Fabio Iocco / ctools

Commit 14f9d87c77c882bb27b52d9dc3e85fc929ea25c3

Authored by Jürgen Knödlseder
2 parents 61ca854e a37d1cc3

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.gitignore
  View file @14f9d87
... ... @@ -46,8 +46,10 @@ doc/man
46 46 src/ctools-setup
47 47 pyext/build/
48 48 pyext/setup.py
  49 +pyext/ctools/__init__.py
49 50 pyext/ctools/tools.py
50 51 pyext/ctools/tools_wrap.cpp
  52 +cscripts/__init__.py
51 53 src/ctbin/ctbin
52 54 src/ctlike/ctlike
53 55 src/cttsmap/cttsmap
... ... @@ -63,6 +65,7 @@ src/ctbutterfly/ctbutterfly
63 65 src/ctulimit/ctulimit
64 66 src/cterror/cterror
65 67 test/pfiles/
  68 +test/caldb/
66 69 test/*.fits
67 70 test/*.dat
68 71 test/*.xml
... ... @@ -70,6 +73,8 @@ test/*.trs
70 73 test/test_cscripts.sh
71 74 test/reports/*.xml
72 75 test/butterfly.txt
  76 +test/model.reg
  77 +test/obs.reg
73 78 examples/*.fits
74 79 examples/*.xml
75 80 examples/*.dat
... ...
... ... @@ -6,4 +6,3 @@ Florent Forest (florent.forest@isae.fr)
6 6 Juergen Knoedlseder (jurgen.knodlseder@irap.omp.eu)
7 7 Chia-Chun Lu (Chia-Chun.Lu@mpi-hd.mpg.de)
8 8 Michael Mayer (michael.mayer@physik.hu-berlin.de)
9   -
... ...
ChangeLog
  View file @14f9d87
  1 +2015-12-18 Juergen Knoedlseder <jurgen.knodlseder@irap.omp.eu>
  2 +
  3 + * Version 1.0.0 released
  4 + ========================
  5 +
  6 + Update end-user documentation
  7 + Rename cshessobs to csiactobs and add csiactdata (#1608)
  8 + Ignore errors in El Capitan post processing (#1605)
  9 + Change GException to RuntimeError in cscripts (#1604)
  10 + Adapt to GammaLib interface changs (#1603)
  11 + Add csobs2caldb script (#1579)
  12 + Add csobsinfo, csmodelinfo, csmodelmerge, cstsmapmerge (#1578)
  13 + Implement handling of stacked data in csspec (#1566)
  14 + Resolve Python test problem on El Capitan (#1563)
  15 +
  16 +
1 17 2015-10-31 Juergen Knoedlseder <jurgen.knodlseder@irap.omp.eu>
2 18  
3 19 * Version 0.10.0 released
... ...
1   -New Features and Important Changes in ctools 0.10.0
  1 +New Features and Important Changes in ctools 1.0.0
2 2  
3 3 Author(s) : Juergen Knoedlseder
4 4  
5   -31 October 2015
  5 +18 December 2015
6 6  
7 7  
8 8 1. Introduction
9 9 ---------------
10 10 This document briefly summarizes executable by executable the most important
11   -changes made since the last release of ctools. The code complies to GammaLib
12   -version 0.11.0 or above.
  11 +changes made since the last release of ctools. The code complies to ctools
  12 +version 1.0.0 or above.
13 13  
14 14  
15 15 2. Configuration
16 16 -----------------
17   -None
  17 +A special post processing of the Python module libraries has been added for
  18 +Mac OS X 10.11 and higher (El Capitan). This post processing is a replacement for
  19 +setting DYLD_LIBRARY_PATH during unit testing since the environment variable is
  20 +ignored in certain circumstances by El Capitan. Any errors that occur in the
  21 +post-processing will be ignored.
18 22  
19 23  
20 24 3. Python interface
21 25 -------------------
22   -A specific cscripts Python module has been created for cscripts. This module
23   -can be imported using
24   -
25   - >>> import cscripts
26   -
27   -The obsutils utility functions have also been moved into the scripts folder.
28   -
29   -The obsutils.spectrum() function has been removed as it is now replaced by the
30   -csspec script.
31   -
32   -Some tests for the installed ctools package have been added. They can be
33   -executed by typing the following under Python:
34   -
35   - >>> cscripts.test()
  26 +None
36 27  
37 28  
38 29 4. Support model
39 30 ----------------
40   -The ctool base class now handles the specification of the --help option on
41   -the command line. For each tools or script, a help text that is generated from
42   -the .rst documentation files is displayed on the console when --help is given.
  31 +Adapt the ctool::create_ebounds() method to the change in the GEbounds
  32 +interface (the extname argument has been removed from the GEbounds::load()
  33 +method and replaced by using the GFilename class to handle extension names
  34 +as part of the file name).
43 35  
44 36  
45 37 5. ctobssim - CTA observation simulation
... ... @@ -54,14 +46,12 @@ None
54 46  
55 47 7. ctbin - CTA event binning
56 48 ----------------------------
57   -ctbin now verifies if an ROI has been set properly, and throws an exception in
58   -case that no ROI information could be found.
  49 +None
59 50  
60 51  
61 52 8. ctlike - Maximum likelihood fitting
62 53 --------------------------------------
63   -The optimizer is now allocated upon construction so that ctlike always returns a
64   -meaningful object using the opt() method.
  54 +None
65 55  
66 56  
67 57 9. cttsmap - Generation of Test Statistics map
... ... @@ -91,8 +81,7 @@ None
91 81  
92 82 14. ctbkgcube - CTA background cube generation
93 83 ----------------------------------------------
94   -Limit the power law prefactor to a range of [0.01,100] and the index to [-5,5]. This
95   -solves some stability problems in csspec (#1547).
  84 +None
96 85  
97 86  
98 87 15. ctcubemask - CTA cube filtering
... ... @@ -112,24 +101,28 @@ None
112 101  
113 102 18. cterror - Likelihood profile error computation
114 103 --------------------------------------------------
115   -Added initial version of the likelihood profile error computation tool. This
116   -tool will scan the likelihood function to find the confidence interval for
117   -all source parameters.
  104 +None
118 105  
119 106  
120   -19. Examples
  107 +19. cscripts
121 108 ------------
122   -None
  109 +The following scripts have been added:
  110 +- csobsinfo: dump information in observation container
  111 +- csmodelinfo: dump information in model container
  112 +- csmodelmerge: merge model containers into single container
  113 +- cstsmapmerge: merge sliced TS map into single map
  114 +- csobs2caldb: creates calibration database from observation
  115 +- csiactdata: inspects IACT data
123 116  
  117 +The cshessobs script has been renamed to csiactobs.
124 118  
125   -20. Scripts
126   ------------
127   -Added csinfo script to provide some information about the GammaLib and ctools
128   -installation. To be run in case of problems to help diagnostics.
  119 +All GExceptions are replaced by Python RuntimeErrors as the GException
  120 +classes are not exposed to Python.
129 121  
130   -The cspull script was extended to now also handle stacked analysis in case
131   -that an observation definition XML file is specified with multiple observations
132   -by the inobs parameter.
  122 +
  123 +20. Examples
  124 +------------
  125 +None
133 126  
134 127  
135 128 21. caldb
... ...
1 1 ctools information
2 2 ==================
3   -Version: 0.10.0 (31 October 2015)
  3 +Version: 1.0.0 (18 December 2015)
4 4 Author: Juergen Knodlseder (jurgen.knodlseder@irap.omp.eu)
5   -GammaLib dependency: 0.11.0
  5 +GammaLib dependency: 1.0.0
6 6  
7 7  
8 8 License information
... ... @@ -38,6 +38,7 @@ The following tools are available:
38 38 ctbkgcube - generate a background cube
39 39 ctbutterfly - create a butterfly
40 40 ctcubemask - mask bins in binned analysis
  41 + cterror - likelihood profile error estimation
41 42 ctexpcube - generate an exposure cube
42 43 ctlike - maximum likelihood model fitting
43 44 ctmodel - generation of model counts map
... ... @@ -51,10 +52,8 @@ The following tools are available:
51 52  
52 53 Web sites
53 54 =========
54   -http://cta.irap.omp.eu/ctools - ctools documentation
  55 +http://cta.irap.omp.eu/ctools - for ctools users
55 56 https://cta-redmine.irap.omp.eu/projects/ctools - for ctools development
56   -https://cta-redmine.irap.omp.eu/projects/gammalib - for GammaLib documentation
57   -https://sourceforge.net/projects/gammalib/ - for GammaLib downloads
58 57  
59 58  
60 59 Prerequisites
... ...
configure.ac
  View file @14f9d87
... ... @@ -29,7 +29,7 @@
29 29 #############################################################################
30 30 # Initialisation #
31 31 #############################################################################
32   -AC_INIT([ctools], [0.10.0], [jurgen.knodlseder@irap.omp.eu], [ctools])
  32 +AC_INIT([ctools], [1.0.0], [jurgen.knodlseder@irap.omp.eu], [ctools])
33 33 AC_CONFIG_SRCDIR([src/ctselect/ctselect.cpp])
34 34 AC_CONFIG_MACRO_DIR([m4])
35 35 #AM_INIT_AUTOMAKE([gnu no-dependencies])
... ... @@ -39,6 +39,27 @@ AC_CONFIG_HEADER([config.h])
39 39  
40 40  
41 41 #############################################################################
  42 +# Library versioning (current:revision:age) #
  43 +# ------------------------------------------------------------------------- #
  44 +# Here are a set of rules to update your library version information: #
  45 +# 1. Update the version information only immediately before a public #
  46 +# release of your software. More frequent updates are unnecessary, #
  47 +# and only guarantee that the current interface number gets larger #
  48 +# faster. #
  49 +# 2. If the library source code has changed at all since the last update, #
  50 +# then increment revision. #
  51 +# 3. If any interfaces have been added, removed, or changed since the last #
  52 +# update, increment current, and set revision to 0. #
  53 +# 4. If any interfaces have been added since the last public release, then #
  54 +# increment age. #
  55 +# 5. If any interfaces have been removed or changed since the last public #
  56 +# release, then set age to 0. #
  57 +#############################################################################
  58 +CTOOLS_LT_VERSION="1:0:0"
  59 +AC_SUBST(CTOOLS_LT_VERSION)
  60 +
  61 +
  62 +#############################################################################
42 63 # Set prefix #
43 64 # ------------------------------------------------------------------------- #
44 65 # By default, ctools get installed into "/usr/local/gamma". The default #
... ... @@ -71,19 +92,42 @@ AC_CANONICAL_HOST
71 92 # #
72 93 # A special kluge was added for Mac OS X >=10.7. As Apple switched to clang #
73 94 # we search from this version on for the clang compiler. #
  95 +# #
  96 +# We also signal whether Mac OS X >=10.11 (El Capitan). #
74 97 #############################################################################
  98 +# Set default Mac OS X version flags
  99 +osx_lion=no
  100 +osx_el_capitan=no
75 101  
76 102 # Set default compiler lists
77 103 cxx_list="g++ c++ gpp aCC CC cxx cc++ cl.exe FCC KCC RCC xlC_r xlC clang++"
78 104 cc_list="gcc cc cl.exe clang"
79 105  
80   -# Check if we have Mac OS X >= 10.7
  106 +# Check if we have Mac OS X >= 10.7 and >= 10.11
81 107 if test `uname -s` = "Darwin"; then
82   - if test `sw_vers -productVersion | sed 's/\(10\.[[0-9]]*\).*/\1/'` '>' 10.6; then
  108 + version=`sw_vers -productVersion | sed 's/\(10\.[[0-9]]*\).*/\1/' | sed -e 's/\.//g'`
  109 + if [ test $version -ge 107 ]; then
83 110 cxx_list="clang++ g++ c++ gpp aCC CC cxx cc++ cl.exe FCC KCC RCC xlC_r xlC"
84 111 cc_list="clang gcc cc cl.exe"
  112 + osx_lion=yes
  113 + fi
  114 + if [ test $version -ge 1011 ]; then
  115 + osx_el_capitan=yes
85 116 fi
86 117 fi
  118 +AC_MSG_CHECKING([for Mac OS X >= 10.7])
  119 +if [test "x$osx_lion" = "xyes"]; then
  120 + AC_MSG_RESULT(yes)
  121 +else
  122 + AC_MSG_RESULT(no)
  123 +fi
  124 +AC_MSG_CHECKING([for Mac OS X >= 10.11])
  125 +if [test "x$osx_el_capitan" = "xyes"]; then
  126 + AC_MSG_RESULT(yes)
  127 +else
  128 + AC_MSG_RESULT(no)
  129 +fi
  130 +AM_CONDITIONAL(IS_ELCAPITAN, test "x$osx_el_capitan" = "xyes")
87 131  
88 132 # Our language is C++
89 133 AC_LANG(C++)
... ... @@ -897,10 +941,12 @@ AC_CONFIG_FILES([Makefile
897 941 test/test_cscripts.sh
898 942 pyext/Makefile
899 943 pyext/setup.py
  944 + pyext/ctools/__init__.py
  945 + cscripts/__init__.py
  946 + cscripts/Makefile
900 947 caldb/Makefile
901 948 models/Makefile
902 949 examples/Makefile
903   - cscripts/Makefile
904 950 ctools.pc
905 951 testconf.sh],
906 952 [if test -f test/test_cscripts.sh; then chmod +x test/test_cscripts.sh; fi;
... ...
cscripts/Makefile.am
  View file @14f9d87
1 1 ## Process this file with automake to produce Makefile.in
2 2  
3   -# Scripts to be distributed in bindir
4   -binscripts = tsmerge.py
5   -
6 3 # Scripts to be distributed in $(pyexecdir)/cscripts
7 4 pythonscripts = __init__.py \
8 5 cspull.py cssens.py cstsdist.py cscaldb.py csresmap.py \
9   - cshessobs.py csobsdef.py csspec.py cslightcrv.py \
10   - csinfo.py \
  6 + csiactobs.py csiactdata.py csobsdef.py csspec.py cslightcrv.py csobsinfo.py \
  7 + csinfo.py csmodelinfo.py csmodelmerge.py cstsmapmerge.py \
  8 + csobs2caldb.py \
11 9 obsutils.py
12 10  
13 11 # Scripts for which symbolic links will be created in bindir
14 12 linkscripts = cspull cssens cstsdist cscaldb csresmap \
15   - cshessobs csobsdef csspec cslightcrv \
16   - csinfo
  13 + csiactobs csiactdata csobsdef csspec cslightcrv csobsinfo \
  14 + csinfo csmodelinfo csmodelmerge cstsmapmerge \
  15 + csobs2caldb
17 16  
18 17 # Distribute scripts
19 18 EXTRA_DIST = $(binscripts) $(pythonscripts)
... ...
cscripts/__init__.py renamed to cscripts/__init__.py.in
  View file @14f9d87
... ... @@ -21,30 +21,42 @@
21 21 # List all scripts in this module
22 22 __all__ = [
23 23 "cscaldb",
24   - "cshessobs",
  24 + "csiactdata",
  25 + "csiactobs",
25 26 "csinfo",
26 27 "cslightcrv",
  28 + "csmodelinfo",
  29 + "csmodelmerge",
  30 + "csobs2caldb",
27 31 "csobsdef",
  32 + "csobsinfo",
28 33 "cspull",
29 34 "csresmap",
30 35 "cssens",
31 36 "csspec",
32 37 "cstsdist",
  38 + "cstsmapmerge",
33 39 "obsutils",
34 40 "test",
35 41 ]
36 42  
37 43 # Import
38   -from .cscaldb import cscaldb
39   -from .cshessobs import cshessobs
40   -from .csinfo import csinfo
41   -from .cslightcrv import cslightcrv
42   -from .csobsdef import csobsdef
43   -from .cspull import cspull
44   -from .csresmap import csresmap
45   -from .cssens import cssens
46   -from .csspec import csspec
47   -from .cstsdist import cstsdist
  44 +from .cscaldb import cscaldb
  45 +from .csiactdata import csiactdata
  46 +from .csiactobs import csiactobs
  47 +from .csinfo import csinfo
  48 +from .cslightcrv import cslightcrv
  49 +from .csmodelinfo import csmodelinfo
  50 +from .csmodelmerge import csmodelmerge
  51 +from .csobs2caldb import csobs2caldb
  52 +from .csobsdef import csobsdef
  53 +from .csobsinfo import csobsinfo
  54 +from .cspull import cspull
  55 +from .csresmap import csresmap
  56 +from .cssens import cssens
  57 +from .csspec import csspec
  58 +from .cstsdist import cstsdist
  59 +from .cstsmapmerge import cstsmapmerge
48 60 from . import obsutils
49 61  
50 62 # Add test function
... ... @@ -53,3 +65,6 @@ def test():
53 65 Run cscripts tests.
54 66 """
55 67 print("No cscripts unit tests have been implemented so far.")
  68 +
  69 +# Add version
  70 +__version__ = '@PACKAGE_VERSION@'
56 71 \ No newline at end of file
... ...
cscripts/cshessobs.py deleted
View file @61ca854
1   -#!/usr/bin/env python
2   -# ==========================================================================
3   -# Generation of an H.E.S.S. observation definition file.
4   -#
5   -# Copyright (C) 2015 Michael Mayer
6   -#
7   -# This program is free software: you can redistribute it and/or modify
8   -# it under the terms of the GNU General Public License as published by
9   -# the Free Software Foundation, either version 3 of the License, or
10   -# (at your option) any later version.
11   -#
12   -# This program is distributed in the hope that it will be useful,
13   -# but WITHOUT ANY WARRANTY; without even the implied warranty of
14   -# MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
15   -# GNU General Public License for more details.
16   -#
17   -# You should have received a copy of the GNU General Public License
18   -# along with this program. If not, see <http://www.gnu.org/licenses/>.
19   -#
20   -# ==========================================================================
21   -import gammalib
22   -import ctools
23   -import sys
24   -import os
25   -import glob
26   -import math
27   -
28   -
29   -# =============== #
30   -# cshessobs class #
31   -# =============== #
32   -class cshessobs(ctools.cscript):
33   - """
34   - This class implements the creation of a observation xml file for HESS
35   - data analysis. This class is dedicated for use inside the HESS Collaboration,
36   - i.e. it can only be used if you have access to HESS data in FITS format.
37   - The HESSFITS environment has to be set correctly to use this script
38   - Please see the internal documentation for this purpose:
39   - https://hess-confluence.desy.de/confluence/display/HESS/HESS+Open+Source+Tools+-+HESS+data+and+IRFs+in+FITS+format
40   - """
41   - def __init__(self, *argv):
42   - """
43   - Constructor.
44   - """
45   - # Set name
46   - self.name = "cshessobs"
47   - self.version = "0.2.0"
48   - self.datapath = ""
49   - self.m_erange = gammalib.GEbounds()
50   -
51   - # Check on existence of HESSFITS environment variable
52   - try:
53   - self.datapath = os.environ["HESSFITS"]
54   - except KeyError:
55   - raise RuntimeError("Environment variable \"HESSFITS\" not set. " \
56   - "Please set the environment variable \"HESSFITS\" to use this script")
57   -
58   - # Initialise some members
59   - self.inmodels = None
60   - self.outobs = "obs.xml"
61   -
62   - # Make sure that parfile exists
63   - file = self.parfile()
64   -
65   - # Initialise application
66   - if len(argv) == 0:
67   - ctools.cscript.__init__(self, self.name, self.version)
68   - elif len(argv) ==1:
69   - ctools.cscript.__init__(self, self.name, self.version, *argv)
70   - else:
71   - raise TypeError("Invalid number of arguments given.")
72   -
73   - # Set logger properties
74   - self.log_header()
75   - self.log.date(True)
76   -
77   - # Return
78   - return
79   -
80   - def __del__(self):
81   - """
82   - Destructor.
83   - """
84   - # Return
85   - return
86   -
87   - def parfile(self):
88   - """
89   - Check if parfile exists. If parfile does not exist then create a
90   - default parfile. This kluge avoids shipping the cscript with a parfile.
91   - """
92   -
93   - # Set parfile name
94   - parfile = self.name+".par"
95   -
96   - try:
97   - pars = gammalib.GApplicationPars(parfile)
98   - except:
99   - # Signal that parfile was not found
100   - print("Parfile \""+parfile+"\" not found. Create default parfile.")
101   -
102   - # Check for folders and possible/available configurations
103   - chains = os.listdir(self.datapath)
104   -
105   - # Initialise folder dictionary
106   - folders = {}
107   -
108   - # Loop over possible analysis chains
109   - for chain in chains:
110   -
111   - # Omit hidden files/folders
112   - if chain[0]=="." or not os.path.isdir(self.datapath+"/"+chain):
113   - continue
114   -
115   - # Initialise dictionary per chain
116   - folders[chain] = {}
117   -
118   - # Read available DST versions
119   - dstversions = os.listdir(self.datapath+"/"+chain)
120   -
121   - # Loop over DST versions
122   - for dstver in dstversions:
123   -
124   - # Omit hidden files/folders
125   - if dstver[0] == "." or not os.path.isdir(self.datapath+"/"+chain+"/"+dstver):
126   - continue
127   -
128   - # Initialise available cut configurations
129   - folders[chain][dstver] = []
130   - configs = os.listdir(self.datapath+"/"+chain+"/"+dstver)
131   -
132   - # Loop over configurations
133   - for config in configs:
134   -
135   - # Omit hidden files/folders
136   - if config[0] == "." or not os.path.isdir(self.datapath+"/"+chain+"/"+dstver+"/"+config):
137   - continue
138   -
139   - # Append configuration to corresponding dictionary
140   - folders[chain][dstver].append(config)
141   -
142   - # Check for appropriate folder structure
143   - checked_folders = self.check_structure(folders)
144   - if not len(checked_folders):
145   - raise KeyError("Appropriate folder structure not found in $HESSFITS. The correct structure can be found on HESS internal documentation")
146   -
147   - # Create default parfile
148   - pars = gammalib.GApplicationPars()
149   -
150   - # Create parameters for each available config
151   - avchains = ""
152   - for chain in checked_folders:
153   - avchains += chain +"|"
154   - avdsts = ""
155   - for dstver in checked_folders[chain]:
156   - avdsts+=dstver+"|"
157   - avconfigs = ""
158   - for config in checked_folders[chain][dstver]:
159   - avconfigs += config+"|"
160   - pars.append(gammalib.GApplicationPar(chain+"_"+dstver+"_config","s","a",checked_folders[chain][dstver][0],avconfigs[:-1],"","Analysis configuration"))
161   - pars.append(gammalib.GApplicationPar(chain+"_dstver","s","a",checked_folders[chain].keys()[0],avdsts[:-1],"","DST version"))
162   - pars.append(gammalib.GApplicationPar("chain","s","a",checked_folders.keys()[0],avchains[:-1],"","Analysis chain"))
163   - pars.append(gammalib.GApplicationPar("runlistfile","f","a","runlist.lis","","","Runlist file"))
164   - pars.append(gammalib.GApplicationPar("inmodel","f","h","NONE","","","Input model XML file (optional)"))
165   - pars.append(gammalib.GApplicationPar("outobs","f","a","obs.xml","","","Observation XML outfile"))
166   - pars.append(gammalib.GApplicationPar("outmodel","f","a","bgmodels.xml","","","Output model XML file"))
167   - pars.append(gammalib.GApplicationPar("datapath","s","h",self.datapath,"","","Data directoy"))
168   - pars.append(gammalib.GApplicationPar("bkgpars","i","a","1","","","Number of free parameters per background model"))
169   - pars.append(gammalib.GApplicationPar("usetrig","b","h","yes","yes|no","","Pre-estimate background normalisation? Recommended for binned analysis"))
170   - pars.append(gammalib.GApplicationPar("bkgtype","s","a","irf","gauss|irf|aeff","","What background model should be used"))
171   - pars.append_standard()
172   - pars.save(parfile)
173   -
174   - # Return
175   - return
176   -
177   - def get_parameters(self):
178   - """
179   - Get parameters from parfile and setup the observation.
180   - """
181   - # Get parameters
182   - self.runlistfile = self["runlistfile"].filename()
183   -
184   - # Read models if user input
185   - self.inmodel = self["inmodel"].filename()
186   - if not (self.inmodel == "NONE" or self.inmodel == ""):
187   - self.inmodels = gammalib.GModels(self.inmodel)
188   -
189   - # Observation outfile
190   - self.outobs = self["outobs"].filename()
191   -
192   - # Output model file
193   - self.outmodel = self["outmodel"].filename()
194   -
195   - # Read hidden parameters
196   - self.bkgpars = self["bkgpars"].integer()
197   - self.bkgtype = self["bkgtype"].string()
198   - self.usetrig = self["usetrig"].boolean()
199   - self.datapath = self["datapath"].string()
200   -
201   - # Read run configuration parameters
202   - self.chain = self["chain"].string()
203   - self.dstver = self[self.chain+"_dstver"].string()
204   - self.config = self[self.chain+"_"+self.dstver+"_config"].string()
205   -
206   - # Build directory name prefix
207   - self.directory = self.datapath+"/"
208   - self.directory += self.chain +"/"
209   - self.directory += self.dstver +"/"
210   - self.directory += self.config +"/"
211   -
212   - if not os.path.isdir(self.directory):
213   - raise gammalib.Exception.runtime_error("Folder structure not found. Please check your HESSFITS environment variable")
214   -
215   - self.m_log = False # Logging in client tools
216   - self.m_debug = False # Debugging in client tools
217   - self.m_clobber = self["clobber"].boolean()
218   -
219   - # Return
220   - return
221   -
222   - def check_structure(self,folders):
223   -
224   - # Initialise valid folders
225   - newfolders = {}
226   -
227   - # Check if we have found possible chains
228   - if len(folders):
229   -
230   - # Loop over chains
231   - for chain in folders:
232   -
233   - # Loop over dst versions
234   - for dst in folders[chain]:
235   -
236   - # Loop over configs:
237   - for config in folders[chain][dst]:
238   -
239   - # check if config is valid
240   - path = self.datapath+"/"+chain+"/"+dst+"/"+config
241   - if os.path.isdir(path) and len(glob.glob(path+"/run*")):
242   - if not chain in newfolders:
243   - newfolders[chain] = {}
244   - if not dst in newfolders[chain]:
245   - newfolders[chain][dst] = []
246   - newfolders[chain][dst].append(config)
247   -
248   - # Return valid configs
249   - return newfolders
250   -
251   - def background_spectrum(self, run, prefactor, index, aefffile = ""):
252   -
253   - scale = pow(10,math.floor(math.log10(abs(prefactor))))
254   -
255   - if index == 0.0 and self.bkgpars <= 1:
256   - spec = gammalib.GModelSpectralConst()
257   - spec["Value"].min(0.1*scale)
258   - spec["Value"].max(10*scale)
259   - spec["Value"].value(prefactor)
260   - spec["Value"].scale(scale)
261   - if self.bkgpars == 0:
262   - spec["Value"].fix()
263   - else:
264   - spec["Value"].free()
265   -
266   - else:
267   -
268   - # Create power law if number of free parameters are less 2 or less
269   - if self.bkgpars <= 2:
270   - e = gammalib.GEnergy(1.0,"TeV")
271   - spec = gammalib.GModelSpectralPlaw(prefactor, index, e)
272   -
273   - # Set parameter ranges
274   - spec[0].scale(scale)
275   - spec[0].min(0.01 * scale)
276   - spec[0].max(100.0 * scale)
277   - spec[1].scale(1)
278   - spec[1].min(-5.0)
279   - spec[1].max(5.0)
280   -
281   - # Set number of free parameters
282   - if self.bkgpars == 0:
283   - spec[0].fix()
284   - spec[1].fix()
285   - elif self.bkgpars == 1:
286   - spec[0].free()
287   - spec[1].fix()
288   - else:
289   - spec[0].free()
290   - spec[1].free()
291   -
292   - else:
293   -
294   - # Use several energy-dependent scaling factors
295   - fits = gammalib.GFits(aefffile)
296   - emin = fits["EFFECTIVE AREA"].real("LO_THRES")
297   - emax = fits["EFFECTIVE AREA"].real("HI_THRES")
298   - fits.close()
299   -
300   - # Create reference powerlaw
301   - plaw = gammalib.GModelSpectralPlaw(prefactor, index, gammalib.GEnergy(1.0,"TeV"))
302   -
303   - # Create spectral model and energy values
304   - spec = gammalib.GModelSpectralNodes()
305   - bounds = gammalib.GEbounds(self.bkgpars,gammalib.GEnergy(emin,"TeV"),gammalib.GEnergy(emax,"TeV"),True)
306   - for i in range(bounds.size()):
307   - energy = bounds.elogmean(i)
308   - spec.append(energy, plaw.eval(energy, gammalib.GTime()))
309   - for par in spec:
310   -
311   - if "Energy" in par.name():
312   - par.fix()
313   - elif "Intensity" in par.name():
314   - parscale = pow(10,math.floor(math.log10(abs(par.value()))))
315   - par.scale(parscale)
316   - par.min(0.01*parscale)
317   - par.max(100.0*parscale)
318   -
319   -
320   - return spec
321   -
322   - def hess_background(self, run, aefffile, trgrate, zenith):
323   -
324   - # Set IrfBackground
325   - if self.bkgtype == "irf":
326   - prefactor = 1.0
327   - index = 0.0
328   - if self.usetrig and trgrate > 0.0:
329   - # Use value from lookup
330   - prefactor = 0.00427233352611 * trgrate + 0.181244590076
331   - spec = self.background_spectrum(run, prefactor, index, aefffile)
332   - # Create background model instance
333   - bck = gammalib.GCTAModelIrfBackground(spec)
334   -
335   - # Set AeffBackground
336   - elif self.bkgtype == "aeff":
337   - prefactor = 5e-14
338   - index = -2.5
339   - # Use values from lookup if possible
340   - if self.usetrig and trgrate > 0.0:
341   - prefactor = 1.52976410372e-16 * trgrate + 2.71805547108e-14
342   - if zenith > 0.0:
343   - index = 0.000271928721732 * zenith * zenith -0.0029602286453 * zenith -2.76404600416
344   -
345   - spec = self.background_spectrum(run, prefactor, index, aefffile)
346   -
347   - # Create background model instance
348   - bck = gammalib.GCTAModelAeffBackground(spec)
349   -
350   - # Set Gaussian Background
351   - elif self.bkgtype == "gauss":
352   - spec = self.background_spectrum(run, 1e-4, -1.8, aefffile)
353   - radial = gammalib.GCTAModelRadialGauss(2.5)
354   - bck = gammalib.GCTAModelRadialAcceptance(radial, spec)
355   -
356   - else:
357   - sys.exit("Background type \""+self.bkgtype+"\" unsupported")
358   -
359   - # Copy model
360   - model = bck.clone()
361   -
362   - # Assign specific run id
363   - model.ids(str(int(run)))
364   -
365   - # Assign instrument
366   - model.instruments("HESS")
367   -
368   - # Set name (arbitrary)
369   - model.name("bkg_"+run)
370   -
371   - # Turn off TS calculation for background model
372   - model.tscalc(False)
373   -
374   - # Return model
375   - return model
376   -
377   -
378   - def erange(self):
379   - """
380   - Returns runlist energy range
381   - """
382   - return self.m_erange
383   -
384   - def execute(self):
385   - """
386   - Execute the script.
387   - """
388   - # Run the script
389   - self.run()
390   -
391   - # Save residual map
392   - self.save(self.outobs, self.m_clobber)
393   -
394   - # Return
395   - return
396   -
397   - # Get runfolder from runnumber (subject to defined folder structure)
398   - def get_runfolder(self,runnr):
399   -
400   - start = runnr[:-2]+"00"
401   - if not int(runnr[-3]) % 2 == 0:
402   - start = str(int(start)-100)
403   - if len(start) == 5:
404   - start = "0"+start
405   - int_end = int(start)+199
406   - end = str(int_end)
407   - if len(end) == 5:
408   - end = "0"+ end
409   -
410   - runfold = runnr
411   - if len(runfold) == 5:
412   - runfold = "0"+runfold
413   -
414   - return self.directory+"/run"+start+"-"+end+"/run"+runfold+"/"
415   -
416   - def run(self):
417   - """
418   - Run the script.
419   - """
420   - # Switch screen logging on in debug mode
421   - if self.logDebug():
422   - self.log.cout(True)
423   -
424   - # Get parameters
425   - self.get_parameters()
426   -
427   - # Write input parameters into logger
428   - if self.logTerse():
429   - self.log_parameters()
430   - self.log("\n")
431   -
432   - # Initialise empty models
433   - self.models = gammalib.GModels()
434   -
435   - # Initialise empty xml file and append an observation list
436   - self.xml = gammalib.GXml()
437   - self.xml.append(gammalib.GXmlElement("observation_list title=\"observation list\""))
438   - lib = self.xml.element("observation_list", 0)
439   -
440   - # Read runlist from file
441   - runlist = []
442   - runfile = open(self.runlistfile)
443   - for line in runfile.readlines():
444   - if len(line) == 0:
445   - continue
446   - if line[0] == '#':
447   - continue
448   - if len(line.split()) > 0:
449   - runlist.append(line.split()[0])
450   - else:
451   - runlist.append('')
452   - runfile.close()
453   -
454   - # Loop over runs
455   - # Log output
456   - if self.logTerse():
457   - self.log("\n")
458   - self.log.header1("Looping over runs")
459   -
460   - # Initialise energy range values for logging
461   - runlist_emin = 100.0
462   - runlist_emax = 0.0
463   -
464   - for runnr in runlist:
465   -
466   - # Unify run number string length
467   - run = runnr
468   - if len(run) == 5:
469   - run = "0"+run
470   -
471   - # Get folder in which run files should be located
472   - runfolder = self.get_runfolder(run)
473   -
474   - # construct filenames
475   - eventfile = runfolder + "hess_events_"+run+".fits.gz"
476   - aefffile = runfolder + "hess_aeff_2d_"+run+".fits.gz"
477   - psffile = runfolder + "hess_psf_king_"+run+".fits.gz"
478   - edispfile = runfolder + "hess_edisp_2d_"+run+".fits.gz"
479   - bgfile = runfolder + "hess_bkg_offruns_"+run+".fits.gz"
480   -
481   - # Check for existence of files
482   - msg = ""
483   - skip = False
484   - if not os.path.isdir(runfolder):
485   - msg = "Run "+str(int(run))+" does not exist in FITS format"
486   - skip = True
487   - elif not os.path.isfile(eventfile):
488   - msg = "Run "+str(int(run))+" has no eventfile - Run is skipped"
489   - skip = True
490   - elif not os.path.isfile(aefffile):
491   - msg = "Run "+str(int(run))+" has no effective area - Run is skipped"
492   - skip = True
493   - elif not os.path.isfile(psffile):
494   - msg = "Run "+str(int(run))+" has no PSF - Run is skipped"
495   - skip = True
496   - elif not os.path.isfile(edispfile):
497   - msg = "Warning: Run "+str(int(run))+" has no energy dispersion - usage of energy dispersion not possible"
498   - skip = False
499   - edispfile = ""
500   - elif not os.path.isfile(bgfile):
501   - msg = "Warning: Run "+str(int(run))+" has no background file - use of IRF background not possible"
502   - skip = False
503   - bgfile = ""
504   - else:
505   - msg = "Adding run "+str(int(run))
506   -
507   - # Log ouput and skip run if not available
508   - if self.logTerse():
509   - self.log(msg+"\n")
510   - if skip:
511   - continue
512   - if self.logExplicit():
513   - self.log(" Event file: "+eventfile+"\n")
514   - self.log(" Effective area: "+aefffile+"\n")
515   - self.log(" Point spread function: "+psffile+"\n")
516   - self.log(" Energy dispersion: "+edispfile+"\n")
517   - self.log(" Background file: "+bgfile+"\n")
518   -
519   - # Open fits file to determine the observation name
520   - fits = gammalib.GFits(eventfile)
521   - object_name = fits["EVENTS"].string("OBJECT")
522   -
523   - # Retrieve trigger rate and zenith if available
524   - trgrate = 0.0
525   - zenith = 0.0
526   - if fits["EVENTS"].has_card("ZTRGRATE"):
527   - trgrate = fits["EVENTS"].real("ZTRGRATE")
528   - if fits["EVENTS"].has_card("ALT_PNT"):
529   - zenith = 90.-fits["EVENTS"].real("ALT_PNT")
530   -
531   - # Close FITS file
532   - fits.close()
533   -
534   - # Open effective area file to look for threshold
535   - aeff_fits = gammalib.GFits(aefffile)
536   - run_emin = aeff_fits["EFFECTIVE AREA"].real("LO_THRES")
537   - run_emax = aeff_fits["EFFECTIVE AREA"].real("HI_THRES")
538   - if run_emin < runlist_emin:
539   - runlist_emin = run_emin
540   - if run_emax > runlist_emax:
541   - runlist_emax = run_emax
542   - aeff_fits.close()
543   -
544   - # Append observation to XML and set attributes
545   - obs = lib.append("observation");
546   - obs.attribute("name", object_name);
547   - obs.attribute("id", str(int(run)));
548   - obs.attribute("instrument", "HESS");
549   -
550   - # Append event file
551   - par = gammalib.GXmlElement("parameter name=\"EventList\"")
552   - par.attribute("file", eventfile);
553   - obs.append(par)
554   -
555   - # Append effective area
556   - aeff = gammalib.GXmlElement("parameter name=\"EffectiveArea\"")
557   - aeff.attribute("file",aefffile)
558   -
559   - # Append PSF
560   - psf = gammalib.GXmlElement("parameter name=\"PointSpreadFunction\"")
561   - psf.attribute("file",psffile)
562   -
563   - # Append energy dispersion
564   - edisp = gammalib.GXmlElement("parameter name=\"EnergyDispersion\"")
565   - edisp.attribute("file",edispfile)
566   -
567   - # Append background
568   - bck = gammalib.GXmlElement("parameter name=\"Background\"")
569   - bck.attribute("file",bgfile)
570   -
571   - # assign events and IRFs to observation
572   - obs.append(aeff)
573   - obs.append(psf)
574   - obs.append(edisp)
575   - obs.append(bck)
576   -
577   - # Append instrumental background model
578   - self.models.append(self.hess_background(run, aefffile, trgrate, zenith))
579   -
580   - # Continue only if there are observations available
581   - if lib.size():
582   -
583   - # Store energy range as member
584   - self.m_erange = gammalib.GEbounds(gammalib.GEnergy(runlist_emin,"TeV"),gammalib.GEnergy(runlist_emax,"TeV"))
585   -
586   - # Write energy range into log file
587   - if self.logTerse():
588   - self.log("\n")
589   - self.log("Eenrgy range of obervation list: ")
590   - self.log(("% 3.2f" % runlist_emin)+" - "+("% 3.2f" % runlist_emax)+" TeV")
591   -
592   - else:
593   - self.log.header2("WARNING: No observation from given runlist available")
594   -
595   - # Append models provided by 'inmodels' if necessary
596   - if not self.inmodels == None:
597   - if self.logTerse():
598   - self.log("\n")
599   - self.log.header1("Appending models")
600   -
601   - # Loop over input models
602   - for model in self.inmodels:
603   - if self.logTerse():
604   - self.log.header3("Adding model \""+model.name()+"\"")
605   - self.models.append(model)
606   -
607   - # Return
608   - return
609   -
610   - def save(self,outfile,clobber):
611   -
612   - # Save observation XML file
613   - self.xml.save(outfile)
614   -
615   - # Save model XML file
616   - self.models.save(self.outmodel)
617   -
618   -
619   -# ======================== #
620   -# Main routine entry point #
621   -# ======================== #
622   -if __name__ == '__main__':
623   - """
624   - Generates observation file.
625   - """
626   - # Create instance of application
627   - app = cshessobs(sys.argv)
628   -
629   - # Open logfile
630   - app.logFileOpen()
631   -
632   - # Execute application
633   - app.execute()
cscripts/csiactdata.py 0 → 100755
  View file @14f9d87
  1 +#!/usr/bin/env python
  2 +# ==========================================================================
  3 +# Inspection of IACT data storage
  4 +#
  5 +# Copyright (C) 2015 Michael Mayer
  6 +#
  7 +# This program is free software: you can redistribute it and/or modify
  8 +# it under the terms of the GNU General Public License as published by
  9 +# the Free Software Foundation, either version 3 of the License, or
  10 +# (at your option) any later version.
  11 +#
  12 +# This program is distributed in the hope that it will be useful,
  13 +# but WITHOUT ANY WARRANTY; without even the implied warranty of
  14 +# MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
  15 +# GNU General Public License for more details.
  16 +#
  17 +# You should have received a copy of the GNU General Public License
  18 +# along with this program. If not, see <http://www.gnu.org/licenses/>.
  19 +#
  20 +# ==========================================================================
  21 +import gammalib
  22 +import ctools
  23 +import sys
  24 +import os
  25 +import json
  26 +
  27 +
  28 +# ================ #
  29 +# csiactdata class #
  30 +# ================ #
  31 +class csiactdata(ctools.cscript):
  32 + """
  33 + This script inspects the available FITS data storage on the user machine
  34 + and writes information about the available FITS configurations into a log
  35 + file or prints it on the screen. These information can be used as input
  36 + for 'csiactobs'.
  37 + """
  38 + def __init__(self, *argv):
  39 + """
  40 + Constructor.
  41 + """
  42 + # Set name
  43 + self.name = "csiactdata"
  44 + self.version = "1.0.0"
  45 + self.datapath = os.getenv("VHEFITS","")
  46 +
  47 + # Make sure that parfile exists
  48 + file = self.parfile()
  49 +
  50 + # Initialise application
  51 + if len(argv) == 0:
  52 + ctools.cscript.__init__(self, self.name, self.version)
  53 + elif len(argv) == 1:
  54 + ctools.cscript.__init__(self, self.name, self.version, *argv)
  55 + else:
  56 + raise TypeError("Invalid number of arguments given.")
  57 +
  58 + # Set logger properties
  59 + self.log_header()
  60 + self.log.date(True)
  61 +
  62 + # Return
  63 + return
  64 +
  65 + def __del__(self):
  66 + """
  67 + Destructor.
  68 + """
  69 + # Return
  70 + return
  71 +
  72 + def parfile(self):
  73 + """
  74 + Check if parfile exists. If parfile does not exist then create a
  75 + default parfile. This kluge avoids shipping the cscript with a
  76 + parfile.
