ..: 3
+
+2011-02-01T09:53:37: Prefactor ................:
+5.7765e-16 +/- 2.43328e-17 [1e-23,1e-13] ph/cm2/s/MeV (free,scale=1e-16)
+
+2011-02-01T09:53:37: Index ....................:
+-2.49937 +/- 0.0330191 [-0,-5] (free,scale=-1)
+
+2011-02-01T09:53:37: PivotEnergy ..............:
+300000 [10000,1e+09] MeV (fixed,scale=1e+06)
+
+2011-02-01T09:53:37: Number of temporal par's ..: 1
+
+2011-02-01T09:53:37: Constant .................: 1
+(relative value) (fixed,scale=1)
+
+2011-02-01T09:53:37: === GCTAModelRadialAcceptance ===
+
+2011-02-01T09:53:37: Name ......................: Background
+
+2011-02-01T09:53:37: Instruments ...............: CTA
+
+2011-02-01T09:53:37: Model type ................: "Gaussian"
+* "PowerLaw" * "Constant"
+
+2011-02-01T09:53:37: Number of parameters ......: 5
+
+2011-02-01T09:53:37: Number of radial par's ....: 1
+
+2011-02-01T09:53:37: Sigma ....................:
+3.00467 +/- 0.071261 [0.01,10] deg2 (free,scale=1)
+
+2011-02-01T09:53:37: Number of spectral par's ..: 3
+
+2011-02-01T09:53:37: Prefactor ................:
+6.17696e-05 +/- 1.89829e-06 [0,0.001] ph/cm2/s/MeV (free,scale=1e-06)
+
+2011-02-01T09:53:37: Index ....................:
+-1.87195 +/- 0.0166039 [-0,-5] (free,scale=-1)
+
+2011-02-01T09:53:37: PivotEnergy ..............:
+1e+06 [10000,1e+09] MeV (fixed,scale=1e+06)
+
+2011-02-01T09:53:37: Number of temporal par's ..: 1
+
+2011-02-01T09:53:37: Constant .................: 1
+(relative value) (fixed,scale=1)
+
+2011-02-01T09:53:37:
+
+2011-02-01T09:53:37: Application "ctlike" terminated after consuming 41
+seconds of CPU time.
+
The +maximum likelihood optimizer required 4 iterations to converge. This is +pretty fast, but recall that we used the same model file for the +simulation and for fitting, hence the initial parameter values are +already very close to the best fitting values. To see the impact of the +initial parameters on the fit result, you may re-run ctlike +using another copy of the model XML file where the value +attributes of the parameters that should be fitted are changed. You +will see that the optimizer requires a couple of more iterations, but +it should converge to the same solution (provided that the initial +values are not too far of the best fitting values). +
+ +As +gamma-ray events are rare, the counts maps generated by ctbin +will in general be sparse, having many empty pixels, in +particular at high energies. An alternative analysis technique consists +of working directly on the event list without binning the events in a +counts map. We +will see the benefit of such an analysis later once we re-run ctlike +in unbinned mode.
+ +For +unbinned analysis we have first to define the data +space region over which the analysis is done. This is similiar to the ctbin +step in binned analysis where we define the size of the counts map, the +energy range, and the time interval. For unbinned analysis we have no +such thing as a counts map, but we have to define over which region of +the data space the selected events are spread (because we have to +integrate +over this region to compute the total number of predicted events in the +data space that we analyse). Furthermore, we have to define what energy +range is covered, and what time interval is spanned by the data. All +this is done by the executable ctselect, +which replaces the ctbin +step in an unbinned analysis.