  77 + """
  78 + # Set parfile name
  79 + parfile = self.name+".par"
  80 +
  81 + try:
  82 + pars = gammalib.GApplicationPars(parfile)
  83 + except:
  84 + # Signal if parfile was not found
  85 + sys.stdout.write("Parfile "+parfile+" not found. Create default parfile.\n")
  86 +
  87 + # Create default parfile
  88 + pars = gammalib.GApplicationPars()
  89 + pars.append(gammalib.GApplicationPar("datapath","s","a",self.datapath,"","","Path were data is located"))
  90 + pars.append(gammalib.GApplicationPar("master_indx","s","h","master.json","","","Name of master index file"))
  91 + pars.append_standard()
  92 + pars.append(gammalib.GApplicationPar("logfile","f","h","csiactdata.log","","","Log filename"))
  93 + pars.save(parfile)
  94 +
  95 + # Return
  96 + return
  97 +
  98 + def get_parameters(self):
  99 + """
  100 + Get parameters from parfile and setup the observation.
  101 + """
  102 +
  103 + # Get datapath if not already set
  104 + if self.datapath == "":
  105 + self.datapath = self["datapath"].string()
  106 +
  107 + # Expand environment
  108 + self.datapath = gammalib.expand_env(self.datapath)
  109 +
  110 + # Get filename of master index file
  111 + self.m_master_indx = self["master_indx"].string()
  112 + self.m_master_file = os.path.join(self.datapath, self.m_master_indx)
  113 +
  114 + # Return
  115 + return
  116 +
  117 + def execute(self):
  118 + """
  119 + Execute the script.
  120 + """
  121 + # Run the script
  122 + self.run()
  123 +
  124 + # Return
  125 + return
  126 +
  127 + def run(self):
  128 + """
  129 + Run the script.
  130 + """
  131 + # Switch screen logging on
  132 + self.log.cout(True)
  133 +
  134 + # Get parameters
  135 + self.get_parameters()
  136 +
  137 + # Write input parameters into logger
  138 + if self.logTerse():
  139 + self.log_parameters()
  140 + self.log("\n")
  141 +
  142 + self.log("\n")
  143 + self.log.header1("Data storage entries")
  144 + self.log("\n")
  145 + self.log.parformat("Master index file")
  146 + self.log(self.m_master_file)
  147 + self.log("\n")
  148 + self.log("\n")
  149 +
  150 + # Open and load JSON file
  151 + json_data = open(self.m_master_file).read()
  152 + data = json.loads(json_data)
  153 + configs = data["datasets"]
  154 +
  155 + # Loop over configs and display unavailable storage first
  156 + for config in configs:
  157 +
  158 + # Create hdu and obs index files
  159 + hdu = os.path.join(self.datapath, config["hduindx"])
  160 + obs = os.path.join(self.datapath, config["obsindx"])
  161 +
  162 + # Check if index files are available
  163 + if not (gammalib.is_fits(str(hdu)) and gammalib.is_fits(str(obs))):
  164 + self.log.parformat(str(config["name"]))
  165 + self.log("Not available")
  166 + self.log("\n")
  167 +
  168 + # Loop over configs and log available configs
  169 + for config in configs:
  170 +
  171 + # Create hdu and obs index files
  172 + hdu = os.path.join(self.datapath, config["hduindx"])
  173 + obs = os.path.join(self.datapath, config["obsindx"])
  174 +
  175 + # Check if index files are available
  176 + if gammalib.is_fits(str(hdu)) and gammalib.is_fits(str(obs)):
  177 +
  178 + # Log data information
  179 + self.log("\n")
  180 + self.log.header3(str(config["name"]))
  181 + for key in config:
  182 + self.log.parformat(str(key))
  183 + self.log(str(config[key]))
  184 + self.log("\n")
  185 +
  186 + # Return
  187 + return
  188 +
  189 +# ======================== #
  190 +# Main routine entry point #
  191 +# ======================== #
  192 +if __name__ == '__main__':
  193 + """
  194 + Shows data storage information
  195 + """
  196 + # Create instance of application
  197 + app = csiactdata(sys.argv)
  198 +
  199 + # Open logfile
  200 + app.logFileOpen()
  201 +
  202 + # Execute application
  203 + app.execute()
... ...
cscripts/csiactobs.py 0 → 100755
  View file @14f9d87
  1 +#!/usr/bin/env python
  2 +# ==========================================================================
  3 +# Generation of an IACT observation definition file.
  4 +#
  5 +# Copyright (C) 2015 Michael Mayer
  6 +#
  7 +# This program is free software: you can redistribute it and/or modify
  8 +# it under the terms of the GNU General Public License as published by
  9 +# the Free Software Foundation, either version 3 of the License, or
  10 +# (at your option) any later version.
  11 +#
  12 +# This program is distributed in the hope that it will be useful,
  13 +# but WITHOUT ANY WARRANTY; without even the implied warranty of
  14 +# MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
  15 +# GNU General Public License for more details.
  16 +#
  17 +# You should have received a copy of the GNU General Public License
  18 +# along with this program. If not, see <http://www.gnu.org/licenses/>.
  19 +#
  20 +# ==========================================================================
  21 +import gammalib
  22 +import ctools
  23 +import sys
  24 +import os
  25 +import json
  26 +
  27 +
  28 +# =============== #
  29 +# csiactobs class #
  30 +# =============== #
  31 +class csiactobs(ctools.cscript):
  32 + """
  33 + This class implements the creation of a observation xml file for IACT
  34 + data analysis. This class is dedicated for use inside a IACT
  35 + Collaboration, i.e. it can only be used if you have access to IACT data
  36 + in FITS format. The FITS data has to be structured and in the format
  37 + described here:
  38 + http://gamma-astro-data-formats.readthedocs.org/en/latest/
  39 + """
  40 + def __init__(self, *argv):
  41 + """
  42 + Constructor.
  43 + """
  44 + # Set name and version
  45 + self.name = "csiactobs"
  46 + self.version = "1.0.0"
  47 +
  48 + # Initialise some members
  49 + self.m_erange = gammalib.GEbounds()
  50 + self.datapath = os.getenv("VHEFITS","")
  51 + self.inmodels = None
  52 + self.outobs = "obs.xml"
  53 +
  54 + # Make sure that parfile exists
  55 + file = self.parfile()
  56 +
  57 + # Initialise application
  58 + if len(argv) == 0:
  59 + ctools.cscript.__init__(self, self.name, self.version)
  60 + elif len(argv) == 1:
  61 + ctools.cscript.__init__(self, self.name, self.version, *argv)
  62 + else:
  63 + raise TypeError("Invalid number of arguments given.")
  64 +
  65 + # Set logger properties
  66 + self.log_header()
  67 + self.log.date(True)
  68 +
  69 + # Return
  70 + return
  71 +
  72 + def __del__(self):
  73 + """
  74 + Destructor.
  75 + """
  76 + # Return
  77 + return
  78 +
  79 + def parfile(self):
  80 + """
  81 + Check if parfile exists. If parfile does not exist then create a
  82 + default parfile. This kluge avoids shipping the cscript with a parfile.
  83 + """
  84 + # Set parfile name
  85 + parfile = self.name+".par"
  86 +
  87 + try:
  88 + pars = gammalib.GApplicationPars(parfile)
  89 + except:
  90 + # Signal if parfile was not found
  91 + sys.stdout.write("Parfile "+parfile+" not found. Create default parfile.\n")
  92 +
  93 + # Create default parfile
  94 + pars = gammalib.GApplicationPars()
  95 + pars.append(gammalib.GApplicationPar("datapath","s","a",self.datapath,"","","Path were data is located"))
  96 + pars.append(gammalib.GApplicationPar("prodname","s","a","","","","Data storage name (Run csdsinfo to view your options)"))
  97 + pars.append(gammalib.GApplicationPar("runlistfile","f","a","runlist.lis","","","Runlist file"))
  98 + pars.append(gammalib.GApplicationPar("bkgpars","i","a","1","","","Number of free parameters per background model"))
  99 + pars.append(gammalib.GApplicationPar("outobs","f","a","obs.xml","","","Observation XML outfile"))
  100 + pars.append(gammalib.GApplicationPar("outmodel","f","a","bgmodels.xml","","","Output model XML file"))
  101 + pars.append(gammalib.GApplicationPar("inmodel","f","h","NONE","","","Input model XML file (optional)"))
  102 + pars.append(gammalib.GApplicationPar("master_indx","s","h","master.json","","","Name of master index file"))
  103 + pars.append(gammalib.GApplicationPar("ev_hiera","s","h","events","","","Hierarchy of event formats"))
  104 + pars.append(gammalib.GApplicationPar("aeff_hiera","s","h","aeff_2d","","","Hierarchy of effective area formats"))
  105 + pars.append(gammalib.GApplicationPar("psf_hiera","s","h","psf_king|psf_3gauss","","","Hierarchy of psf formats"))
  106 + pars.append(gammalib.GApplicationPar("edisp_hiera","s","h","edisp_2d","","","Hierarchy of energy dispersion formats"))
  107 + pars.append(gammalib.GApplicationPar("bkg_hiera","s","h","bkg_3d","","","Hierarchy of background formats"))
  108 + pars.append(gammalib.GApplicationPar("bkg_mod_hiera","s","h","irf","irf|aeff|gauss","","Hierarchy of background models"))
  109 + pars.append(gammalib.GApplicationPar("bkg_gauss_norm","r","h","1e-8","","","Input normalisation for Gaussian background"))
  110 + pars.append(gammalib.GApplicationPar("bkg_gauss_index","r","h","-2.0","","","Input spectral index for Gaussian background"))
  111 + pars.append(gammalib.GApplicationPar("bkg_gauss_sigma","r","h","2.5","","","Input sigma for Gaussian background"))
  112 + pars.append(gammalib.GApplicationPar("bkg_aeff_norm","r","h","1e-14","","","Input normalisation for effective area background"))
  113 + pars.append(gammalib.GApplicationPar("bkg_aeff_index","r","h","-2.0","","","Input spectral index for effective area background"))
  114 + pars.append(gammalib.GApplicationPar("bkg_range_factor","r","h","100.0","","","Factor to determine range of background normalisation"))
  115 + pars.append_standard()
  116 + pars.append(gammalib.GApplicationPar("logfile","f","h","csiactobs.log","","","Log filename"))
  117 + pars.save(parfile)
  118 +
  119 + # Return
  120 + return
  121 +
  122 + def get_parameters(self):
  123 + """
  124 + Get parameters from parfile and setup the observation.
  125 + """
  126 +
  127 + if self.datapath == "":
  128 + self.datapath = self["datapath"].string()
  129 +
  130 + # Expand environment
  131 + self.datapath = gammalib.expand_env(self.datapath)
  132 +
  133 + # Read user parameters
  134 + self.m_prodname = self["prodname"].string()
  135 + self.m_runlistfile = gammalib.expand_env(self["runlistfile"].filename())
  136 + self.m_bkgpars = self["bkgpars"].integer()
  137 +
  138 + # Output model file
  139 + self.outmodel = self["outmodel"].filename()
  140 +
  141 + # Observation outfile
  142 + self.outobs = self["outobs"].filename()
  143 +
  144 + # Master index file name
  145 + self.m_master_indx = self["master_indx"].string()
  146 +
  147 + # Read hierarchy of file loading
  148 + self.m_ev_hiera = self["ev_hiera"].string().split("|")
  149 + self.m_aeff_hiera = self["aeff_hiera"].string().split("|")
  150 + self.m_psf_hiera = self["psf_hiera"].string().split("|")
  151 + self.m_bkg_hiera = self["bkg_hiera"].string().split("|")
  152 + self.m_edisp_hiera = self["edisp_hiera"].string().split("|")
  153 + self.m_bkg_mod_hiera = self["bkg_mod_hiera"].string().split("|")
  154 +
  155 + # Read hidden background parameters
  156 + self.m_bkg_gauss_norm = self["bkg_gauss_norm"].real()
  157 + self.m_bkg_gauss_index = self["bkg_gauss_index"].real()
  158 + self.m_bkg_gauss_sigma = self["bkg_gauss_sigma"].real()
  159 + self.m_bkg_aeff_index = self["bkg_aeff_index"].real()
  160 + self.m_bkg_aeff_norm = self["bkg_aeff_norm"].real()
  161 + self.m_bkg_range_factor = self["bkg_range_factor"].real()
  162 +
  163 + # Open master index file and look for prodname
  164 + master_file = os.path.join(self.datapath, self.m_master_indx)
  165 + if not os.path.isfile(master_file):
  166 + raise RuntimeError("FITS data store not available. No master index file found. Make sure the file is copied from the server and your datapath is set correctly.")
  167 +
  168 + # Open and load JSON file
  169 + json_data = open(master_file).read()
  170 + data = json.loads(json_data)
  171 + if not "datasets" in data:
  172 + raise RuntimeError("Key \"datasets\" not available in master index file.")
  173 +
  174 + # Get configurations
  175 + configs = data["datasets"]
  176 +
  177 + # Initialise HDUs
  178 + self.m_hdu_index = self.m_obs_index = ""
  179 +
  180 + # Get HDUs
  181 + for config in configs:
  182 + if self.m_prodname == config["name"]:
  183 + self.m_hdu_index = str(os.path.join(self.datapath, config["hduindx"]))
  184 + self.m_obs_index = str(os.path.join(self.datapath, config["obsindx"]))
  185 + break
  186 +
  187 + # Check HDUs
  188 + if self.m_hdu_index == "" or self.m_obs_index == "":
  189 + raise RuntimeError("FITS data store \""+self.m_prodname+"\" not available. Run csdsinfo to get a list of available storage names")
  190 + if not gammalib.is_fits(self.m_hdu_index+"[HDU_INDEX]"):
  191 + raise RuntimeError("HDU index file \""+self.m_hdu_index+"[HDU_INDEX]\" for FITS data store \""+self.m_prodname+"\" not available. Check your master index file or run csdsinfo to get a list of available storage names.")
  192 +
  193 + # Load index
  194 + if gammalib.is_fits(self.m_obs_index+"[OBS_INDEX]"):
  195 + fits = gammalib.GFits(self.m_obs_index)
  196 + self.has_bkg_scale = fits["OBS_INDEX"].contains("BKG_SCALE")
  197 + fits.close()
  198 + else:
  199 + self.has_bkg_scale = False
  200 +
  201 + # Create base data directory from hdu index file location
  202 + self.subdir = os.path.dirname(self.m_hdu_index)
  203 + self.m_log = False # Logging in client tools
  204 + self.m_debug = False # Debugging in client tools
  205 + self.m_clobber = self["clobber"].boolean()
  206 +
  207 + # Return
  208 + return
  209 +
  210 + def background_spectrum(self, run, prefactor, index, emin, emax):
  211 +
  212 + # Handle constant spectral model
  213 + if index == 0.0 and self.m_bkgpars <= 1:
  214 + spec = gammalib.GModelSpectralConst()
  215 + spec["Value"].min(prefactor / self.m_bkg_range_factor)
  216 + spec["Value"].max(prefactor * self.m_bkg_range_factor)
  217 + spec["Value"].value(prefactor)
  218 + if self.m_bkgpars == 0:
  219 + spec["Value"].fix()
  220 + else:
  221 + spec["Value"].free()
  222 +
  223 + else:
  224 +
  225 + # Create power law model
  226 + if self.m_bkgpars <= 2:
  227 + e = gammalib.GEnergy(1.0,"TeV")
  228 + spec = gammalib.GModelSpectralPlaw(prefactor, index, e)
  229 +
  230 + # Set parameter ranges
  231 + spec[0].min(0.01 * prefactor)
  232 + spec[0].max(100.0 * prefactor)
  233 + spec[1].scale(1)
  234 + spec[1].min(-5.0)
  235 + spec[1].max(5.0)
  236 +
  237 + # Set number of free parameters
  238 + if self.m_bkgpars == 0:
  239 + spec[0].fix()
  240 + spec[1].fix()
  241 + elif self.m_bkgpars == 1:
  242 + spec[0].free()
  243 + spec[1].fix()
  244 + else:
  245 + spec[0].free()
  246 + spec[1].free()
  247 +
  248 + else:
  249 +
  250 + # Create reference powerlaw
  251 + plaw = gammalib.GModelSpectralPlaw(prefactor, index, gammalib.GEnergy(1.0,"TeV"))
  252 +
  253 + # Create spectral model and energy values
  254 + spec = gammalib.GModelSpectralNodes()
  255 + bounds = gammalib.GEbounds(self.bkgpars,gammalib.GEnergy(emin,"TeV"),gammalib.GEnergy(emax,"TeV"),True)
  256 + for i in range(bounds.size()):
  257 + energy = bounds.elogmean(i)
  258 + value = plaw.eval(energy, gammalib.GTime())
  259 + spec.append(energy, value)
  260 + for par in spec:
  261 +
  262 + if "Energy" in par.name():
  263 + par.fix()
  264 + elif "Intensity" in par.name():
  265 + par.min(value / self.m_bkg_range_factor)
  266 + par.max(value * self.m_bkg_range_factor)
  267 +
  268 + # Return spectrum
  269 + return spec
  270 +
  271 + def iact_background(self, telescope, obs_id, bkg_scale, bkgtype, emin=0.1, emax=100):
  272 +
  273 + # handle IrfBackground
  274 + if bkgtype == "irf":
  275 + prefactor = 1.0
  276 + index = 0.0
  277 + prefactor *= bkg_scale
  278 + spec = self.background_spectrum(obs_id, prefactor, index, emin, emax)
  279 +
  280 + # Create background model instance
  281 + bck = gammalib.GCTAModelIrfBackground(spec)
  282 +
  283 + # Set AeffBackground
  284 + elif self.bkgtype == "aeff":
  285 +
  286 + prefactor = bkg_scale * self.m_bkg_aeff_norm
  287 + spec = self.background_spectrum(obs_id, prefactor, self.m_bkg_aeff_index, emin, emax)
  288 +
  289 + # Create background model instance
  290 + bck = gammalib.GCTAModelAeffBackground(spec)
  291 +
  292 + # Set Gaussian Background
  293 + elif self.bkgtype == "gauss":
  294 + prefactor = bkg_scale * self.m_bkg_gauss_norm
  295 + spec = self.background_spectrum(obs_id, prefactor, self.m_bkg_gauss_index, emin, emax)
  296 + radial = gammalib.GCTAModelRadialGauss(self.m_bkg_gauss_sigma)
  297 + bck = gammalib.GCTAModelRadialAcceptance(radial, spec)
  298 +
  299 + else:
  300 + sys.exit("Background type \""+self.bkgtype+"\" unsupported")
  301 +
  302 + # Copy model
  303 + model = bck.clone()
  304 +
  305 + # Assign specific run id
  306 + model.ids(str(obs_id))
  307 +
  308 + # Assign instrument
  309 + model.instruments(telescope)
  310 +
  311 + # Set name (arbitrary)
  312 + model.name("bkg_"+str(obs_id))
  313 +
  314 + # Turn off TS calculation for background model
  315 + model.tscalc(False)
  316 +
  317 + # Return model
  318 + return model
  319 +
  320 + def erange(self):
  321 + """
  322 + Returns runlist energy range
  323 + """
  324 + return self.m_erange
  325 +
  326 + def execute(self):
  327 + """
  328 + Execute the script.
  329 + """
  330 + # Run the script
  331 + self.run()
  332 +
  333 + # Save residual map
  334 + self.save(self.outobs, self.m_clobber)
  335 +
  336 + # Return
  337 + return
  338 +
  339 + def run(self):
  340 + """
  341 + Run the script.
  342 + """
  343 + # Switch screen logging on in debug mode
  344 + if self.logDebug():
  345 + self.log.cout(True)
  346 +
  347 + # Get parameters
  348 + self.get_parameters()
  349 +
  350 + # Write input parameters into logger
  351 + if self.logTerse():
  352 + self.log_parameters()
  353 + self.log("\n")
  354 +
  355 + # Initialise empty models
  356 + self.models = gammalib.GModels()
  357 +
  358 + # Initialise empty xml file and append an observation list
  359 + self.xml = gammalib.GXml()
  360 + self.xml.append(gammalib.GXmlElement("observation_list title=\"observation list\""))
  361 + lib = self.xml.element("observation_list", 0)
  362 +
  363 + # Read runlist from file
  364 + runlist = []
  365 + runfile = open(self.m_runlistfile)
  366 + for line in runfile.readlines():
  367 + if len(line) == 0:
  368 + continue
  369 + if line[0] == '#':
  370 + continue
  371 + if len(line.split()) > 0:
  372 + runlist.append(line.split()[0])
  373 + else:
  374 + runlist.append('')
  375 + runfile.close()
  376 +
  377 + # Loop over runs
  378 + # Log output
  379 + if self.logTerse():
  380 + self.log("\n")
  381 + self.log.header1("Looping over runs")
  382 +
  383 + # Initialise energy range values for logging
  384 + runlist_emin = 100.0
  385 + runlist_emax = 0.0
  386 +
  387 + for obs_id in runlist:
  388 +
  389 + obs_selection = "[OBS_ID=="+str(obs_id)+"]"
  390 +
  391 + hduindx = gammalib.GFits(self.m_hdu_index+"[HDU_INDEX]"+obs_selection)
  392 + hduindx_hdu = hduindx["HDU_INDEX"]
  393 +
  394 + eventfile = aefffile = psffile = edispfile = bkgfile = ""
  395 + eventhdu = aeffhdu = ""
  396 +
  397 + types = []
  398 + formats = []
  399 + for i in range(hduindx_hdu.nrows()):
  400 + types.append(hduindx_hdu["HDU_TYPE"][i])
  401 + formats.append(hduindx_hdu["HDU_CLASS"][i])
  402 +
  403 + # Handle events
  404 + index = -1
  405 + for version in self.m_ev_hiera:
  406 + n = formats.count(version)
  407 + if n > 0:
  408 + index = formats.index(version)
  409 + break
  410 + if index >= 0:
  411 + eventfile = os.path.join(self.subdir, hduindx_hdu["FILE_DIR"][index], hduindx_hdu["FILE_NAME"][index])
  412 + eventhdu = hduindx_hdu["HDU_NAME"][index]
  413 + eventfile += "["+eventhdu+"]"
  414 + if not gammalib.is_fits(eventfile):
  415 + if self.logTerse():
  416 + self.log("Skipping observation "+str(obs_id)+": eventfile \""+eventfile+"\" not found\n")
  417 + continue
  418 +
  419 + # Handle Aeff
  420 + index = -1
  421 + for version in self.m_aeff_hiera:
  422 + n = formats.count(version)
  423 + if n > 0:
  424 + index = formats.index(version)
  425 + break
  426 + if index >= 0:
  427 + aefffile = os.path.join(self.subdir, hduindx_hdu["FILE_DIR"][index], hduindx_hdu["FILE_NAME"][index])
  428 + aeffhdu = hduindx_hdu["HDU_NAME"][index]
  429 + aefffile += "["+aeffhdu+"]"
  430 + if not gammalib.is_fits(aefffile):
  431 + if self.logTerse():
  432 + self.log("Skipping observation "+str(obs_id)+": effective area \""+aefffile+"\" not found\n")
  433 + continue
  434 +
  435 + # Handle psf
  436 + index = -1
  437 + for version in self.m_psf_hiera:
  438 + n = formats.count(version)
  439 + if n > 0:
  440 + index = formats.index(version)
  441 + break
  442 + if index >= 0:
  443 + psffile = os.path.join(self.subdir, hduindx_hdu["FILE_DIR"][index], hduindx_hdu["FILE_NAME"][index])
  444 + psffile += "["+hduindx_hdu["HDU_NAME"][index]+"]"
  445 + if not gammalib.is_fits(psffile):
  446 + if self.logTerse():
  447 + self.log("Skipping observation "+str(obs_id)+": point spread function \""+psffile+"\" not found\n")
  448 + continue
  449 +
  450 + # Handle edisp
  451 + index = -1
  452 + for version in self.m_edisp_hiera:
  453 + n = formats.count(version)
  454 + if n > 0:
  455 + index = formats.index(version)
  456 + break
  457 + if index >= 0:
  458 + edispfile = os.path.join(self.subdir, hduindx_hdu["FILE_DIR"][index], hduindx_hdu["FILE_NAME"][index])
  459 + edispfile += "["+hduindx_hdu["HDU_NAME"][index]+"]"
  460 + if not gammalib.is_fits(edispfile):
  461 + if self.logTerse():
  462 + self.log("Warning: observation "+str(obs_id)+" has no energy dispersion \""+edispfile+"\" information\n")
  463 + edispfile = ""
  464 +
  465 + # Handle background
  466 + index = -1
  467 + bkg_mod_hierarchy = self.m_bkg_mod_hiera
  468 + for version in self.m_bkg_hiera:
  469 + n = formats.count(version)
  470 + if n > 0:
  471 + index = formats.index(version)
  472 + break
  473 + if index >= 0:
  474 + bkgfile = os.path.join(self.subdir, hduindx_hdu["FILE_DIR"][index], hduindx_hdu["FILE_NAME"][index])
  475 + bkgfile += "["+hduindx_hdu["HDU_NAME"][index]+"]"
  476 + if not gammalib.is_fits(bkgfile):
  477 + if self.logTerse():
  478 + self.log("Warning: observation "+str(obs_id)+" has no background information in \""+bkgfile+"\". IRF background cannot be used\n")
  479 + bkgfile = ""
  480 + bkg_mod_hierarchy.remove("irf")
  481 +
  482 + # Handle background scale information if available
  483 + bkg_scale = 1.0
  484 + if self.has_bkg_scale:
  485 + obsindx = gammalib.GFits(self.m_obs_index+"[OBS_INDEX]"+obs_selection)
  486 + bkg_scale = obsindx["OBS_INDEX"]["BKG_SCALE"][0]
  487 + obsindx.close()
  488 +
  489 + # Open fits file to determine the observation name
  490 + fits = gammalib.GFits(eventfile)
  491 + events = fits[eventhdu]
  492 + object_name = events.string("OBJECT")
  493 + telescope = events.string("TELESCOP")
  494 +
  495 + # Close FITS file
  496 + fits.close()
  497 +
  498 + # Open effective area file to look for threshold
  499 + aeff_fits = gammalib.GFits(aefffile)
  500 + aeff_table = aeff_fits[aeffhdu]
  501 +
  502 + # Initialise energy range in case no threshold is available
  503 + run_emin = 0.1
  504 + run_emax = 100.0
  505 +
  506 + # Set energy range from heady keywords
  507 + if aeff_table.has_card("LO_THRES") and aeff_table.has_card["HI_THRES"]:
  508 + run_emin = aeff_table.real("LO_THRES")
  509 + run_emax = aeff_table.real("HI_THRES")
  510 +
  511 + # Close Aeff fits file
  512 + aeff_fits.close()
  513 +
  514 + # Adapt runlist energy range if necessary
  515 + if run_emin < runlist_emin:
  516 + runlist_emin = run_emin
  517 + if run_emax > runlist_emax:
  518 + runlist_emax = run_emax
  519 +
  520 + # Logging
  521 + if self.logTerse():
  522 + self.log("Adding observation "+str(obs_id)+" (\""+object_name+"\")\n")
  523 +
  524 + if self.logExplicit():
  525 + self.log(" Event file: "+eventfile+"\n")
  526 + self.log(" Effective area: "+aefffile+"\n")
  527 + self.log(" Point spread function: "+psffile+"\n")
  528 + self.log(" Energy dispersion: "+edispfile+"\n")
  529 + self.log(" Background file: "+bkgfile+"\n")
  530 + if self.has_bkg_scale:
  531 + self.log(" Background scale: "+str(bkg_scale)+"\n")
  532 + self.log("\n")
  533 +
  534 + # Append observation to XML and set attributes
  535 + obs = lib.append("observation");
  536 + obs.attribute("name", object_name);
  537 + obs.attribute("id", str(obs_id));
  538 + obs.attribute("instrument", telescope);
  539 +
  540 + # Append event file
  541 + ev = gammalib.GXmlElement("parameter name=\"EventList\"")
  542 + ev.attribute("file", eventfile);
  543 +
  544 + # Append effective area
  545 + aeff = gammalib.GXmlElement("parameter name=\"EffectiveArea\"")
  546 + aeff.attribute("file",aefffile)
  547 +
  548 + # Append PSF
  549 + psf = gammalib.GXmlElement("parameter name=\"PointSpreadFunction\"")
  550 + psf.attribute("file",psffile)
  551 +
  552 + # Append energy dispersion
  553 + edisp = gammalib.GXmlElement("parameter name=\"EnergyDispersion\"")
  554 + edisp.attribute("file",edispfile)
  555 +
  556 + # Append background
  557 + bck = gammalib.GXmlElement("parameter name=\"Background\"")
  558 + bck.attribute("file",bkgfile)
  559 +
  560 + # assign events and IRFs to observation
  561 + obs.append(ev)
  562 + obs.append(aeff)
  563 + obs.append(psf)
  564 + obs.append(edisp)
  565 + obs.append(bck)
  566 +
  567 + # Append instrumental background model
  568 + self.models.append(self.iact_background(telescope, obs_id, bkg_scale, bkg_mod_hierarchy[0], run_emin, run_emax))
  569 +
  570 + # Continue only if there are observations available
  571 + if lib.size():
  572 +
  573 + # Store energy range as member
  574 + self.m_erange = gammalib.GEbounds(gammalib.GEnergy(runlist_emin,"TeV"),gammalib.GEnergy(runlist_emax,"TeV"))
  575 +
  576 + # Write energy range into log file
  577 + if self.logTerse():
  578 + self.log("\n")
  579 + self.log("Eenrgy range of obervation list: ")
  580 + self.log(("% 3.2f" % runlist_emin)+" - "+("% 3.2f" % runlist_emax)+" TeV")
  581 + self.log("\n")
  582 +
  583 + else:
  584 + self.log.header2("WARNING: No observation from given runlist available")
  585 +
  586 + # Append models provided by 'inmodels' if necessary
  587 + if not self.inmodels == None:
  588 + if self.logTerse():
  589 + self.log("\n")
  590 + self.log.header1("Appending models")
  591 +
  592 + # Loop over input models
  593 + for model in self.inmodels:
  594 + if self.logTerse():
  595 + self.log.header3("Adding model \""+model.name()+"\"")
  596 + self.models.append(model)
  597 +
  598 + # Return
  599 + return
  600 +
  601 + def save(self,outfile,clobber):
  602 +
  603 + # Save observation XML file
  604 + self.xml.save(outfile)
  605 +
  606 + # Save model XML file
  607 + self.models.save(self.outmodel)
  608 +
  609 + # Return
  610 + return
  611 +
  612 +# ======================== #
  613 +# Main routine entry point #
  614 +# ======================== #
  615 +if __name__ == '__main__':
  616 + """
  617 + Generates observation file.
  618 + """
  619 + # Create instance of application
  620 + app = csiactobs(sys.argv)
  621 +
  622 + # Open logfile
  623 + app.logFileOpen()
  624 +
  625 + # Execute application
  626 + app.execute()
... ...
cscripts/cslightcrv.py
  View file @14f9d87
... ... @@ -98,15 +98,15 @@ class cslightcrv(ctools.cscript):
98 98  
99 99 # Create default parfile
100 100 pars = gammalib.GApplicationPars()
101   - pars.append(gammalib.GApplicationPar("inobs","f","a","events.fits","","","Event list, counts cube, or observation definition file"))
102   - pars.append(gammalib.GApplicationPar("inmodel","f","a","$CTOOLS/share/models/crab.xml","","","Source model"))
  101 + pars.append(gammalib.GApplicationPar("inobs","f","a","events.fits","","","Input event list, counts cube, or observation definition XML file"))
  102 + pars.append(gammalib.GApplicationPar("inmodel","f","a","$CTOOLS/share/models/crab.xml","","","Input model XML file"))
103 103 pars.append(gammalib.GApplicationPar("srcname","s","a","Crab","","","Source name"))
104   - pars.append(gammalib.GApplicationPar("outfile","f","a","lightcurve.fits","","","Output file name"))
105   - pars.append(gammalib.GApplicationPar("expcube","f","a","NONE","","","Exposure cube file (only needed for stacked analysis)"))
106   - pars.append(gammalib.GApplicationPar("psfcube","f","a","NONE","","","PSF cube file (only needed for stacked analysis)"))
107   - pars.append(gammalib.GApplicationPar("bkgcube","s","a","NONE","","","Background cube file (only needed for stacked analysis)"))
  104 + pars.append(gammalib.GApplicationPar("expcube","f","a","NONE","","","Input exposure cube file (only needed for stacked analysis)"))
  105 + pars.append(gammalib.GApplicationPar("psfcube","f","a","NONE","","","Input PSF cube file (only needed for stacked analysis)"))
  106 + pars.append(gammalib.GApplicationPar("bkgcube","s","a","NONE","","","Input background cube file (only needed for stacked analysis)"))
108 107 pars.append(gammalib.GApplicationPar("caldb","s","a","prod2","","","Calibration database"))
109   - pars.append(gammalib.GApplicationPar("irf","s","a","South_50h","","","Instrument response function"))
  108 + pars.append(gammalib.GApplicationPar("irf","s","a","South_0.5h","","","Instrument response function"))
  109 + pars.append(gammalib.GApplicationPar("outfile","f","a","lightcurve.fits","","","Output light curve file"))
110 110 pars.append(gammalib.GApplicationPar("tbinalg","s","a","GTI","FILE|LIN|GTI","", "Algorithm for defining time bins"))
111 111 pars.append(gammalib.GApplicationPar("tmin","r","a","51544.5","","days","Lightcurve start time [MJD]"))
112 112 pars.append(gammalib.GApplicationPar("tmax","r","a","51544.6","","days","Lightcurve stop time [MJD]"))
... ...
cscripts/csmodelinfo.py 0 → 100755
  View file @14f9d87
  1 +#!/usr/bin/env python
  2 +# ==========================================================================
  3 +# Dump information about models into log file
  4 +#
  5 +# Copyright (C) 2015 Michael Mayer
  6 +#
  7 +# This program is free software: you can redistribute it and/or modify
  8 +# it under the terms of the GNU General Public License as published by
  9 +# the Free Software Foundation, either version 3 of the License, or
  10 +# (at your option) any later version.
  11 +#
  12 +# This program is distributed in the hope that it will be useful,
  13 +# but WITHOUT ANY WARRANTY; without even the implied warranty of
  14 +# MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
  15 +# GNU General Public License for more details.
  16 +#
  17 +# You should have received a copy of the GNU General Public License
  18 +# along with this program. If not, see <http://www.gnu.org/licenses/>.
  19 +#
  20 +# ==========================================================================
  21 +import gammalib
  22 +import ctools
  23 +import sys
  24 +
  25 +
  26 +# ================= #
  27 +# csmodelinfo class #
  28 +# ================= #
  29 +class csmodelinfo(ctools.cscript):
  30 + """
  31 + This class dumps information about a model container into a logfile or
  32 + on screen. This might be helpful for quick access to the model container,
  33 + showing, e.g., number of sources, background models, free and fixed
  34 + parameters etc. The tool can also dump the models into a region file to
  35 + display e.g. with ds9.
  36 + """
  37 + def __init__(self, *argv):
  38 + """
  39 + Constructor.
  40 + """
  41 + # Set name
  42 + self.name = "csmodelinfo"
  43 + self.version = "1.1.0"
  44 +
  45 + # Make sure that parfile exists
  46 + file = self.parfile()
  47 +
  48 + # Initialise application
  49 + if len(argv) == 0:
  50 + ctools.cscript.__init__(self, self.name, self.version)
  51 + elif len(argv) == 1:
  52 + ctools.cscript.__init__(self, self.name, self.version, *argv)
  53 + else:
  54 + raise TypeError("Invalid number of arguments given.")
  55 +
  56 + # Set logger properties
  57 + self.log_header()
  58 + self.log.date(True)
  59 +
  60 + # Return
  61 + return
  62 +
  63 + def __del__(self):
  64 + """
  65 + Destructor.
  66 + """
  67 + # Return
  68 + return
  69 +
  70 + def parfile(self):
  71 + """
  72 + Check if parfile exists. If parfile does not exist then create a
  73 + default parfile. This kluge avoids shipping the cscript with a
  74 + parfile.
  75 + """
  76 +
  77 + # Set parfile name
  78 + parfile = self.name+".par"
  79 +
  80 + try:
  81 + pars = gammalib.GApplicationPars(parfile)
  82 + except:
  83 + # Signal that parfile was not found
  84 + print("Parfile \""+parfile+"\" not found. Create default parfile.")
  85 +
  86 + # Create default parfile
  87 + pars = gammalib.GApplicationPars()
  88 + pars.append(gammalib.GApplicationPar("inmodel","f","a","model.xml","","","Input model XML file"))
  89 + pars.append(gammalib.GApplicationPar("ds9file","f","h","NONE","","","DS9 region file containing models"))
  90 + pars.append(gammalib.GApplicationPar("pnt_type","s","h","cross","circle|box|diamond|cross|x|arrow|boxcircle","","Marker type for point sources"))
  91 + pars.append(gammalib.GApplicationPar("pnt_mark_size","i","h","12","","","Marker size for point sources"))
  92 + pars.append(gammalib.GApplicationPar("show_labels","b","h","yes","yes|no","","Add source labels?"))
  93 + pars.append(gammalib.GApplicationPar("width","i","h","2","","","Line width for regions"))
  94 + pars.append(gammalib.GApplicationPar("font","s","h","helvetica","helvetica|times|courier","","Font for source labels"))
  95 + pars.append(gammalib.GApplicationPar("fontsize","i","h","12","","","Font size for source labels"))
  96 + pars.append(gammalib.GApplicationPar("fonttype","s","h","normal","normal|bold","","Use normal or bold font?"))
  97 + pars.append(gammalib.GApplicationPar("fonttype2","s","h","roman","roman|italic","","Use roman or italic font?"))
  98 + pars.append(gammalib.GApplicationPar("show_ext_type","b","h","yes","yes|no","","Show type of extended model in source name"))
  99 + pars.append(gammalib.GApplicationPar("free_color","s","h","green","","","Color for sources with free parameters (any ds9 color or hex code)"))
  100 + pars.append(gammalib.GApplicationPar("fixed_color","s","h","magenta","","","Color for source without free parameters (any ds9 color or hex code)"))
  101 + pars.append_standard()
  102 + pars.append(gammalib.GApplicationPar("logfile","f","h","csmodelinfo.log","","","Log filename"))
  103 + pars.save(parfile)
  104 +
  105 + # Return
  106 + return
  107 +
  108 + def get_parameters(self):
  109 + """
  110 + Get parameters from parfile and setup the observation.
  111 + """
  112 + # Get models
  113 + self.models = gammalib.GModels(self["inmodel"].filename())
  114 +
  115 + # Get ds9 filename
  116 + self.ds9file = self["ds9file"].filename()
  117 +
  118 + # Get hidden parameters for region file
  119 + self.pnt_type = self["pnt_type"].string()
  120 + self.pnt_mark_size = self["pnt_mark_size"].integer()
  121 + self.show_labels = self["show_labels"].boolean()
  122 + self.width = self["width"].integer()
  123 + self.font = self["font"].string()
  124 + self.fontsize = self["fontsize"].integer()
  125 + self.fonttype = self["fonttype"].string()
  126 + self.fonttype2 = self["fonttype2"].string()
  127 + self.show_ext_type = self["show_ext_type"].boolean()
  128 + self.free_color = self["free_color"].string()
  129 + self.fixed_color = self["fixed_color"].string()
  130 +
  131 + # Return
  132 + return
  133 +
  134 + def run(self):
  135 + """
  136 + Run the script.
  137 + """
  138 + # Switch screen logging on in debug mode
  139 + if self.logDebug():
  140 + self.log.cout(True)
  141 +
  142 + # Get parameters
  143 + self.get_parameters()
  144 +
  145 + # Write input parameters into logger
  146 + if self.logTerse():
  147 + self.log_parameters()
  148 + self.log("\n")
  149 +
  150 + if self.logVerbose():
  151 + self.log("\n")
  152 + self.log.header1("Models in detail")
  153 + self.log("\n")
  154 + self.log(str(self.models))
  155 + self.log("\n")
  156 +
  157 + # Initialise output values
  158 + types = {}
  159 + instruments = {}
  160 + ts = {}
  161 + pars_at_limit = {}
  162 + free_src_pars = {}
  163 + n_par_total = 0
  164 + n_par_free = 0
  165 + n_par_fixed = 0
  166 + n_par_at_limit = 0
  167 + n_par_free_bkg = 0
  168 + n_par_free_src = 0
  169 + n_par_free_spec = 0
  170 + n_par_free_spat = 0
  171 + n_par_free_temp = 0
  172 +
  173 + # Loop over models and initialise dictionaries with model names
  174 + for model in self.models:
  175 + types[model.type()] = 0
  176 + instruments[model.instruments()] = 0
  177 + pars_at_limit[model.name()] = []
  178 +
  179 + # Loop over models again and fill values to be dumped
  180 + for model in self.models:
  181 +
  182 + # Model types
  183 + types[model.type()] += 1
  184 +
  185 + # Model instruments
  186 + instruments[model.instruments()] += 1
  187 +
  188 + # TS
  189 + if model.has_ts():
  190 + ts[model.name()] = model.ts()
  191 +
  192 + # Skymodel?