+ +ctselect +performs an event selection by choosing only events within a +given +region-of-interest (ROI), within a given energy band, and within a +given time interval from the input event list. The ROI is a circular +region on the sky, for which we define the centre (in celestial +coordinates) and the radius. Such a circular ROI is sometimes also +called an acceptance cone. +The following example shows how ctselect +is invoked on the simulated +test data:
+ +
+> ctselect
+
+Input event data file [test/data/crab_events.fits.gz]
+events.fits
+
+Output event data file [selected_events.fits]
+
+RA for ROI centre (degrees) (0-360) [83.63]
+
+Dec for ROI centre (degrees) (-90-90) [22.01]
+
+Radius of ROI (degrees) (0-180) [3.0]
+
+Start time (MET in s) (0) [0.0]
+
+End time (MET in s) (0) [1800.0]
+
+Lower energy limit (TeV) (0) [0.1]
+
+Upper energy limit (TeV) (0) [100.0]
+
+
ctselect +takes the input event list events.fits, +performs an event selection, and writes the selected event into the +file selected_events.fits. +The parameters it will query for are the centre of the ROI, the +radius of the ROI, the start and stop time (in seconds), and the energy +lower and upper limits (in TeV). The event selection information is +also written as a set of data +selection keywords to the output events file selected_events.fits, +by respecting the same syntax that has been implemented for Fermi-LAT. +The following image is a screen dump of the data +selection keywords that have been written to the EVENTS +header in the file selected_events.fits:
+ + 
+
It +is important for unbinned analysis that these data selection keywords +exist. If they don't exist, ctlike +will not execute in unbinned mode.
+ +Below +we show also for completeness the last few lines of the ctselect.log +file. It gives information about the specific data selection that has +been performed. +
+ +
+2011-02-01T19:58:34: +=================+
+
+2011-02-01T19:58:34: | Event selection |
+
+2011-02-01T19:58:34: +=================+
+
+2011-02-01T19:58:34: Time range ................: 0-1800
+
+2011-02-01T19:58:34: Energy range ..............: 0.1-100 TeV
+
+2011-02-01T19:58:34: Acceptance cone centre ....: RA=83.63,
+DEC=22.01 deg
+
+2011-02-01T19:58:34: Acceptance cone radius ....: 3 deg
+
+2011-02-01T19:58:34: cfitsio selection .........: TIME
+>= 0 && TIME <= 1800 &&
+ENERGY >= 0.1 && ENERGY <= 100
+&& ANGSEP(83.63,
+
+22.01,RA,DEC) <= 3
+
+2011-02-01T19:58:34: FITS filename .............:
+events.fits[EVENTS][TIME >= 0 && TIME <=
+1800 && ENERGY >= 0.1 && ENERGY
+<=
+
+100 && ANGSEP(83.63,22.01,RA,DEC) <= 3]
+
+2011-02-01T19:58:34:
+
+2011-02-01T19:58:34: Application "ctselect" terminated after consuming
+10 seconds of CPU time.
+
+
+
+
Now +that the event selection has been performed, ctlike +can be run in unbinned mode. To do this, you have to type UNBINNED +when the maximum likelihood method is queried. The remaining parameters +are similar to binned mode, except for the last one that asks now for +an event data file instead of a counts map. Specify here the selected +event list selected_events.fits +that has been produced by ctselect. +To run ctlike +in unbinned mode, type the following: +
+ +
+> ctlike
+
+Maximum likelihood method [BINNED] UNBINNED
+
+Calibration database [test/irf] /usr/local/gamma/share/caldb/cta
+
+Instrument response function [kb_E_50h_v3]
+
+Source model [test/data/crab.xml] /usr/local/gamma/share/models/crab.xml
+
+Source model output file [crab_results.xml]
+
+Event data file name [test/data/crab_events.fits.gz]
+selected_events.fits
+
You +will recognise that ctlike +runs much faster in unbinned mode compared to binned mode. This is +understandable as the selected event list contains only 4048 events, +while the binned counts map we used before had 200 x 200 x 20 = 800000 +pixels. As unbinned maximum likelihood fitting loops over the events +(while binned maximum likelihood loops over the pixels), there are much +less operations to perform in unbinned than in binned mode (there is +some additional overhead in unbinned mode that comes from integrating +the models over the region of interest, yet this is negligible compared +to the operations needed when looping over the pixels). So as long as +you work with +short event lists, unbinned mode is faster. Unbinned ctlike +should also be more +precise as no binning is performed, hence there is no loss of +information due to histogramming.