  193 + skymodel = (model.classname() == "GModelSky")
  194 + if skymodel:
  195 + free_src_pars[model.name()] = []
  196 +
  197 + # Loop over model parameters
  198 + for par in model:
  199 +
  200 + # Increment total parameters
  201 + n_par_total += 1
  202 +
  203 + # Check if parameter is at limit
  204 + if par.has_range():
  205 + if par.value() == par.min() or par.value() == par.max():
  206 + pars_at_limit[model.name()].append(par.name())
  207 + n_par_at_limit += 1
  208 +
  209 + # Check if model parameter is free/fixed and
  210 + # increment respective variable
  211 + if par.is_free():
  212 + n_par_free += 1
  213 + if skymodel:
  214 + free_src_pars[model.name()].append(par)
  215 + n_par_free_src += 1
  216 + else:
  217 + n_par_free_bkg += 1
  218 + else:
  219 + n_par_fixed += 1
  220 +
  221 + # If sky model, divide free parameters into spatial, spectral and temporal
  222 + if skymodel:
  223 + for par in model.spectral():
  224 + if par.is_free():
  225 + n_par_free_spec += 1
  226 + for par in model.spatial():
  227 + if par.is_free():
  228 + n_par_free_spat += 1
  229 + for par in model.temporal():
  230 + if par.is_free():
  231 + n_par_free_temp += 1
  232 +
  233 + # Log summary
  234 + self.log("\n")
  235 + self.log.header1("Summary")
  236 +
  237 + # Log instruments
  238 + self.log.header3("Instrument specific models")
  239 + for inst, n_inst in instruments.items():
  240 + if inst == "":
  241 + inst = "All"
  242 + self.log.parformat(inst)
  243 + self.log(str(n_inst))
  244 + self.log("\n")
  245 +
  246 + # Log model types
  247 + self.log.header3("Model types")
  248 + for modeltype, n_types in types.items():
  249 + self.log.parformat(modeltype)
  250 + self.log(str(n_types))
  251 + self.log("\n")
  252 +
  253 + # Log parameter information
  254 + self.log("\n")
  255 + self.log.header1("Parameter information")
  256 + self.log.parformat("All parameters")
  257 + self.log(str(n_par_total))
  258 + self.log("\n")
  259 + self.log.parformat("Fixed parameters")
  260 + self.log(str(n_par_fixed))
  261 + self.log("\n")
  262 + self.log.parformat("Free parameters (total)")
  263 + self.log(str(n_par_free))
  264 + self.log("\n")
  265 + self.log.parformat("Free background parameters")
  266 + self.log(str(n_par_free_bkg))
  267 + self.log("\n")
  268 + self.log.parformat("Free source parameters")
  269 + self.log(str(n_par_free_src))
  270 + self.log("\n")
  271 + if n_par_free_spec > 0:
  272 + self.log.parformat("Free spectral parameters")
  273 + self.log(str(n_par_free_spec))
  274 + self.log("\n")
  275 + if n_par_free_spat > 0:
  276 + self.log.parformat("Free spatial parameters")
  277 + self.log(str(n_par_free_spat))
  278 + self.log("\n")
  279 + if n_par_free_temp > 0:
  280 + self.log.parformat("Free temporal parameters")
  281 + self.log(str(n_par_free_temp))
  282 + self.log("\n")
  283 + self.log.parformat("Parameters at limit")
  284 + self.log(str(n_par_at_limit))
  285 + self.log("\n")
  286 +
  287 + # Log parameters at limit (if any)
  288 + if n_par_at_limit > 0:
  289 + self.log.header3("Parameters at limit")
  290 + for source, parameter in pars_at_limit.items():
  291 + if len(parameter):
  292 + for par in parameter:
  293 + self.log.parformat(source)
  294 + self.log(par)
  295 + self.log("\n")
  296 +
  297 + # Log free parameters if requested
  298 + if self.logExplicit() and len(free_src_pars):
  299 + self.log("\n")
  300 + self.log.header2("Free source parameters")
  301 + for source, parameter in free_src_pars.items():
  302 + if len(parameter):
  303 + self.log.header3(source)
  304 + for par in parameter:
  305 + self.log(str(par))
  306 + self.log("\n")
  307 + self.log("\n")
  308 +
  309 + # Log TS values if available
  310 + if len(ts):
  311 + self.log.header3("Test statistics")
  312 + for source,tsvalue in ts.items():
  313 + self.log.parformat(source)
  314 + self.log("%.2f"%tsvalue)
  315 + self.log("\n")
  316 +
  317 + # Return
  318 + return
  319 +
  320 + def save(self):
  321 + """
  322 + Save models to ds9 region file if required
  323 + """
  324 +
  325 + # Check if ds9 file is valid
  326 + if not self.ds9file == "NONE":
  327 +
  328 + self.log("\n")
  329 + self.log.header1("Save region file")
  330 +
  331 + # Open file
  332 + f = open(self.ds9file,"w")
  333 +
  334 + # Write coordinate system
  335 + f.write("fk5\n")
  336 +
  337 + # Loop over models
  338 + for model in self.models:
  339 +
  340 + # Continue only if point source or extended source model
  341 + if model.type() == "PointSource" or model.type() == "ExtendedSource":
  342 +
  343 + line = self.model2ds9string(model)
  344 + if len(line):
  345 + f.write(line+"\n")
  346 +
  347 + # Logging for diffuse components
  348 + elif model.type() == "DiffuseSource":
  349 + self.log("Skipping diffuse model "+model.name()+"\n")
  350 +
  351 + # Logging for background components
  352 + else:
  353 + if self.logExplicit():
  354 + self.log("Skipping background model "+model.name()+"\n")
  355 +
  356 + # Close file
  357 + f.close()
  358 +
  359 + # Return
  360 + return
  361 +
  362 + def model2ds9string(self, model):
  363 + """
  364 + Converts model instance to ds9 region string
  365 + """
  366 +
  367 + # Initialise return string
  368 + ds9string = ""
  369 +
  370 + # Determine color
  371 + color = self.fixed_color
  372 + for par in model:
  373 + if par.is_free():
  374 + color = self.free_color
  375 + break
  376 +
  377 + # Initialise flag ot continue
  378 + is_valid = True
  379 +
  380 + # Retrieve model position
  381 + try:
  382 + modelpos = model.spatial().dir()
  383 + except AttributeError:
  384 + self.log("Skipping source "+model.name()+": Could not determine sky position\n")
  385 + is_valid = False
  386 +
  387 + # Continue only if position was found
  388 + if is_valid:
  389 +
  390 + # Retrieve model type and name
  391 + modeltype = model.type()
  392 + modelname = model.name()
  393 +
  394 + # Handle point source
  395 + if modeltype == "PointSource":
  396 +
  397 + ds9string += "point("
  398 + ds9string += str(modelpos.ra_deg())
  399 + ds9string += ","
  400 + ds9string += str(modelpos.dec_deg())
  401 + ds9string += ") # "
  402 + ds9string += "point="+self.pnt_type+" "
  403 + ds9string += str(self.pnt_mark_size)+" "
  404 +
  405 + # Hanlde extended sources
  406 + elif modeltype == "ExtendedSource":
  407 +
  408 + # Retrieve spatial model
  409 + spatial = model.spatial()
  410 + classname = spatial.classname()
  411 +
  412 + # Handle radial sources
  413 + if "Radial" in classname:
  414 +
  415 + # Retrieve short name of model class (e.g. "Gauss" or "Disk)
  416 + shorttype = classname.split("Radial")[-1]
  417 +
  418 + # Handle Disk and Shell model
  419 + if classname == "GModelSpatialRadialDisk" or classname == "GModelSpatialRadialShell":
  420 + size = spatial.radius()
  421 +
  422 + # Handle Gauss Model
  423 + elif classname == "GModelSpatialRadialGauss":
  424 + size = spatial.sigma()
  425 +
  426 + # Skip if source is unknown
  427 + else:
  428 + self.log("Skipping source "+model.name()+": Spatial model \""+classname+"\" unkown\n")
  429 + is_valid = False
  430 +
  431 + # Append radial ds9 string
  432 + if is_valid:
  433 + ds9string += "circle("
  434 + ds9string += str(modelpos.ra_deg())
  435 + ds9string += ","
  436 + ds9string += str(modelpos.dec_deg())
  437 + ds9string += ","
  438 + ds9string += str(size*3600.)+"\") #"
  439 +
  440 + # Handle elliptical sources
  441 + elif "Elliptical" in classname:
  442 +
  443 + # Retrieve short name and source size
  444 + shorttype = classname.split("Elliptical")[-1]
  445 + size1 = spatial.semimajor()
  446 + size2 = spatial.semiminor()
  447 + angle = spatial.posangle()
  448 +
  449 + # Append elliptical ds9 string
  450 + ds9string += "ellipse("
  451 + ds9string += str(modelpos.ra_deg())
  452 + ds9string += ","
  453 + ds9string += str(modelpos.dec_deg())
  454 + ds9string += ","
  455 + ds9string += str(size1*3600.)+"\""
  456 + ds9string += ","
  457 + ds9string += str(size2*3600.)+"\""
  458 + ds9string += ","
  459 + ds9string += str(angle+90.0)+") # "
  460 +
  461 + # Skip if source is neither radial nor elliptical
  462 + else:
  463 + self.log("Skipping source "+model.name()+": Spatial model neither \"Radial\" nor \"Elliptical\"\n")
  464 +
  465 + # Add short name to modelname
  466 + if self.show_ext_type:
  467 + modelname +=" ("+shorttype+")"
  468 +
  469 + # Add user defined attributes
  470 + ds9string += "color="+color+" "
  471 + ds9string += "width="+str(self.width)+" "
  472 + ds9string += "font=\""+self.font+" "+str(self.fontsize)+" "+self.fonttype+" "+self.fonttype2+"\" "
  473 + if self.show_labels:
  474 + ds9string += "text={"+modelname+"}"
  475 +
  476 + # Return string
  477 + return ds9string
  478 +
  479 + def execute(self):
  480 + """
  481 + Execute the script.
  482 + """
  483 + # Run the script
  484 + self.run()
  485 +
  486 + # Save ds9 file if required
  487 + self.save()
  488 +
  489 + # Return
  490 + return
  491 +
  492 +
  493 +# ======================== #
  494 +# Main routine entry point #
  495 +# ======================== #
  496 +if __name__ == '__main__':
  497 + """
  498 + Generates model information output.
  499 + """
  500 + # Create instance of application
  501 + app = csmodelinfo(sys.argv)
  502 +
  503 + # Open logfile
  504 + app.logFileOpen()
  505 +
  506 + # Execute application
  507 + app.execute()
... ...
cscripts/csmodelmerge.py 0 → 100755
  View file @14f9d87
  1 +#!/usr/bin/env python
  2 +# ==========================================================================
  3 +# Merges model XML files into one file
  4 +#
  5 +# Copyright (C) 2015 Michael Mayer
  6 +#
  7 +# This program is free software: you can redistribute it and/or modify
  8 +# it under the terms of the GNU General Public License as published by
  9 +# the Free Software Foundation, either version 3 of the License, or
  10 +# (at your option) any later version.
  11 +#
  12 +# This program is distributed in the hope that it will be useful,
  13 +# but WITHOUT ANY WARRANTY; without even the implied warranty of
  14 +# MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
  15 +# GNU General Public License for more details.
  16 +#
  17 +# You should have received a copy of the GNU General Public License
  18 +# along with this program. If not, see <http://www.gnu.org/licenses/>.
  19 +#
  20 +# ==========================================================================
  21 +import gammalib
  22 +import ctools
  23 +import sys
  24 +import glob
  25 +
  26 +
  27 +# ================== #
  28 +# csmodelmerge class #
  29 +# ================== #
  30 +class csmodelmerge(ctools.cscript):
  31 + """
  32 + This class merges an arbitray number of model container into one output
  33 + model XML file.
  34 + """
  35 + def __init__(self, *argv):
  36 + """
  37 + Constructor.
  38 + """
  39 + # Set name
  40 + self.name = "csmodelmerge"
  41 + self.version = "1.1.0"
  42 +
  43 + # Make sure that parfile exists
  44 + file = self.parfile()
  45 +
  46 + # Initialise application
  47 + if len(argv) == 0:
  48 + ctools.cscript.__init__(self, self.name, self.version)
  49 + elif len(argv) == 1:
  50 + ctools.cscript.__init__(self, self.name, self.version, *argv)
  51 + else:
  52 + raise TypeError("Invalid number of arguments given.")
  53 +
  54 + # Set logger properties
  55 + self.log_header()
  56 + self.log.date(True)
  57 +
  58 + # Return
  59 + return
  60 +
  61 + def __del__(self):
  62 + """
  63 + Destructor.
  64 + """
  65 + # Return
  66 + return
  67 +
  68 + def parfile(self):
  69 + """
  70 + Check if parfile exists. If parfile does not exist then create a
  71 + default parfile. This kluge avoids shipping the cscript with a
  72 + parfile.
  73 + """
  74 +
  75 + # Set parfile name
  76 + parfile = self.name+".par"
  77 +
  78 + try:
  79 + pars = gammalib.GApplicationPars(parfile)
  80 + except:
  81 + # Signal that parfile was not found
  82 + print("Parfile \""+parfile+"\" not found. Create default parfile.")
  83 +
  84 + # Create default parfile
  85 + pars = gammalib.GApplicationPars()
  86 + pars.append(gammalib.GApplicationPar("inmodels","s","a","model.xml","","","Input model XML files"))
  87 + pars.append(gammalib.GApplicationPar("outmodel","f","a","NONE","","","Output model file"))
  88 + pars.append_standard()
  89 + pars.append(gammalib.GApplicationPar("logfile","f","h","csmodelmerge.log","","","Log filename"))
  90 + pars.save(parfile)
  91 +
  92 + # Return
  93 + return
  94 +
  95 + def get_parameters(self):
  96 + """
  97 + Get parameters from parfile and setup the observation.
  98 + """
  99 + # Get input models
  100 + self.inmodels = self["inmodels"].string()
  101 +
  102 + # Interpet inmodels string
  103 + # Handle ascii files
  104 + if "@" == self.inmodels[0]:
  105 + self.files = open(self.inmodels.replace("@","")).read().splitlines()
  106 +
  107 + # Handle wild card strings
  108 + elif "*" in self.inmodels:
  109 + self.files = glob.glob(self.inmodels)
  110 +
  111 + # Handle space-separated list
  112 + elif " " in self.inmodels:
  113 + self.files = self.inmodels.split(" ")
  114 +
  115 + # Handle comma-separated list
  116 + elif "," in self.inmodels:
  117 + self.files = self.inmodels.split(",")
  118 +
  119 + # Throw exception if input models cannot be decoded
  120 + else:
  121 + msg = "Parameter \"inmodels\" must contain either an @ASCII"+\
  122 + " file, a comma-separated or whitespace-separated list"+\
  123 + " of files or a wildcard string"
  124 + raise RuntimeError(msg)
  125 +
  126 + # Get output file
  127 + self.outmodel = self["outmodel"].filename()
  128 +
  129 + # Return
  130 + return
  131 +
  132 + def run(self):
  133 + """
  134 + Run the script.
  135 + """
  136 + # Switch screen logging on in debug mode
  137 + if self.logDebug():
  138 + self.log.cout(True)
  139 +
  140 + # Get parameters
  141 + self.get_parameters()
  142 +
  143 + # Write input parameters into logger
  144 + if self.logTerse():
  145 + self.log_parameters()
  146 + self.log("\n")
  147 +
  148 + # Dump header
  149 + if self.logTerse():
  150 + self.log("\n")
  151 + self.log.header1("Merging Models")
  152 + self.log("\n")
  153 +
  154 + # Initialise output model container
  155 + self.models = gammalib.GModels()
  156 +
  157 + # Loop over model files
  158 + for modelfile in self.files:
  159 +
  160 + # Logging
  161 + self.log("Adding "+modelfile)
  162 + self.log("\n")
  163 +
  164 + # Open models
  165 + model_add = gammalib.GModels(modelfile)
  166 +
  167 + # Append models to container
  168 + for model in model_add:
  169 + self.models.append(model)
  170 +
  171 + # Return
  172 + return
  173 +
  174 + def save(self):
  175 + """
  176 + Save pointings to ds9 region file if required
  177 + """
  178 + # Logging
  179 + if self.logExplicit():
  180 + self.log("\n")
  181 + self.log.header1("Saving model file")
  182 + self.log("\n")
  183 +
  184 + # Save models
  185 + self.models.save(self.outmodel)
  186 +
  187 + # Return
  188 + return
  189 +
  190 + def execute(self):
  191 + """
  192 + Execute the script.
  193 + """
  194 + # Run the script
  195 + self.run()
  196 +
  197 + # Save ds9 file if required
  198 + self.save()
  199 +
  200 + # Return
  201 + return
  202 +
  203 +
  204 +# ======================== #
  205 +# Main routine entry point #
  206 +# ======================== #
  207 +if __name__ == '__main__':
  208 + """
  209 + Merges model XML files
  210 + """
  211 + # Create instance of application
  212 + app = csmodelmerge(sys.argv)
  213 +
  214 + # Open logfile
  215 + app.logFileOpen()
  216 +
  217 + # Execute application
  218 + app.execute()
... ...
cscripts/csobs2caldb.py 0 → 100755
  View file @14f9d87
  1 +#!/usr/bin/env python
  2 +# ==========================================================================
  3 +# Generation of an caldb entry from general IACT observation.
  4 +#
  5 +# Copyright (C) 2015 Michael Mayer
  6 +#
  7 +# This program is free software: you can redistribute it and/or modify
  8 +# it under the terms of the GNU General Public License as published by
  9 +# the Free Software Foundation, either version 3 of the License, or
  10 +# (at your option) any later version.
  11 +#
  12 +# This program is distributed in the hope that it will be useful,
  13 +# but WITHOUT ANY WARRANTY; without even the implied warranty of
  14 +# MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
  15 +# GNU General Public License for more details.
  16 +#
  17 +# You should have received a copy of the GNU General Public License
  18 +# along with this program. If not, see <http://www.gnu.org/licenses/>.
  19 +#
  20 +# ==========================================================================
  21 +import gammalib
  22 +import ctools
  23 +import sys
  24 +import os
  25 +import datetime
  26 +
  27 +
  28 +# ================= #
  29 +# csobs2caldb class #
  30 +# ================= #
  31 +class csobs2caldb(ctools.cscript):
  32 + """
  33 + This class implements the creation of a caldb entry for a particular
  34 + observation, which might be helpful for running simulations for current
  35 + IACTs. It takes an observation definition file as input and uses the
  36 + first observation to create a caldb entry which can be used for
  37 + simulations and sensitivity studies later on.
  38 + """
  39 + def __init__(self, *argv):
  40 + """
  41 + Constructor.
  42 + """
  43 + # Set name
  44 + self.name = "csobs2caldb"
  45 + self.version = "1.1.0"
  46 +
  47 + # Make sure that parfile exists
  48 + file = self.parfile()
  49 +
  50 + # Initialise application
  51 + if len(argv) == 0:
  52 + ctools.cscript.__init__(self, self.name, self.version)
  53 + elif len(argv) == 1:
  54 + ctools.cscript.__init__(self, self.name, self.version, *argv)
  55 + else:
  56 + raise TypeError("Invalid number of arguments given.")
  57 +
  58 + # Set logger properties
  59 + self.log_header()
  60 + self.log.date(True)
  61 +
  62 + # Return
  63 + return
  64 +
  65 + def __del__(self):
  66 + """
  67 + Destructor.
  68 + """
  69 + # Return
  70 + return
  71 +
  72 + def parfile(self):
  73 + """
  74 + Check if parfile exists. If parfile does not exist then create a
  75 + default parfile. This kluge avoids shipping the cscript with a
  76 + parfile.
  77 + """
  78 +
  79 + # Set parfile name
  80 + parfile = self.name+".par"
  81 +
  82 + try:
  83 + pars = gammalib.GApplicationPars(parfile)
  84 + except:
  85 + # Signal that parfile was not found
  86 + print("Parfile \""+parfile+"\" not found. Create default parfile.")
  87 +
  88 + # Create default parfile
  89 + pars = gammalib.GApplicationPars()
  90 + pars.append(gammalib.GApplicationPar("inobs","f","a","obs.xml","","","Input observation definition file"))
  91 + pars.append(gammalib.GApplicationPar("rspname","s","a","NONE","","","Response output name (e.g. Zenith50)"))
  92 + pars.append(gammalib.GApplicationPar("outirfs","f","h","irf_file.fits","","","Output IRF file name"))
  93 + pars.append(gammalib.GApplicationPar("index","i","h","0","","","Index of observation to be used from XML file"))
  94 + pars.append_standard()
  95 + pars.append(gammalib.GApplicationPar("logfile","f","h","csobs2caldb.log","","","Log filename"))
  96 + pars.save(parfile)
  97 +
  98 + # Return
  99 + return
  100 +
  101 + def get_parameters(self):
  102 + """
  103 + Get parameters from parfile and setup the observation.
  104 + """
  105 + # Get parameters
  106 + self.inobs = self["inobs"].filename()
  107 + self.obs = gammalib.GObservations(self.inobs)
  108 +
  109 + # Get index of observation to be used (0=default)
  110 + inx = self["index"].integer()
  111 +
  112 + # Get observation
  113 + self.observation = self.obs[inx]
  114 +
  115 + # Set instrument mission to cta
  116 + # This is to be compliant with standard gammalib caldb
  117 + self.m_mission = "CTA"
  118 +
  119 + # Get instrument name
  120 + self.m_instrument = self.observation.instrument()
  121 +
  122 + # Get config and file name
  123 + self.m_rspname = self["rspname"].string()
  124 + self.m_outfile = self["outirfs"].filename()
  125 +
  126 + # Make sure we have a cta observation
  127 + if not self.observation.classname() == "GCTAObservation":
  128 + raise gammalib.Exception.runtime_error("Input observation not of type \"GCTAObservation\"")
  129 +
  130 + # Make sure we have an irf response
  131 + if not self.observation.response().classname() == "GCTAResponseIrf":
  132 + raise gammalib.Exception.runtime_error("Response of input observation not of type \"GCTAResponseIrf\"")
  133 +
  134 + # Get other parameters
  135 + self.m_clobber = self["clobber"].boolean()
  136 +
  137 + # Return
  138 + return
  139 +
  140 + def make_irf_file(self):
  141 +
  142 + # retrieve response component
  143 + rsp = self.observation.response()
  144 +
  145 + # Initialise FITS file
  146 + fits = gammalib.GFits()
  147 +
  148 + # Create GFilename instances
  149 + fname_aeff = gammalib.GFilename(rsp.aeff().filename())
  150 + fname_psf = gammalib.GFilename(rsp.psf().filename())
  151 + fname_edisp = gammalib.GFilename(rsp.edisp().filename())
  152 + fname_bkg = gammalib.GFilename(rsp.background().filename())
  153 +
  154 + # Open FITS files of response components
  155 + fits_aeff = gammalib.GFits(fname_aeff.filename())
  156 + fits_psf = gammalib.GFits(fname_psf.filename())
  157 + fits_edisp = gammalib.GFits(fname_edisp.filename())
  158 + fits_bkg = gammalib.GFits(fname_bkg.filename())
  159 +
  160 + # Bundle IRFs into one file
  161 + fits.append(fits_aeff[fname_aeff.extname("EFFECTIVE AREA")])
  162 + fits.append(fits_psf[fname_psf.extname("POINT SPREAD FUNCTION")])
  163 + fits.append(fits_edisp[fname_edisp.extname("ENERGY DISPERSION")])
  164 + fits.append(fits_bkg[fname_bkg.extname("BACKGROUND")])
  165 +
  166 + # Return fits file
  167 + return fits
  168 +
  169 + def make_caldb_index(self):
  170 +
  171 + # Open calibration database index
  172 + indx_file = self.base_dir+"/caldb.indx"
  173 +
  174 + # Check if indx file exists (create if not existent)
  175 + if os.path.isfile(indx_file):
  176 + cif = gammalib.GFits(indx_file)
  177 + else:
  178 + cif = gammalib.GFits(indx_file, True)
  179 +
  180 + # Retrieve "CIF" table
  181 + if cif.contains("CIF"):
  182 + table = cif.table("CIF")
  183 + else:
  184 + # Create binary table if not available
  185 + bintable = gammalib.GFitsBinTable()
  186 + bintable.extname("CIF")
  187 + bintable.card("CIFVERSN", "1992a", "Version of CIF format")
  188 + cif.append(bintable)
  189 +
  190 + table = cif.table("CIF")
  191 +
  192 + # Copied from cta_root2caldb.py
  193 + # Attach columns. Reference: CAL/GEN/92-008
  194 + table.append(gammalib.GFitsTableStringCol("TELESCOP", 0, 10))
  195 + table.append(gammalib.GFitsTableStringCol("INSTRUME", 0, 10))
  196 + table.append(gammalib.GFitsTableStringCol("DETNAM", 0, 20))
  197 + table.append(gammalib.GFitsTableStringCol("FILTER", 0, 10))
  198 + table.append(gammalib.GFitsTableStringCol("CAL_DEV", 0, 20))
  199 + table.append(gammalib.GFitsTableStringCol("CAL_DIR", 0, 70))
  200 + table.append(gammalib.GFitsTableStringCol("CAL_FILE", 0, 40))
  201 + table.append(gammalib.GFitsTableStringCol("CAL_CLAS", 0, 3))
  202 + table.append(gammalib.GFitsTableStringCol("CAL_DTYP", 0, 4))
  203 + table.append(gammalib.GFitsTableStringCol("CAL_CNAM", 0, 20))
  204 + table.append(gammalib.GFitsTableStringCol("CAL_CBD", 0, 70, 9))
  205 + table.append(gammalib.GFitsTableShortCol("CAL_XNO", 0))
  206 + table.append(gammalib.GFitsTableStringCol("CAL_VSD", 0, 10))
  207 + table.append(gammalib.GFitsTableStringCol("CAL_VST", 0, 8))
  208 + table.append(gammalib.GFitsTableDoubleCol("REF_TIME", 0))
  209 + table.append(gammalib.GFitsTableShortCol("CAL_QUAL", 0))
  210 + table.append(gammalib.GFitsTableStringCol("CAL_DATE", 0, 8))
  211 + table.append(gammalib.GFitsTableStringCol("CAL_DESC", 0, 70))
  212 +
  213 + # Check if output config already exist
  214 + has_config = False
  215 + row_index = -1
  216 + for caldir in table["CAL_DIR"]:
  217 + row_index += 1
  218 + if caldir == self.cal_dir:
  219 + has_config = True
  220 + break
  221 +
  222 + # Create columns if not available
  223 + if not has_config:
  224 + # Append 4 rows to CIF extension
  225 + table.append_rows(4)
  226 + row_index = table.nrows()
  227 + else:
  228 + row_index += 4
  229 +
  230 + # Add generic information for these 4 rows
  231 + for i in range(4):
  232 +
  233 + # Set row number
  234 + row = i + row_index-4
  235 +
  236 + # Set date
  237 + now = str(datetime.datetime.now())
  238 + today, time = now.split()
  239 +
  240 + # Set element
  241 + table["TELESCOP"][row] = self.m_mission
  242 + table["INSTRUME"][row] = self.m_instrument
  243 + table["DETNAM"][row] = "NONE"
  244 + table["FILTER"][row] = "NONE"
  245 + table["CAL_DEV"][row] = "ONLINE"
  246 + table["CAL_CLAS"][row] = "BCF"
  247 + table["CAL_DTYP"][row] = "DATA"
  248 + table["CAL_VSD"][row] = today
  249 + table["CAL_VST"][row] = time.split(".")[0]
  250 + table["REF_TIME"][row] = 51544.0
  251 + table["CAL_QUAL"][row] = 0
  252 + table["CAL_CBD"][row] = "NAME("+self.m_rspname+")"
  253 + table["CAL_DATE"][row] = today.replace("-","/")[2:]
  254 + table["CAL_DIR"][row] = self.cal_dir
  255 + table["CAL_FILE"][row] = self.m_outfile
  256 +
  257 + # Add effective area information
  258 + row = row_index-4
  259 + table["CAL_CNAM"][row] = "EFF_AREA"
  260 + table["CAL_DESC"][row] = self.m_instrument+" effective area"
  261 +
  262 + # Add point spread function information
  263 + row = row_index-3
  264 + table["CAL_CNAM"][row] = "RPSF"
  265 + table["CAL_DESC"][row] = self.m_instrument+" point spread function"
  266 +
  267 + # Add energy dispersion information
  268 + row = row_index-2
  269 + table["CAL_CNAM"][row] = "EDISP"
  270 + table["CAL_DESC"][row] = self.m_instrument+" energy dispersion"
  271 +
  272 + # Add background information
  273 + row = row_index-1
  274 + table["CAL_CNAM"][row] = "BGD"
  275 + table["CAL_DESC"][row] = self.m_instrument+" background"
  276 +
  277 + # Return CIF FITS file
  278 + return cif
  279 +
  280 + def make_dirs(self):
  281 +
  282 + # Create gammalib Caldb
  283 + caldb = gammalib.GCaldb()
  284 +
  285 + # Set calibration directory
  286 + self.cal_dir = "data"
  287 + self.cal_dir += "/"+self.m_mission.lower()
  288 + self.cal_dir += "/"+self.m_instrument.lower()
  289 + self.cal_dir += "/bcf/"+self.m_rspname
  290 +
  291 + # Set absolute path
  292 + self.base_dir = caldb.rootdir() +"/data"
  293 + self.base_dir += "/"+self.m_mission.lower()
  294 + self.base_dir += "/"+self.m_instrument.lower()
  295 +
  296 + # Set directory for irf file
  297 + self.rsp_dir = caldb.rootdir() + "/" + self.cal_dir
  298 +
  299 + # Create directories and log information
  300 + if not os.path.isdir(self.rsp_dir):
  301 + if self.logExplicit():
  302 + self.log(gammalib.parformat("Directory"))
  303 + self.log(self.rsp_dir)
  304 + self.log("\n")
  305 + os.makedirs(self.rsp_dir)
  306 + else:
  307 + if self.logExplicit():
  308 + self.log(gammalib.parformat("Directory (existing)"))
  309 + self.log(self.rsp_dir)
  310 + self.log("\n")
  311 +
  312 + # Return
  313 + return
  314 +
  315 + def run(self):
  316 + """
  317 + Run the script.
  318 + """
  319 + # Switch screen logging on in debug mode
  320 + if self.logDebug():
  321 + self.log.cout(True)
  322 +
  323 + # Get parameters
  324 + self.get_parameters()
  325 +
  326 + # Write input parameters into logger
  327 + if self.logTerse():
  328 + self.log_parameters()
  329 + self.log("\n\n")
  330 + self.log.header1("Creating directory structure")
  331 +
  332 + # Create directory structure
  333 + self.make_dirs()
  334 +
  335 + # Logging
  336 + if self.logTerse():
  337 + self.log("\n")
  338 + self.log.header1("Updating calibration database")
  339 +
  340 + # Create/update calibration database
  341 + self.caldb_inx = self.make_caldb_index()
  342 +
  343 + # Logging
  344 + if self.logTerse():
  345 + self.log("\n")
  346 + self.log.header1("Creating response file")
  347 +
  348 + # Create IRF file
  349 + self.irf_fits = self.make_irf_file()
  350 +
  351 + # Return
  352 + return
  353 +
  354 + def save(self):
  355 +
  356 + # Save caldb index file
  357 + self.caldb_inx.save(self.m_clobber)
  358 +
  359 + # Save response file
  360 + self.irf_fits.saveto(self.rsp_dir + "/" + self.m_outfile, self.m_clobber)
  361 +
  362 + # Return
  363 + return
  364 +
  365 + def execute(self):
  366 + """
  367 + Execute the script.
  368 + """
  369 + # Run the script
  370 + self.run()
  371 +
  372 + # Save to disk
  373 + self.save()
  374 +
  375 + # Return
  376 + return
  377 +
  378 +
  379 +# ======================== #
  380 +# Main routine entry point #
  381 +# ======================== #
  382 +if __name__ == '__main__':
  383 + """
  384 + Generates caldb entry.
  385 + """
  386 + # Create instance of application
  387 + app = csobs2caldb(sys.argv)
  388 +
  389 + # Open logfile
  390 + app.logFileOpen()
  391 +
  392 + # Execute application
  393 + app.execute()
... ...
cscripts/csobsdef.py
  View file @14f9d87
... ... @@ -29,7 +29,7 @@ import sys
29 29 class csobsdef(ctools.cscript):
30 30 """
31 31 The csobsdef class generates an observation definition file from a
32   - pointing list. The pointing list is a colon separated value ASCII
  32 + pointing list. The pointing list is a comma-separated value ASCII
33 33 file with header keywords in the first row followed by a list of
34 34 pointings (one pointing per row). The following header keywords
35 35 are supported (case sensitive, column order irrelevant):
... ... @@ -51,7 +51,7 @@ class csobsdef(ctools.cscript):
51 51 Only the pairs (ra,dec) or (lon,lat) are mandatory header keywords.
52 52 All other keywords are optional and can be specified when calling
53 53 csobsdef as user parameters. The only exception is the "duration"
54   - keyword that will automatically queried.
  54 + keyword that will automatically be queried.
55 55  
56 56 Here some usage examples:
57 57  
... ... @@ -128,8 +128,8 @@ class csobsdef(ctools.cscript):
128 128  
129 129 # Create default parfile
130 130 pars = gammalib.GApplicationPars()
131   - pars.append(gammalib.GApplicationPar("inpnt","f","a","NONE","","","Pointing definition file"))
132   - pars.append(gammalib.GApplicationPar("outobs","f","a","obs.xml","","","Output observation definition file"))
  131 + pars.append(gammalib.GApplicationPar("inpnt","f","a","NONE","","","Input pointing definition file"))
  132 + pars.append(gammalib.GApplicationPar("outobs","f","a","obs.xml","","","Output observation definition XML file"))
133 133 pars.append(gammalib.GApplicationPar("duration","r","a","1800.0","","","Pointing duration (seconds)"))
134 134 pars.append(gammalib.GApplicationPar("caldb","s","h","","","","Calibration database"))
135 135 pars.append(gammalib.GApplicationPar("irf","s","h","","","","Instrument response function"))
... ... @@ -249,8 +249,7 @@ class csobsdef(ctools.cscript):
249 249 pntdir = gammalib.GSkyDir()
250 250 pntdir.lb_deg(lon,lat)
251 251 else:
252   - raise gammalib.GException.invalid_value(self.name,
253   - "No (ra,dec) or (lon,lat) columns found in pointing"
  252 + raise RuntimeError("No (ra,dec) or (lon,lat) columns found in pointing"
254 253 " definition file.")
255 254 obs.pointing(gammalib.GCTAPointing(pntdir))
256 255  
... ...
cscripts/csobsinfo.py 0 → 100755
  View file @14f9d87
  1 +#!/usr/bin/env python
  2 +# ==========================================================================
  3 +# Dump information about observation into log file
  4 +#
  5 +# Copyright (C) 2015 Michael Mayer
  6 +#
  7 +# This program is free software: you can redistribute it and/or modify
  8 +# it under the terms of the GNU General Public License as published by
  9 +# the Free Software Foundation, either version 3 of the License, or
  10 +# (at your option) any later version.
  11 +#
  12 +# This program is distributed in the hope that it will be useful,
  13 +# but WITHOUT ANY WARRANTY; without even the implied warranty of
  14 +# MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
  15 +# GNU General Public License for more details.
  16 +#
  17 +# You should have received a copy of the GNU General Public License
  18 +# along with this program. If not, see <http://www.gnu.org/licenses/>.
  19 +#
  20 +# ==========================================================================
  21 +import gammalib
  22 +import ctools
  23 +import sys
  24 +
  25 +
  26 +# =============== #
  27 +# csobsinfo class #
  28 +# =============== #
  29 +class csobsinfo(ctools.cscript):
  30 + """
  31 + This class dumps information about an observation container into a
  32 + logfile or on screen. This might be helpful for quick access to an
  33 + observation container showing, e.g., total lifetime, energy range etc.
  34 + """
  35 + def __init__(self, *argv):
  36 + """
  37 + Constructor.
  38 + """
  39 + # Set name
  40 + self.name = "csobsinfo"
  41 + self.version = "1.1.0"
  42 +
  43 + # Make sure that parfile exists
  44 + file = self.parfile()
  45 +
  46 + # Initialise application
  47 + if len(argv) == 0:
  48 + ctools.cscript.__init__(self, self.name, self.version)
  49 + elif len(argv) == 1:
  50 + ctools.cscript.__init__(self, self.name, self.version, *argv)
  51 + else:
  52 + raise TypeError("Invalid number of arguments given.")
  53 +
  54 + # Set logger properties
  55 + self.log_header()
  56 + self.log.date(True)
  57 +
  58 + # Return
  59 + return
  60 +
  61 + def __del__(self):
  62 + """
  63 + Destructor.
  64 + """
  65 + # Return
  66 + return
  67 +
  68 + def parfile(self):
  69 + """
  70 + Check if parfile exists. If parfile does not exist then create a
  71 + default parfile. This kluge avoids shipping the cscript with a
  72 + parfile.
  73 + """
  74 +
  75 + # Set parfile name
  76 + parfile = self.name+".par"
  77 +
  78 + try:
  79 + pars = gammalib.GApplicationPars(parfile)
  80 + except:
  81 + # Signal that parfile was not found
  82 + print("Parfile \""+parfile+"\" not found. Create default parfile.")
  83 +
  84 + # Create default parfile
  85 + pars = gammalib.GApplicationPars()
  86 + pars.append(gammalib.GApplicationPar("inobs","f","a","obs.xml","","","Event list, counts cube, or observation definition file"))
  87 + pars.append(gammalib.GApplicationPar("offset","b","h","no","","","Compute offset from target to pointing positions"))
  88 + pars.append(gammalib.GApplicationPar("ra","r","a","0.0","","","Target Right Ascension"))
  89 + pars.append(gammalib.GApplicationPar("dec","r","a","0.0","","","Target Declination"))
  90 + pars.append(gammalib.GApplicationPar("ds9file","f","h","NONE","","","DS9 region file containing pointings"))
  91 + pars.append_standard()
  92 + pars.append(gammalib.GApplicationPar("logfile","f","h","csobsinfo.log","","","Log filename"))
  93 + pars.save(parfile)
  94 +
  95 + # Return
  96 + return
  97 +
  98 + def get_parameters(self):
  99 + """
  100 + Get parameters from parfile and setup the observation.
  101 + """
  102 + # Get parameters
  103 + self.require_inobs("csobsinfo::get_parameters")
  104 + self.obs = self.get_observations(False)
  105 +
  106 + # Initialise object position
  107 + self.obj_dir = gammalib.GSkyDir()
  108 +
  109 + # Get (optional) offset parameters
  110 + self.m_offset = self["offset"].boolean()
  111 + if self.m_offset:
  112 + ra = self["ra"].real()
  113 + dec = self["dec"].real()
  114 + self.obj_dir.radec_deg(ra,dec)
  115 +
  116 + # Get (optional) DS9 filename
  117 + self.ds9file = self["ds9file"].filename()
  118 +
  119 + # Return
  120 + return
  121 +
  122 + def run(self):
  123 + """
  124 + Run the script.
  125 + """
  126 + # Switch screen logging on in debug mode
  127 + if self.logDebug():
  128 + self.log.cout(True)
  129 +
  130 + # Get parameters
  131 + self.get_parameters()
  132 +
  133 + # Write input parameters into logger
  134 + if self.logTerse():
  135 + self.log_parameters()
  136 + self.log("\n")
  137 +
  138 + # Initialise arrays to store certain values for reuse
  139 + # Todo, think about using a python dictionary
  140 + self.offsets = []
  141 + self.zeniths = []
  142 + self.azimuths = []
  143 + self.pnt_ra = []
  144 + self.pnt_dec = []
  145 + obs_names = []
  146 +
  147 + # Initialise output to be filled
  148 + self.ebounds = gammalib.GEbounds()
  149 + self.gti = gammalib.GGti()
  150 + ontime = 0.0
  151 + livetime = 0.0
  152 + n_events = 0
  153 + n_eventbins = 0
  154 + n_obs_binned = 0
  155 + n_obs_unbinned = 0
  156 +
  157 + # Logging
  158 + self.log.header1("Looping over observations")
  159 +
  160 + # Loop over observations
  161 + for obs in self.obs:
  162 +
  163 +
  164 + # Skip non-CTA observations
  165 + if not obs.classname() == "GCTAObservation":
  166 + self.log("Skipping "+obs.instrument()+" observation\n")
  167 + continue
  168 +
  169 + # Use observed object as observation name
  170 + # if name is not given
  171 + obs_name = obs.name()
  172 + if obs_name == "":
  173 + obs_name = obs.object()
  174 +
  175 + # Logging
  176 + if self.logTerse():
  177 + self.log.header2(obs_name)
  178 +
  179 + # Retrieve observation name
  180 + obs_names.append(obs_name)
  181 +
  182 + # Retrieve energy boundaries
  183 + obs_bounds = obs.events().ebounds()
  184 +
  185 + # Retrieve time interval
  186 + obs_gti = obs.events().gti()
  187 +
  188 + # Compute mean time and dead time fraction in percent
  189 + tmean = (obs_gti.tstart() + obs_gti.tstop())
  190 + tmean *= 0.5
  191 + deadfrac = (1.0-obs.deadc(tmean))*100.0
  192 +
  193 + # Retrieve pointing and store Ra,Dec
  194 + pnt_dir = obs.pointing().dir()
  195 + self.pnt_ra.append(pnt_dir.ra_deg())
  196 + self.pnt_dec.append(pnt_dir.dec_deg())
  197 +
  198 + # If avaliable append energy boundaries
  199 + if obs_bounds.size() > 0 :
  200 + self.ebounds.merge(obs_bounds.emin(),obs_bounds.emax())
  201 +
  202 + # Append time interval
  203 + self.gti.merge(obs_gti.tstart(), obs_gti.tstop())
  204 +
  205 + # increment global livetime and ontime
  206 + ontime += obs.ontime()
  207 + livetime += obs.livetime()
  208 +
  209 + # Log the event type (binned or unbinned)
  210 + if self.logTerse():
  211 + self.log.parformat("binned")
  212 +
  213 + if obs.eventtype() == "CountsCube":
  214 + n_eventbins += obs.events().size()
  215 + n_obs_binned += 1
  216 + if self.logTerse():
  217 + self.log("yes")
  218 + self.log("\n")
  219 + self.log.parformat("Number of bins")
  220 + self.log(str(obs.events().size()))
  221 + self.log("\n")
  222 + else:
  223 + n_events += obs.events().size()
  224 + n_obs_unbinned += 1
  225 + if self.logTerse():
  226 + self.log("no")
  227 + self.log("\n")
  228 + self.log.parformat("Number of events")
  229 + self.log(str(obs.events().size()))
  230 + self.log("\n")
  231 +
  232 + # Log option
  233 + if self.logTerse():
  234 +
  235 + # Log the observation energy range (if available)
  236 + self.log.parformat("Energy range")
  237 + if obs_bounds.size() == 0:
  238 + self.log("undefined")
  239 + else:
  240 + self.log(str(obs_bounds.emin())+" - "+str(obs_bounds.emax()))
  241 + self.log("\n")
  242 +
  243 + # Log observation time interval
  244 + self.log.parformat("Time range (MJD)")
  245 + if obs_gti.size() == 0:
  246 + self.log("undefined")
  247 + else:
  248 + self.log(str(obs_gti.tstart().mjd())+" - "+str(obs_gti.tstop().mjd()))
  249 + self.log("\n")
  250 +
  251 + # Log ontime
  252 + self.log.parformat("Ontime [s]")
  253 + self.log(str(obs.ontime()))
  254 + self.log("\n")
  255 +
  256 + # Log livetime
  257 + self.log.parformat("Livetime [s]")
  258 + self.log(str(obs.livetime()))
  259 + self.log("\n")
  260 +
  261 + # Log dead time fraction
  262 + self.log.parformat("Dead-time fraction (%)")
  263 + self.log("%.3f" % (deadfrac))
  264 + self.log("\n")
  265 +
  266 + # Log pointing direction
  267 + self.log.parformat("Pointing")
  268 + self.log(str(pnt_dir))
  269 + self.log("\n")
  270 +
  271 + # Log offset if possible
  272 + if self.m_offset:
  273 + offset = pnt_dir.dist_deg(self.obj_dir)
  274 + self.offsets.append(offset)
  275 + self.log.parformat("Offset")
  276 + self.log("%.2f" % (offset))
  277 + self.log("\n")
  278 + else:
  279 + self.offsets.append(-1.0)
  280 +
  281 + # Retrieve zenith and azimuth and store for later use
  282 + zenith = obs.pointing().zenith()
  283 + azimuth = obs.pointing().azimuth()
  284 + self.zeniths.append(zenith)
  285 + self.azimuths.append(azimuth)
  286 +
  287 + # Log Zenith and Azimuth if required
  288 + if self.logExplicit():
  289 + self.log.parformat("Zenith angle")
  290 + self.log("%.2f" % (zenith))
  291 + self.log("\n")
  292 + self.log.parformat("Azimuth angle")
  293 + self.log("%.2f" % (azimuth))
  294 + self.log("\n\n")
  295 +
  296 + # Log summary
  297 + self.log("\n")
  298 + self.log.header1("Summary")
  299 +
  300 + # Log general summary
  301 + self.log.parformat("Unbinned observations")
  302 + self.log(str(n_obs_unbinned))
  303 + self.log("\n")
  304 + self.log.parformat("Number of events")
  305 + self.log(str(n_events))
  306 + self.log("\n")
  307 + self.log.parformat("Binned observations")
  308 + self.log(str(n_obs_binned))
  309 + self.log("\n")
  310 + self.log.parformat("Number of bins")
  311 + self.log(str(n_eventbins))
  312 + self.log("\n\n")
  313 +
  314 + # Log pointing summary
  315 + self.log.header3("Pointings")
  316 +
  317 + # Log mean offset if possible
  318 + if self.m_offset:
  319 + self.log.parformat("Mean offset angle")
  320 + self.log("%.2f" % (sum(self.offsets)/len(self.offsets)))
  321 + self.log("\n")
  322 +
  323 + # Log mean azimuth and zenith angle
  324 + self.log.parformat("Mean zenith angle")
  325 + self.log("%.2f" % (sum(self.zeniths)/len(self.zeniths)))
  326 + self.log("\n")
  327 + self.log.parformat("Mean azimuth angle")
  328 + self.log("%.2f" % (sum(self.azimuths)/len(self.azimuths)))
  329 + self.log("\n")
  330 +
  331 + # Log name of observations if requested
  332 + if self.logExplicit():
  333 + obs_set = set(obs_names)
  334 + for name in obs_set:
  335 + self.log.parformat("\""+name+"\"")
  336 + self.log(str(obs_names.count(name)))
  337 + self.log("\n")
  338 + self.log("\n")
  339 +
  340 + # Log energy range
  341 + self.log.header3("Energy range")
  342 + self.log.parformat("Emin")
  343 + if self.ebounds.size() == 0:
  344 + self.log("undefined")
  345 + else:
  346 + self.log(str(self.ebounds.emin()))
  347 + self.log("\n")
  348 + self.log.parformat("Emax")
  349 + if self.ebounds.size() == 0:
  350 + self.log("undefined")
  351 + else:
  352 + self.log(str(self.ebounds.emax()))
  353 + self.log("\n\n")
  354 +
  355 + # Log time range
  356 + self.log.header3("Time range")
  357 + self.log.parformat("Start [MJD]")
  358 + self.log(str(self.gti.tstart().mjd()))
  359 + self.log("\n")
  360 + self.log.parformat("Stop [MJD]")
  361 + self.log(str(self.gti.tstop().mjd()))
  362 + self.log("\n")
  363 +
  364 + # Log ontime and livetime in different units
  365 + self.log.parformat("Total ontime")
  366 + self.log("%.2f s = %.2f min = %.2f h" % (ontime, ontime/60., ontime/3600.))
  367 + self.log("\n")
  368 + self.log.parformat("Total livetime")
  369 + self.log("%.2f s = %.2f min = %.2f h" % (livetime, livetime/60.0, livetime/3600.))
  370 + self.log("\n")
  371 +
  372 + # Return
  373 + return
  374 +
  375 + def save(self):
  376 + """
  377 + Save pointings to ds9 region file if required
  378 + """
  379 +
  380 + # Check if ds9 file is valid
  381 + if not self.ds9file == "NONE":
  382 +
  383 + # Open file
  384 + f = open(self.ds9file,"w")
  385 +
  386 + # Write coordinate system
  387 + f.write("fk5\n")
  388 +
  389 + # Loop over pointings
  390 + for i in range(len(self.pnt_ra)):
  391 +
  392 + # Create string
  393 + line = "point("
  394 + line+=str(self.pnt_ra[i])+","+str(self.pnt_dec[i])+")"
  395 + line+=" # point=cross 20 width=3 \n"
  396 +
  397 + # Write to file
  398 + f.write(line)
  399 +
  400 + # Close file
  401 + f.close()
  402 +
  403 + # Return
  404 + return
  405 +
  406 +
  407 + def zeniths(self):
  408 + """
  409 + Return zenith angles
  410 + """
  411 + return self.zeniths
  412 +
  413 + def azimuths(self):
  414 + """
  415 + Return azimuth angles
  416 + """
  417 + return self.azimuths
  418 +
  419 + def offsets(self):
  420 + """
  421 + Return offset angles
  422 + """
  423 + return self.offsets
  424 +
  425 + def ebounds(self):
  426 + """
  427 + Return energy boundaries
  428 + """
  429 + return self.ebounds
  430 +
  431 + def gti(self):
  432 + """
  433 + Return good time intervals
  434 + """
  435 + return self.gti
  436 +
  437 + def execute(self):
  438 + """
  439 + Execute the script.
  440 + """
  441 + # Run the script
  442 + self.run()
  443 +
  444 + # Save ds9 file if required
  445 + self.save()
  446 +
  447 + # Return
  448 + return
  449 +
  450 +
  451 +# ======================== #
  452 +# Main routine entry point #
  453 +# ======================== #
  454 +if __name__ == '__main__':
  455 + """
  456 + Generates information about an observation container.
  457 + """
  458 + # Create instance of application
  459 + app = csobsinfo(sys.argv)
  460 +
  461 + # Open logfile
  462 + app.logFileOpen()
  463 +
  464 + # Execute application
  465 + app.execute()
... ...
cscripts/cspull.py
  View file @14f9d87
... ... @@ -101,13 +101,13 @@ class cspull(ctools.cscript):
101 101  
102 102 # Create default parfile
103 103 pars = gammalib.GApplicationPars()
104   - pars.append(gammalib.GApplicationPar("inobs","f","h","NONE","","","Event list, counts cube, or observation definition file"))
105   - pars.append(gammalib.GApplicationPar("inmodel","f","a","$CTOOLS/share/models/crab.xml","","","Source model"))
106   - pars.append(gammalib.GApplicationPar("outfile","f","a","pull.dat","","","Output file name"))
  104 + pars.append(gammalib.GApplicationPar("inobs","f","h","NONE","","","Input event list, counts cube, or observation definition XML file"))
  105 + pars.append(gammalib.GApplicationPar("inmodel","f","a","$CTOOLS/share/models/crab.xml","","","Input model XML file"))
107 106 pars.append(gammalib.GApplicationPar("caldb","s","a","prod2","","","Calibration database"))
108   - pars.append(gammalib.GApplicationPar("irf","s","a","South_50h","","","Instrument response function"))
109   - pars.append(gammalib.GApplicationPar("deadc","r","h","0.95","0","1","Deadtime correction factor"))
  107 + pars.append(gammalib.GApplicationPar("irf","s","a","South_0.5h","","","Instrument response function"))
110 108 pars.append(gammalib.GApplicationPar("edisp","b","h","no","","","Apply energy dispersion?"))
  109 + pars.append(gammalib.GApplicationPar("deadc","r","h","0.95","0","1","Deadtime correction factor"))
  110 + pars.append(gammalib.GApplicationPar("outfile","f","a","pull.dat","","","Output pull distribution file"))
111 111 pars.append(gammalib.GApplicationPar("profile","b","h","no","","","Use likelihood profile method for errors?"))
112 112 pars.append(gammalib.GApplicationPar("ntrials","i","a","10","","","Number of trials"))
113 113 pars.append(gammalib.GApplicationPar("ra","r","a","83.6331","0","360","RA of pointing (deg)"))
... ...
cscripts/csresmap.py
  View file @14f9d87
... ... @@ -103,16 +103,16 @@ class csresmap(ctools.cscript):
103 103  
104 104 # Create default parfile
105 105 pars = gammalib.GApplicationPars()
106   - pars.append(gammalib.GApplicationPar("inobs","f","a","events.fits","","","Event list, counts cube, or observation definition file"))
107   - pars.append(gammalib.GApplicationPar("modcube","f","a","NONE","","","Model cube file (generated with ctmodel)"))
108   - pars.append(gammalib.GApplicationPar("expcube","f","a","NONE","","","Exposure cube file (only needed for stacked analysis)"))
109   - pars.append(gammalib.GApplicationPar("psfcube","f","a","NONE","","","PSF cube file (only needed for stacked analysis)"))
110   - pars.append(gammalib.GApplicationPar("bkgcube","f","a","NONE","","","Background cube file (only needed for stacked analysis)"))
111   - pars.append(gammalib.GApplicationPar("inmodel","f","a","$CTOOLS/share/models/crab.xml","","","Source model"))
112   - pars.append(gammalib.GApplicationPar("outmap","f","a","resmap.fits","","","Output residual map"))
113   - pars.append(gammalib.GApplicationPar("edisp","b","h","no","","","Apply energy dispersion?"))
  106 + pars.append(gammalib.GApplicationPar("inobs","f","a","events.fits","","","Input event list, counts cube, or observation definition XML file"))
  107 + pars.append(gammalib.GApplicationPar("modcube","f","a","NONE","","","Input model cube file (generated with ctmodel)"))
  108 + pars.append(gammalib.GApplicationPar("expcube","f","a","NONE","","","Input exposure cube file (only needed for stacked analysis)"))
  109 + pars.append(gammalib.GApplicationPar("psfcube","f","a","NONE","","","Input PSF cube file (only needed for stacked analysis)"))
  110 + pars.append(gammalib.GApplicationPar("bkgcube","f","a","NONE","","","Input background cube file (only needed for stacked analysis)"))
  111 + pars.append(gammalib.GApplicationPar("inmodel","f","a","$CTOOLS/share/models/crab.xml","","","Input model XML file"))
114 112 pars.append(gammalib.GApplicationPar("caldb","s","a","prod2","","","Calibration database"))
115   - pars.append(gammalib.GApplicationPar("irf","s","a","South_50h","","","Instrument response function"))
  113 + pars.append(gammalib.GApplicationPar("irf","s","a","South_0.5h","","","Instrument response function"))
  114 + pars.append(gammalib.GApplicationPar("edisp","b","h","no","","","Apply energy dispersion?"))
  115 + pars.append(gammalib.GApplicationPar("outmap","f","a","resmap.fits","","","Output residual map file"))
116 116 pars.append(gammalib.GApplicationPar("ebinalg","s","h","LOG","LIN|LOG|FILE","","Binning algorithm"))
117 117 pars.append(gammalib.GApplicationPar("emin","r","h","0.1","","","Lower energy limit (TeV)"))
118 118 pars.append(gammalib.GApplicationPar("emax","r","h","100.0","","","Upper energy limit (TeV)"))
... ...
cscripts/cssens.py
  View file @14f9d87
... ... @@ -97,14 +97,14 @@ class cssens(ctools.cscript):
97 97  
98 98 # Create default parfile
99 99 pars = gammalib.GApplicationPars()
100   - pars.append(gammalib.GApplicationPar("inobs","f","h","NONE","","","Event list, counts cube, or observation definition file"))
101   - pars.append(gammalib.GApplicationPar("inmodel","f","a","$CTOOLS/share/models/crab.xml","","","Source model"))
  100 + pars.append(gammalib.GApplicationPar("inobs","f","h","NONE","","","Input event list, counts cube, or observation definition XML file"))
  101 + pars.append(gammalib.GApplicationPar("inmodel","f","a","$CTOOLS/share/models/crab.xml","","","Input model XML file"))
102 102 pars.append(gammalib.GApplicationPar("srcname","s","a","Crab","","","Source name"))
103   - pars.append(gammalib.GApplicationPar("offset","r","h","0.0","","","Source offset angle (deg)"))
104 103 pars.append(gammalib.GApplicationPar("caldb","s","a","prod2","","","Calibration database"))
105   - pars.append(gammalib.GApplicationPar("irf","s","a","South_50h","","","Instrument response function"))
  104 + pars.append(gammalib.GApplicationPar("irf","s","a","South_0.5h","","","Instrument response function"))
106 105 pars.append(gammalib.GApplicationPar("deadc","r","h","0.95","0","1","Deadtime correction factor"))
107   - pars.append(gammalib.GApplicationPar("outfile","f","h","sensitivity.dat","","","Output file name"))
  106 + pars.append(gammalib.GApplicationPar("outfile","f","h","sensitivity.dat","","","Output sensitivity ASCII file"))
  107 + pars.append(gammalib.GApplicationPar("offset","r","h","0.0","","","Source offset angle (deg)"))
108 108 pars.append(gammalib.GApplicationPar("duration","r","a","180000.0","","","Effective exposure time (s)"))
109 109 pars.append(gammalib.GApplicationPar("rad","r","a","5.0","","","Radius of ROI (deg)"))
110 110 pars.append(gammalib.GApplicationPar("edisp","b","h","no","","","Apply energy dispersion?"))
... ... @@ -241,7 +241,7 @@ class cssens(ctools.cscript):
241 241 else:
242 242 msg = "Invalid sensitivity type \""+self.m_type+"\" encountered."+ \
243 243 " Either use \"Differential\" or \"Integral\"."
244   - raise gammalib.GException.invalid_value("cssens", msg)
  244 + raise RuntimeError(msg)
245 245  
246 246 # Determine sensitivity
247 247 result = self.get_sensitivity(self.obs, emin, emax,
... ... @@ -347,7 +347,7 @@ class cssens(ctools.cscript):
347 347 if not model.has_par("Prefactor"):
348 348 msg = "Model \""+self.m_srcname+"\" has no parameter \"Prefactor\"."+ \
349 349 " Only spectral models with a \"Prefactor\" parameter are supported."
350   - raise gammalib.GException.invalid_value("cssens", msg)
  350 + raise RuntimeError(msg)
351 351  
352 352 # Set source position
353 353 if self.m_ra != None and self.m_dec != None:
... ...
cscripts/csspec.py
  View file @14f9d87
... ... @@ -43,7 +43,7 @@ class csspec(ctools.cscript):
43 43 self.version = "1.0.0"
44 44  
45 45 # Initialise some members
46   - self.obs = None
  46 + self.obs = gammalib.GObservations()
47 47 self.fits = None
48 48  
49 49 # Initialise some members
... ... @@ -100,30 +100,21 @@ class csspec(ctools.cscript):
100 100  
101 101 # Create default parfile
102 102 pars = gammalib.GApplicationPars()
103   - pars.append(gammalib.GApplicationPar("inobs","f","a","events.fits","","","Event list, counts cube, or observation definition file"))
104   - pars.append(gammalib.GApplicationPar("inmodel","f","a","$CTOOLS/share/models/crab.xml","","","Source model"))
  103 + pars.append(gammalib.GApplicationPar("inobs","f","a","events.fits","","","Input event list, counts cube, or observation definition XML file"))
  104 + pars.append(gammalib.GApplicationPar("inmodel","f","a","$CTOOLS/share/models/crab.xml","","","Input model XML file"))
105 105 pars.append(gammalib.GApplicationPar("srcname","s","a","Crab","","","Source name"))
106   - pars.append(gammalib.GApplicationPar("outfile","f","a","spectrum.fits","","","Output file name"))
107   - pars.append(gammalib.GApplicationPar("expcube","f","a","NONE","","","Exposure cube file (only needed for stacked analysis)"))
108   - pars.append(gammalib.GApplicationPar("psfcube","f","a","NONE","","","PSF cube file (only needed for stacked analysis)"))
109   - pars.append(gammalib.GApplicationPar("bkgcube","s","a","NONE","","","Background cube file (only needed for stacked analysis)"))
  106 + pars.append(gammalib.GApplicationPar("expcube","f","a","NONE","","","Input exposure cube file (only needed for stacked analysis)"))
  107 + pars.append(gammalib.GApplicationPar("psfcube","f","a","NONE","","","Input PSF cube file (only needed for stacked analysis)"))
  108 + pars.append(gammalib.GApplicationPar("bkgcube","f","a","NONE","","","Input background cube file (only needed for stacked analysis)"))
110 109 pars.append(gammalib.GApplicationPar("caldb","s","a","prod2","","","Calibration database"))
111   - pars.append(gammalib.GApplicationPar("irf","s","a","South_50h","","","Instrument response function"))
  110 + pars.append(gammalib.GApplicationPar("irf","s","a","South_0.5h","","","Instrument response function"))
112 111 pars.append(gammalib.GApplicationPar("edisp","b","h","no","","","Apply energy dispersion?"))
113   - pars.append(gammalib.GApplicationPar("emin","r","h","0.1","","","Lower energy limit for spectral points(TeV)"))
114   - pars.append(gammalib.GApplicationPar("emax","r","h","100.0","","","Upper energy limit for spectral points(TeV)"))
115   - pars.append(gammalib.GApplicationPar("enumbins","i","a","20","","","Number of spectral points"))
116   - pars.append(gammalib.GApplicationPar("ebinalg","s", "h","LOG","FILE|LIN|LOG","", "Algorithm for defining energy bins"))
117   - pars.append(gammalib.GApplicationPar("binned","b","a","no","yes|no","","Use binned analysis in each energy bin"))
118   - pars.append(gammalib.GApplicationPar("nebins","i","h","5","","","Number of energy bins per spectral point"))
119   - pars.append(gammalib.GApplicationPar("coordsys","s","a","CEL","CEL|GAL","","Coordinate System"))
120   - pars.append(gammalib.GApplicationPar("proj","s","a","CAR","AIT|AZP|CAR|MER|MOL|STG|TAN","","Projection method"))
121   - pars.append(gammalib.GApplicationPar("xref","r","a","83.63","0","360","First coordinate of image center in degrees (RA or galactic l)"))
122   - pars.append(gammalib.GApplicationPar("yref","r","a","22.01","-90","90","Second coordinate of image center in degrees (DEC or galactic b)"))
123   - pars.append(gammalib.GApplicationPar("nxpix","i","a","200","","","Size of the X axis in pixels"))
124   - pars.append(gammalib.GApplicationPar("nypix","i","a","200","","","Size of the Y axis in pixels"))
125   - pars.append(gammalib.GApplicationPar("binsz","r","a","0.02","","","Pixel size (deg/pixel)"))
126   - pars.append(gammalib.GApplicationPar("anumbins","i","h","200","","","Angular separation bins for PSF cube in binned mode"))
  112 + pars.append(gammalib.GApplicationPar("outfile","f","a","spectrum.fits","","","Output spectrum file"))
  113 + pars.append(gammalib.GApplicationPar("emin","r","a","0.1","","","Lower energy limit for spectral points (TeV)"))
  114 + pars.append(gammalib.GApplicationPar("emax","r","a","100.0","","","Upper energy limit for spectral points (TeV)"))
  115 + pars.append(gammalib.GApplicationPar("enumbins","i","a","20","1","10000","Number of spectral points"))
  116 + pars.append(gammalib.GApplicationPar("ebinalg","s","a","LOG","FILE|LIN|LOG","", "Algorithm for defining energy bins"))
  117 + pars.append(gammalib.GApplicationPar("ebinfile","f","a","NONE","","", "Name of the file containing the energy bin definition"))
127 118 pars.append(gammalib.GApplicationPar("calc_ts","b","h","yes","yes|no","","Compute TS value in each bin"))
128 119 pars.append(gammalib.GApplicationPar("calc_ulim","b","h","yes","yes|no","","Compute upper limit in each bin"))
129 120 pars.append(gammalib.GApplicationPar("fix_srcs","b","h","yes","yes|no","","Fix other skymodel parameters"))
... ... @@ -143,6 +134,13 @@ class csspec(ctools.cscript):
143 134 if self.obs == None or self.obs.size() == 0:
144 135 self.require_inobs("csspec::get_parameters()")
145 136 self.obs = self.get_observations()
  137 +
  138 + # Check if we have one binned cta observation, i.e. if we are in binned mode
  139 + self.m_binned_mode = False
  140 + if self.obs.size() == 1:
  141 + if self.obs[0].classname() == "GCTAObservation":
  142 + if self.obs[0].eventtype() == "CountsCube":
  143 + self.m_binned_mode = True
146 144  
147 145 # Set models if we have none
148 146 if self.obs.models().size() == 0:
... ... @@ -151,25 +149,11 @@ class csspec(ctools.cscript):
151 149 # Get source name
152 150 self.m_srcname = self["srcname"].string()
153 151  
154   - # Get ebounds
155   - self.m_ebounds = self.create_ebounds()
156   -
157   - # Get binning flag
158   - self.m_binned = self["binned"].boolean()
159   -
  152 + # Set ebounds
  153 + self.set_ebounds()
  154 +
160 155 # Get edisp flag
161 156 self.m_edisp = self["edisp"].boolean()
162   -
163   - if self.m_binned:
164   - self.m_xref = self["xref"].real()
165   - self.m_yref = self["yref"].real()
166   - self.m_nxpix = self["nxpix"].integer()
167   - self.m_nypix = self["nypix"].integer()
168   - self.m_binsz = self["binsz"].real()
169   - self.m_coordsys = self["coordsys"].string()
170   - self.m_proj = self["proj"].string()
171   - self.m_ebins = self["nebins"].integer()
172   - self.m_anumbins = self["anumbins"].integer()
173 157  
174 158 # Read other parameters
175 159 self.m_outfile = self["outfile"].filename()
... ... @@ -189,6 +173,66 @@ class csspec(ctools.cscript):
189 173 # Return
190 174 return
191 175  
  176 + def set_ebounds(self):
  177 + """
  178 + Set energy boundaries.
  179 + """
  180 + # Get ebounds
  181 + if self.m_binned_mode:
  182 +
  183 + # Extract cube ebounds
  184 + cube_ebounds = self.obs[0].events().ebounds()
  185 +
  186 + # Read user parameters
  187 + self.m_enumbins = self["enumbins"].integer()
  188 + self.m_emin = self["emin"].real() - 1e-6 # Rounding tolerance
  189 + self.m_emax = self["emax"].real() + 1e-6 # Rounding tolerance
  190 +
  191 + # Set energy range
  192 + emin = gammalib.GEnergy(self.m_emin, "TeV")
  193 + emax = gammalib.GEnergy(self.m_emax, "TeV")
  194 +
  195 + # Determine all cube layers that overlap with the [emin,emax]
  196 + # energy range.
  197 + use_layers = []
  198 + for i in range(cube_ebounds.size()):
  199 + if cube_ebounds.emin(i) < emax and cube_ebounds.emax(i) > emin:
  200 + use_layers.append(i)
  201 +
  202 + # If no layers overlap then throw an exception
  203 + if (len(use_layers) == 0):
  204 + msg = "Energy range ["+str(cube_ebounds.emin(i))+ \
  205 + ", "+str(cube_ebounds.emax(i))+"] of counts "+ \
  206 + "cube does not overlap with specified energy range ["+ \
  207 + str(emin)+", "+str(emax)+"]. Specify "+ \
  208 + "overlapping energy range."
  209 + raise RuntimeError(msg)
  210 +
  211 + # Determine number of layers to use for each spectral bin
  212 + n_layers = int(len(use_layers) / self.m_enumbins)
  213 +
  214 + # Don't allow zero layers
  215 + if n_layers == 0:
  216 + n_layers = 1
  217 +
  218 + # Create energy boundaries
  219 + self.m_ebounds = gammalib.GEbounds()
  220 + for i in range(len(use_layers))[::n_layers]:
  221 + i_start = i
  222 + i_stop = i + n_layers - 1
  223 + if i_stop >= len(use_layers):
  224 + i_stop = len(use_layers) - 1
  225 + ebinmin = cube_ebounds.emin(use_layers[i_start])
  226 + ebinmax = cube_ebounds.emax(use_layers[i_stop])
  227 + self.m_ebounds.append(ebinmin, ebinmax)
  228 +
  229 + # Unbinned mode
  230 + else:
  231 + self.m_ebounds = self.create_ebounds()
  232 +
  233 + # Return
  234 + return
  235 +
192 236 def models(self, models):
193 237 """
194 238 Set model.
... ... @@ -235,6 +279,24 @@ class csspec(ctools.cscript):
235 279 self.log_parameters()
236 280 self.log("\n")
237 281  
  282 + # Write spectral binning into header
  283 + if self.logTerse():
  284 + self.log("\n")
  285 + self.log.header1("Spectral binning")
  286 + if self.m_binned_mode:
  287 + cube_ebounds = self.obs[0].events().ebounds()
  288 + self.log.parformat("Counts cube energy range")
  289 + self.log(str(cube_ebounds.emin()))
  290 + self.log(" - ")
  291 + self.log(str(cube_ebounds.emax()))
  292 + self.log("\n")
  293 + for i in range(self.m_ebounds.size()):
  294 + self.log.parformat("Bin "+str(i+1))
  295 + self.log(str(self.m_ebounds.emin(i)))
  296 + self.log(" - ")
  297 + self.log(str(self.m_ebounds.emax(i)))
  298 + self.log("\n")
  299 +
238 300 # Write observation into logger
239 301 if self.logTerse():
240 302 self.log("\n")
... ... @@ -286,7 +348,8 @@ class csspec(ctools.cscript):
286 348 # Write header
287 349 if self.logTerse():
288 350 self.log("\n")
289   - self.log.header1("Generate spectrum")
  351 + self.log.header1("Generate spectrum")
  352 + self.log(str(self.m_ebounds))
290 353  
291 354 # Initialise FITS Table with extension "SPECTRUM"
292 355 table = gammalib.GFitsBinTable(self.m_ebounds.size())
... ... @@ -298,26 +361,25 @@ class csspec(ctools.cscript):
298 361  
299 362 # Create FITS table columns
300 363 energy = gammalib.GFitsTableDoubleCol("Energy", self.m_ebounds.size())
301   - energy.unit("TeV")
302 364 energy_low = gammalib.GFitsTableDoubleCol("ed_Energy", self.m_ebounds.size())
303   - energy_low.unit("TeV")
304 365 energy_high = gammalib.GFitsTableDoubleCol("eu_Energy", self.m_ebounds.size())
305   - energy_high.unit("TeV")
306 366 flux = gammalib.GFitsTableDoubleCol("Flux", self.m_ebounds.size())
307   - flux.unit("erg/cm2/s")
308 367 flux_err = gammalib.GFitsTableDoubleCol("e_Flux", self.m_ebounds.size())
309   - flux_err.unit("erg/cm2/s")
310 368 TSvalues = gammalib.GFitsTableDoubleCol("TS", self.m_ebounds.size())
311 369 ulim_values = gammalib.GFitsTableDoubleCol("UpperLimit", self.m_ebounds.size())
312   - ulim_values.unit("erg/cm2/s")
313 370 Npred_values = gammalib.GFitsTableDoubleCol("Npred", self.m_ebounds.size())
314   -
  371 + energy.unit("TeV")
  372 + energy_low.unit("TeV")
  373 + energy_high.unit("TeV")
  374 + flux.unit("erg/cm2/s")
  375 + flux_err.unit("erg/cm2/s")
  376 + ulim_values.unit("erg/cm2/s")
315 377  
316 378 # Loop over energy bins
317 379 for i in range(self.m_ebounds.size()):
318 380  
319 381 # Log information
320   - if self.logTerse():
  382 + if self.logExplicit():
321 383 self.log("\n")
322 384 self.log.header2("Energy bin "+str(i+1))
323 385  
... ... @@ -334,8 +396,8 @@ class csspec(ctools.cscript):
334 396 energy_low[i] = (elogmean - emin).TeV()
335 397 energy_high[i] = (emax - elogmean).TeV()
336 398  
337   - # unbinned analysis
338   - if not self.m_binned:
  399 + # use ctselect for unbinned analysis
  400 + if not self.m_binned_mode:
339 401  
340 402 # Log information
341 403 if self.logExplicit():
... ... @@ -355,129 +417,43 @@ class csspec(ctools.cscript):
355 417 # Retrieve observation
356 418 obs = select.obs()
357 419  
358   - # Binned analysis
  420 + # use ctcubemask for binned analysis
359 421 else:
360 422  
361 423 # Header
362   - if self.logTerse():
363   - self.log.header3("Binning events")
364   -
365   - # Bin events
366   - bin = ctools.ctbin(self.obs)
367   - bin["usepnt"] = False
368   - bin["ebinalg"] = "LOG"
369   - bin["xref"] = self.m_xref
370   - bin["yref"] = self.m_yref
371   - bin["binsz"] = self.m_binsz
372   - bin["nxpix"] = self.m_nxpix
373   - bin["nypix"] = self.m_nypix
374   - bin["enumbins"] = self.m_ebins
375   - bin["emin"] = emin.TeV()
376   - bin["emax"] = emax.TeV()
377   - bin["coordsys"] = self.m_coordsys
378   - bin["proj"] = self.m_proj
379   - bin.run()
380   -
381   - # Header
382   - if self.logTerse():
383   - self.log.header3("Creating exposure cube")
384   -
385   - # Create exposure cube
386   - expcube = ctools.ctexpcube(self.obs)
387   - expcube["incube"] = "NONE"
388   - expcube["usepnt"] = False
389   - expcube["ebinalg"] = "LOG"
390   - expcube["edisp"] = self.m_edisp
391   - expcube["xref"] = self.m_xref
392   - expcube["yref"] = self.m_yref
393   - expcube["binsz"] = self.m_binsz
394   - expcube["nxpix"] = self.m_nxpix
395   - expcube["nypix"] = self.m_nypix
396   - expcube["enumbins"] = self.m_ebins
397   - expcube["emin"] = emin.TeV()
398   - expcube["emax"] = emax.TeV()
399   - expcube["coordsys"] = self.m_coordsys
400   - expcube["proj"] = self.m_proj
401   - expcube.run()
402   -
403   - # Header
404   - if self.logTerse():
405   - self.log.header3("Creating PSF cube")
406   -
407   - # Create psf cube
408   - psfcube = ctools.ctpsfcube(self.obs)
409   - psfcube["incube"] = "NONE"
410   - psfcube["usepnt"] = False
411   - psfcube["ebinalg"] = "LOG"
412   - psfcube["edisp"] = self.m_edisp
413   - psfcube["xref"] = self.m_xref
414   - psfcube["yref"] = self.m_yref
415   - psfcube["binsz"] = self.m_binsz*20.0 # Slow Psf variation
416   - psfcube["nxpix"] = self.m_nxpix/20+1
417   - psfcube["nypix"] = self.m_nypix/20+1
418   - psfcube["enumbins"] = self.m_ebins
419   - psfcube["anumbins"] = self.m_anumbins
420   - psfcube["emin"] = emin.TeV()
421   - psfcube["emax"] = emax.TeV()
422   - psfcube["coordsys"] = self.m_coordsys
423   - psfcube["proj"] = self.m_proj
424   - psfcube.run()
425   -
426   - # Header
427   - if self.logTerse():
428   - self.log.header3("Creating background cube")
429   -
430   - # Create background cube
431   - bkgcube = ctools.ctbkgcube(self.obs)
432   - bkgcube["incube"] = "NONE"
433   - bkgcube["usepnt"] = False
434   - bkgcube["ebinalg"] = "LOG"
435   - bkgcube["xref"] = self.m_xref
436   - bkgcube["yref"] = self.m_yref
437   - bkgcube["binsz"] = self.m_binsz
438   - bkgcube["nxpix"] = self.m_nxpix
439   - bkgcube["nypix"] = self.m_nypix
440   - bkgcube["enumbins"] = self.m_ebins
441   - bkgcube["emin"] = emin.TeV()
442   - bkgcube["emax"] = emax.TeV()
443   - bkgcube["coordsys"] = self.m_coordsys
444   - bkgcube["proj"] = self.m_proj
445   - bkgcube.run()
446   -
  424 + if self.logExplicit():
  425 + self.log.header3("Filtering cube")
  426 +
  427 + # Select layers
  428 + cubemask = ctools.ctcubemask(self.obs)
  429 + cubemask["regfile"] = "NONE"
  430 + cubemask["ra"] = "UNDEFINED"
  431 + cubemask["dec"] = "UNDEFINED"
  432 + cubemask["rad"] = "UNDEFINED"
  433 + cubemask["emin"] = emin.TeV()
  434 + cubemask["emax"] = emax.TeV()
  435 + cubemask.run()
  436 +
447 437 # Set new binned observation
448   - obs = bin.obs()
449   -
450   - # Set precomputed binned response
451   - obs[0].response(expcube.expcube(), psfcube.psfcube(), bkgcube.bkgcube())
452   -
453   - # Get new models
454   - models = bkgcube.models()
455   -
456   - # Fix background models if required
457   - if self.m_fix_bkg:
458   - for model in models:
459   - if not model.classname() == "GModelSky":
460   - for par in model:
461   - par.fix()
462   -
463   - # Set new models to binned observation
464   - obs.models(models)
  438 + obs = cubemask.obs()
465 439  
466 440 # Header
467   - if self.logTerse():
  441 + if self.logExplicit():
468 442 self.log.header3("Performing fit")
469 443  
470 444 # Likelihood
471   - like = ctools.ctlike(obs)
472   - like["edisp"].boolean(self.m_edisp)
  445 + like = ctools.ctlike(obs)
  446 + like["edisp"] = self.m_edisp
473 447 like.run()
474 448  
475 449 # Skip bin if no event was present
476 450 if like.obs().logL() == 0.0:
477 451  
478 452 # Log information
479   - if self.logTerse():
480   - self.log("No event in this bin. Likelihood is zero. Bin is skipped\n")
  453 + if self.logExplicit():
  454 + self.log("No event in this bin. ")
  455 + self.log("Likelihood is zero. ")
  456 + self.log("Bin is skipped.")
481 457  
482 458 # Set all values to 0
483 459 flux[i] = 0.0
... ... @@ -496,21 +472,21 @@ class csspec(ctools.cscript):
496 472 if self.m_calc_ulimit:
497 473  
498 474 # Logging information
499   - if self.logTerse():
  475 + if self.logExplicit():
500 476 self.log.header3("Computing upper limit")
501 477  
502 478 # Create upper limit object
503 479 ulimit = ctools.ctulimit(like.obs())
504 480 ulimit["srcname"] = self.m_srcname
505   - ulimit["eref"] = elogmean.TeV()
  481 + ulimit["eref"] = elogmean.TeV()
506 482  
507 483 # Try to run upper limit and catch exceptions
508 484 try:
509 485 ulimit.run()
510 486 ulimit_value = ulimit.diff_ulimit()
511 487 except:
512   - if self.logTerse():
513   - self.log("Upper limit calculation failed\n")
  488 + if self.logExplicit():
  489 + self.log("Upper limit calculation failed.")
514 490 ulimit_value = -1.0
515 491  
516 492 # Get TS value
... ... @@ -518,9 +494,9 @@ class csspec(ctools.cscript):
518 494 if self.m_calc_ts:
519 495 TS = source.ts()
520 496  
521   - # Compute Npred value
  497 + # Compute Npred value (only works for unbinned analysis)
522 498 Npred = 0.0
523   - if not self.m_binned:
  499 + if not self.m_binned_mode:
524 500 for observation in like.obs():
525 501 Npred += observation.npred(source)
526 502  
... ... @@ -529,8 +505,8 @@ class csspec(ctools.cscript):
529 505  
530 506 # Compute flux error
531 507 parvalue = source.spectral()[0].value()
532   - rel_error = source.spectral()[0].error()/parvalue
533   - e_flux = fitted_flux*rel_error
  508 + rel_error = source.spectral()[0].error() / parvalue
  509 + e_flux = fitted_flux * rel_error
534 510  
535 511 # Set values for storage
536 512 TSvalues[i] = TS
... ... @@ -545,15 +521,17 @@ class csspec(ctools.cscript):
545 521 ulim_values[i] = ulimit_value * elogmean2 * gammalib.MeV2erg
546 522  
547 523 # Log information
548   - if self.logExplicit():
549   - self.log("Bin "+str(i)+" ["+str(emin.TeV())+"-"+str(emax.TeV())+"] TeV: ")
550   - self.log("Flux = "+str(flux[i]))
551   - self.log(" +- "+str(flux_err[i])+" [erg/cm2/s]")
552   - if self.m_calc_ts and TSvalues[i] > 0.0:
553   - self.log(", TS = "+str(TS))
554   - if self.m_calc_ulimit and ulim_values[i] > 0.0:
555   - self.log(", UL = "+str(ulim_values[i])+" [erg/cm2/s]")
  524 + if self.logTerse():
556 525 self.log("\n")
  526 + self.log.parformat("Bin "+str(i+1))
  527 + self.log(str(flux[i]))
  528 + self.log(" +/- ")
  529 + self.log(str(flux_err[i]))
  530 + if self.m_calc_ulimit and ulim_values[i] > 0.0:
  531 + self.log(" [< "+str(ulim_values[i])+"]")
  532 + self.log(" erg/cm2/s")
  533 + if self.m_calc_ts and TSvalues[i] > 0.0:
  534 + self.log(" (TS = "+str(TS)+")")
557 535  
558 536 # Append filled columns to fits table
559 537 table.append(energy)
... ...
cscripts/cstsdist.py
  View file @14f9d87
... ... @@ -94,17 +94,17 @@ class cstsdist(ctools.cscript):
94 94  
95 95 # Create default parfile
96 96 pars = gammalib.GApplicationPars()
97   - pars.append(gammalib.GApplicationPar("inobs","f","h","NONE","","","Event list, counts cube, or observation definition file"))
98   - pars.append(gammalib.GApplicationPar("inmodel","f","a","$CTOOLS/share/models/crab.xml","","","Source model"))
  97 + pars.append(gammalib.GApplicationPar("inobs","f","h","NONE","","","Input event list, counts cube, or observation definition XML file"))
  98 + pars.append(gammalib.GApplicationPar("inmodel","f","a","$CTOOLS/share/models/crab.xml","","","Input model XML file"))
99 99 pars.append(gammalib.GApplicationPar("srcname","s","a","Crab","","","Source name"))
100   - pars.append(gammalib.GApplicationPar("outfile","f","a","ts.dat","","","Output file name"))
101   - pars.append(gammalib.GApplicationPar("expcube","s","a","NONE","","","Exposure cube file (only needed for stacked analysis)"))
102   - pars.append(gammalib.GApplicationPar("psfcube","s","a","NONE","","","PSF cube file (only needed for stacked analysis)"))
103   - pars.append(gammalib.GApplicationPar("bkgcube","s","a","NONE","","","Background cube file (only needed for stacked analysis)"))
  100 + pars.append(gammalib.GApplicationPar("expcube","s","a","NONE","","","Input exposure cube file (only needed for stacked analysis)"))
  101 + pars.append(gammalib.GApplicationPar("psfcube","s","a","NONE","","","Input PSF cube file (only needed for stacked analysis)"))
  102 + pars.append(gammalib.GApplicationPar("bkgcube","s","a","NONE","","","Input background cube file (only needed for stacked analysis)"))
104 103 pars.append(gammalib.GApplicationPar("caldb","s","a","prod2","","","Calibration database"))
105   - pars.append(gammalib.GApplicationPar("irf","s","a","South_50h","","","Instrument response function"))
  104 + pars.append(gammalib.GApplicationPar("irf","s","a","South_0.5h","","","Instrument response function"))
106 105 pars.append(gammalib.GApplicationPar("deadc","r","h","0.95","","","Deadtime correction factor"))
107 106 pars.append(gammalib.GApplicationPar("edisp","b","h","no","","","Apply energy dispersion?"))
  107 + pars.append(gammalib.GApplicationPar("outfile","f","a","ts.dat","","","Output Test Statistics distribution file"))
108 108 pars.append(gammalib.GApplicationPar("ntrials","i","a","10","","","Number of trials"))
109 109 pars.append(gammalib.GApplicationPar("ra","r","a","83.63","0","360","RA of pointing (deg)"))
110 110 pars.append(gammalib.GApplicationPar("dec","r","a","22.01","-90","90","Dec of pointing (deg)"))
... ... @@ -275,7 +275,7 @@ class cstsdist(ctools.cscript):
275 275 if not model.has_par("Prefactor"):
276 276 msg = "Model \""+self.m_srcname+"\" has no parameter \"Prefactor\"."+ \
277 277 " Only spectral models with a \"Prefactor\" parameter are supported."
278   - raise gammalib.GException.invalid_value("cssens", msg)
  278 + raise RuntimeError(msg)
279 279  
280 280 # Fit or fix spatial parameters
281 281 if fitpos:
... ...
cscripts/cstsmapmerge.py 0 → 100755
  View file @14f9d87
  1 +#!/usr/bin/env python
  2 +# ==========================================================================
  3 +# Merges sliced TS map files into one map
  4 +#
  5 +# Copyright (C) 2015 Michael Mayer
  6 +#
  7 +# This program is free software: you can redistribute it and/or modify
  8 +# it under the terms of the GNU General Public License as published by
  9 +# the Free Software Foundation, either version 3 of the License, or
  10 +# (at your option) any later version.