+ +Below +you see the corresponding output from the ctlike.log +file. The fitted parameters are essentially identical to the ones found +in binned mode. The slight +difference with respect to the binned analysis may be explained by the +different event sample that has been used for the analysis: while +binned likelihood works on rectangular counts maps, unbinned likelihood +works on circular event selection regions. It is thus not possible to +select exactly the same events for both analyses!
+ +
+2011-02-02T14:32:54: +=================================+
+
+2011-02-02T14:32:54: | Maximum likelihood optimisation |
+
+2011-02-02T14:32:54: +=================================+
+
+2011-02-02T14:32:54: Initial iteration: func=33730.9,
+Lambda=0.001
+
+2011-02-02T14:32:54: Iteration 1: func=33728.3,
+Lambda=0.0001, delta=2.56377
+
+2011-02-02T14:32:54: Iteration 2: func=33728.3, Lambda=1e-05,
+delta=0.00443209
+
+2011-02-02T14:32:54: Iteration 3: func=33728.3, Lambda=1e-06,
+delta=5.81336e-06
+
+2011-02-02T14:32:54: Iteration 4: func=33728.3, Lambda=1e-07,
+delta=1.31549e-08
+
+2011-02-02T14:32:54:
+
+2011-02-02T14:32:54: +=========================================+
+
+2011-02-02T14:32:54: | Maximum likelihood optimisation results |
+
+2011-02-02T14:32:54: +=========================================+
+
+2011-02-02T14:32:54: === GOptimizerLM ===
+
+2011-02-02T14:32:54: Optimized function value ..: 33728.3
+
+2011-02-02T14:32:54: Absolute precision ........: 1e-06
+
+2011-02-02T14:32:54: Optimization status .......: converged
+
+2011-02-02T14:32:54: Number of parameters ......: 11
+
+2011-02-02T14:32:54: Number of free parameters .: 5
+
+2011-02-02T14:32:54: Number of iterations ......: 4
+
+2011-02-02T14:32:54: Lambda ....................: 1e-07
+
+2011-02-02T14:32:54: Maximum log likelihood ....: -33728.3
+
+2011-02-02T14:32:54: Npred .....................: 4048
+
+2011-02-02T14:32:54: === GModels ===
+
+2011-02-02T14:32:54: Number of models ..........: 2
+
+2011-02-02T14:32:54: Number of parameters ......: 11
+
+2011-02-02T14:32:54: === GModelPointSource ===
+
+2011-02-02T14:32:54: Name ......................: MAGIC Crab
+(Albert et al. 2008, ApJ, 674, 1037)
+
+2011-02-02T14:32:54: Instruments ...............: all
+
+2011-02-02T14:32:54: Number of parameters ......: 6
+
+2011-02-02T14:32:54: Number of spatial par's ...: 2
+
+2011-02-02T14:32:54: RA .......................:
+83.6331 [-360,360] deg (fixed,scale=1)
+
+2011-02-02T14:32:54: DEC ......................:
+22.0145 [-90,90] deg (fixed,scale=1)
+
+2011-02-02T14:32:54: Number of spectral par's ..: 3
+
+2011-02-02T14:32:54: Prefactor ................:
+5.83432e-16 +/- 2.44527e-17 [1e-23,1e-13] ph/cm2/s/MeV
+(free,scale=1e-16)
+
+2011-02-02T14:32:54: Index ....................:
+-2.50725 +/- 0.0328297 [-0,-5] (free,scale=-1)
+
+2011-02-02T14:32:54: PivotEnergy ..............:
+300000 [10000,1e+09] MeV (fixed,scale=1e+06)
+
+2011-02-02T14:32:54: Number of temporal par's ..: 1
+
+2011-02-02T14:32:54: Constant .................: 1
+(relative value) (fixed,scale=1)
+
+2011-02-02T14:32:54: === GCTAModelRadialAcceptance ===
+
+2011-02-02T14:32:54: Name ......................: Background
+
+2011-02-02T14:32:54: Instruments ...............: CTA
+
+2011-02-02T14:32:54: Model type ................: "Gaussian"
+* "PowerLaw" * "Constant"
+
+2011-02-02T14:32:54: Number of parameters ......: 5
+
+2011-02-02T14:32:54: Number of radial par's ....: 1
+
+2011-02-02T14:32:54: Sigma ....................:
+3.03472 +/- 0.0398509 [0.01,10] deg2 (free,scale=1)