  11 +#
  12 +# This program is distributed in the hope that it will be useful,
  13 +# but WITHOUT ANY WARRANTY; without even the implied warranty of
  14 +# MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
  15 +# GNU General Public License for more details.
  16 +#
  17 +# You should have received a copy of the GNU General Public License
  18 +# along with this program. If not, see <http://www.gnu.org/licenses/>.
  19 +#
  20 +# ==========================================================================
  21 +import gammalib
  22 +import ctools
  23 +import sys
  24 +import glob
  25 +import os
  26 +
  27 +
  28 +# ================== #
  29 +# cstsmapmerge class #
  30 +# ================== #
  31 +class cstsmapmerge(ctools.cscript):
  32 + """
  33 + This class merges TS map files into one TS map
  34 + """
  35 + def __init__(self, *argv):
  36 + """
  37 + Constructor.
  38 + """
  39 + # Set name
  40 + self.name = "cstsmapmerge"
  41 + self.version = "1.1.0"
  42 +
  43 + # Make sure that parfile exists
  44 + file = self.parfile()
  45 +
  46 + # Initialise application
  47 + if len(argv) == 0:
  48 + ctools.cscript.__init__(self, self.name, self.version)
  49 + elif len(argv) == 1:
  50 + ctools.cscript.__init__(self, self.name, self.version, *argv)
  51 + else:
  52 + raise TypeError("Invalid number of arguments given.")
  53 +
  54 + # Set logger properties
  55 + self.log_header()
  56 + self.log.date(True)
  57 +
  58 + # Return
  59 + return
  60 +
  61 + def __del__(self):
  62 + """
  63 + Destructor.
  64 + """
  65 + # Return
  66 + return
  67 +
  68 + def parfile(self):
  69 + """
  70 + Check if parfile exists. If parfile does not exist then create a
  71 + default parfile. This kluge avoids shipping the cscript with a
  72 + parfile.
  73 + """
  74 +
  75 + # Set parfile name
  76 + parfile = self.name+".par"
  77 +
  78 + try:
  79 + pars = gammalib.GApplicationPars(parfile)
  80 + except:
  81 + # Signal that parfile was not found
  82 + print("Parfile \""+parfile+"\" not found. Create default parfile.")
  83 +
  84 + # Create default parfile
  85 + pars = gammalib.GApplicationPars()
  86 + pars.append(gammalib.GApplicationPar("inmaps","s","a","tsmap.fits","","","Input TS map FITS files"))
  87 + pars.append(gammalib.GApplicationPar("outmap","f","a","NONE","","","Output TS map FITS file"))
  88 + pars.append(gammalib.GApplicationPar("overwrite","b","h","yes","","","Overwrite previously filled bins?"))
  89 + pars.append(gammalib.GApplicationPar("delete","b","h","no","","","Delete merged files?"))
  90 + pars.append_standard()
  91 + pars.append(gammalib.GApplicationPar("logfile","f","h","cstsmapmerge.log","","","Log filename"))
  92 + pars.save(parfile)
  93 +
  94 + # Return
  95 + return
  96 +
  97 + def get_parameters(self):
  98 + """
  99 + Get parameters from parfile and setup the observation.
  100 + """
  101 + # Get input models
  102 + self.inmodels = self["inmaps"].string()
  103 +
  104 + # Interpet inmodels string
  105 + # Handle ascii files
  106 + if "@" == self.inmodels[0]:
  107 + self.files = open(self.inmodels.replace("@","")).read().splitlines()
  108 +
  109 + # Handle wild card strings
  110 + elif "*" in self.inmodels:
  111 + self.files = glob.glob(self.inmodels)
  112 +
  113 + # Handle space-separated list
  114 + elif " " in self.inmodels:
  115 + self.files = self.inmodels.split(" ")
  116 +
  117 + # Handle comma-separated list
  118 + elif "," in self.inmodels:
  119 + self.files = self.inmodels.split(",")
  120 +
  121 + # Throw exception if input models cannot be decoded
  122 + else:
  123 + msg = "Parameter \"inmmaps\" must contain either an @ASCII file,"+\
  124 + " a comma-separated or whitespace-separated list of files"+\
  125 + " or a wildcard string"
  126 + raise RuntimeError(msg)
  127 +
  128 + # Check number of files. We need at least two files.
  129 + if len(self.files) <= 1:
  130 + msg = "Need at least two files to start merging, "+\
  131 + str(len(self.files))+" files given."
  132 + raise RuntimeError(msg)
  133 +
  134 + # Get output file
  135 + self.outmap = self["outmap"].filename()
  136 +
  137 + # Get other parameters
  138 + self.overwrite = self["overwrite"].boolean()
  139 + self.delete = self["delete"].boolean()
  140 +
  141 + # Return
  142 + return
  143 +
  144 + def init_map(self, fitsfile):
  145 + """
  146 + """
  147 + # Set filename
  148 + self.in_filename = fitsfile
  149 +
  150 + # Open FITS file
  151 + fits = gammalib.GFits(fitsfile)
  152 + self.tsmap = gammalib.GSkyMap()
  153 + self.tsmap.read(fits[0])
  154 + self.statusmap = gammalib.GSkyMap()
  155 + self.statusmap.read(fits["STATUS MAP"])
  156 +
  157 + # Get other maps
  158 + self.maps = []
  159 + self.mapnames = []
  160 +
  161 + # Loop over extensions
  162 + for hdu in fits:
  163 +
  164 + # Leave out primary and status extension
  165 + if hdu.extname() != "IMAGE" and hdu.extname() != "STATUS MAP":
  166 +
  167 + # Add present maps
  168 + skymap = gammalib.GSkyMap()
  169 + skymap.read(hdu)
  170 + self.maps.append(skymap)
  171 + self.mapnames.append(hdu.extname())
  172 +
  173 + # Close FITS file
  174 + fits.close()
  175 +
  176 + # Return
  177 + return
  178 +
  179 + # Add map instances to each other. In this way the TS maps get merged
  180 + def add(self, fitsfile):
  181 +
  182 + # open FITS file
  183 + fits = gammalib.GFits(fitsfile)
  184 + add_tsmap = gammalib.GSkyMap()
  185 + add_tsmap.read(fits[0])
  186 + add_statusmap = gammalib.GSkyMap()
  187 + add_statusmap.read(fits["STATUS MAP"])
  188 +
  189 + # Get other maps
  190 + add_maps = []
  191 +
  192 + # Loop over extensions
  193 + for hdu in fits:
  194 +
  195 + # Leave out primary and status extension
  196 + if hdu.extname() != "IMAGE" and hdu.extname() != "STATUS MAP":
  197 +
  198 + # Add present maps
  199 + skymap = gammalib.GSkyMap()
  200 + skymap.read(hdu)
  201 + add_maps.append(skymap)
  202 +
  203 + # Close FITS file
  204 + fits.close()
  205 +
  206 + # Compare size of other maps
  207 + if not len(add_maps) == len(self.maps):
  208 + self.error("Maps cannot be added: Maps from \""+self.in_filename+"\" do not match from \""+fitsfile+"\"")
  209 +
  210 + # Loop over bins
  211 + for i in range(self.tsmap.npix()):
  212 + if add_statusmap[i] > 0.5:
  213 +
  214 + # Throw exception if this bin has already been computed
  215 + if self.statusmap[i] > 0.5 and not self.overwrite:
  216 + msg = "Attempt to merge bin which apparently has already"+\
  217 + " been merged. File \""+fitsfile+"\" contains"+\
  218 + " already merged bins. Set hidden parameter"+\
  219 + " overwrite=yes to avoid this error."
  220 + raise RuntimeError(msg)
  221 +
  222 + # Copy TS values
  223 + self.tsmap[i] = add_tsmap[i]
  224 +
  225 + # Copy status
  226 + self.statusmap[i] = add_statusmap[i]
  227 +
  228 + # Loop over maps and copy entries
  229 + for j in range(len(self.maps)):
  230 + self.maps[j][i] = add_maps[j][i]
  231 +
  232 + # Return
  233 + return
  234 +
  235 + def run(self):
  236 + """
  237 + Run the script.
  238 + """
  239 + # Switch screen logging on in debug mode
  240 + if self.logDebug():
  241 + self.log.cout(True)
  242 +
  243 + # Get parameters
  244 + self.get_parameters()
  245 +
  246 + # Write input parameters into logger
  247 + if self.logTerse():
  248 + self.log_parameters()
  249 + self.log("\n")
  250 +
  251 + if self.logTerse():
  252 + self.log("\n")
  253 + self.log.header1("Merging sliced TS map files")
  254 + self.log("\n")
  255 +
  256 + # Initialise file to start with
  257 + file0 = ""
  258 +
  259 + self.added_files = []
  260 +
  261 + # Test files for the entry status map
  262 + # use the first one to appear useful
  263 + for fitsfile in self.files:
  264 + if not gammalib.is_fits(fitsfile):
  265 + self.log("Skipping file \""+fitsfile+" (not a FITS file)\n")
  266 + fits = gammalib.GFits(fitsfile)
  267 +
  268 + if fits.contains("STATUS MAP"):
  269 + self.log("Using file \""+fitsfile+"\" as initialising map\n")
  270 + file0 = fitsfile
  271 + break
  272 + else:
  273 + if self.logExplicit():
  274 + self.log("File \""+fitsfile+"\" has not \"STATUS MAP\" extension\n")
  275 +
  276 + # Print an error message if no suitable file was provided
  277 + if file0 == "":
  278 + if self.logTerse():
  279 + self.log("None of the provided file seems to be a sliced ts map file (no \"STATUS MAP\" extension)\n")
  280 +
  281 + # Otherwise merge files
  282 + else:
  283 +
  284 + # copy file list
  285 + workfiles = self.files
  286 +
  287 + # Remove entry which will be used to initalise the map
  288 + workfiles.remove(file0)
  289 +
  290 + # Initialise map from first file
  291 + self.init_map(file0)
  292 +
  293 + # Append to added files
  294 + self.added_files.append(file0)
  295 +
  296 + # Loop over files
  297 + for fitsfile in workfiles:
  298 +
  299 + # Skip if file is not FITS
  300 + if not gammalib.is_fits(fitsfile):
  301 + if self.logTerse():
  302 + self.log("Skipping file \""+fitsfile+" (not a FITS file)\n")
  303 + continue
  304 +
  305 + # Skip if file does not contain status map
  306 + fits = gammalib.GFits(fitsfile)
  307 + if not fits.contains("STATUS MAP"):
  308 + if self.logTerse():
  309 + self.log("Skipping file \""+fitsfile+" (not a FITS file)\n")
  310 + continue
  311 +
  312 + # Logging
  313 + if self.logTerse():
  314 + self.log("Adding TS map slice \""+fitsfile+"\"\n")
  315 +
  316 + # Add file
  317 + self.add(fitsfile)
  318 +
  319 + # Append to added files
  320 + self.added_files.append(fitsfile)
  321 +
  322 + # Return
  323 + return
  324 +
  325 + def save(self):
  326 + """
  327 + Save merged tsmap file and remove slices if requested
  328 + """
  329 +
  330 + # Logging
  331 + if self.logExplicit():
  332 + self.log("\n")
  333 + self.log.header1("Saving merged TS map")
  334 + self.log("\n")
  335 +
  336 + # Create FITS file
  337 + fits = gammalib.GFits()
  338 +
  339 + # Write TS map into primary
  340 + self.tsmap.write(fits)
  341 +
  342 + # Loop over maps and write them to fits
  343 + for i in range(len(self.maps)):
  344 + self.maps[i].write(fits)
  345 +
  346 + # Set map names as extensions
  347 + for i in range(len(self.mapnames)):
  348 + fits[i+1].extname(self.mapnames[i])
  349 +
  350 + # Check if map is fully done
  351 + done = True
  352 + for pix in self.statusmap:
  353 + if pix < 0.5:
  354 + done = False
  355 + break
  356 +
  357 + # Write Status map if we are not done yet
  358 + if not done:
  359 + self.statusmap.write(fits)
  360 + fits[fits.size()-1].extname("STATUS MAP")
  361 +
  362 + # Save FITS file
  363 + fits.saveto(self.outmap, self.clobber())
  364 + if self.logExplicit():
  365 + self.log("Saved output map to \""+self.outmap+"\"\n")
  366 + if self.delete:
  367 + if self.logTerse():
  368 + self.log("\n")
  369 + self.log.header1("Deleting slices")
  370 + self.log("\n")
  371 + for filename in self.added_files:
  372 + if self.logExplicit():
  373 + self.log("Deleting file \""+filename+"\"\n")
  374 + os.remove(filename)
  375 +
  376 + # Return
  377 + return
  378 +
  379 + def execute(self):
  380 + """
  381 + Execute the script.
  382 + """
  383 + # Run the script
  384 + self.run()
  385 +
  386 + # Save ds9 file if required
  387 + self.save()
  388 +
  389 + # Return
  390 + return
  391 +
  392 +
  393 +# ======================== #
  394 +# Main routine entry point #
  395 +# ======================== #
  396 +if __name__ == '__main__':
  397 + """
  398 + Merges ts map slices.
  399 + """
  400 + # Create instance of application
  401 + app = cstsmapmerge(sys.argv)
  402 +
  403 + # Open logfile
  404 + app.logFileOpen()
  405 +
  406 + # Execute application
  407 + app.execute()
... ...
cscripts/tsmerge.py deleted
View file @61ca854
1   -#!/usr/bin/env python
2   -
3   -import gammalib
4   -import sys
5   -import os
6   -import glob
7   -import json
8   -
9   -def print_help():
10   - print("")
11   - print("tsmerge.py expects two keyword argumens: use via command line as follows")
12   - print("tsmerge.py files=<list of files> outfile=<desired outfile name>")
13   - print("-------------------------------------------------------------------------")
14   - print("*** \"outfile\" should be a path to a fits file")
15   - print("*** \"files\" should be either be:")
16   - print(" - an ascii-file listing the files your want to merge")
17   - print(" OR - a wildcard string describing the files for merging")
18   - print("-------------------------------------------------------------------------")
19   - print("")
20   - print("Example: python tsmerge,py files=tsmap*.fits outfile=tsmap.fits")
21   - print("")
22   - sys.exit(-1)
23   -
24   -
25   -# Maps class holding the different sky maps
26   -# created by cttsmap
27   -class maps:
28   -
29   - # Constructor
30   - def __init__(self,fitsfile):
31   -
32   - self.filename = fitsfile
33   - if not os.path.isfile(fitsfile):
34   - self.error("Maps instance cannot be constructed: File \""+self.filename+"\" does not exist")
35   -
36   - # open FITS file
37   - fits = gammalib.GFits(fitsfile)
38   -
39   - # get TS map
40   - self.tsmap = gammalib.GSkyMap()
41   - self.tsmap.read(fits[0])
42   -
43   - # Get status map
44   - if not fits.contains("STATUS MAP"):
45   - self.error("No extension \"STATUS MAP\" found in \""+self.filename+"\"")
46   - self.statusmap = gammalib.GSkyMap()
47   - self.statusmap.read(fits["STATUS MAP"])
48   -
49   - # Get other maps
50   - self.maps = []
51   - self.mapnames = []
52   - for hdu in fits:
53   - if hdu.extname() != "IMAGE" and hdu.extname() != "STATUS MAP":
54   - skymap = gammalib.GSkyMap()
55   - skymap.read(hdu)
56   - self.maps.append(skymap)
57   - self.mapnames.append(hdu.extname())
58   -
59   - # len operator
60   - def __len__(self):
61   - return len(self.maps)
62   -
63   - # operator []
64   - def __getitem__(self,index):
65   - return self.maps[index]
66   -
67   - # Check the status map for completeness
68   - def check_status(self):
69   - check = True
70   - for pix in self.statusmap:
71   - if pix < 0.5:
72   - check = False
73   - break
74   - return check
75   -
76   - # Save maps to outfile
77   - def save(self,outfile):
78   -
79   - fits = gammalib.GFits()
80   - self.tsmap.write(fits)
81   -
82   - for i in range(len(self.maps)):
83   - self.maps[i].write(fits)
84   -
85   - for i in range(len(self.mapnames)):
86   - fits[i+1].extname(self.mapnames[i])
87   -
88   - if not self.check_status():
89   - self.statusmap.write(fits)
90   - fits[fits.size()-1].extname("STATUS MAP")
91   - fits.saveto(outfile,True)
92   -
93   - # Add map instances to each other
94   - # in this way the TS maps get merged
95   - def add(self,addmaps):
96   - if not len(addmaps) == len(self.maps):
97   - self.error("Maps cannot be added: Maps from \""+self.filename+"\" do not match from \""+addmaps.filename+"\"")
98   -
99   - # Loop over bins
100   - for i in range(self.tsmap.npix()):
101   - if addmaps.statusmap[i] > 0.5:
102   - self.tsmap[i] = addmaps.tsmap[i]
103   - self.statusmap[i] = addmaps.statusmap[i]
104   - for j in range(len(self.maps)):
105   - self.maps[j][i] = addmaps[j][i]
106   - # Unify error messages
107   - def error(self,message):
108   - print("*** ERROR ***: "+message)
109   - sys.exit(-1)
110   -
111   -
112   -def pars_from_argv(argv):
113   -
114   - if argv is None:
115   - argv = sys.argv
116   -
117   - args = []
118   - kwargs = {}
119   - for s in argv[1:]:
120   - if s.count('=') == 1:
121   - key, value = s.split('=', 1)
122   - else:
123   - key, value = None, s
124   - try:
125   - value = json.loads(value)
126   - except ValueError:
127   - pass
128   - if key:
129   - kwargs[key] = value
130   - else:
131   - args.append(value)
132   - return args, kwargs
133   -
134   -
135   -def get_kwargs(argv):
136   - kwargs = {}
137   -
138   - for s in argv:
139   - if s.count('=') == 1:
140   - key, value = s.split('=', 1)
141   - kwargs[key] = value
142   -
143   - else:
144   - print_help()
145   -
146   - return kwargs
147   -
148   -if __name__ == "__main__":
149   - # Initialise list of files
150   -
151   - kwargs = get_kwargs(sys.argv[1:])
152   - if "outfile" not in kwargs or "files" not in kwargs:
153   - print_help()
154   - outfile = kwargs["outfile"]
155   - files = kwargs["files"]
156   - allfiles = []
157   - if os.path.isfile(files):
158   - allfiles = open(files).read().splitlines()
159   - else:
160   - allfiles = glob.glob(files)
161   -
162   - # Initialise files to be merged
163   - mergefiles = []
164   -
165   - # Test files for the entry status map
166   - # and add them to the file list
167   - for fitsfile in allfiles:
168   - fits = gammalib.GFits(fitsfile)
169   - if fits.contains("STATUS MAP"):
170   - mergefiles.append(fitsfile)
171   - fits.close()
172   -
173   - # create a maps instance from the first file
174   - finalmaps = maps(mergefiles[0])
175   -
176   - # add other files to the maps instance
177   - for fitsfile in mergefiles[1:]:
178   - finalmaps.add(maps(fitsfile))
179   -
180   - # save the filled maps to file
181   - finalmaps.save(outfile=outfile)
ctools.pc.in
  View file @14f9d87
... ... @@ -6,9 +6,9 @@ includedir=${prefix}/include
6 6 Name: ctools
7 7 Description: CTA science analysis tools
8 8 URL: http://cta.irap.omp.eu/ctools
9   -Version: 0.10.0
  9 +Version: 1.0.0
10 10 Requires:
11   -Requires.private: gammalib >= 0.11.0
  11 +Requires.private: gammalib >= 1.0.0
12 12 Conflicts:
13 13 Cflags: -I${includedir}/ctools @OPENMP_CXXFLAGS@
14 14 Libs: -L${libdir} -lctools
... ...
doc/Doxyfile
  View file @14f9d87
... ... @@ -32,7 +32,7 @@ PROJECT_NAME = ctools
32 32 # This could be handy for archiving the generated documentation or
33 33 # if some version control system is used.
34 34  
35   -PROJECT_NUMBER = 0.10.0
  35 +PROJECT_NUMBER = 1.0.0
36 36  
37 37 # Using the PROJECT_BRIEF tag one can provide an optional one line description
38 38 # for a project that appears at the top of each page and should give viewer
... ...
doc/source/conf.py
  View file @14f9d87
... ... @@ -66,10 +66,10 @@ copyright = u&#39;2014-2015, ctools developers&#39;
66 66 # built documents.
67 67 #
68 68 # The short X.Y version.
69   -version = '0.10'
  69 +version = '1.0'
70 70  
71 71 # The full version, including alpha/beta/rc tags.
72   -release = '0.10.0'
  72 +release = '1.0.0'
73 73  
74 74 # The language for content autogenerated by Sphinx. Refer to documentation
75 75 # for a list of supported languages.
... ...
doc/source/develop.rst
  View file @14f9d87
... ... @@ -8,12 +8,12 @@ to the development.
8 8 Contributions can come in any areas: writing C++ code, contributing Python
9 9 scripts, writing documentation, testing code, etc.
10 10  
11   -The ctools development is managed by a development platform that is
12   -accessible at `<https://cta-redmine.irap.omp.eu/projects/ctools/>`_.
  11 +The ctools software development is managed by a
  12 +`Redmine <https://cta-redmine.irap.omp.eu/projects/ctools/>`_ platform.
13 13 Please check out the
14 14 `Wiki <https://cta-redmine.irap.omp.eu/projects/ctools/wiki/Contributing_to_ctools>`_
15   -on that platform that contains information on how to contribute to the
16   -ctools development.
  15 +on that platform to learn how you can contribute to the ctools software
  16 +development.
17 17  
18 18 You may also want to get in the ctools information flow by subscribing to
19 19 the ctools@irap.omp.eu mailing list.
... ... @@ -24,5 +24,5 @@ to allow newcomers to get familiar with the code base and the coding
24 24 practices.
25 25 You are highly invited to join one of the next coding sprints.
26 26  
27   -You can also follow `@gammalib <https://twitter.com/gammalib>`_ on
28   -twitter to get informed about new release of GammaLib and ctools.
29 27 \ No newline at end of file
  28 +You can also follow `@ctools_software <https://twitter.com/ctools_software>`_ on
  29 +twitter to get informed about new ctools releases.
30 30 \ No newline at end of file
... ...
doc/source/download.rst
  View file @14f9d87
... ... @@ -13,7 +13,7 @@ bugs.
13 13 Releases
14 14 --------
15 15  
16   -The latest ctools release is ``ctools-0.10.0`` (1 November 2015).
  16 +The latest ctools release is ``ctools-1.0.0`` (18 December 2015).
17 17  
18 18 Below a table of ctools releases. Please note that at this stage of the
19 19 project there is a strict link between the ctools and gammalib versions.
... ... @@ -28,6 +28,9 @@ gammalib.
28 28 * - `ctools <http://cta.irap.omp.eu/ctools/releases/ctools/ChangeLog>`_
29 29 - `gammalib <http://cta.irap.omp.eu/ctools/releases/gammalib/ChangeLog>`_
30 30 - Mac OS X package
  31 + * - `1.0.0 <http://cta.irap.omp.eu/ctools/releases/ctools/ctools-1.0.0.tar.gz>`_
  32 + - `1.0.0 <http://cta.irap.omp.eu/ctools/releases/gammalib/gammalib-1.0.0.tar.gz>`_
  33 + - `ctools-1.0.0-macosx10.3.dmg <http://cta.irap.omp.eu/ctools/releases/ctools/ctools-1.0.0-macosx10.3.dmg>`_
31 34 * - `0.10.0 <http://cta.irap.omp.eu/ctools/releases/ctools/ctools-0.10.0.tar.gz>`_
32 35 - `0.11.0 <http://cta.irap.omp.eu/ctools/releases/gammalib/gammalib-0.11.0.tar.gz>`_
33 36 - `ctools-0.10.0-macosx10.3.dmg <http://cta.irap.omp.eu/ctools/releases/ctools/ctools-0.10.0-macosx10.3.dmg>`_
... ...
doc/source/help.rst
  View file @14f9d87
... ... @@ -3,8 +3,44 @@
3 3 Getting Help
4 4 ============
5 5  
6   -Any questions, bug reports, or suggested enhancements related to
7   -ctools should be submitted via the
8   -`issue tracker <https://cta-redmine.irap.omp.eu/projects/ctools/issues/new>`_
9   -or the
10   -`mailing list <mailto:ctools@irap.omp.eu>`_.
11 6 \ No newline at end of file
  7 +If you need help you should first check the
  8 +:ref:`Frequently Asked Questions <faq>` and the list of
  9 +:ref:`Known Issues <issues>`.
  10 +In case that you do not find an answer to your question you may post your
  11 +question on the ctools@irap.omp.eu mailing list.
  12 +To subscribe to this list you simply need to send an e-mail to
  13 +ctools-subscribe@irap.omp.eu (content is irrelevant).
  14 +
  15 +You can also use the `Redmine <https://cta-redmine.irap.omp.eu/projects/ctools>`_
  16 +system that we use for the ctools software development management to ask for
  17 +support, report a bug, or request a new feature. To use the system you
  18 +will first need to
  19 +`register <https://cta-redmine.irap.omp.eu/account/register>`_.
  20 +
  21 +Once registered, you can sign-in and ask for support by creating a
  22 +`support issue <https://cta-redmine.irap.omp.eu/projects/ctools/issues/new>`_.
  23 +Specify ``Support`` as Tracker, choose a short and meaningful subject,
  24 +and add an exhaustive description of your request.
  25 +
  26 +If you find a bug you should first check the
  27 +`list of bugs <https://cta-redmine.irap.omp.eu/projects/ctools/issues?utf8=?&set_filter=1&f%5B%5D=status_id&op%5Bstatus_id%5D=*&f%5B%5D=tracker_id&op%5Btracker_id%5D=%3D&v%5Btracker_id%5D%5B%5D=1&f%5B%5D=&c%5B%5D=tracker&c%5B%5D=status&c%5B%5D=priority&c%5B%5D=subject&c%5B%5D=assigned_to&c%5B%5D=updated_on&c%5B%5D=fixed_version&c%5B%5D=done_ratio&group_by=>`_
  28 +to see whether your bug is already known. If the bug is known, you may edit
  29 +the issue and add some information (e.g. a log file, screen shot, etc.).
  30 +If the bug is not yet known, please create a
  31 +`bug issue <https://cta-redmine.irap.omp.eu/projects/ctools/issues/new>`_.
  32 +Specify ``Bug`` as Tracker, provide a short and meaningful subject, and add
  33 +an exhaustive description of the bug. Include the ctools software version,
  34 +your operating system, and the conditions under which the bug occurred. Ideally
  35 +you should provide all files and the command sequence (or a script) that
  36 +will allow us to reproduce the bug.
  37 +
  38 +If you would like to suggest some enhancements to ctools you should create
  39 +a
  40 +`feature issue <https://cta-redmine.irap.omp.eu/projects/ctools/issues/new>`_.
  41 +Specify ``Feature`` as Tracker, choose a short and meaningful subject,
  42 +and add an exhaustive description of your feature request.
  43 +Also explain the motivation for your request and provide some hint on how
  44 +urgently you need the new feature.
  45 +
  46 +You may click on ``Watch`` in the top-right corner of the issue page to make sure
  47 +that you will receive an e-mail notification when the issue is updated.
12 48 \ No newline at end of file
... ...
doc/source/issues.rst
  View file @14f9d87
... ... @@ -11,7 +11,6 @@ list of
11 11  
12 12 - :ref:`Certificate problem when cloning from Git <issue_ssl>`
13 13 - :ref:`Python module does not work <issue_python>`
14   -- :ref:`Python unit test fails on El Capitan <issue_elcapitan>`
15 14 - :ref:`Installing on Solaris <issue_solaris>`
16 15 - :ref:`Installing on OpenSolaris <issue_opensolaris>`
17 16  
... ... @@ -68,16 +67,6 @@ Installation issues
68 67 If the ``Python.h`` header file does not exist then install the Python
69 68 development package.
70 69  
71   -.. _issue_elcapitan:
72   -
73   -.. topic:: Python unit test fails on El Capitan
74   -
75   - On Mac OS X 10.11 (El Capitan) the Python unit tests fail when ctools
76   - are not installed due to the way the ``DYLD_LIBRARY_PATH`` environment
77   - variable is handled by the operating system. A (not very elegant)
78   - workaround is to install the ctools before running the unit test using
79   - ``make check``.
80   -
81 70 .. _issue_solaris:
82 71  
83 72 .. topic:: Installing on Solaris
... ...
doc/source/reference_manual/cscaldb.rst
  View file @14f9d87
1   -.. _cscaldb: cscaldb ======= Dumps all available instrument response functions into log fil. Synopsis -------- This scripts dumps all instrument response functions that are available in the calibration database into the log file. If you want the information on the screen, add the ``debug=yes`` parameter. General parameters ------------------ None Standard parameters ------------------- ``(chatter = 2) [integer]`` Verbosity of the executable: chatter = 0: no information will be logged chatter = 1: only errors will be logged chatter = 2: errors and actions will be logged chatter = 3: report about the task execution chatter = 4: detailed report about the task execution ``(clobber = yes) [boolean]`` Specifies whether an existing output counts cube should be overwritten. ``(debug = no) [boolean]`` Enables debug mode. In debug mode the executable will dump any log file output to the console. ``(mode = ql) [string]`` Mode of automatic parameters (default is "ql", i.e. "query and learn"). Related tools ------------- None
2 1 \ No newline at end of file
  2 +.. _cscaldb:
  3 +
  4 +cscaldb
  5 +=======
  6 +
  7 +Dumps all available instrument response functions into log file.
  8 +
  9 +
  10 +Synopsis
  11 +--------
  12 +
  13 +This scripts dumps all instrument response functions that are available
  14 +in the calibration database into the log file. If you want the information
  15 +on the screen, add the ``debug=yes`` parameter.
  16 +
  17 +
  18 +General parameters
  19 +------------------
  20 +
  21 +None
  22 +
  23 +
  24 +Standard parameters
  25 +-------------------
  26 +
  27 +``(chatter = 2) [integer]``
  28 + Verbosity of the executable:
  29 + chatter = 0: no information will be logged
  30 +
  31 + chatter = 1: only errors will be logged
  32 +
  33 + chatter = 2: errors and actions will be logged
  34 +
  35 + chatter = 3: report about the task execution
  36 +
  37 + chatter = 4: detailed report about the task execution
  38 +
  39 +``(clobber = yes) [boolean]``
  40 + Specifies whether an existing output counts cube should be overwritten.
  41 +
  42 +``(debug = no) [boolean]``
  43 + Enables debug mode. In debug mode the executable will dump any log file output to the console.
  44 +
  45 +``(mode = ql) [string]``
  46 + Mode of automatic parameters (default is "ql", i.e. "query and learn").
  47 +
  48 +
  49 +Related tools of scripts
  50 +------------------------
  51 +
  52 +None
... ...
doc/source/reference_manual/cslightcrv.rst
  View file @14f9d87
... ... @@ -9,12 +9,14 @@ Computes a lightcurve for a given source.
9 9 Synopsis
10 10 --------
11 11  
12   -Computes a lightcurve by performing a maximum likekihood fit in a series of
13   -time bins. The time bins can be either specified in an ASCII file, as an
14   -interval divided into equally sized time bins, or can be taken from the Good
15   -Time Intervals of the observation(s). The format of the ASCII file is one
16   -row per time bin, each specifying the start of stop value of the bin, separated
17   -by a whitespace. The times are given in Modified Julian Days (MJD).
  12 +This script computes a lightcurve by performing a maximum likelihood fit
  13 +using :doc:`ctlike` in a series of time bins. The time bins can be either
  14 +specified in an ASCII file, as an interval divided into equally sized time
  15 +bins, or can be taken from the Good Time Intervals of the observation(s).
  16 +The format of the ASCII file is one row per time bin, each specifying the
  17 +start of stop value of the bin, separated by a whitespace. The times are
  18 +given in Modified Julian Days (MJD).
  19 +
18 20 cslightcrv writes the fitted model parameters and their statistical errors
19 21 in a FITS file. In addition, it computes for each time bin the statistical
20 22 significance of the detection, expressed by the Test Statistics, and the
... ... @@ -28,7 +30,7 @@ General parameters
28 30 Input event list, counts cube or observation definition XML file.
29 31  
30 32 ``inmodel [file]``
31   - Input source model XML file.
  33 + Input model XML file.
32 34  
33 35 ``srcname [string]``
34 36 Name of the source in the source model XML file which should be used
... ... @@ -141,7 +143,7 @@ Standard parameters
141 143 Log filename.
142 144  
143 145  
144   -Related tools
145   --------------
  146 +Related tools or scripts
  147 +------------------------
146 148  
147   -None
  149 +:doc:`ctlike`
... ...
doc/source/reference_manual/csmodelinfo.rst 0 → 100644
  View file @14f9d87
  1 +.. _csmodelinfo:
  2 +
  3 +csmodelinfo
  4 +===========
  5 +
  6 +Dumps information about a model container into log file or on screen.
  7 +
  8 +
  9 +Synopsis
  10 +--------
  11 +
  12 +This script provides detailled information about a given model container.
  13 +It presents the number of parameters, the number of free parameters (sub-
  14 +divided by spectral, spatial and temporal type). The tool further creates
  15 +information about any parameter that is stuck at the parameter boundaries.
  16 +This might be quite useful for debugging a fit. Finally the tool also list
  17 +the TS values of each source that was fitted, in order have a quick overview
  18 +on these quantities on the screen.
  19 +
  20 +In addition the tool is also capable of exporting the input model XML container
  21 +to a region file which is compatible to be read with ds9 or other displying
  22 +tools. To create a region file, the hidden parameter "ds9file" needs to be
  23 +specified. There are quite a few further hidden parameters to steer e.g.
  24 +color, font, etc of the region file output.
  25 +
  26 +
  27 +General parameters
  28 +------------------
  29 +
  30 +``inmodel [file]``
  31 + Event list, counts cube, or observation definition file
  32 +
  33 +``(ds9file = NONE) [file]``
  34 + Output DS9 region file containing models
  35 +
  36 +``(pnt_type=cross) <circle|box|diamond|cross|x|arrow|boxcircle> [string]``
  37 + Marker type for point sources
  38 +
  39 +``pnt_mark_size [integer]``
  40 + Marker size for point sources
  41 +
  42 +``(show_labels=yes) [boolean]``
  43 + Add source labels?
  44 +
  45 +``(width=2) [integer]``
  46 + Line width for regions
  47 +
  48 + ``(font=helvetica) <helvetica|times|courier> [string]``
  49 + Font for source labels
  50 +
  51 +``(fontsize=12) [integer]``
  52 + Font size for source labels
  53 +
  54 +``(fonttype=normal) <normal|bold> [string]``
  55 + Use normal or bold font?
  56 +
  57 +``(fonttype2=roman) <roman|italic> [string]``
  58 + Use roman or italic font?
  59 +
  60 +``(show_ext_type=yes) [boolean]``
  61 + Show type of extended model in source name?
  62 +
  63 +``(free_color=green) [string]``
  64 + Color for sources with free parameters (any ds9 color or hex code)
  65 +
  66 +``(fixed_color=magenta) [string]``
  67 + Color for sources without free parameters (any ds9 color or hex code)
  68 +
  69 +
  70 +Standard parameters
  71 +-------------------
  72 +
  73 +``(chatter = 2) [integer]``
  74 + Verbosity of the executable:
  75 + chatter = 0: no information will be logged
  76 +
  77 + chatter = 1: only errors will be logged
  78 +
  79 + chatter = 2: errors and actions will be logged
  80 +
  81 + chatter = 3: report about the task execution
  82 +
  83 + chatter = 4: detailed report about the task execution
  84 +
  85 +``(clobber = yes) [boolean]``
  86 + Specifies whether an existing output counts cube should be overwritten.
  87 +
  88 +``(debug = no) [boolean]``
  89 + Enables debug mode. In debug mode the executable will dump any log file output to the console.
  90 +
  91 +``(mode = ql) [string]``
  92 + Mode of automatic parameters (default is "ql", i.e. "query and learn").
  93 +
  94 +``(logfile = csmodelinfo.log) [filename]``
  95 + Log filename.
  96 +
  97 +
  98 +Related tools or scripts
  99 +------------------------
  100 +
  101 +None
0 102 \ No newline at end of file
... ...
doc/source/reference_manual/csmodelmerge.rst 0 → 100644
  View file @14f9d87
  1 +.. _csmodelmerge:
  2 +
  3 +csmodelmerge
  4 +============
  5 +
  6 +Merges an arbitrary number of model XML files into a single file.
  7 +
  8 +
  9 +Synopsis
  10 +--------
  11 +
  12 +This script merges several model XML file into a single model XML file. The
  13 +files are passed via the ``inmodels`` parameter. There are 4 options to specify
  14 +a list of files that should be merged:
  15 +- a space-separated list of file names (e.g. model1.xml model2.xml)
  16 +- a comma-separated list of file names (e.g. model1.xml,model2.xml)
  17 +- a wildcard string (e.g. mymodel*.xml)
  18 +- an ASCII file containing the file names, one file per line (e.g. @mymodels.txt)
  19 +
  20 +Note that the "@" needs to be specified in case of an ASCII file name. It is
  21 +also important to note that models with the same name cannot be appended. The
  22 +tool will throw and exception if the provided file contain models with the same
  23 +name.
  24 +
  25 +
  26 +General parameters
  27 +------------------
  28 +
  29 +``inmodels [string]``
  30 + Input model XML files
  31 +
  32 +``outmodel [file]``
  33 + Output model file
  34 +
  35 +
  36 +Standard parameters
  37 +-------------------
  38 +
  39 +``(chatter = 2) [integer]``
  40 + Verbosity of the executable:
  41 + chatter = 0: no information will be logged
  42 +
  43 + chatter = 1: only errors will be logged
  44 +
  45 + chatter = 2: errors and actions will be logged
  46 +
  47 + chatter = 3: report about the task execution
  48 +
  49 + chatter = 4: detailed report about the task execution
  50 +
  51 +``(clobber = yes) [boolean]``
  52 + Specifies whether an existing output counts cube should be overwritten.
  53 +
  54 +``(debug = no) [boolean]``
  55 + Enables debug mode. In debug mode the executable will dump any log file output to the console.
  56 +
  57 +``(mode = ql) [string]``
  58 + Mode of automatic parameters (default is "ql", i.e. "query and learn").
  59 +
  60 +``(logfile = csmodelmerge.log) [filename]``
  61 + Log filename.
  62 +
  63 +
  64 +Related tools or scripts
  65 +------------------------
  66 +
  67 +None
0 68 \ No newline at end of file
... ...
doc/source/reference_manual/csobs2caldb.rst 0 → 100644
  View file @14f9d87
  1 +.. _csobs2caldb:
  2 +
  3 +csobs2caldb
  4 +===========
  5 +
  6 +Creates a caldb entry from an input observation.
  7 +
  8 +
  9 +Synopsis
  10 +--------
  11 +
  12 +This script creates an entry in the local calibration database from an
  13 +input observation container. The caldb entry can be used for simulations
  14 +with :doc:`ctobssim` later on. On default csobs2caldb uses the first observation
  15 +in the given container. This can be modified using the hidden parameter "index"
  16 +(e.g. index=3 instructs the tool to use the third observation in the container).
  17 +Note that for the moment, the script only works for unbinned observations which
  18 +use the latest CTA IRF format (i.e. 2D/3D FITS binary tables).
  19 +
  20 +In particular this script might be useful for simulations of current IACT data.
  21 +Provided a specific observation with IRFs e.g. at certain zenith/azimuth angle,
  22 +the user can create a caldb entry using this tool and subsequently simulate e.g.
  23 +50 hours using this configuration.
  24 +
  25 +General parameters
  26 +------------------
  27 +
  28 +``inobs [file]``
  29 + Input event list, counts cube or observation definition XML file.
  30 +
  31 +``rspname [string]``
  32 + Response output name (e.g. Zenith50).
  33 +
  34 +``(outirfs = irf_file.fits) [file]``
  35 + Output IRF file name.
  36 +
  37 +``(index = 0) [integer]``
  38 + Index of observation to be used from XML file.
  39 +
  40 +
  41 +Standard parameters
  42 +-------------------
  43 +
  44 +``(chatter = 2) [integer]``
  45 + Verbosity of the executable:
  46 + chatter = 0: no information will be logged
  47 +
  48 + chatter = 1: only errors will be logged
  49 +
  50 + chatter = 2: errors and actions will be logged
  51 +
  52 + chatter = 3: report about the task execution
  53 +
  54 + chatter = 4: detailed report about the task execution
  55 +
  56 +``(clobber = yes) [boolean]``
  57 + Specifies whether an existing output counts cube should be overwritten.
  58 +
  59 +``(debug = no) [boolean]``
  60 + Enables debug mode. In debug mode the executable will dump any log file output to the console.
  61 +
  62 +``(mode = ql) [string]``
  63 + Mode of automatic parameters (default is "ql", i.e. "query and learn").
  64 +
  65 +``(logfile = csobs2caldb.log) [filename]``
  66 + Log filename.
  67 +
  68 +
  69 +Related tools or scripts
  70 +------------------------
  71 +
  72 +:doc:`cscaldb`
... ...
doc/source/reference_manual/csobsdef.rst
  View file @14f9d87
... ... @@ -10,9 +10,9 @@ Synopsis
10 10 --------
11 11  
12 12 The csobsdef script generates an observation definition file from
13   -a pointing list. The pointing list is a colon separated value ASCII
14   -file with header keywords in the first row followed by a list of
15   -pointings (one pointing per row). The following header keywords
  13 +a pointing list. The pointing list is a comma-separated value (CSV)
  14 +ASCII file with header keywords in the first row followed by a list
  15 +of pointings (one pointing per row). The following header keywords
16 16 are supported (case sensitive, column order irrelevant):
17 17  
18 18 * name - Observation name string
... ... @@ -32,7 +32,7 @@ are supported (case sensitive, column order irrelevant):
32 32 Only the pairs (ra,dec) or (lon,lat) are mandatory header keywords.
33 33 All other keywords are optional and can be specified when calling
34 34 csobsdef as user parameters. The only exception is the "duration"
35   -keyword that will automatically queried.
  35 +keyword that will automatically be queried.
36 36  
37 37 Here some usage examples:
38 38  
... ... @@ -46,15 +46,15 @@ Here some usage examples:
46 46 Creates observation definition file with a ROI radius of 5 deg.
47 47  
48 48 ``csobsdef caldb=prod2 irf=South_50h``
49   - Creates observation definition file using the "South_50h" IRF in the
50   - "prod2" calibration database.
  49 + Creates observation definition file using the ``South_50h`` IRF in the
  50 + ``prod2`` calibration database.
51 51  
52 52  
53 53 General parameters
54 54 ------------------
55 55  
56 56 ``inpnt [file]``
57   - Pointing definition ASCII file in colon separated values format.
  57 + Pointing definition ASCII file in comma-separated value (CSV) format.
58 58  
59 59 ``outobs [file]``
60 60 Output Observation Definition XML file.
... ... @@ -109,7 +109,7 @@ Standard parameters
109 109 Log filename.
110 110  
111 111  
112   -Related tools
113   --------------
  112 +Related tools or scripts
  113 +------------------------
114 114  
115 115 None
... ...
doc/source/reference_manual/csobsinfo.rst 0 → 100644
  View file @14f9d87
  1 +.. _csobsinfo:
  2 +
  3 +csobsinfo
  4 +=========
  5 +
  6 +Dumps information about an observation container into log file or on
  7 +screen.
  8 +
  9 +
  10 +Synopsis
  11 +--------
  12 +
  13 +This script provides detailed information about a given observation container.
  14 +For IACT observations usually several observations with different configurations
  15 +are combined. The script computes e.g. the overall energy range which could be
  16 +an important input for :doc:`ctbin` to create a suitable energy range. In
  17 +addition the script prints the pointing attributes like the average
  18 +zenith/azimuth angle. If the hidden boolean parameter "offset" is specified to
  19 +"yes", the script queries for the target position and computes the run-by-run
  20 +offset as well as its average. In the observation summary, the time range of
  21 +the observations including total ontime and (dead-time corrected) livetime is
  22 +shown.
  23 +
  24 +The script further contains the hidden parameter "ds9file". If specified with
  25 +a file name, the tool writes out a ds9 region file including a cross for each
  26 +pointing position in the sky.
  27 +
  28 +When executed from within python, the script provides methods to return arrays
  29 +containing observation-wise parameters. This might be useful for graphical
  30 +display within a script. The following methods are implemented:
  31 +- zeniths (returning all zenith angles)
  32 +- azimuths (returning all azimuth angles)
  33 +- offsets (returning all offset angles, provided the hidden parameter offset=yes)
  34 +- ebounds (returning energy boundaries)
  35 +- gtis (returning good time intervals)
  36 +
  37 +
  38 +General parameters
  39 +------------------
  40 +
  41 +``inobs [file]``
  42 + Event list, counts cube, or observation definition file
  43 +
  44 +``(offset = no) [file]``
  45 + Compute offset from target to pointing positions
  46 +
  47 +``ra [real]``
  48 + Target right ascension for offset computation (only queried if offset=yes)
  49 +
  50 +``dec [real]``
  51 + Target declination for offset computation (only queried if offset=yes)
  52 +
  53 +``(ds9file = NONE) [file]``
  54 + DS9 region file containing pointings
  55 +
  56 +
  57 +Standard parameters
  58 +-------------------
  59 +
  60 +``(chatter = 2) [integer]``
  61 + Verbosity of the executable:
  62 + chatter = 0: no information will be logged
  63 +
  64 + chatter = 1: only errors will be logged
  65 +
  66 + chatter = 2: errors and actions will be logged
  67 +
  68 + chatter = 3: report about the task execution
  69 +
  70 + chatter = 4: detailed report about the task execution
  71 +
  72 +``(clobber = yes) [boolean]``
  73 + Specifies whether an existing output counts cube should be overwritten.
  74 +
  75 +``(debug = no) [boolean]``
  76 + Enables debug mode. In debug mode the executable will dump any log file output to the console.
  77 +
  78 +``(mode = ql) [string]``
  79 + Mode of automatic parameters (default is "ql", i.e. "query and learn").
  80 +
  81 +``(logfile = csobsinfo.log) [filename]``
  82 + Log filename.
  83 +
  84 +
  85 +Related tools or scripts
  86 +------------------------
  87 +
  88 +None
0 89 \ No newline at end of file
... ...
doc/source/reference_manual/cspull.rst
  View file @14f9d87
... ... @@ -3,17 +3,33 @@
3 3 cspull
4 4 ======
5 5  
6   -Generates pull distribution for all model parameters.
  6 +Generates pull distribution for all free model parameters.
7 7  
8 8  
9 9 Synopsis
10 10 --------
11 11  
12   -Generates pull distributions for all parameters in a model. The pull is
13   -defined by the fitted value minus the simulated true value, devided by
14   -the statistical uncertainty. For unbiased parameter estimates, the pull
15   -distribution should follow a Gaussian centred on 0 and a sigma parameter
16   -of 1.
  12 +This script generates pull distributions for all free model parameters.
  13 +The pull is defined as the fitted model parameter value minus the true
  14 +value, devided by the parameter error. cspull will perform ``ntrials``
  15 +statistically independent Monte Carlo simulations followed by maximum
  16 +likelihood model fitting to derive the pull distribution for each free
  17 +model parameter. If the model fit is unbiased and the parameters are
  18 +correct, the pull distribution should follow a Gaussian centred on 0
  19 +and with a sigma parameter of 1.
  20 +
  21 +cspull will generate an ASCII file in comma-separated value (CSV) format,
  22 +containing one row per pull. The first row is a header row providing the
  23 +column names. The following rows give the pull results, one row per pull.
  24 +This includes for each parameter the parameter value, error and pull. The
  25 +maximum likelihood value and the observed and the estimated number of counts
  26 +are also given.
  27 +
  28 +From the output file, pull distribution plots can be generated using for
  29 +example the ``show_pull_histogram.py`` script in the examples folder. The
  30 +script ``show_pull_evolution.py`` in the same folder shows the evolution
  31 +of the mean and standard deviation of the pull as function of the number
  32 +of trials. Both scripts require matplotlib for plotting.
17 33  
18 34  
19 35 General parameters
... ... @@ -23,8 +39,7 @@ General parameters
23 39 Event list, counts cube, or observation definition XML file.
24 40  
25 41 ``inmodel [file]``
26   - XML file that describes the astrophysical sources and the instrumental
27   - background.
  42 + Input model XML file.
28 43  
29 44 ``outfile [file]``
30 45 ASCII file containing the individual pull values.
... ... @@ -118,7 +133,8 @@ Standard parameters
118 133 Log filename.
119 134  
120 135  
121   -Related tools
122   --------------
  136 +Related tools or scripts
  137 +------------------------
123 138  
124   -None
  139 +:doc:`ctlike`
  140 +:doc:`cstsdist`
... ...
doc/source/reference_manual/csresmap.rst
  View file @14f9d87
... ... @@ -3,13 +3,26 @@
3 3 csresmap
4 4 ========
5 5  
6   -Generates residual counts map.
  6 +Generates residual map.
7 7  
8 8  
9 9 Synopsis
10 10 --------
11 11  
12   -This scripts generates a residual counts map.
  12 +This scripts generates a residual map for a given model. It works for
  13 +event lists, counts cubes or observation definition files. For event
  14 +lists, parameters that define the spatial and spectral binning need to
  15 +be provided so that the script can bin the data internally. The model
  16 +is then convolved with the instrumental response function for that
  17 +binning and used for residual computation. Before residual computation,
  18 +the counts and model cubes are collapsed into maps by summing over all
  19 +energies. Three options exist then for residual computation:
  20 +
  21 +* the subtraction of the model from the counts (SUB)
  22 +* the subtraction and division by the model (SUBDIV)
  23 +* the subtraction and division by the square root of the model (SUBDIVSQRT)
  24 +
  25 +The residual map is written into a FITS file.
13 26  
14 27  
15 28 General parameters
... ... @@ -19,7 +32,7 @@ General parameters
19 32 Input event list, counts cube or observation definition XML file.
20 33  
21 34 ``inmodel [file]``
22   - Model XML file.
  35 + Input model XML file.
23 36  
24 37 ``outmap [file]``
25 38 Output residual counts map file.
... ... @@ -94,8 +107,11 @@ Standard parameters
94 107 ``(mode = ql) [string]``
95 108 Mode of automatic parameters (default is "ql", i.e. "query and learn").
96 109  
  110 +``(logfile = csresmap.log) [string]``
  111 + Log filename.
  112 +
97 113  
98   -Related tools
99   --------------
  114 +Related tools or scripts
  115 +------------------------
100 116  
101 117 None
... ...
doc/source/reference_manual/cssens.rst
  View file @14f9d87
... ... @@ -3,18 +3,40 @@
3 3 cssens
4 4 ======
5 5  
6   -Computes the CTA sensitivity for a number of energy bins.
  6 +Computes differential or integrated CTA sensitivity.
7 7  
8 8  
9 9 Synopsis
10 10 --------
11 11  
12   -Computes the CTA sensitivity for a number of energy bins using :doc:`ctlike`.
13   -Crab spectra are fitted in narrow energy bins to simulated data, and the
14   -flux level is determined that leads to a particular significance. The
15   -significance is estimated using the Test Statistic value. The simplified
16   -assumption is made that the significance (in Gaussian sigma) is the square
17   -root of the Test Statistic.
  12 +This script computes the differential or integrated CTA sensitivity using
  13 +maximum likelihood fitting of a test source. The differential sensitivity
  14 +is determined for a number of energy bins, the integral sensitivity is
  15 +determined for a number of energy thresholds. The test source is fitted to
  16 +simulated data using :doc:`ctlike` to determine it's detection significance
  17 +as a function of source flux. The source flux is then varied until the
  18 +source significance achieves a given level, specified by the (hidden)
  19 +significance parameter ``sigma``. To damp variations between individual
  20 +Monte Carlo simulations, a sliding average is applied in the significance
  21 +computation (controlled by hidden ``num_avg`` parameter).
  22 +
  23 +The significance is estimated using the Test Statistic value, defined as
  24 +twice the log-likelihood difference that is obtained when fitting the
  25 +simulated data with and without the test source. The simplified assumption
  26 +is made that the significance (in Gaussian sigma) is the square root of
  27 +the Test Statistic.
  28 +
  29 +cssens will generate an ASCII file in comma-separated value (CSV) format
  30 +containing the sensitivity as function of energy. The first row is a header
  31 +row providing the column names. The following rows provide the mean
  32 +logarithmic energy and the boundaries of the energy bin for which the
  33 +sensitivity was computed. They also provide the flux within the energy bin
  34 +in Crab units, in photons (ph/cm2/s) and in energy (ers/cm2/s). Finally,
  35 +the sensitivity is given as the test source spectrum evaluated at the mean
  36 +logarithmic energy multiplied by the energy squared (erg/cm2/s).
  37 +
  38 +The sensitivity can be displayed using the ``show_sensitivity.py`` script
  39 +in the example folder. Matplotlib is required to execute the script.
18 40  
19 41  
20 42 General parameters
... ... @@ -24,7 +46,7 @@ General parameters
24 46 Input event list, counts cube or observation definition XML file.
25 47  
26 48 ``inmodel [file]``
27   - Input source model XML file.
  49 + Input model XML file.
28 50  
29 51 ``srcname [string]``
30 52 Name of the source in the source model XML file which should be used
... ... @@ -110,7 +132,7 @@ Standard parameters
110 132 Log filename.
111 133  
112 134  
113   -Related tools
114   --------------
  135 +Related tools or scripts
  136 +------------------------
115 137  
116   -None
  138 +:doc:`ctlike`
... ...
doc/source/reference_manual/csspec.rst
  View file @14f9d87
... ... @@ -9,7 +9,40 @@ Computes spectrum for a given source.
9 9 Synopsis
10 10 --------
11 11  
12   -Computes spectral points for a given source.
  12 +This script computes the source spectrum by fitting a model in a given set
  13 +of spectral bins. The model fit per spectral bin is performed using :doc:`ctlike`
  14 +and the script provides the possibility to fix sources other than the
  15 +source of interest (hidden parameter ``fix_srcs``) or to fix the background
  16 +model component(s) (hidden parameter ``fix_bkg``). The script computes the
  17 +source flux and its uncertainty in each spectral bin, as well as the
  18 +significance of the source detection. Optionally, it also computes an upper
  19 +flux limit that is particularily useful in case that the source is not
  20 +significantly detected within a spectral bin (hidden parameter ``calc_ulim``).
  21 +
  22 +The script works on binned and unbinned data.
  23 +
  24 +For unbinned data, the spectral binning is either defined by a FITS file
  25 +containing the energy boundaries of each bin (option ``ebinalg=FILE``) or
  26 +as ``enumbins`` bins spread linearly (option ``ebinalg=LIN``) or
  27 +logarithmically (option ``ebinalg=LOG``) from a minimum energy given by
  28 +``emin`` to a maximum energy given by ``emax``.
  29 +
  30 +For binned data, all energy bins within the counts cube that overlap with
  31 +the energy range spanned by ``emin`` and ``emax`` are considered. The number
  32 +of spectral bins is only approximately determined by the ``enumbins`` parameter.
  33 +Naturally, the script cannot create more spectral bins than the number of
  34 +energy bins that are available in the cube. Also, in case that ``enumbins``
  35 +is smaller than the number of energy bins in the cube, the script will fit
  36 +several layers of the counts cube for each spectral bin. The number of
  37 +layers fit is determined by the total number of energy bins divided by the
  38 +``enumbins`` parameter.
  39 +
  40 +On output, the script will provide a FITS file with the fitted source
  41 +spectrum in form of a binary table. Each row corresponds to a spectral bin.
  42 +The columns are the mean as well as the boundaries of the spectral bin,
  43 +the fitted flux and flux error, the Test Statistics value (option
  44 +``calc_ts=yes``), the upper flux limit (option ``calc_ulim=yes``) and the
  45 +predicted number of events (only for unbinned data).
13 46  
14 47  
15 48 General parameters
... ... @@ -19,7 +52,7 @@ General parameters
19 52 Input event list, counts cube or observation definition XML file.
20 53  
21 54 ``inmodel [file]``
22   - Input source model XML file.
  55 + Input model XML file.
23 56  
24 57 ``srcname [string]``
25 58 Name of the source in the source model XML file which should be used
... ... @@ -43,6 +76,9 @@ General parameters
43 76 ``irf [string]``
44 77 Instrumental response function.
45 78  
  79 +``(edisp = no) [boolean]``
  80 + Apply energy dispersion to response computation?
  81 +
46 82 ``emin [real]``
47 83 Lower energy limit of events (in TeV).
48 84  
... ... @@ -50,41 +86,14 @@ General parameters
50 86 Upper energy limit of events (in TeV).
51 87  
52 88 ``enumbins [integer]``
53   - Number of energy bins (0=unbinned).
  89 + Number of energy bins.
54 90  
55   -``(ebinalg = LOG) <FILE|LIN|LOG> [string]``
  91 +``ebinalg <FILE|LIN|LOG> [string]``
56 92 Algorithm for defining energy bins.
57 93  
58   -``binned [boolean]``
59   - Specifies whether a binned computation should be used.
60   -
61   -``(nebins = 5) [integer]``
62   - Number of bins per spectral point for binned analysis.
63   -
64   -``coordsys <CEL|GAL> [string]``
65   - Coordinate system (CEL - celestial, GAL - galactic).
66   -
67   -``proj <AIT|AZP|CAR|MER|MOL|STG|TAN> [string]``
68   - Projection method.
69   -
70   -``xref [real]``
71   - Right Ascension / Galactic longitude of image centre (J2000, in degrees).
72   -
73   -``yref [real]``
74   - Declination / Galactic latitude of image centre (J2000, in degrees).
  94 +``ebinfile [file]``
  95 + Name of the file containing the energy bin definition.
75 96  
76   -``nxpix [integer]``
77   - Size of the Right Ascension / Galactic longitude axis (in pixels).
78   -
79   -``nypix [integer]``
80   - Size of the Declination / Galactic latitude axis (in pixels).
81   -
82   -``binsz [real]``
83   - Pixel size (in degrees/pixel).
84   -
85   -``(anumbins = 200) [integer]``
86   - Number of angular separation bins.
87   -
88 97 ``(calc_ts = yes) [boolean]``
89 98 Compute TS for each spectral point?
90 99  
... ... @@ -126,7 +135,7 @@ Standard parameters
126 135 Log filename.
127 136  
128 137  
129   -Related tools
130   --------------
  138 +Related tools or scripts
  139 +------------------------
131 140  
132   -None
  141 +:doc:`ctlike`
... ...
doc/source/reference_manual/cstsdist.rst
  View file @14f9d87
... ... @@ -3,14 +3,30 @@
3 3 cstsdist
4 4 ========
5 5  
6   -Generates the TS distribution for a particular model.
  6 +Generates the TS distribution for a given source.
7 7  
8 8  
9 9 Synopsis
10 10 --------
11 11  
12   -Generates the Test Statistics (TS) distribution for a particular model
13   -based on Monte-Carlo simulations.
  12 +This script generates the Test Statistics (TS) distribution for a given
  13 +source by repeatedly computing the TS value for ``ntrials`` simulated data
  14 +sets. The Test Statistics is defined as twice the log-likelihood difference
  15 +that is obtained when fitting simulated data with and without a given
  16 +source model component.
  17 +
  18 +This script either performs an unbinned or a binned simulation, stacked
  19 +analysis is not yet supported.
  20 +
  21 +cstsdist will create an ASCII file in comma-separated value (CSV) format,
  22 +containing one row per TS computation. The first row is a header row providing
  23 +the column names. The following rows give the TS value, the log-likelihood
  24 +values of the fit with or without the source, the number of observed and
  25 +fitted events, as well as the values and errors for all fitted parameters.
  26 +
  27 +From the output file, TS distribution plots can be generated using for
  28 +example the ``show_ts_distribution.py`` script in the examples folder. The
  29 +script require matplotlib for plotting.
14 30  
15 31  
16 32 General parameters
... ... @@ -20,11 +36,11 @@ General parameters
20 36 Input event list, counts cube or observation definition XML file.
21 37  
22 38 ``inmodel [file]``
23   - Input source model XML file.
  39 + Input model XML file.
24 40  
25 41 ``srcname [string]``
26 42 Name of the source in the source model XML file which should be used
27   - for sensitivity computation.
  43 + for Test Statistics computation.
28 44  
29 45 ``outfile [file]``
30 46 ASCII file containing the TS distribution values.
... ... @@ -118,7 +134,9 @@ Standard parameters
118 134 Log filename.
119 135  
120 136  
121   -Related tools
122   --------------
  137 +Related tools or scripts
  138 +------------------------
  139 +
  140 +:doc:`ctlike`
  141 +:doc:`cspull`
123 142  
124   -None
... ...
doc/source/reference_manual/cstsmapmerge.rst 0 → 100644
  View file @14f9d87
  1 +.. _cstsmapmerge:
  2 +
  3 +cstsmapmerge
  4 +============
  5 +
  6 +Merges slices of splitted tsmap computations.
  7 +
  8 +
  9 +Synopsis
  10 +--------
  11 +
  12 +In case a TS map has been computed using the option to split the calculations
  13 +into several jobs, this tool is required to merge the output into one final
  14 +map again. Running :doc:`cttsmap` with the hidden parameters ``binmin`` and
  15 +``binmax`` specified will result in several sliced TS maps. This script merges
  16 +them into one FITS file. The input slices can be passed via the ``inmaps``
  17 +parameter. There are 4 options to specify a list of files that should be merged:
  18 +- a space-separated list of file names (e.g. tsmap1.fits tsmap2.fits)
  19 +- a comma-separated list of file names (e.g. tsmap1.fits,tsmap2.fits)
  20 +- a wildcard string (e.g. tsmap*.xml)
  21 +- an ASCII file containing the file names, one file per line (e.g. @mymaps.txt)
  22 +
  23 +Note that the "@" needs to be specified in case of an ASCII file name.
  24 +
  25 +General parameters
  26 +------------------
  27 +
  28 +``inmaps [string]``
  29 + Input TS map FITS files
  30 +
  31 +``outmap [file]``
  32 + Output TS map FITS file
  33 +
  34 +``(overwrite=yes) [boolean]``
  35 + Overwrite previously filled bins?
  36 +
  37 +``(delete=no) [boolean]``
  38 + Delete merged files?
  39 +
  40 +
  41 +Standard parameters
  42 +-------------------
  43 +
  44 +``(chatter = 2) [integer]``
  45 + Verbosity of the executable:
  46 + chatter = 0: no information will be logged
  47 +
  48 + chatter = 1: only errors will be logged
  49 +
  50 + chatter = 2: errors and actions will be logged
  51 +
  52 + chatter = 3: report about the task execution
  53 +
  54 + chatter = 4: detailed report about the task execution
  55 +
  56 +``(clobber = yes) [boolean]``
  57 + Specifies whether an existing output counts cube should be overwritten.
  58 +
  59 +``(debug = no) [boolean]``
  60 + Enables debug mode. In debug mode the executable will dump any log file output to the console.
  61 +
  62 +``(mode = ql) [string]``
  63 + Mode of automatic parameters (default is "ql", i.e. "query and learn").
  64 +
  65 +``(logfile = cstsmapmerge.log) [filename]``
  66 + Log filename.
  67 +
  68 +
  69 +Related tools or scripts
  70 +------------------------
  71 +
  72 +:ref:`cstsmap`
... ...
doc/source/reference_manual/ctbin.rst
  View file @14f9d87
... ... @@ -3,18 +3,27 @@
3 3 ctbin
4 4 =====
5 5  
6   -Generate a counts cube for binned maximum likelihood analysis.
  6 +Generate counts cube from event list(s).
7 7  
8 8  
9 9 Synopsis
10 10 --------
11 11  
12   -This tool computes the counts cube for use in a binned maximum likelihood
13   -analysis. The counts cubes are 3-dimensional data cubes spanned by Right
14   -Ascension or Galactic longitude, Declination or Galactic latitude, and energy.
15   -The energy binning may be either linear, logarithmic, or custom defined.
16   -If an observation definition XML file containing several observations is
17   -provided on input, the tool will stack all data into a single counts cube.
  12 +This tool creates a counts cube and fills it with events. A counts cube is
  13 +a 3-dimensional data cube spanned by Right Ascension or Galactic longitude,
  14 +Declination or Galactic latitude, and energy. The energy binning may be either
  15 +linear, logarithmic, or custom defined using an input file. The events are
  16 +either taken from a single event list file or from the event lists that are
  17 +specified in an observation definition file. In case that multiple event
  18 +lists are given in an observation definition file, the tool will loop over
  19 +all event lists and fill all events into a single counts cube.
  20 +
  21 +ctbin generates a counts cube FITS file comprising three extensions. The
  22 +primary extension contains a 3-dimensional image that contains the counts
  23 +cube values. The next extension named ``EBOUNDS`` contains a binary table
  24 +that defines the energy boundaries of the counts cube. The last extension
  25 +named ``GTI`` contains a binary table that defines the Good Time Intervals
  26 +of all event lists that have been filled into the counts cube.
18 27  
19 28  
20 29 General parameters
... ... @@ -94,7 +103,9 @@ Standard parameters
94 103 Name of log file.
95 104  
96 105  
97   -Related tools
98   --------------
  106 +Related tools or scripts
  107 +------------------------
99 108  
100   -None
  109 +:doc:`ctexpcube`
  110 +:doc:`ctpsfcube`
  111 +:doc:`ctbkgcube`
... ...
doc/source/reference_manual/ctbkgcube.rst
  View file @14f9d87
... ... @@ -3,36 +3,70 @@
3 3 ctbkgcube
4 4 =========
5 5  
6   -Generate a background cube for binned maximum likelihood analysis.
  6 +Generate background cube for a counts cube.
7 7  
8 8  
9 9 Synopsis
10 10 --------
11 11  
12   -This tool generates a background cube for use in a binned maximum
13   -likelihood analysis.
  12 +This tool generates a background cube for a counts cube based on an input
  13 +model. A background cube is a 3-dimensional cube spanned by Right Ascension
  14 +or Galactic longitude, Declination or Galactic latitude, and energy. The
  15 +energy binning may be either linear, logarithmic, or custom defined using an
  16 +input file. The input model is used to predict the expected number of
  17 +background counts in each background cube bin.
  18 +
  19 +ctbkgcube requires on input the event list or observation definition file
  20 +that has been used in the generation of the counts cube using :doc:`ctbin`.
  21 +
  22 +To assure consistency between an existing counts cube and the
  23 +corresponding background cube, it is recommended to specify the counts
  24 +cube as ``incube`` parameter. This will instruct ctbkgcube to extract the
  25 +background cube definition (such as sky coordinates and projection, number
  26 +of pixels, pixel scale, energy binning) from the counts cube.
  27 +
  28 +ctbkgcube generates a background cube FITS file comprising two extensions.
  29 +The primary extension contains a 3-dimensional image that contains the
  30 +background cube values. The next extension named ``EBOUNDS`` contains a
  31 +binary table that defines the energy boundaries of the background cube.
  32 +
  33 +ctbkgcube generates also an output model XML file that can serve as input
  34 +for a maximum likelihood analysis. The output model XML file is a copy of
  35 +the input model XML file where the input background model has been replaced
  36 +by a background model of type ``CTACubeBackground``. The ``CTACubeBackground``
  37 +background model instructs any tool analysing binned data to extract
  38 +background information from a background cube. The ``CTACubeBackground``
  39 +model has a spectral component that can be adjusted in a maximum
  40 +likelihood fit to accomodate for uncertainties in the prediction of the
  41 +energy dependence of the background rate. ctbkgcube will use a power law
  42 +as spectral component, but you can replace this by any component of your
  43 +choice.
  44 +
14 45  
15 46  
16 47 General parameters
17 48 ------------------
18 49  
19 50 ``inobs [file]``
20   - Input event list, cube or observation definition XML file.
  51 + Input event list or observation definition XML file.
21 52  
22 53 ``inmodel [file]``
23   - Input (background) model XML file.
  54 + Input model XML file.
24 55  
25 56 ``incube [file]``
26   - Counts cube for background cube definition.
27   -
28   -``outcube [file]``
29   - Output background cube file.
  57 + Input counts cube file to extract background cube definition.
30 58  
31 59 ``caldb [string]``
32 60 Calibration database.
33 61  
34 62 ``irf [string]``
35   - Response function.
  63 + Instrument response function.
  64 +
  65 +``outcube [file]``
  66 + Output background cube file.
  67 +
  68 +``outmodel [file]``
  69 + Output model XML file.
36 70  
37 71 ``ebinalg <FILE|LIN|LOG> [string]``
38 72 Algorithm for defining energy bins.
... ... @@ -102,7 +136,7 @@ Standard parameters
102 136 Name of log file.
103 137  
104 138  
105   -Related tools
106   --------------
  139 +Related tools or scripts
  140 +------------------------
107 141  
108   -None
  142 +:doc:`ctbin`
... ...
doc/source/reference_manual/ctbutterfly.rst
  View file @14f9d87
... ... @@ -9,16 +9,31 @@ Computes butterfly diagram for a power law model.
9 9 Synopsis
10 10 --------
11 11  
12   -Calculates the confidence band of a power law model, taking into account the
13   -covariance matrix resulting from a maximum likelihood fit. The tool derives
14   -the envelope of all power law models whose prefactor and spectral index fall
15   -within the error ellipse that is associated with the covariance of the
16   -parameters. It outputs an ASCII file in column separated value (CSV) format
17   -containing the results. Each row in the result file corresponds to an energy.
18   -The columns give the energy in MeV, the fitted intensity in ph/cm2/s/MeV,
19   -and the minimum and maximum intensity that envelope the power law model
20   -with a given confidence (by default a confidence level of 68% is used, but
21   -the level can be adjusted using the ``confidence`` parameter).
  12 +This tool calculates a butterfly diagram for a specific source with power law
  13 +spectral model. The butterfly diagram is the envelope of all power law models
  14 +that are within a given confidence limit compatible with the data. By default
  15 +a confidence level of 68% is used, but the level can be adjusted using the
  16 +hidden ``confidence`` parameter. ctbutterfly computes this envelope by
  17 +evaluating for each energy the minimum and maximum intensity of all power law
  18 +models that fall within the error ellipse of the prefactor and index parameters.
  19 +The error ellipse is derived from the covariance matrix of a maximum likelihood
  20 +fit.
  21 +
  22 +ctbutterfly assumes that the input model (parameter ``inmodel``) has been
  23 +adjusted using :doc:`ctlike` to the data, but if this is not the case you
  24 +can request a maximum likelihood fit by setting the hidden parameter ``fit=yes``.
  25 +
  26 +ctbutterfly writes the butterfly diagram into an ASCII file with 4 columns
  27 +separated by a whitespace. Each row in the result file corresponds to a specific
  28 +energy. The meaning of the columns are:
  29 +
  30 +* Energy in MeV
  31 +* Fitted intensity for that energy in ph/cm2/s/MeV
  32 +* Minimum intensity for that energy in ph/cm2/s/MeV
  33 +* Maximum intensity for that energy in ph/cm2/s/MeV
  34 +
  35 +The butterfly diagram can be displayed using the ``show_butterfly.py`` script
  36 +in the example folder.
22 37  
23 38  
24 39 General parameters
... ... @@ -28,19 +43,19 @@ General parameters
28 43 Input event list, counts cube or observation definition XML file.
29 44  
30 45 ``inmodel [file]``
31   - Model XML file containing the source and background definitions.
  46 + Input model XML file.
32 47  
33 48 ``srcname [string]``
34   - Name of model component for which butterfly should be computed.
  49 + Name of source model for which the butterfly diagram should be computed.
35 50  
36 51 ``expcube [file]``
37   - Exposure cube file (only needed for stacked analysis).
  52 + Input exposure cube file (only needed for stacked analysis).
38 53  
39 54 ``psfcube [file]``
40   - PSF cube file (only needed for stacked analysis).
  55 + Input PSF cube file (only needed for stacked analysis).
41 56  
42 57 ``bkgcube [file]``
43   - Background cube file (only needed for stacked analysis).
  58 + Input background cube file (only needed for stacked analysis).
44 59  
45 60 ``caldb [string]``
46 61 Calibration database.
... ... @@ -54,8 +69,9 @@ General parameters
54 69 ``outfile [file]``
55 70 Output butterfly ASCII file name.
56 71  
57   -``(refit = no) [boolean]``
58   - Performs refitting of solution ignoring any provided covariance matrix.
  72 +``(fit = no) [boolean]``
  73 + Performs maximum likelihood fitting of input model ignoring any provided
  74 + covariance matrix.
59 75  
60 76 ``(confidence = 0.68) [real]``
61 77 Confidence level for error computation.
... ... @@ -107,8 +123,9 @@ Standard parameters
107 123 Name of log file.
108 124  
109 125  
110   -Related tools
111   --------------
  126 +Related tools or scripts
  127 +------------------------
112 128  
  129 +:doc:`ctlike`
113 130 :ref:`ctulimit`
114 131 :ref:`cterror`
... ...
doc/source/reference_manual/ctcubemask.rst
  View file @14f9d87
... ... @@ -3,14 +3,32 @@
3 3 ctcubemask
4 4 ==========
5 5  
6   -Filter a counts cube.
  6 +Mask out bins of a counts cube.
7 7  
8 8  
9 9 Synopsis
10 10 --------
11 11  
12 12 This tool masks out specific regions from a counts cube by setting the
13   -corresponding pixels to negative values.
  13 +corresponding bin values to -1. Bins with negative values will be ignored
  14 +in a maximum likelihood analysis. A mask is applied spatially and spectrally.
  15 +
  16 +ctcubemask applies a spatial mask that is comprised of a circular selection
  17 +region and a list of circular exclusion regions. The circular selection region
  18 +is specified by the sky direction of the centre and the radius of the circle.
  19 +The circular exclusion regions are specified by an ASCII file in ds9 format.
  20 +The ASCII file contains one row per exclusion region, given in the format
  21 +
  22 +``circle(83.63, 21.5, 0.4)``
  23 +
  24 +where ``83.63`` and ``21.5`` are the Right Ascension and Declination of
  25 +the centre and ``0.4`` is the radius (in degrees) of the exclusion circle.
  26 +
  27 +ctcubemask also selects only counts cube energy layers that are fully comprised
  28 +in the energy interval specified by the ``emin`` and ``emax`` parameters.
  29 +
  30 +ctcubemask generates a counts cube FITS file that is a copy of the input
  31 +counts cube and for which all masked bins have been set to -1.
14 32  
15 33  
16 34 General parameters
... ... @@ -19,9 +37,6 @@ General parameters
19 37 ``inobs [file]``
20 38 Input counts cube or observation definition XML file.
21 39  
22   -``regfile [file]``
23   - Exclusion region file in ds9 format.
24   -
25 40 ``outcube [file]``
26 41 Output counts cube or observation definition XML file.
27 42  
... ... @@ -41,6 +56,9 @@ General parameters
41 56 ``rad [real]``
42 57 Radius of circular selection region (in degrees).
43 58  
  59 +``regfile [file]``
  60 + Input exclusion region file in ds9 format.
  61 +
44 62 ``emin [real]``
45 63 Lower energy limit (in TeV).
46 64  
... ... @@ -72,11 +90,11 @@ Standard parameters
72 90 ``(mode = ql) [string]``
73 91 Mode of automatic parameters (default is "ql", i.e. "query and learn").
74 92  
75   -``(logfile = ctexpcube.log) [string]``
  93 +``(logfile = ctcubemask.log) [string]``
76 94 Name of log file.
77 95  
78 96  
79   -Related tools
80   --------------
  97 +Related tools or scripts
  98 +------------------------
81 99  
82   -None
  100 +:doc:`ctbin`
... ...
doc/source/reference_manual/cterror.rst
  View file @14f9d87
... ... @@ -3,15 +3,26 @@
3 3 cterror
4 4 =======
5 5  
6   -Computes parameter errors for a specific sky model component using
7   -a likelihood profile method.
  6 +Computes parameter errors for a source model from the likelihood profiles.
8 7  
9 8  
10 9 Synopsis
11 10 --------
12 11  
13   -This tool computes the parameter errors for a specific sky model using
14   -a likelihood profile method.
  12 +This tool computes the parameter errors for a specific source model using
  13 +the likelihood profiles. Starting from the maximum likelihood model parameters,
  14 +the tool finds the minimum and maximum model parameters that lead to a decrease
  15 +of the likelihood that corresponds to a given confidence level. By default a
  16 +confidence level of 68% is used, but this level can be adjusted using the hidden
  17 +``confidence`` parameter.
  18 +
  19 +cterror generates an output model XML file that contains the values of the
  20 +best fitting model parameters. For all free parameters, an ``error`` attribute
  21 +is added that provides the statistical uncertainty in the parameter estimate
  22 +as obtained from the likelihood profile. While cterror computes asymmetrical
  23 +errors, which are written into the log file, the XML file will contain the
  24 +mean error that is obtained by computing the mean of the negative and the
  25 +positive parameter errors.
15 26  
16 27  
17 28 General parameters
... ... @@ -21,22 +32,19 @@ General parameters
21 32 Input event list, counts cube or observation definition XML file.
22 33  
23 34 ``inmodel [file]``
24   - Model XML file containing the source and background definitions.
25   -
26   -``outmodel [file]``
27   - Model XML file with updated error information.
  35 + Input model XML file.
28 36  
29 37 ``srcname [string]``
30   - Name of model component for which upper limit should be computed.
  38 + Name of source model for which the parameter errors should be computed.
31 39  
32 40 ``expcube [file]``
33   - Exposure cube file (only needed for stacked analysis).
  41 + Input exposure cube file (only needed for stacked analysis).
34 42  
35 43 ``psfcube [file]``
36   - PSF cube file (only needed for stacked analysis).
  44 + Input PSF cube file (only needed for stacked analysis).
37 45  
38 46 ``bkgcube [file]``
39   - Background cube file (only needed for stacked analysis).
  47 + Input background cube file (only needed for stacked analysis).
40 48  
41 49 ``caldb [string]``
42 50 Calibration database.
... ... @@ -47,6 +55,9 @@ General parameters
47 55 ``(edisp = no) [boolean]``
48 56 Applies energy dispersion to response computation.
49 57  
  58 +``outmodel [file]``
  59 + Output model XML file with updated error information.
  60 +
50 61 ``(confidence = 0.68) [real]``
51 62 Confidence level for error computation.
52 63  
... ... @@ -86,8 +97,9 @@ Standard parameters
86 97 Name of log file.
87 98  
88 99  
89   -Related tools
90   --------------
  100 +Related tools or scripts
  101 +------------------------
91 102  
  103 +:ref:`ctlike`
92 104 :ref:`ctulimit`
93 105 :ref:`ctbutterfly`
... ...
doc/source/reference_manual/ctexpcube.rst
  View file @14f9d87
... ... @@ -3,14 +3,39 @@
3 3 ctexpcube
4 4 =========
5 5  
6   -Generate an exposure cube for binned maximum likelihood analysis.
  6 +Generate exposure cube for a counts cube.
7 7  
8 8  
9 9 Synopsis
10 10 --------
11 11  
12   -This tool generates an exposure cube for use in a binned maximum likelihood
13   -analysis.
  12 +This tool generates an exposure cube for a counts cube. An exposure cube is
  13 +a 3-dimensional cube spanned by Right Ascension or Galactic longitude,
  14 +Declination or Galactic latitude, and energy, that gives the exposure
  15 +as function of true sky direction and energy. The energy binning of the cube
  16 +may be either linear, logarithmic, or custom defined using an input file.
  17 +
  18 +ctexpcube requires on input the event list or observation definition file
  19 +that has been used in the generation of the counts cube using :doc:`ctbin`.
  20 +
  21 +For the user's convenience, the counts cube can be specified as ``incube``
  22 +parameter which will instruct ctexpcube to extract the exposure cube
  23 +definition (such as sky coordinates and projection, number of pixels, pixel
  24 +scale, energy binning) from the counts cube. Note, however, that the exposure
  25 +cube is defined in true sky coordinates and energy while the counts cube is
  26 +defined in measured sky coordinates and energy. Consequently, the sky area
  27 +and energy range covered by the exposure cube should be slightly larger than
  28 +that of the counts cube to accomodate for spill over of events due to the
  29 +point spread function and energy dispersion. By computing the exposure map
  30 +on the same grid as the counts cube, the spill over of events from sources at
  31 +the edge of cube will not be handled correctly.
  32 +
  33 +ctexpcube generates an exposure cube FITS file comprising three extensions.
  34 +The primary extension contains a 3-dimensional image that contains the
  35 +exposure values. The next extension named ``EBOUNDS`` contains a binary table
  36 +that defines the energy boundaries of the exposure cube. The last extension
  37 +named ``GTI`` contains a binary table that defines the Good Time Intervals
  38 +of the exposure cube.
14 39  
15 40  
16 41 General parameters
... ... @@ -20,20 +45,20 @@ General parameters
20 45 Input event list or observation definition XML file.
21 46  
22 47 ``incube [file]``
23   - Counts cube for PSF cube definition.
24   -
25   -``outcube [file]``
26   - Output exposure cube file.
  48 + Input counts cube file to extract exposure cube definition.
27 49  
28 50 ``caldb [string]``
29 51 Calibration database.
30 52  
31 53 ``irf [string]``
32   - Response function.
  54 + Instrument response function.
33 55  
34 56 ``(edisp = no) [boolean]``
35 57 Apply energy dispersion for response computation?
36 58  
  59 +``outcube [file]``
  60 + Output exposure cube file.
  61 +
37 62 ``ebinalg <FILE|LIN|LOG> [string]``
38 63 Algorithm for defining energy bins.
39 64  
... ... @@ -102,7 +127,7 @@ Standard parameters
102 127 Name of log file.
103 128  
104 129  
105   -Related tools
106   --------------
  130 +Related tools or scripts
  131 +------------------------
107 132  
108   -None
  133 +:doc:`ctbin`
... ...
doc/source/reference_manual/ctlike.rst
  View file @14f9d87
... ... @@ -3,26 +3,54 @@
3 3 ctlike
4 4 ======
5 5  
6   -Performs binned and unbinned maximum likelihood analysis of CTA data.
  6 +Perform maximum likelihood model fitting.
7 7  
8 8  
9 9 Synopsis
10 10 --------
11 11  
12   -Determines the flux, spectral index, position or extent of gamma-ray
13   -sources using maximum likelihood model fitting of CTA data. The analysis
14   -can be done in a binned or an unbinned formulation of the log-likelihood
15   -function. For binned analysis, a counts cube produced by :doc:`ctbin` is
16   -required. If several observations have been stacked into a single counts
17   -cube, an exposure cube, a PSF cube and a background cube have to be
18   -provided. For a single observation it is sufficient to specify the
19   -instrument response function. For unbinned analysis, an event list
20   -processed by :doc:`ctselect` is required. Based on files specified on
21   -input, ctlike automatically selects between binned or unbinned analysis.
22   -The tool can also be applied to lists of observations, specified in form
23   -of an observation definition file in XML format. Events of each observation
24   -are kept separate, and are associated to their appropriate instrument
25   -response function.
  12 +This tool performs a maximum likelihood fitting of a model to unbinned or
  13 +binned data. All model parameters marked with the attribute ``free="1"``
  14 +in the input model XML file will be adjusted to the value that maximises
  15 +the probability that the observed data have been drawn from the model.
  16 +The tool can mix the analysis of unbinned and binned data, and is also able
  17 +to perform a joint maximum likelihood analysis of data collected in
  18 +separate observations or with different instruments.
  19 +
  20 +ctlike will automatically switch between unbinned, binned and joint analysis
  21 +on basis of the file provided on input (parameter ``inobs``). Providing an
  22 +event list will lead to an unbinned analysis while providing a counts cube
  23 +will lead to a binned analysis. If several observations have been stacked
  24 +into a single counts cube, an exposure cube, a point spread function cube and
  25 +a background cube need also to be provided. ctlike will automatically prompt
  26 +for these parameters in case that a counts cube is given. Answering ``NONE``
  27 +will ignore the exposure cube, point spread function cube and background cube
  28 +and handle the data as a single observation using the specified instrument
  29 +response function (parameters ``caldb`` and ``irf``).