+
+2011-02-02T14:32:54: Number of spectral par's ..: 3
+
+2011-02-02T14:32:54: Prefactor ................:
+6.18897e-05 +/- 1.74306e-06 [0,0.001] ph/cm2/s/MeV (free,scale=1e-06)
+
+2011-02-02T14:32:54: Index ....................:
+-1.86369 +/- 0.0156024 [-0,-5] (free,scale=-1)
+
+2011-02-02T14:32:54: PivotEnergy ..............:
+1e+06 [10000,1e+09] MeV (fixed,scale=1e+06)
+
+2011-02-02T14:32:54: Number of temporal par's ..: 1
+
+2011-02-02T14:32:54: Constant .................: 1
+(relative value) (fixed,scale=1)
+
+2011-02-02T14:32:54:
+
+2011-02-02T14:32:54: Application "ctlike" terminated after consuming 2
+seconds of CPU time.
+
+
First +you should notice that ctatools +are in the prototyping phase. If GammaLib and ctatools are +installed on your system you should be able to run the above example +without any problems, and you can do even much more.
+ +You +may specify longer integration times for the simulation and for the +analysis, you can have several point sources in the +XML file, and you may try to fit all sources simultaneously using ctlike. +Yet, for the moment, +you are limited to point sources (type="PointSource") +and their spectra should be power laws (type="PowerLaw"). +Although there are already a number of other spectral types available +in GammaLib, I have not yet had the time to implement their Monte Carlo +generator, hence you cannot simulate events for spectral laws different +from power laws for the moment. You may try, however, fitting the +sources with other spectral laws, yet I have not tried this, and I +cannot guarantee that it works.
+ +There +is also only one radial acceptance model defined so far, and you should +use the model definition that is given in the example.
+ +Also, +don't fiddle around with +other projections and coordinate systems in +ctbin. +The cartesian projection is the only one that so far is +implemented, and galactic coordinates have not been tested so far.
+ +The +instrument response function that has been implemented so far in +GammaLib (yes, it is in GammaLib, not in ctatools) is very simple. It +just reads Konrad's effective area files to get an effective area that is so far +independent of offset angle. ctobssim +and ctlike +query for the name of the instrument response function file, and you +may specify different +response files if you like. To see what is available, type (adjust the +path corresponding to your installation directory): +
+ +> ls
+/usr/local/gamma/share/caldb/cta
+
+kb_A_50h_v3.dat
+kb_D_50h_v3.dat
+kb_G_50h_v3.dat
+kb_J_50h_v3.dat
+kb_NB_50h_v3.dat
+
+kb_B_50h_v3.dat
+kb_E_50h_v3.dat
+kb_H_50h_v3.dat
+kb_K_50h_v3.dat
+
+kb_C_50h_v3.dat
+kb_F_50h_v3.dat
+kb_I_50h_v3.dat
+kb_NA_50h_v3.dat
+
+
The +point spread function (PSF) definition is also read from these files. +So far, the PSF is a +simple Gaussian. The energy dependent Gaussian +width is defined by +the r68 parameter in Konrad's response files.
+ +Lifetime +is assumed to be 100%. I'm not sure whether lifetime is +folded in the +effective areas of Konrad's response files, if not, a corresponding +correction should be applied to all source fluxes obtained with the +ctatools. +
+ +Finally, +if +you want to have the log file also dumped to the screen as the +executable runs, add debug=yes +on the command line, e.g. +
+ +> ctlike debug=yes +
+ ++And now: enjoy playing +with ctatools. +
+ ++Any questions, bug reports, or suggested enhancements related to +ctatools and GammaLib should be submitted +to knodlseder@cesr.fr +. +
+ + +