  30 +
  31 +Multiple observations, including data collected with different instruments,
  32 +can be handled by specifying an observation definition file on input. Each of
  33 +the observations will be kept separatly and associated with its appropriate
  34 +instrument response functions, as opposed to a stacked analysis where average
  35 +response functions, computed using :doc:`ctexpcube`, :doc:`ctpsfcube` and :doc:`ctbkgcube`,
  36 +are used. If an observation definition file is provided, ctlike will use the
  37 +joint likelihood of all the observations for parameter optimisation.
  38 +
  39 +By default, ctlike will use the Poisson statistics for likelihood computation,
  40 +but for binned analysis also Gaussian statistics can be specified (parameter
  41 +``stat``). Optionally, a refit can be done after an initial fit (parameter ``refit``),
  42 +but normally this is not needed. For all model components that have the
  43 +``tscalc="1"`` attribute set, ctlike will also compute the Test Statistics
  44 +value that is a measure of the source significance. Optionally, the spatial
  45 +model parameters can be kept fixed during that computation (parameter
  46 +``fix_spat_for_ts``).
  47 +
  48 +ctlike generates an output model XML file that contains the values of the
  49 +best fitting model parameters. For all free parameters, an ``error`` attribute
  50 +is added that provides the statistical uncertainty in the parameter estimate.
  51 +If computation of the Test Statistics has been requested for a model component,
  52 +a ``ts`` attribute providing the Test Statistics value is added. The output
  53 +model can be used as an input model for other ctools.
26 54  
27 55  
28 56 General parameters
... ... @@ -32,16 +60,16 @@ General parameters
32 60 Input event list, counts cube or observation definition XML file.
33 61  
34 62 ``inmodel [string]``
35   - Source model input XML file.
  63 + Input model XML file.
36 64  
37 65 ``expcube [file]``
38   - Exposure cube file (only needed for stacked analysis).
  66 + Input exposure cube file (only needed for stacked analysis).
39 67  
40 68 ``psfcube [file]``
41   - PSF cube file (only needed for stacked analysis).
  69 + Input PSF cube file (only needed for stacked analysis).
42 70  
43 71 ``bkgcube [file]``
44   - Background cube file (only needed for stacked analysis).
  72 + Input background cube file (only needed for stacked analysis).
45 73  
46 74 ``caldb [string]``
47 75 Calibration database.
... ... @@ -49,18 +77,21 @@ General parameters
49 77 ``irf [string]``
50 78 Instrument response function.
51 79  
  80 +``(edisp = no) [boolean]``
  81 + Applies energy dispersion to response computation.
  82 +
52 83 ``outmodel [string]``
53   - Source model result XML file with values and uncertainties updated by
  84 + Output model XML file with values and uncertainties updated by
54 85 the maximum likelihood fit.
55 86  
56 87 ``(stat = POISSON) [string]``
57 88 Fitting statistics (POISSON or GAUSSIAN; only affects binned analysis).
58 89  
59   -``(edisp = no) [boolean]``
60   - Applies energy dispersion to response computation.
61   -
62 90 ``(refit = no) [boolean]``
63   - Performs refitting of solution after initial fit.
  91 + Perform refitting of solution after initial fit.
  92 +
  93 +``(fix_spat_for_ts = no) [boolean]``
  94 + Fix spatial parameters for TS computation.
64 95  
65 96  
66 97  
... ... @@ -92,7 +123,7 @@ Standard parameters
92 123 Name of log file.
93 124  
94 125  
95   -Related tools
96   --------------
  126 +Related tools or scripts
  127 +------------------------
97 128  
98 129 None
... ...
doc/source/reference_manual/ctmodel.rst
  View file @14f9d87
... ... @@ -3,48 +3,67 @@
3 3 ctmodel
4 4 =======
5 5  
6   -Computes model counts cube.
  6 +Generate model cube.
7 7  
8 8  
9 9 Synopsis
10 10 --------
11 11  
12   -This tool computes a model counts cube based on an XML model. The counts
13   -cube is a 3-dimensional data cube spanned by Right Ascension or Galactic
14   -longitude, Declination or Galactic latitude, and energy.
  12 +This tool generates a model cube based on an input model. A model cube is
  13 +a 3-dimensional cube providing the number of predicted counts for a model as
  14 +function of Right Ascension or Galactic longitude, Declination or Galactic
  15 +latitude, and energy. The energy binning may be either linear, logarithmic,
  16 +or custom defined using an input file.
  17 +
  18 +ctmodel requires on input either a counts cube, an event list or an observation
  19 +definition file.
  20 +
  21 +If a counts cube is provided, ctmodel will use the definition of this cube
  22 +(such as sky coordinates and projection, number of pixels, pixel scale,
  23 +energy binning) to compute a model cube. In case that the counts cube combines
  24 +multiple observations (i.e. for a so-called "stacked cube"), an exposure cube,
  25 +a point spread function cube and a background cube have to be provided
  26 +(otherwise you may just enter ``NONE`` when the names of these files are
  27 +queried).
  28 +
  29 +If an event list is provided, ctmodel will query for a counts cube to
  30 +extract the model cube definition (parameter ``incube``). If no counts cube
  31 +is provided (``incube=NONE``), ctmodel tools will query for cube definition
  32 +parameters.
  33 +
  34 +If an observation definition file is provided, ctmodel will query for a counts
  35 +cube to extract the model cube definition, unless the observation definition
  36 +file contains a single binned observation (in that case, the counts cube of
  37 +that observation will be used to extract the model cube definition).
  38 +
  39 +ctmodel generates a model cube FITS file comprising three extensions. The
  40 +primary extension contains a 3-dimensional image that contains the model
  41 +cube values. The next extension named ``EBOUNDS`` contains a binary table
  42 +that defines the energy boundaries of the background cube. The last extension
  43 +named ``GTI`` contains a binary table that defines the Good Time Intervals
  44 +that are covered by the model cube.
15 45  
16 46  
17 47 General parameters
18 48 ------------------
19 49  
20   -``incube [file]``
21   - Input counts cube. If a filename is given the counts cube will be
22   - used to define the dimensions of the model cube. The content of
23   - the counts cube is not relevant.
  50 +``inobs [file]``
  51 + Input event list, counts cube or observation definition XML file.
24 52  
25 53 ``inmodel [string]``
26   - Source model XML file.
27   -
28   -``outcube [file]``
29   - Output model counts cube.
30   -
31   -``(edisp = no) [boolean]``
32   - Apply energy dispersion to response computation.
  54 + Input model XML file.
33 55  
34   -``inobs [file]``
35   - Input event list, counts cube or observation definition XML file.
36   - This information is needed to determine the observation information
37   - (number of observations, duration, liftime, pointing, eventually
38   - observation specific instrument response functions, etc.).
  56 +``incube [file]``
  57 + Input counts cube file to extract model cube definition.
39 58  
40 59 ``expcube [file]``
41   - Exposure cube file (only needed for stacked analysis).
  60 + Input exposure cube file (only needed for stacked analysis).
42 61  
43 62 ``psfcube [file]``
44   - PSF cube file (only needed for stacked analysis).
  63 + Input PSF cube file (only needed for stacked analysis).
45 64  
46 65 ``bkgcube [file]``
47   - Background cube file (only needed for stacked analysis).
  66 + Input background cube file (only needed for stacked analysis).
48 67  
49 68 ``caldb [string]``
50 69 Calibration database.
... ... @@ -52,6 +71,12 @@ General parameters
52 71 ``irf [string]``
53 72 Instrument response function.
54 73  
  74 +``(edisp = no) [boolean]``
  75 + Apply energy dispersion to response computation.
  76 +
  77 +``outcube [file]``
  78 + Output model cube file.
  79 +
55 80 ``ra [real]``
56 81 Right Ascension of pointing (J2000, in degrees).
57 82  
... ... @@ -138,7 +163,10 @@ Standard parameters
138 163 Name of log file.
139 164  
140 165  
141   -Related tools
142   --------------
  166 +Related tools or scripts
  167 +------------------------
143 168  
144   -None
  169 +:doc:`ctbin`
  170 +:doc:`ctexpcube`
  171 +:doc:`ctpsfcube`
  172 +:doc:`ctbkgcube`
... ...
doc/source/reference_manual/ctobssim.rst
  View file @14f9d87
... ... @@ -3,14 +3,39 @@
3 3 ctobssim
4 4 ========
5 5  
6   -Simulates CTA events.
  6 +Simulate event list(s).
7 7  
8 8  
9 9 Synopsis
10 10 --------
11 11  
12   -Generate photon events from astrophysical sources and background events
13   -from an instrumental background model.
  12 +This tool simulates event list(s) using the instrument characteristics
  13 +specified by the instrument response function(s) and an input model. The
  14 +simulation includes photon events from astrophysical sources and background
  15 +events from an instrumental background model.
  16 +
  17 +By default, ctobssim creates a single event list. ctobssim queries a pointing
  18 +direction, the radius of the simulation region, a time interval, an energy
  19 +interval, an instrumental response function, and an input model. ctobssim uses
  20 +a numerical random number generator for the simulations with a seed value
  21 +provided by the hidden ``seed`` parameter. Changing this parameter for
  22 +subsequent runs will lead to different event samples.
  23 +
  24 +ctobssim performs a safety check on the maximum photon rate for all model
  25 +components to avoid that the tool locks up and requests huge memory
  26 +ressources, which may happen if a mistake was made in setting up the input
  27 +model (for example if an error in the flux units is made). The maximum allowed
  28 +photon rate is controlled by the hidden ``maxrate`` parameter, which by default
  29 +is set to 1e6.
  30 +
  31 +ctobssim can also generate multiple event lists if an observation definition
  32 +file is specified on input using the hidden ``inobs`` parameter. In that
  33 +case, simulation information will be gathered from the file, and for each
  34 +observation an event list will be created.
  35 +
  36 +For each event file, the simulation parameters will be written as data
  37 +selection keywords to the FITS header. These keywords are mandatory for any
  38 +unbinned maximum likelihood analysis of the event data.
14 39  
15 40  
16 41 General parameters
... ... @@ -23,14 +48,7 @@ General parameters
23 48 simulation.
24 49  
25 50 ``inmodel [file]``
26   - XML file that describes the astrophysical sources and the instrumental
27   - background model.
28   -
29   -``outevents [file]``
30   - Output event list or observation definition XML file.
31   -
32   -``(prefix = sim_events_) [string]``
33   - Prefix for event list in observation definition XML file.
  51 + Input model XML file.
34 52  
35 53 ``caldb [string]``
36 54 Calibration database.
... ... @@ -38,6 +56,15 @@ General parameters
38 56 ``irf [string]``
39 57 Instrumental response function.
40 58  
  59 +``(edisp = no) [boolean]``
  60 + Apply energy dispersion?
  61 +
  62 +``outevents [file]``
  63 + Output event list or observation definition XML file.
  64 +
  65 +``(prefix = sim_events_) [string]``
  66 + Prefix for event list in observation definition XML file.
  67 +
41 68 ``(seed = 1) [integer]``
42 69 Integer seed value to be used for Monte Carlo simulations. Keep this
43 70 parameter at the same value for repeatable simulations, or increment
... ... @@ -65,9 +92,6 @@ General parameters
65 92 ``emax [real]``
66 93 Upper energy limit of simulated events (in TeV).
67 94  
68   -``(edisp = no) [boolean]``
69   - Apply energy dispersion?
70   -
71 95 ``(deadc = 0.95) [real]``
72 96 Average deadtime correction factor.
73 97  
... ... @@ -107,7 +131,7 @@ Standard parameters
107 131 Name of log file.
108 132  
109 133  
110   -Related tools
111   --------------
  134 +Related tools or scripts
  135 +------------------------
112 136  
113   -None
  137 +:doc:`csobsdef`
... ...
doc/source/reference_manual/ctpsfcube.rst
  View file @14f9d87
... ... @@ -3,15 +3,39 @@
3 3 ctpsfcube
4 4 =========
5 5  
6   -Generate a point spread function cube for binned maximum likelihood
7   -analysis.
  6 +Generate point spread function cube for a counts cube.
8 7  
9 8  
10 9 Synopsis
11 10 --------
12 11  
13   -This tool generates a point spread function cube for use in a binned
14   -maximum likelihood analysis.
  12 +This tool generates a point spread function cube for a counts cube. A point
  13 +spread function cube is a 4-dimensional cube spanned by Right Ascension or
  14 +Galactic longitude, Declination or Galactic latitude, energy, and offset
  15 +angle between true and measured arrival direction of a photon. The energy
  16 +binning of the cube may be either linear, logarithmic, or custom defined
  17 +using an input file.
  18 +
  19 +ctpsfcube requires on input the event list or observation definition file
  20 +that has been used in the generation of the counts cube using :doc:`ctbin`.
  21 +
  22 +It is not recommended to use the counts cube for the point spread function
  23 +cube definition, although this is formally possibly by specifying the counts
  24 +cube as ``incube`` parameter. This leads however to a large FITS file on
  25 +output since the number of bins in the counts cube will be multiplied by
  26 +the number of offset angle bins (typically 200). Since the point spread
  27 +function varies only little over the field of fiew of the camera it is
  28 +recommended to use a rather coarse spatial binning to keep the file size
  29 +manageable (with a typical value of ``binsz=1.0``).
  30 +
  31 +ctpsfcube generates a point spread function cube FITS file comprising three
  32 +extensions. The primary extension contains a 3-dimensional image that contains
  33 +the point spread function values. The energy and offset angle dimensions
  34 +of the point spread function cube are folded into the 3rd dimension of the
  35 +FITS image. The next extension named ``EBOUNDS`` contains a binary table
  36 +that defines the energy boundaries of the exposure cube. The last extension
  37 +named ``DELTAS`` contains a binary table that defines the offset angles
  38 +between true and measured arrival direction of the photon.
15 39  
16 40  
17 41 General parameters
... ... @@ -21,20 +45,20 @@ General parameters
21 45 Input event list or observation definition XML file.
22 46  
23 47 ``incube [file]``
24   - Counts cube for PSF cube definition.
25   -
26   -``outcube [file]``
27   - Output PSF cube file.
  48 + Input counts cube file to extract point spread function cube definition.
28 49  
29 50 ``caldb [string]``
30 51 Calibration database.
31 52  
32 53 ``irf [string]``
33   - Response function.
  54 + Instrument response function.
34 55  
35 56 ``(edisp = no) [boolean]``
36 57 Apply energy dispersion for response computation.
37 58  
  59 +``outcube [file]``
  60 + Output point spread function cube file.
  61 +
38 62 ``ebinalg <FILE|LIN|LOG> [string]``
39 63 Algorithm for defining energy bins.
40 64  
... ... @@ -110,7 +134,7 @@ Standard parameters
110 134 Name of log file.
111 135  
112 136  
113   -Related tools
114   --------------
  137 +Related tools or scripts
  138 +------------------------
115 139  
116   -None
  140 +:doc:`ctbin`
... ...
doc/source/reference_manual/ctselect.rst
  View file @14f9d87
... ... @@ -3,14 +3,36 @@
3 3 ctselect
4 4 ========
5 5  
6   -Performs sub-selections of event data.
  6 +Select events from event list(s).
7 7  
8 8  
9 9 Synopsis
10 10 --------
11 11  
12   -Creates a new FITS file of selected events from an input event list based
13   -on spatial, temporal, and energy cuts.
  12 +This tool selects events from one or several event lists. Event selection
  13 +is based on a circular acceptance region, a time interval and an energy
  14 +interval. In addition, any expression following the cfitsio syntax can be
  15 +used for event selection.
  16 +
  17 +Optionally, ctselect may also apply energy thresholds. If ``usethres=DEFAULT``
  18 +is specified, ctselect will extract any save thresholds from the instrument
  19 +response functions, and if they exist, will apply them to the respective
  20 +event list. Alternatively, if ``usethres=USER`` is specified, ctselect will
  21 +extract any user thresholds from the observation definition file (attributes
  22 +``emin`` and ``emax``), and if either of the attributes exists, will apply
  23 +them to the respective event list.
  24 +
  25 +If an event list is provided on input, ctselect creates a new FITS file on
  26 +output that contains only the selected events. In case that an observation
  27 +definition file is specified on input, ctselect creates for each event file
  28 +referenced in the observation definition file a new FITS file with the value
  29 +of ``prefix`` prepended to the file name that contains only the selected
  30 +events. In addition, a new observation definition file will be written
  31 +that references the new FITS files.
  32 +
  33 +For each event file, the event selection parameters will be writted as data
  34 +selection keywords to the FITS header. These keywords are mandatory for any
  35 +unbinned maximum likelihood analysis of the event data.
14 36  
15 37  
16 38 General parameters
... ... @@ -98,7 +120,7 @@ Standard parameters
98 120 Name of log file.
99 121  
100 122  
101   -Related tools
102   --------------
  123 +Related tools or scripts
  124 +------------------------
103 125  
104 126 None
... ...
doc/source/reference_manual/ctskymap.rst
  View file @14f9d87
... ... @@ -3,13 +3,18 @@
3 3 ctskymap
4 4 ========
5 5  
6   -Computes sky map from CTA data.
  6 +Generate sky map from event list(s).
7 7  
8 8  
9 9 Synopsis
10 10 --------
11 11  
12   -This tool generates a sky map from CTA data.
  12 +This tool creates a sky map from either a single event list or event lists
  13 +provided in an observation definition file. The tool will loop over all event
  14 +lists that are provided and fill all events into a single sky map. Only events
  15 +within an energy interval spanned by ``emin`` and ``emax`` are considered.
  16 +
  17 +ctskymap generates a FITS file comprising a sky map as primary extension.
13 18  
14 19  
15 20 General parameters
... ... @@ -19,7 +24,7 @@ General parameters
19 24 Input event list or observation definition XML file.
20 25  
21 26 ``outmap [file]``
22   - Output sky map.
  27 + Output sky map file.
23 28  
24 29 ``emin [real]``
25 30 Minimum energy in map (in TeV).
... ... @@ -80,7 +85,7 @@ Standard parameters
80 85 Name of log file.
81 86  
82 87  
83   -Related tools
84   --------------
  88 +Related tools or scripts
  89 +------------------------
85 90  
86 91 None
... ...
doc/source/reference_manual/cttsmap.rst
  View file @14f9d87
... ... @@ -3,13 +3,25 @@
3 3 cttsmap
4 4 =======
5 5  
6   -Generate a Test Statistic map.
  6 +Generate a Test Statistic (TS) map.
7 7  
8 8  
9 9 Synopsis
10 10 --------
11 11  
12   -This tool generates a Test Statistic map.
  12 +This tool generates a Test Statistic (TS) map for a specific source model.
  13 +cttsmap works for point, radial and elliptical source models. The tool
  14 +displaces the specified source on a grid of sky directions and computes for
  15 +each direction the TS value for the model. The TS value is defined as twice
  16 +the difference between the log-likelihood obtained for the full model
  17 +(including the specified source) and the log-likelihood obtained for a model
  18 +that excludes the specified source. The square-root of the TS values
  19 +corresponds roughly to the pre-trial detection signifiance of the source (in
  20 +Gaussian sigma).
  21 +
  22 +cttsmap generates a FITS file comprising a sky map of TS values followed by
  23 +one extension per free parameter that contains sky maps of the fitted
  24 +parameter values.
13 25  
14 26  
15 27 General parameters
... ... @@ -19,26 +31,25 @@ General parameters
19 31 Input event list, counts cube or observation definition XML file.
20 32  
21 33 ``inmodel [file]``
22   - Input source model XML file.
  34 + Input model XML file.
23 35  
24 36 ``srcname [string]``
25   - Name of the source in the source model XML file for which the Test
26   - Statistic map should be computed.
  37 + Name of source model for which the TS map should be computed.
27 38  
28 39 ``expcube [file]``
29   - Exposure cube file (only needed for stacked analysis).
  40 + Input exposure cube file (only needed for stacked analysis).
30 41  
31 42 ``psfcube [file]``
32   - PSF cube file (only needed for stacked analysis).
  43 + Input PSF cube file (only needed for stacked analysis).
33 44  
34 45 ``bkgcube [file]``
35   - Background cube file (only needed for stacked analysis).
  46 + Input background cube file (only needed for stacked analysis).
36 47  
37 48 ``caldb [string]``
38 49 Calibration database.
39 50  
40 51 ``irf [string]``
41   - Response function.
  52 + Instrumental response function.
42 53  
43 54 ``(edisp = no) [boolean]``
44 55 Applies energy dispersion to response computation.
... ... @@ -108,7 +119,8 @@ Standard parameters
108 119 Name of log file.
109 120  
110 121  
111   -Related tools
112   --------------
  122 +Related tools or scripts
  123 +------------------------
  124 +
  125 +:ref:`cstsmapmerge`
113 126  
114   -None
... ...
doc/source/reference_manual/ctulimit.rst
  View file @14f9d87
1 1 .. _ctulimit:
2 2  
3 3 ctulimit
4   -===========
  4 +========
5 5  
6   -Computes upper limit for a specific sky model component.
  6 +Computes upper flux limit for a source model.
7 7  
8 8  
9 9 Synopsis
10 10 --------
11 11  
12   -Computes the upper limit flux of a given source.
  12 +This tools computes the upper flux limit for a specific source model. Except
  13 +of the node function, all spectral models are supported. Starting from the
  14 +maximum likelihood model parameters, the tool finds the model flux that leads
  15 +to a decrease of the likelihood that corresponds to a given confidence level.
  16 +By default a confidence level of 95% is used, but this level can be adjusted
  17 +using the hidden ``confidence`` parameter.
  18 +
  19 +ctulimit writes the differential upper flux limit at a given reference
  20 +energy (specified by the hidden parameter ``eref``) and the integrated
  21 +upper flux limit (specified by the hidden parameters ``emin`` and ``emax``)
  22 +into the log file.
  23 +
13 24  
14 25  
15 26 General parameters
... ... @@ -19,19 +30,19 @@ General parameters
19 30 Input event list, counts cube or observation definition XML file.
20 31  
21 32 ``inmodel [file]``
22   - Model XML file containing the source and background definitions.
  33 + Input model XML file.
23 34  
24 35 ``srcname [string]``
25   - Name of model component for which upper limit should be computed.
  36 + Name of source model for which the upper flux limit should be computed.
26 37  
27 38 ``expcube [file]``
28   - Exposure cube file (only needed for stacked analysis).
  39 + Input exposure cube file (only needed for stacked analysis).
29 40  
30 41 ``psfcube [file]``
31   - PSF cube file (only needed for stacked analysis).
  42 + Input PSF cube file (only needed for stacked analysis).
32 43  
33 44 ``bkgcube [file]``
34   - Background cube file (only needed for stacked analysis).
  45 + Input background cube file (only needed for stacked analysis).
35 46  
36 47 ``caldb [string]``
37 48 Calibration database.
... ... @@ -53,11 +64,14 @@ General parameters
53 64 Maximum boundary to start searching for upper limit value.
54 65 Number of standard deviations above best fit value
55 66  
  67 +``(eref = 1.0) [real])``
  68 + Reference energy for differential limit (in TeV).
  69 +
56 70 ``(emin = 1.0) [real])``
57   - Minimum energy of flux limits (in TeV).
  71 + Minimum energy for integral flux limit (in TeV).
58 72  
59 73 ``(emax = 100) [real]``
60   - Maximum energy of flux limits (in TeV).
  74 + Maximum energy for integral flux limit (in TeV).
61 75  
62 76 ``(tol = 1e-5) [real]``
63 77 Computation tolerance.
... ... @@ -98,4 +112,6 @@ Standard parameters
98 112 Related tools
99 113 -------------
100 114  
101   -:ref:`cterror`
102 115 \ No newline at end of file
  116 +:ref:`ctlike`
  117 +:ref:`cterror`
  118 +:ref:`ctbutterfly`
... ...
doc/source/reference_manual/index.rst
  View file @14f9d87
... ... @@ -45,3 +45,8 @@ cscripts
45 45 csspec --- Computes spectral points <csspec>
46 46 csresmap --- Generates residual map <csresmap>
47 47 cstsdist --- Generates TS distribution <cstsdist>
  48 + csobsinfo --- Shows observation container content <csobsinfo>
  49 + csmodelinfo --- Shows model container content <csmodelinfo>
  50 + csmodelmerge --- Merges several model containers into one file <csmodelmerge>
  51 + cstsmapmerge --- Merges slices from ts map computations <cstsmapmerge>
  52 + csobs2caldb --- Creates a caldb entry from an input observation <csobs2caldb>
... ...
doc/source/user_manual/enhancing.rst deleted
View file @61ca854
1   -Enhancing ctools
2   -================
3   -
4   -Most ctools users will run the existing ctools or cscripts,
5   -which cover the most common simulation and analysis needs.
6   -
7   -Advanced users and developers can write their own tools and scripts.
8   -The following C++ and Python examples can help get you started:
9   -
10   -* :doxy:`ctlike`
11   -* :doxy:`obsutils`
12   -* :doxy:`cstsdist`
13   -
14   -Building your own cscripts
15   ---------------------------
16   -
17   -To be written ...
18   -
19   -
20   -Building your own ctools
21   -------------------------
22   -
23   -To be written ...
doc/source/user_manual/expert.rst deleted
View file @61ca854
1   -Behind the scenes
2   -=================
3   -
4   -CTA data structure
5   -------------------
6   -
7   -To be written ...
8   -
9   -
10   -Instrument response functions
11   ------------------------------
12   -
13   -To be written ...
14   -
15   -
16   -Maximum likelihood fitting
17   ---------------------------
18   -
19   -To be written ...
doc/source/user_manual/getting.rst
  View file @14f9d87
... ... @@ -29,15 +29,15 @@ No system administrator privileges are needed to install ctools.
29 29  
30 30 .. _sec_installing_gammalib:
31 31  
32   -Installing gammalib
  32 +Installing GammaLib
33 33 -------------------
34 34  
35   -ctools is built on top of gammalib, hence gammalib needs to be built,
  35 +ctools is built on top of GammaLib, hence GammaLib needs to be built,
36 36 installed and configured before ctools can be installed. In case that
37 37 ctools is already installed on your system you may skip reading this
38 38 section and continue with the :ref:`sec_building_ctools` section.
39 39  
40   -You will need the following to build the gammalib:
  40 +You will need the following to build the GammaLib:
41 41  
42 42 - About 200 MB of free disk space.
43 43  
... ... @@ -58,12 +58,12 @@ You will need the following to build the gammalib:
58 58 Furthermore it is recommended to have readline and ncurses installed
59 59 (including the developer packages).
60 60  
61   -After downloading the gammalib tarball (see :ref:`download`), save it
  61 +After downloading the GammaLib tarball (see :ref:`download`), save it
62 62 in an appropriate location (for example ``$HOME/builds``), and type
63 63  
64 64 .. code-block:: bash
65 65  
66   - $ tar xvfz gammalib-0.11.0.tar.gz
  66 + $ tar xvfz gammalib-1.0.0.tar.gz
67 67  
68 68 (the ``$`` symbol indicates the console prompt and is not part of the
69 69 command that you should type in).
... ... @@ -73,7 +73,7 @@ typing
73 73  
74 74 .. code-block:: bash
75 75  
76   - $ cd gammalib-0.11.0
  76 + $ cd gammalib-1.0.0
77 77 $ ./configure
78 78 $ make
79 79 $ make check
... ... @@ -82,6 +82,8 @@ typing
82 82 The last step may require system administator privileges. In this case,
83 83 use
84 84  
  85 +.. code-block:: bash
  86 +
85 87 $ sudo make install
86 88  
87 89 If you do not have system administrator privileges, change the install
... ... @@ -133,7 +135,7 @@ an appropriate location (for example ``$HOME/builds``), and type
133 135  
134 136 .. code-block:: bash
135 137  
136   - $ tar xvfz ctools-0.10.0.tar.gz
  138 + $ tar xvfz ctools-1.0.0.tar.gz
137 139  
138 140 (the ``$`` symbol indicates the console prompt and is not part of the
139 141 command that you should type in).
... ... @@ -142,7 +144,7 @@ Step in the directory and build the ctools by typing
142 144  
143 145 .. code-block:: bash
144 146  
145   - $ cd ctools-0.10.0
  147 + $ cd ctools-1.0.0
146 148 $ ./configure
147 149 $ make
148 150  
... ... @@ -181,7 +183,7 @@ following output at the end of the unit testing:
181 183 PASS: test_python.py
182 184 make[4]: Nothing to be done for `all'.
183 185 ============================================================================
184   - Testsuite summary for ctools 0.10.0
  186 + Testsuite summary for ctools 1.0.0
185 187 ============================================================================
186 188 # TOTAL: 3
187 189 # PASS: 3
... ... @@ -219,6 +221,18 @@ For older automake version, you should see
219 221 * Test cscripts *
220 222 *****************
221 223 Test csobsdef: .. ok
  224 + Test csobs2caldb: .. ok
  225 + Test csobsinfo: .. ok
  226 + Test csiactobs: .. ok
  227 + Test csmodelinfo: .. ok
  228 + Test csmodelmerge (space-separated): .. ok
  229 + Test csmodelmerge (comma-separated): .. ok
  230 + Test csmodelmerge (wildcard string): .. ok
  231 + Test csmodelmerge (ascii-file): .. ok
  232 + Test cstsmapmerge (comma-separated): .. ok
  233 + Test cstsmapmerge (space-separated): .. ok
  234 + Test cstsmapmerge (wildcard string): .. ok
  235 + Test cstsmapmerge (ascii-file): .. ok
222 236 Test cspull: .. ok
223 237 Test cssens: .. ok
224 238 Test cstsdist: .. ok
... ... @@ -345,19 +359,8 @@ As a quick check that your setup is okay you can run ``csinfo check``:
345 359 ===> Your Gammalib / ctools setup is OK.
346 360  
347 361 If the setup is not okay, run the ``csinfo info`` command to print
348   -detailed information about your setup.
349   -There's also a ``csinfo list`` command to quickly list the available tools:
350   -
351   -.. code-block:: bash
352   -
353   - $ csinfo
354   -
355   - Print info about Gammalib and ctools to the console.
356   -
357   - Available commands:
358   - csinfo list List available ctools and cscripts
359   - csinfo check Check Gammalib / ctools setup
360   - csinfo info Print Gammalib / ctools setup info
  362 +detailed information about your setup. There's also a ``csinfo list``
  363 +command to quickly list the available tools.
361 364  
362 365  
363 366 .. _sec_known_problems:
... ...
doc/source/user_manual/getting_started/beyond.rst
  View file @14f9d87
... ... @@ -3,12 +3,12 @@
3 3 Beyond the first steps
4 4 ----------------------
5 5  
6   -Assuming that you have read the :ref:`quickstart <quickstart>` tutorial,
7   -here now some chapters to read if you intend to do more complex
8   -analyses.
9   -Once you have gone through these chapters you should have a pretty complete
  6 +Now that you are familiar with the ctools basics, here are some sections
  7 +to read if you intend to do more complex analyses.
  8 +Once you have gone through these sections you should have a pretty complete
10 9 picture about the capabilities of ctools.
11   -And you should be ready for doing your own cutting edge analyses.
  10 +And you should be ready for doing your own cutting edge CTA science data
  11 +analyses.
12 12  
13 13 .. toctree::
14 14 :maxdepth: 2
... ... @@ -19,11 +19,3 @@ And you should be ready for doing your own cutting edge analyses.
19 19 beyond_residual
20 20 beyond_irf
21 21 beyond_model
22   -
23   -
24   -
25   -
26   -
27   -
28   -
29   -
... ...
doc/source/user_manual/getting_started/beyond_combine.rst
  View file @14f9d87
... ... @@ -25,9 +25,9 @@ nebula, each offset by 0.5 deg from the nebula in opposite directions:
25 25 Lower energy limit (TeV) [0.1]
26 26 Upper energy limit (TeV) [100.0]
27 27 Calibration database [prod2]
28   - Instrument response function [South_50h]
29   - Model [$CTOOLS/share/models/crab.xml]
30   - Output event data file or observation definition file [events.fits] events1.fits
  28 + Instrument response function [South_0.5h]
  29 + Input model XML file [$CTOOLS/share/models/crab.xml]
  30 + Output event data file or observation definition XML file [events.fits] events1.fits
31 31  
32 32 .. code-block:: bash
33 33  
... ... @@ -40,16 +40,16 @@ nebula, each offset by 0.5 deg from the nebula in opposite directions:
40 40 Lower energy limit (TeV) [0.1]
41 41 Upper energy limit (TeV) [100.0]
42 42 Calibration database [prod2]
43   - Instrument response function [South_50h]
44   - Model [$CTOOLS/share/models/crab.xml]
45   - Output event data file or observation definition file [events1.fits] events2.fits
  43 + Instrument response function [South_0.5h]
  44 + Input model XML file [$CTOOLS/share/models/crab.xml]
  45 + Output event data file or observation definition XML file [events1.fits] events2.fits
46 46  
47 47 This will produce the two event files ``events1.fits`` and ``events2.fits``
48 48 on disk.
49 49  
50   -As next step we have to create an **observation definition XML file** that
  50 +As next step you have to create an **observation definition XML file** that
51 51 collects both observations in a list.
52   -Here is how such a file would look like:
  52 +Here is how that file looks like:
53 53  
54 54 .. code-block:: xml
55 55  
... ... @@ -86,116 +86,140 @@ ctools knows which instrument specific functions need to be called.**
86 86 Imaging Air Cherenkov Telescope in a joint analysis.
87 87 **Please recall that instrument strings are case sensitive.**
88 88  
89   -Now we are ready to do a joint maximum likelihood analysis using
90   -:ref:`ctlike`:
  89 +Now you are ready to do a joint maximum likelihood analysis using
  90 +:ref:`ctlike`. Type:
91 91  
92 92 .. code-block:: bash
93 93  
94   - $ ctlike
95   - Event list, counts cube or observation definition file [selected_events.fits] obs.xml
  94 + $ ctlike chatter=3
  95 + Input event list, counts cube or observation definition XML file [events.fits] obs.xml
96 96 Calibration database [prod2]
97   - Instrument response function [South_50h]
98   - Source model [$CTOOLS/share/models/crab.xml]
99   - Source model output file [crab_results.xml]
  97 + Instrument response function [South_0.5h]
  98 + Input model XML file [$CTOOLS/share/models/crab.xml]
  99 + Output model XML file [crab_results.xml]
100 100  
101   -Instead of providing an event list or a counts cube, we now provided the
  101 +Instead of providing an event list or a counts cube, you now provided the
102 102 filename of the observation definition XML file (here ``obs.xml``) as input
103   -parameter.
104   -:ref:`ctlike` recognises this format and automatically performs a
105   -joint analysis, as indicated in the log file:
  103 +parameter. :ref:`ctlike` recognises this format and automatically performs a
  104 +joint analysis. To see the result of this you needed to specify the
  105 +``chatter=3`` parameter so that the chattiness is increased in the log
  106 +file:
106 107  
107 108 .. code-block:: xml
108 109  
109   - 2015-05-22T20:17:07: +==============+
110   - 2015-05-22T20:17:07: | Observations |
111   - 2015-05-22T20:17:07: +==============+
112   - 2015-05-22T20:17:07: === GObservations ===
113   - 2015-05-22T20:17:07: Number of observations ....: 2
114   - 2015-05-22T20:17:07: Number of predicted events : 0
115   - 2015-05-22T20:17:07: === GCTAObservation ===
116   - 2015-05-22T20:17:07: Name ......................:
117   - 2015-05-22T20:17:07: Identifier ................: 00001
118   - 2015-05-22T20:17:07: Instrument ................: CTA
119   - 2015-05-22T20:17:07: Event file ................: events1.fits
120   - 2015-05-22T20:17:07: Event type ................: EventList
121   - 2015-05-22T20:17:07: Statistics ................: Poisson
122   - 2015-05-22T20:17:07: Ontime ....................: 1800 s
123   - 2015-05-22T20:17:07: Livetime ..................: 1710 s
124   - 2015-05-22T20:17:07: Deadtime correction .......: 0.95
125   - 2015-05-22T20:17:07: User energy range .........: undefined
126   - 2015-05-22T20:17:07: === GCTAPointing ===
127   - 2015-05-22T20:17:07: Pointing direction ........: (RA,Dec)=(83.63,21.51)
  110 + 2015-12-07T21:23:07: +==============+
  111 + 2015-12-07T21:23:07: | Observations |
  112 + 2015-12-07T21:23:07: +==============+
  113 + 2015-12-07T21:23:07: === GObservations ===
  114 + 2015-12-07T21:23:07: Number of observations ....: 2
  115 + 2015-12-07T21:23:07: Number of models ..........: 2
  116 + 2015-12-07T21:23:07: Number of predicted events : 0
  117 + 2015-12-07T21:23:07: === GCTAObservation ===
  118 + 2015-12-07T21:23:07: Name ......................: Crab
  119 + 2015-12-07T21:23:07: Identifier ................: 00001
  120 + 2015-12-07T21:23:07: Instrument ................: CTA
  121 + 2015-12-07T21:23:07: Event file ................: events1.fits
  122 + 2015-12-07T21:23:07: Event type ................: EventList
  123 + 2015-12-07T21:23:07: Statistics ................: Poisson
  124 + 2015-12-07T21:23:07: Ontime ....................: 1800 s
  125 + 2015-12-07T21:23:07: Livetime ..................: 1710 s
  126 + 2015-12-07T21:23:07: Deadtime correction .......: 0.95
  127 + 2015-12-07T21:23:07: User energy range .........: undefined
  128 + 2015-12-07T21:23:07: === GCTAPointing ===
  129 + 2015-12-07T21:23:07: Pointing direction ........: (RA,Dec)=(83.63,21.51)
  130 + 2015-12-07T21:23:07: === GCTAResponseIrf ===
  131 + 2015-12-07T21:23:07: Caldb mission .............: cta
  132 + 2015-12-07T21:23:07: Caldb instrument ..........: prod2
  133 + 2015-12-07T21:23:07: Response name .............: South_0.5h
  134 + 2015-12-07T21:23:07: Energy dispersion .........: Not used
  135 + 2015-12-07T21:23:07: Save energy range .........: undefined
  136 + 2015-12-07T21:23:07: === GCTAEventList ===
  137 + 2015-12-07T21:23:07: Number of events ..........: 22593
  138 + 2015-12-07T21:23:07: Time interval .............: 51544.5 - 51544.5 days
  139 + 2015-12-07T21:23:07: Energy interval ...........: 0.1 - 100 TeV
  140 + 2015-12-07T21:23:07: Region of interest ........: RA=83.63, DEC=21.51 [0,0] Radius=5 deg
  141 + 2015-12-07T21:23:07: === GCTAObservation ===
  142 + 2015-12-07T21:23:07: Name ......................: Crab
  143 + 2015-12-07T21:23:07: Identifier ................: 00002
  144 + 2015-12-07T21:23:07: Instrument ................: CTA
  145 + 2015-12-07T21:23:07: Event file ................: events2.fits
  146 + 2015-12-07T21:23:07: Event type ................: EventList
  147 + 2015-12-07T21:23:07: Statistics ................: Poisson
  148 + 2015-12-07T21:23:07: Ontime ....................: 1800 s
  149 + 2015-12-07T21:23:07: Livetime ..................: 1710 s
  150 + 2015-12-07T21:23:07: Deadtime correction .......: 0.95
  151 + 2015-12-07T21:23:07: User energy range .........: undefined
  152 + 2015-12-07T21:23:07: === GCTAPointing ===
  153 + 2015-12-07T21:23:07: Pointing direction ........: (RA,Dec)=(83.63,22.51)
  154 + 2015-12-07T21:23:07: === GCTAResponseIrf ===
  155 + 2015-12-07T21:23:07: Caldb mission .............: cta
  156 + 2015-12-07T21:23:07: Caldb instrument ..........: prod2
  157 + 2015-12-07T21:23:07: Response name .............: South_0.5h
  158 + 2015-12-07T21:23:07: Energy dispersion .........: Not used
  159 + 2015-12-07T21:23:07: Save energy range .........: undefined
  160 + 2015-12-07T21:23:07: === GCTAEventList ===
  161 + 2015-12-07T21:23:07: Number of events ..........: 22529
  162 + 2015-12-07T21:23:07: Time interval .............: 51544.5 - 51544.5 days
  163 + 2015-12-07T21:23:07: Energy interval ...........: 0.1 - 100 TeV
  164 + 2015-12-07T21:23:07: Region of interest ........: RA=83.63, DEC=22.51 [0,0] Radius=5 deg
128 165 ...
129   - 2015-05-22T20:17:07: === GCTAObservation ===
130   - 2015-05-22T20:17:07: Name ......................:
131   - 2015-05-22T20:17:07: Identifier ................: 00002
132   - 2015-05-22T20:17:07: Instrument ................: CTA
133   - 2015-05-22T20:17:07: Event file ................: events2.fits
134   - 2015-05-22T20:17:07: Event type ................: EventList
135   - 2015-05-22T20:17:07: Statistics ................: Poisson
136   - 2015-05-22T20:17:07: Ontime ....................: 1800 s
137   - 2015-05-22T20:17:07: Livetime ..................: 1710 s
138   - 2015-05-22T20:17:07: Deadtime correction .......: 0.95
139   - 2015-05-22T20:17:07: User energy range .........: undefined
140   - 2015-05-22T20:17:07: === GCTAPointing ===
141   - 2015-05-22T20:17:07: Pointing direction ........: (RA,Dec)=(83.63,22.51)
  166 + 2015-12-07T21:23:07: +=================================+
  167 + 2015-12-07T21:23:07: | Maximum likelihood optimisation |
  168 + 2015-12-07T21:23:07: +=================================+
  169 + 2015-12-07T21:23:07: >Iteration 0: -logL=304176.886, Lambda=1.0e-03
  170 + 2015-12-07T21:23:08: >Iteration 1: -logL=304161.799, Lambda=1.0e-03, delta=15.088, max(|grad|)=12.922804 [Index:3]
  171 + 2015-12-07T21:23:08: >Iteration 2: -logL=304161.783, Lambda=1.0e-04, delta=0.015, max(|grad|)=0.098155 [Index:3]
  172 + 2015-12-07T21:23:08: >Iteration 3: -logL=304161.783, Lambda=1.0e-05, delta=0.000, max(|grad|)=0.000598 [Index:3]
142 173 ...
143   - 2015-05-22T20:17:07: +=================================+
144   - 2015-05-22T20:17:07: | Maximum likelihood optimisation |
145   - 2015-05-22T20:17:07: +=================================+
146   - 2015-05-22T20:17:07: >Iteration 0: -logL=201836.657, Lambda=1.0e-03
147   - 2015-05-22T20:17:07: >Iteration 1: -logL=201829.438, Lambda=1.0e-03, delta=7.220, max(|grad|)=22.756507 [Index:7]
148   - 2015-05-22T20:17:07: >Iteration 2: -logL=201829.432, Lambda=1.0e-04, delta=0.005, max(|grad|)=0.086395 [Index:3]
149   - 2015-05-22T20:17:07: >Iteration 3: -logL=201829.432, Lambda=1.0e-05, delta=0.000, max(|grad|)=0.001287 [Index:3]
150   - 2015-05-22T20:17:07:
151   - 2015-05-22T20:17:07: +=========================================+
152   - 2015-05-22T20:17:07: | Maximum likelihood optimization results |
153   - 2015-05-22T20:17:07: +=========================================+
154   - 2015-05-22T20:17:07: === GOptimizerLM ===
155   - 2015-05-22T20:17:07: Optimized function value ..: 201829.432
156   - 2015-05-22T20:17:07: Absolute precision ........: 0.005
157   - 2015-05-22T20:17:07: Acceptable value decrease .: 2
158   - 2015-05-22T20:17:07: Optimization status .......: converged
159   - 2015-05-22T20:17:07: Number of parameters ......: 10
160   - 2015-05-22T20:17:07: Number of free parameters .: 4
161   - 2015-05-22T20:17:07: Number of iterations ......: 3
162   - 2015-05-22T20:17:07: Lambda ....................: 1e-06
163   - 2015-05-22T20:17:07: Maximum log likelihood ....: -201829.432
164   - 2015-05-22T20:17:07: Observed events (Nobs) ...: 31799.000
165   - 2015-05-22T20:17:07: Predicted events (Npred) ..: 31799.000 (Nobs - Npred = 2.67544e-06)
166   - 2015-05-22T20:17:07: === GModels ===
167   - 2015-05-22T20:17:07: Number of models ..........: 2
168   - 2015-05-22T20:17:07: Number of parameters ......: 10
169   - 2015-05-22T20:17:07: === GModelSky ===
170   - 2015-05-22T20:17:07: Name ......................: Crab
171   - 2015-05-22T20:17:07: Instruments ...............: all
172   - 2015-05-22T20:17:07: Instrument scale factors ..: unity
173   - 2015-05-22T20:17:07: Observation identifiers ...: all
174   - 2015-05-22T20:17:07: Model type ................: PointSource
175   - 2015-05-22T20:17:07: Model components ..........: "SkyDirFunction" * "PowerLaw" * "Constant"
176   - 2015-05-22T20:17:07: Number of parameters ......: 6
177   - 2015-05-22T20:17:07: Number of spatial par's ...: 2
178   - 2015-05-22T20:17:07: RA .......................: 83.6331 [-360,360] deg (fixed,scale=1)
179   - 2015-05-22T20:17:07: DEC ......................: 22.0145 [-90,90] deg (fixed,scale=1)
180   - 2015-05-22T20:17:07: Number of spectral par's ..: 3
181   - 2015-05-22T20:17:07: Prefactor ................: 5.8727e-16 +/- 8.04314e-18 [1e-23,1e-13] ph/cm2/s/MeV (free,scale=1e-16,gradient)
182   - 2015-05-22T20:17:07: Index ....................: -2.49825 +/- 0.0118418 [-0,-5] (free,scale=-1,gradient)
183   - 2015-05-22T20:17:07: PivotEnergy ..............: 300000 [10000,1e+09] MeV (fixed,scale=1e+06,gradient)
184   - 2015-05-22T20:17:07: Number of temporal par's ..: 1
185   - 2015-05-22T20:17:07: Normalization ............: 1 (relative value) (fixed,scale=1,gradient)
186   - 2015-05-22T20:17:07: === GCTAModelIrfBackground ===
187   - 2015-05-22T20:17:07: Name ......................: CTABackgroundModel
188   - 2015-05-22T20:17:07: Instruments ...............: CTA
189   - 2015-05-22T20:17:07: Instrument scale factors ..: unity
190   - 2015-05-22T20:17:07: Observation identifiers ...: all
191   - 2015-05-22T20:17:07: Model type ................: "PowerLaw" * "Constant"
192   - 2015-05-22T20:17:07: Number of parameters ......: 4
193   - 2015-05-22T20:17:07: Number of spectral par's ..: 3
194   - 2015-05-22T20:17:07: Prefactor ................: 1.01608 +/- 0.0152751 [0.001,1000] ph/cm2/s/MeV (free,scale=1,gradient)
195   - 2015-05-22T20:17:07: Index ....................: 0.0226023 +/- 0.0086794 [-5,5] (free,scale=1,gradient)
196   - 2015-05-22T20:17:07: PivotEnergy ..............: 1e+06 [10000,1e+09] MeV (fixed,scale=1e+06,gradient)
197   - 2015-05-22T20:17:07: Number of temporal par's ..: 1
198   - 2015-05-22T20:17:07: Normalization ............: 1 (relative value) (fixed,scale=1,gradient)
  174 +
  175 + 2015-12-07T21:23:08: +=========================================+
  176 + 2015-12-07T21:23:08: | Maximum likelihood optimisation results |
  177 + 2015-12-07T21:23:08: +=========================================+
  178 + 2015-12-07T21:23:08: === GOptimizerLM ===
  179 + 2015-12-07T21:23:08: Optimized function value ..: 304161.783
  180 + 2015-12-07T21:23:08: Absolute precision ........: 0.005
  181 + 2015-12-07T21:23:08: Acceptable value decrease .: 2
  182 + 2015-12-07T21:23:08: Optimization status .......: converged
  183 + 2015-12-07T21:23:08: Number of parameters ......: 10
  184 + 2015-12-07T21:23:08: Number of free parameters .: 4
  185 + 2015-12-07T21:23:08: Number of iterations ......: 3
  186 + 2015-12-07T21:23:08: Lambda ....................: 1e-06
  187 + 2015-12-07T21:23:08: Maximum log likelihood ....: -304161.783
  188 + 2015-12-07T21:23:08: Observed events (Nobs) ...: 45122.000
  189 + 2015-12-07T21:23:08: Predicted events (Npred) ..: 45122.000 (Nobs - Npred = 1.04131e-06)
  190 + 2015-12-07T21:23:08: === GModels ===
  191 + 2015-12-07T21:23:08: Number of models ..........: 2
  192 + 2015-12-07T21:23:08: Number of parameters ......: 10
  193 + 2015-12-07T21:23:08: === GModelSky ===
  194 + 2015-12-07T21:23:08: Name ......................: Crab
  195 + 2015-12-07T21:23:08: Instruments ...............: all
  196 + 2015-12-07T21:23:08: Instrument scale factors ..: unity
  197 + 2015-12-07T21:23:08: Observation identifiers ...: all
  198 + 2015-12-07T21:23:08: Model type ................: PointSource
  199 + 2015-12-07T21:23:08: Model components ..........: "SkyDirFunction" * "PowerLaw" * "Constant"
  200 + 2015-12-07T21:23:08: Number of parameters ......: 6
  201 + 2015-12-07T21:23:08: Number of spatial par's ...: 2
  202 + 2015-12-07T21:23:08: RA .......................: 83.6331 [-360,360] deg (fixed,scale=1)
  203 + 2015-12-07T21:23:08: DEC ......................: 22.0145 [-90,90] deg (fixed,scale=1)
  204 + 2015-12-07T21:23:08: Number of spectral par's ..: 3
  205 + 2015-12-07T21:23:08: Prefactor ................: 5.78382e-16 +/- 7.27218e-18 [1e-23,1e-13] ph/cm2/s/MeV (free,scale=1e-16,gradient)
  206 + 2015-12-07T21:23:08: Index ....................: -2.5314 +/- 0.0112546 [-0,-5] (free,scale=-1,gradient)
  207 + 2015-12-07T21:23:08: PivotEnergy ..............: 300000 [10000,1e+09] MeV (fixed,scale=1e+06,gradient)
  208 + 2015-12-07T21:23:08: Number of temporal par's ..: 1
  209 + 2015-12-07T21:23:08: Normalization ............: 1 (relative value) (fixed,scale=1,gradient)
  210 + 2015-12-07T21:23:08: === GCTAModelIrfBackground ===
  211 + 2015-12-07T21:23:08: Name ......................: CTABackgroundModel
  212 + 2015-12-07T21:23:08: Instruments ...............: CTA
  213 + 2015-12-07T21:23:08: Instrument scale factors ..: unity
  214 + 2015-12-07T21:23:08: Observation identifiers ...: all
  215 + 2015-12-07T21:23:08: Model type ................: "PowerLaw" * "Constant"
  216 + 2015-12-07T21:23:08: Number of parameters ......: 4
  217 + 2015-12-07T21:23:08: Number of spectral par's ..: 3
  218 + 2015-12-07T21:23:08: Prefactor ................: 1.0008 +/- 0.00839192 [0.001,1000] ph/cm2/s/MeV (free,scale=1,gradient)
  219 + 2015-12-07T21:23:08: Index ....................: 0.0102998 +/- 0.0051965 [-5,5] (free,scale=1,gradient)
  220 + 2015-12-07T21:23:08: PivotEnergy ..............: 1e+06 [10000,1e+09] MeV (fixed,scale=1e+06,gradient)
  221 + 2015-12-07T21:23:08: Number of temporal par's ..: 1
  222 + 2015-12-07T21:23:08: Normalization ............: 1 (relative value) (fixed,scale=1,gradient)
199 223  
200 224 The log file indicates that the fit converged quickly, the spectral
201 225 parameters of the Crab nebula have now been constrained using the events
... ...
doc/source/user_manual/getting_started/beyond_irf.rst
  View file @14f9d87
... ... @@ -6,9 +6,9 @@ Connecting observations to dedicated instrument response functions
6 6 So far the same instrument response function has been used for all
7 7 observations in our analysis examples.
8 8 You may have recognised that we always specified the calibration database
9   -``prod2`` and the instrument response function ``South_50h`` that
  9 +``prod2`` and the instrument response function ``South_0.5h`` that
10 10 are shipped with ctools.
11   -When combining multiple observations in a joint analysis we may however
  11 +When combining multiple observations in a joint analysis you may however
12 12 need to specify dedicated instrument response functions for the
13 13 different observations.
14 14  
... ... @@ -26,40 +26,40 @@ the northern array and the other with the southern array:
26 26 Lower energy limit (TeV) [0.1]
27 27 Upper energy limit (TeV) [100.0]
28 28 Calibration database [prod2]
29   - Instrument response function [South_50h] North_50h
30   - Model [$CTOOLS/share/models/crab.xml]
31   - Output event data file or observation definition file [events.fits] events1.fits
  29 + Instrument response function [South_0.5h] North_0.5h
  30 + Input model XML file [$CTOOLS/share/models/crab.xml]
  31 + Output event data file or observation definition XML file [events.fits] north.fits
32 32  
33 33 .. code-block:: bash
34 34  
35 35 $ ctobssim
36 36 RA of pointing (degrees) (0-360) [83.63]
37   - Dec of pointing (degrees) (-90-90) [22.01] 22.51
  37 + Dec of pointing (degrees) (-90-90) [21.51] 22.51
38 38 Radius of FOV (degrees) (0-180) [5.0]
39 39 Start time (MET in s) [0.0]
40 40 End time (MET in s) [1800.0]
41 41 Lower energy limit (TeV) [0.1]
42 42 Upper energy limit (TeV) [100.0]
43 43 Calibration database [prod2]
44   - Instrument response function [North_50h] South_50h
45   - Model [$CTOOLS/share/models/crab.xml]
46   - Output event data file or observation definition file [events1.fits] events2.fits
  44 + Instrument response function [North_0.5h] South_0.5h
  45 + Input model XML file [$CTOOLS/share/models/crab.xml]
  46 + Output event data file or observation definition XML file [north.fits] south.fits
47 47  
48   -Now we combine the information about these two observations in an
  48 +You now need to combine the information about these two observations in an
49 49 observation definition XML file:
50 50  
51 51 .. code-block:: xml
52 52  
53   - <?xml version="1.0" standalone="no"?>
54   - <observation_list title="observation library">
55   - <observation name="Crab" id="00001" instrument="CTA">
56   - <parameter name="EventList" file="events1.fits"/>
57   - <parameter name="Calibration" database="prod2" response="North_50h"/>
58   - </observation>
59   - <observation name="Crab" id="00002" instrument="CTA">
60   - <parameter name="EventList" file="events2.fits"/>
61   - <parameter name="Calibration" database="prod2" response="South_50h"/>
62   - </observation>
  53 + <?xml version="1.0" standalone="no"?>
  54 + <observation_list title="observation library">
  55 + <observation name="Crab" id="00001" instrument="CTA">
  56 + <parameter name="EventList" file="north.fits"/>
  57 + <parameter name="Calibration" database="prod2" response="North_0.5h"/>
  58 + </observation>
  59 + <observation name="Crab" id="00002" instrument="CTA">
  60 + <parameter name="EventList" file="south.fits"/>
  61 + <parameter name="Calibration" database="prod2" response="South_0.5h"/>
  62 + </observation>
63 63 </observation_list>
64 64  
65 65 Each observation now has a ``Calibration`` parameter with the attributes
... ... @@ -97,126 +97,136 @@ Within this database there are six response functions:
97 97 ``North_0.5h``, ``North_5h``, ``North_50h``,
98 98 ``South_0.5h``, ``South_5h``, and ``South_50h``.
99 99  
100   -We now jointly fit both observations using :ref:`ctlike`:
  100 +You now jointly fit both observations using :ref:`ctlike`:
101 101  
102 102 .. code-block:: bash
103 103  
104   - $ ctlike
105   - Event list, counts cube or observation definition file [obs.xml] obs_irf.xml
106   - Source model [$CTOOLS/share/models/crab.xml]
107   - Source model output file [crab_results.xml]
  104 + $ ctlike chatter=3
  105 + Input event list, counts cube or observation definition XML file [events.fits] obs_irf.xml
  106 + Input model XML file [$CTOOLS/share/models/crab.xml]
  107 + Output model XML file [crab_results.xml]
108 108  
109 109 To see the usage of the individual response functions you may inspect the
110   -log file. You will notice that each observation now has a specific response
  110 +log file (you need to set ``chatter=3`` to see the details of the
  111 +observations in the log file).
  112 +You will notice that each observation now has a specific response
111 113 function and that the filename of the response information differs for
112 114 both observations.
113 115  
114 116 .. code-block:: xml
115 117  
116   - 2015-05-22T22:06:43: +==============+
117   - 2015-05-22T22:06:43: | Observations |
118   - 2015-05-22T22:06:43: +==============+
119   - 2015-05-22T22:06:43: === GObservations ===
120   - 2015-05-22T22:06:43: Number of observations ....: 2
121   - 2015-05-22T22:06:43: Number of predicted events : 0
122   - 2015-05-22T22:06:43: === GCTAObservation ===
123   - 2015-05-22T22:06:43: Name ......................:
124   - 2015-05-22T22:06:43: Identifier ................: 00001
125   - 2015-05-22T22:06:43: Instrument ................: CTA
126   - 2015-05-22T22:06:43: Event file ................: events1.fits
127   - 2015-05-22T22:06:43: Event type ................: EventList
128   - 2015-05-22T22:06:43: Statistics ................: Poisson
129   - 2015-05-22T22:06:43: Ontime ....................: 1800 s
130   - 2015-05-22T22:06:43: Livetime ..................: 1710 s
131   - 2015-05-22T22:06:43: Deadtime correction .......: 0.95
132   - 2015-05-22T22:06:43: User energy range .........: undefined
133   - 2015-05-22T22:06:43: === GCTAPointing ===
134   - 2015-05-22T22:06:43: Pointing direction ........: (RA,Dec)=(83.63,21.51)
135   - 2015-05-22T22:06:43: === GCTAResponseIrf ===
136   - 2015-05-22T22:06:43: Caldb mission .............: cta
137   - 2015-05-22T22:06:43: Caldb instrument ..........: prod2
138   - 2015-05-22T22:06:43: Response name .............: North_50h
139   - 2015-05-22T22:06:43: Energy dispersion .........: Not used
140   - 2015-05-22T22:06:43: Save energy range .........: undefined
  118 + 2015-12-07T22:22:18: +==============+
  119 + 2015-12-07T22:22:18: | Observations |
  120 + 2015-12-07T22:22:18: +==============+
  121 + 2015-12-07T22:22:18: === GObservations ===
  122 + 2015-12-07T22:22:18: Number of observations ....: 2
  123 + 2015-12-07T22:22:18: Number of models ..........: 2
  124 + 2015-12-07T22:22:18: Number of predicted events : 0
  125 + 2015-12-07T22:22:18: === GCTAObservation ===
  126 + 2015-12-07T22:22:18: Name ......................: Crab
  127 + 2015-12-07T22:22:18: Identifier ................: 00001
  128 + 2015-12-07T22:22:18: Instrument ................: CTA
  129 + 2015-12-07T22:22:18: Event file ................: north.fits
  130 + 2015-12-07T22:22:18: Event type ................: EventList
  131 + 2015-12-07T22:22:18: Statistics ................: Poisson
  132 + 2015-12-07T22:22:18: Ontime ....................: 1800 s
  133 + 2015-12-07T22:22:18: Livetime ..................: 1710 s
  134 + 2015-12-07T22:22:18: Deadtime correction .......: 0.95
  135 + 2015-12-07T22:22:18: User energy range .........: undefined
  136 + 2015-12-07T22:22:18: === GCTAPointing ===
  137 + 2015-12-07T22:22:18: Pointing direction ........: (RA,Dec)=(83.63,21.51)
  138 + 2015-12-07T22:22:18: === GCTAResponseIrf ===
  139 + 2015-12-07T22:22:18: Caldb mission .............: cta
  140 + 2015-12-07T22:22:18: Caldb instrument ..........: prod2
  141 + 2015-12-07T22:22:18: Response name .............: North_0.5h
  142 + 2015-12-07T22:22:18: Energy dispersion .........: Not used
  143 + 2015-12-07T22:22:18: Save energy range .........: undefined
  144 + 2015-12-07T22:22:18: === GCTAEventList ===
  145 + 2015-12-07T22:22:18: Number of events ..........: 8469
  146 + 2015-12-07T22:22:18: Time interval .............: 51544.5 - 51544.5 days
  147 + 2015-12-07T22:22:18: Energy interval ...........: 0.1 - 100 TeV
  148 + 2015-12-07T22:22:18: Region of interest ........: RA=83.63, DEC=21.51 [0,0] Radius=5 deg
  149 + 2015-12-07T22:22:18: === GCTAObservation ===
  150 + 2015-12-07T22:22:18: Name ......................: Crab
  151 + 2015-12-07T22:22:18: Identifier ................: 00002
  152 + 2015-12-07T22:22:18: Instrument ................: CTA
  153 + 2015-12-07T22:22:18: Event file ................: south.fits
  154 + 2015-12-07T22:22:18: Event type ................: EventList
  155 + 2015-12-07T22:22:18: Statistics ................: Poisson
  156 + 2015-12-07T22:22:18: Ontime ....................: 1800 s
  157 + 2015-12-07T22:22:18: Livetime ..................: 1710 s
  158 + 2015-12-07T22:22:18: Deadtime correction .......: 0.95
  159 + 2015-12-07T22:22:18: User energy range .........: undefined
  160 + 2015-12-07T22:22:18: === GCTAPointing ===
  161 + 2015-12-07T22:22:18: Pointing direction ........: (RA,Dec)=(83.63,22.51)
  162 + 2015-12-07T22:22:18: === GCTAResponseIrf ===
  163 + 2015-12-07T22:22:18: Caldb mission .............: cta
  164 + 2015-12-07T22:22:18: Caldb instrument ..........: prod2
  165 + 2015-12-07T22:22:18: Response name .............: South_0.5h
  166 + 2015-12-07T22:22:18: Energy dispersion .........: Not used
  167 + 2015-12-07T22:22:18: Save energy range .........: undefined
  168 + 2015-12-07T22:22:18: === GCTAEventList ===
  169 + 2015-12-07T22:22:18: Number of events ..........: 22529
  170 + 2015-12-07T22:22:18: Time interval .............: 51544.5 - 51544.5 days
  171 + 2015-12-07T22:22:18: Energy interval ...........: 0.1 - 100 TeV
  172 + 2015-12-07T22:22:18: Region of interest ........: RA=83.63, DEC=22.51 [0,0] Radius=5 deg
141 173 ...
142   - 2015-05-22T22:06:43: === GCTAObservation ===
143   - 2015-05-22T22:06:43: Name ......................:
144   - 2015-05-22T22:06:43: Identifier ................: 00002
145   - 2015-05-22T22:06:43: Instrument ................: CTA
146   - 2015-05-22T22:06:43: Event file ................: events2.fits
147   - 2015-05-22T22:06:43: Event type ................: EventList
148   - 2015-05-22T22:06:43: Statistics ................: Poisson
149   - 2015-05-22T22:06:43: Ontime ....................: 1800 s
150   - 2015-05-22T22:06:43: Livetime ..................: 1710 s
151   - 2015-05-22T22:06:43: Deadtime correction .......: 0.95
152   - 2015-05-22T22:06:43: User energy range .........: undefined
153   - 2015-05-22T22:06:43: === GCTAPointing ===
154   - 2015-05-22T22:06:43: Pointing direction ........: (RA,Dec)=(83.63,22.51)
155   - 2015-05-22T22:06:43: === GCTAResponseIrf ===
156   - 2015-05-22T22:06:43: Caldb mission .............: cta
157   - 2015-05-22T22:06:43: Caldb instrument ..........: prod2
158   - 2015-05-22T22:06:43: Response name .............: South_50h
159   - 2015-05-22T22:06:43: Energy dispersion .........: Not used
160   - 2015-05-22T22:06:43: Save energy range .........: undefined
  174 + 2015-12-07T22:22:18: +=================================+
  175 + 2015-12-07T22:22:18: | Maximum likelihood optimisation |
  176 + 2015-12-07T22:22:18: +=================================+
  177 + 2015-12-07T22:22:18: >Iteration 0: -logL=214691.468, Lambda=1.0e-03
  178 + 2015-12-07T22:22:18: >Iteration 1: -logL=214679.380, Lambda=1.0e-03, delta=12.088, max(|grad|)=9.713100 [Index:3]
  179 + 2015-12-07T22:22:18: >Iteration 2: -logL=214679.365, Lambda=1.0e-04, delta=0.015, max(|grad|)=0.092975 [Index:3]
  180 + 2015-12-07T22:22:18: >Iteration 3: -logL=214679.365, Lambda=1.0e-05, delta=0.000, max(|grad|)=0.000749 [Index:3]
161 181 ...
162   - 2015-05-22T22:06:43: +=================================+
163   - 2015-05-22T22:06:43: | Maximum likelihood optimisation |
164   - 2015-05-22T22:06:43: +=================================+
165   - 2015-05-22T22:06:43: >Iteration 0: -logL=138039.472, Lambda=1.0e-03
166   - 2015-05-22T22:06:43: >Iteration 1: -logL=138035.501, Lambda=1.0e-03, delta=3.971, max(|grad|)=16.203761 [Index:7]
167   - 2015-05-22T22:06:43: >Iteration 2: -logL=138035.496, Lambda=1.0e-04, delta=0.005, max(|grad|)=-0.053284 [Index:7]
168   - 2015-05-22T22:06:43: >Iteration 3: -logL=138035.496, Lambda=1.0e-05, delta=0.000, max(|grad|)=0.001386 [Index:7]
169   - 2015-05-22T22:06:44:
170   - 2015-05-22T22:06:44: +=========================================+
171   - 2015-05-22T22:06:44: | Maximum likelihood optimization results |
172   - 2015-05-22T22:06:44: +=========================================+
173   - 2015-05-22T22:06:44: === GOptimizerLM ===
174   - 2015-05-22T22:06:44: Optimized function value ..: 138035.496
175   - 2015-05-22T22:06:44: Absolute precision ........: 0.005
176   - 2015-05-22T22:06:44: Acceptable value decrease .: 2
177   - 2015-05-22T22:06:44: Optimization status .......: converged
178   - 2015-05-22T22:06:44: Number of parameters ......: 10
179   - 2015-05-22T22:06:44: Number of free parameters .: 4
180   - 2015-05-22T22:06:44: Number of iterations ......: 3
181   - 2015-05-22T22:06:44: Lambda ....................: 1e-06
182   - 2015-05-22T22:06:44: Maximum log likelihood ....: -138035.496
183   - 2015-05-22T22:06:44: Observed events (Nobs) ...: 20814.000
184   - 2015-05-22T22:06:44: Predicted events (Npred) ..: 20814.000 (Nobs - Npred = 2.67698e-06)
185   - 2015-05-22T22:06:44: === GModels ===
186   - 2015-05-22T22:06:44: Number of models ..........: 2
187   - 2015-05-22T22:06:44: Number of parameters ......: 10
188   - 2015-05-22T22:06:44: === GModelSky ===
189   - 2015-05-22T22:06:44: Name ......................: Crab
190   - 2015-05-22T22:06:44: Instruments ...............: all
191   - 2015-05-22T22:06:44: Instrument scale factors ..: unity
192   - 2015-05-22T22:06:44: Observation identifiers ...: all
193   - 2015-05-22T22:06:44: Model type ................: PointSource
194   - 2015-05-22T22:06:44: Model components ..........: "SkyDirFunction" * "PowerLaw" * "Constant"
195   - 2015-05-22T22:06:44: Number of parameters ......: 6
196   - 2015-05-22T22:06:44: Number of spatial par's ...: 2
197   - 2015-05-22T22:06:44: RA .......................: 83.6331 [-360,360] deg (fixed,scale=1)
198   - 2015-05-22T22:06:44: DEC ......................: 22.0145 [-90,90] deg (fixed,scale=1)
199   - 2015-05-22T22:06:44: Number of spectral par's ..: 3
200   - 2015-05-22T22:06:44: Prefactor ................: 5.9184e-16 +/- 9.68924e-18 [1e-23,1e-13] ph/cm2/s/MeV (free,scale=1e-16,gradient)
201   - 2015-05-22T22:06:44: Index ....................: -2.49569 +/- 0.0145376 [-0,-5] (free,scale=-1,gradient)
202   - 2015-05-22T22:06:44: PivotEnergy ..............: 300000 [10000,1e+09] MeV (fixed,scale=1e+06,gradient)
203   - 2015-05-22T22:06:44: Number of temporal par's ..: 1
204   - 2015-05-22T22:06:44: Normalization ............: 1 (relative value) (fixed,scale=1,gradient)
205   - 2015-05-22T22:06:44: === GCTAModelIrfBackground ===
206   - 2015-05-22T22:06:44: Name ......................: CTABackgroundModel
207   - 2015-05-22T22:06:44: Instruments ...............: CTA
208   - 2015-05-22T22:06:44: Instrument scale factors ..: unity
209   - 2015-05-22T22:06:44: Observation identifiers ...: all
210   - 2015-05-22T22:06:44: Model type ................: "PowerLaw" * "Constant"
211   - 2015-05-22T22:06:44: Number of parameters ......: 4
212   - 2015-05-22T22:06:44: Number of spectral par's ..: 3
213   - 2015-05-22T22:06:44: Prefactor ................: 1.02524 +/- 0.0182054 [0.001,1000] ph/cm2/s/MeV (free,scale=1,gradient)
214   - 2015-05-22T22:06:44: Index ....................: 0.0229728 +/- 0.0104713 [-5,5] (free,scale=1,gradient)
215   - 2015-05-22T22:06:44: PivotEnergy ..............: 1e+06 [10000,1e+09] MeV (fixed,scale=1e+06,gradient)
216   - 2015-05-22T22:06:44: Number of temporal par's ..: 1
217   - 2015-05-22T22:06:44: Normalization ............: 1 (relative value) (fixed,scale=1,gradient)
218   -
219   -
  182 + 2015-12-07T22:22:18: +=========================================+
  183 + 2015-12-07T22:22:18: | Maximum likelihood optimisation results |
  184 + 2015-12-07T22:22:18: +=========================================+
  185 + 2015-12-07T22:22:18: === GOptimizerLM ===
  186 + 2015-12-07T22:22:18: Optimized function value ..: 214679.365
  187 + 2015-12-07T22:22:18: Absolute precision ........: 0.005
  188 + 2015-12-07T22:22:18: Acceptable value decrease .: 2
  189 + 2015-12-07T22:22:18: Optimization status .......: converged
  190 + 2015-12-07T22:22:18: Number of parameters ......: 10
  191 + 2015-12-07T22:22:18: Number of free parameters .: 4
  192 + 2015-12-07T22:22:18: Number of iterations ......: 3
  193 + 2015-12-07T22:22:18: Lambda ....................: 1e-06
  194 + 2015-12-07T22:22:18: Maximum log likelihood ....: -214679.365
  195 + 2015-12-07T22:22:18: Observed events (Nobs) ...: 30998.000
  196 + 2015-12-07T22:22:18: Predicted events (Npred) ..: 30998.000 (Nobs - Npred = 1.02755e-06)
  197 + 2015-12-07T22:22:18: === GModels ===
  198 + 2015-12-07T22:22:18: Number of models ..........: 2
  199 + 2015-12-07T22:22:18: Number of parameters ......: 10
  200 + 2015-12-07T22:22:18: === GModelSky ===
  201 + 2015-12-07T22:22:18: Name ......................: Crab
  202 + 2015-12-07T22:22:18: Instruments ...............: all
  203 + 2015-12-07T22:22:18: Instrument scale factors ..: unity
  204 + 2015-12-07T22:22:18: Observation identifiers ...: all
  205 + 2015-12-07T22:22:18: Model type ................: PointSource
  206 + 2015-12-07T22:22:18: Model components ..........: "SkyDirFunction" * "PowerLaw" * "Constant"
  207 + 2015-12-07T22:22:18: Number of parameters ......: 6
  208 + 2015-12-07T22:22:18: Number of spatial par's ...: 2
  209 + 2015-12-07T22:22:18: RA .......................: 83.6331 [-360,360] deg (fixed,scale=1)
  210 + 2015-12-07T22:22:18: DEC ......................: 22.0145 [-90,90] deg (fixed,scale=1)
  211 + 2015-12-07T22:22:18: Number of spectral par's ..: 3
  212 + 2015-12-07T22:22:18: Prefactor ................: 5.81237e-16 +/- 8.63534e-18 [1e-23,1e-13] ph/cm2/s/MeV (free,scale=1e-16,gradient)
  213 + 2015-12-07T22:22:18: Index ....................: -2.53954 +/- 0.0137432 [-0,-5] (free,scale=-1,gradient)
  214 + 2015-12-07T22:22:18: PivotEnergy ..............: 300000 [10000,1e+09] MeV (fixed,scale=1e+06,gradient)
  215 + 2015-12-07T22:22:18: Number of temporal par's ..: 1
  216 + 2015-12-07T22:22:18: Normalization ............: 1 (relative value) (fixed,scale=1,gradient)
  217 + 2015-12-07T22:22:18: === GCTAModelIrfBackground ===
  218 + 2015-12-07T22:22:18: Name ......................: CTABackgroundModel
  219 + 2015-12-07T22:22:18: Instruments ...............: CTA
  220 + 2015-12-07T22:22:18: Instrument scale factors ..: unity
  221 + 2015-12-07T22:22:18: Observation identifiers ...: all
  222 + 2015-12-07T22:22:18: Model type ................: "PowerLaw" * "Constant"
  223 + 2015-12-07T22:22:18: Number of parameters ......: 4
  224 + 2015-12-07T22:22:18: Number of spectral par's ..: 3
  225 + 2015-12-07T22:22:18: Prefactor ................: 1.01067 +/- 0.0103997 [0.001,1000] ph/cm2/s/MeV (free,scale=1,gradient)
  226 + 2015-12-07T22:22:18: Index ....................: 0.0135414 +/- 0.0064452 [-5,5] (free,scale=1,gradient)
  227 + 2015-12-07T22:22:18: PivotEnergy ..............: 1e+06 [10000,1e+09] MeV (fixed,scale=1e+06,gradient)
  228 + 2015-12-07T22:22:18: Number of temporal par's ..: 1
  229 + 2015-12-07T22:22:18: Normalization ............: 1 (relative value) (fixed,scale=1,gradient)
220 230  
221 231 A more fine grained control over the response function can be achieved by
222 232 specifying individual filenames for the various response components.
... ... @@ -228,18 +238,18 @@ This is definitely expert mode, to be used with utmost care.
228 238 <?xml version="1.0" standalone="no"?>
229 239 <observation_list title="observation library">
230 240 <observation name="Crab" id="00001" instrument="CTA">
231   - <parameter name="EventList" file="events1.fits"/>
232   - <parameter name="EffectiveArea" file="$(CALDB)/data/cta/prod2/bcf/North_50h/irf_file.fits.gz"/>
233   - <parameter name="PointSpreadFunction" file="$(CALDB)/data/cta/prod2/bcf/North_50h/irf_file.fits.gz"/>
234   - <parameter name="EnergyDispersion" file="$(CALDB)/data/cta/prod2/bcf/North_50h/irf_file.fits.gz"/>
235   - <parameter name="Background" file="$(CALDB)/data/cta/prod2/bcf/North_50h/irf_file.fits.gz"/>
  241 + <parameter name="EventList" file="north.fits"/>
  242 + <parameter name="EffectiveArea" file="$(CALDB)/data/cta/prod2/bcf/North_0.5h/irf_file.fits.gz"/>
  243 + <parameter name="PointSpreadFunction" file="$(CALDB)/data/cta/prod2/bcf/North_0.5h/irf_file.fits.gz"/>
  244 + <parameter name="EnergyDispersion" file="$(CALDB)/data/cta/prod2/bcf/North_0.5h/irf_file.fits.gz"/>
  245 + <parameter name="Background" file="$(CALDB)/data/cta/prod2/bcf/North_0.5h/irf_file.fits.gz"/>
236 246 </observation>
237 247 <observation name="Crab" id="00002" instrument="CTA">
238   - <parameter name="EventList" file="events2.fits"/>
239   - <parameter name="EffectiveArea" file="$(CALDB)/data/cta/prod2/bcf/South_50h/irf_file.fits.gz"/>
240   - <parameter name="PointSpreadFunction" file="$(CALDB)/data/cta/prod2/bcf/South_50h/irf_file.fits.gz"/>
241   - <parameter name="EnergyDispersion" file="$(CALDB)/data/cta/prod2/bcf/South_50h/irf_file.fits.gz"/>
242   - <parameter name="Background" file="$(CALDB)/data/cta/prod2/bcf/South_50h/irf_file.fits.gz"/>
  248 + <parameter name="EventList" file="south.fits"/>
  249 + <parameter name="EffectiveArea" file="$(CALDB)/data/cta/prod2/bcf/South_0.5h/irf_file.fits.gz"/>
  250 + <parameter name="PointSpreadFunction" file="$(CALDB)/data/cta/prod2/bcf/South_0.5h/irf_file.fits.gz"/>
  251 + <parameter name="EnergyDispersion" file="$(CALDB)/data/cta/prod2/bcf/South_0.5h/irf_file.fits.gz"/>
  252 + <parameter name="Background" file="$(CALDB)/data/cta/prod2/bcf/South_0.5h/irf_file.fits.gz"/>
243 253 </observation>
244 254 </observation_list>
245 255  
... ... @@ -264,5 +274,3 @@ file is given below:
264 274 <parameter name="BkgCube" file="bkgcube2.fits"/>
265 275 </observation>
266 276 </observation_list>
267   -
268   -
... ...
doc/source/user_manual/getting_started/beyond_model.rst
  View file @14f9d87
... ... @@ -26,20 +26,15 @@ specified by the following observation definition XML file:
26 26 </observation>
27 27 </observation_list>
28 28  
29   -Each observation has a **unique identifier string** and we can use this
30   -unique string to connect that observation to a specific model component.
  29 +Each observation has a **unique identifier string** and you can use this
  30 +unique string to connect an observation to a specific model component.
31 31 This is illustrated in the model XML file below that now has two background
32 32 components.
33   -**Model components in a XML file need to have a unique name**, for this
34   -reason we have named the components ``Background_00001`` and
35   -``Background_00002``.
36   -Both components now have an ``id`` attribute that ties the model to
37   -an observation.
38   -In other words, the model is only applicable to a specific observation
39   -(it will be ignored for all other observations).
40   -In our case, model ``Background_00001`` applies to the ``events1.fits``
41   -event list while model ``Background_00002`` applies to the ``events2.fits``
42   -event list.
  33 +Both components have an ``id`` attribute that ties the model to a specific
  34 +observation.
  35 +Using ``id="00001"``, the first background model is tied to the
  36 +``events1.fits`` file, using ``id="00002"``, the second background model is
  37 +tied to the ``events2.fits`` file.
43 38  
44 39 .. code-block:: xml
45 40  
... ... @@ -72,13 +67,21 @@ event list.
72 67 </source>
73 68 </source_library>
74 69  
75   -Note that both background model components distinguish in their event rate;
76   -component ``Background_00002`` has a ten times larger background rate than
77   -component ``Background_00001``.
78   -To illustrate this difference, we simulated two observations offset by
79   -+/- 2 degrees from the Crab nebulae using :ref:`ctobssim`.
80   -We then performed a joint fit of the observations using :ref:`ctlike`
81   -and created a resdiual map using :ref:`csresmap` that is shown below.
  70 +.. note::
  71 +
  72 + **Model components in a XML file need to have a unique name.**
  73 + For this reason the components are named here ``Background_00001``
  74 + and ``Background_00002``.
  75 +
  76 +Note that both background model components distinguish in their event rate.
  77 +``Background_00002`` has a ten times larger background rate than
  78 +``Background_00001``.
  79 +To illustrate this difference, two observations offset by +/- 2 degrees from
  80 +the Crab nebulae have been simulated using :ref:`ctobssim`.
  81 +A joint fit of the observations is then performed using :ref:`ctlike` and
  82 +a residual map is created using :ref:`csresmap`.
  83 +
  84 +The result is shown below.
82 85 Obviously, the upper observation has larger residuals owing to the ten
83 86 times larger background rate that was used in the simulation of the
84 87 associated data.
... ...
doc/source/user_manual/getting_started/beyond_residual.rst
  View file @14f9d87
... ... @@ -22,11 +22,11 @@ Suppose that you have done the following unbinned ``ctlike`` analysis:
22 22 .. code-block:: bash
23 23  
24 24 $ ctlike
25   - Event list, counts cube or observation definition file [events.fits] obs.xml
  25 + Input event list, counts cube or observation definition XML file [events.fits] obs.xml
26 26 Calibration database [prod2]
27   - Instrument response function [South_50h]
28   - Source model [$CTOOLS/share/models/crab.xml]
29   - Source model output file [crab_results.xml]
  27 + Instrument response function [South_0.5h]
  28 + Input model XML file [$CTOOLS/share/models/crab.xml]
  29 + Output model XML file [crab_results.xml]
30 30  
31 31 The :ref:`csresmap` script is then used as follows:
32 32  
... ... @@ -34,18 +34,19 @@ The :ref:`csresmap` script is then used as follows:
34 34  
35 35 $ csresmap
36 36 Parfile csresmap.par not found. Create default parfile.
37   - Event list, counts cube, or observation definition file [events.fits] obs.xml
  37 + Input event list, counts cube, or observation definition XML file [events.fits] obs.xml
38 38 Calibration database [prod2]
39   - Instrument response function [South_50h]
40   - Source model [$CTOOLS/share/models/crab.xml] crab_results.xml
41   - Output residual map [resmap.fits]
42   - First coordinate of image center in degrees (RA or galactic l) [83.63]
43   - Second coordinate of image center in degrees (DEC or galactic b) [22.01]
  39 + Instrument response function [South_0.5h]
  40 + Input model XML file [$CTOOLS/share/models/crab.xml] crab_results.xml
  41 + First coordinate of image center in degrees (RA or galactic l) (0-360) [83.63]
  42 + Second coordinate of image center in degrees (DEC or galactic b) (-90-90) [22.01]
44 43 Coordinate System (CEL|GAL) [CEL]
45   - Projection method e.g. AIT|AZP|CAR|MER|MOL|STG|TAN (AIT|AZP|CAR|MER|MOL|STG|TAN) [CAR]
  44 + Projection method (AIT|AZP|CAR|MER|MOL|STG|TAN) [CAR]
46 45 Size of the X axis in pixels [200]
47 46 Size of the Y axis in pixels [200]
48 47 Pixel size (deg/pixel) [0.02]
  48 + Output residual map file [resmap.fits]
  49 + Residual map computation algorithm (SUB|SUBDIV|SUBDIVSQRT) [SUBDIV]
49 50  
50 51 In our example, the map will cover a field of 4 x 4 degrees centred on the
51 52 Crab nebula at a pixel scale of 0.02 degrees per pixel.
... ...
doc/source/user_manual/getting_started/beyond_stacked.rst
  View file @14f9d87
... ... @@ -6,16 +6,15 @@ Performing a stacked analysis
6 6 A stacked analysis is a binned analysis where all data from multiple
7 7 observations are stacked into a single counts cube.
8 8 The event stacking is done using the :ref:`ctbin` tool.
9   -Instead of providing to :ref:`ctbin` an event list we
10   -now specify the observation definition XML file ``obs.xml``
11   -on input.
  9 +Instead of providing to :ref:`ctbin` an event list you should now
  10 +specify the observation definition XML file ``obs.xml`` on input.
12 11 :ref:`ctbin` will then loop over all observations and collect all events
13 12 into a single counts cube:
14 13  
15 14 .. code-block:: bash
16 15  
17 16 $ ctbin
18   - Event list or observation definition file [events.fits] obs.xml
  17 + Input event list or observation definition XML file [events.fits] obs.xml
19 18 First coordinate of image center in degrees (RA or galactic l) (0-360) [83.63]
20 19 Second coordinate of image center in degrees (DEC or galactic b) (-90-90) [22.01]
21 20 Projection method (AIT|AZP|CAR|MER|MOL|STG|TAN) [CAR]
... ... @@ -27,37 +26,37 @@ into a single counts cube:
27 26 Start value for first energy bin in TeV [0.1]
28 27 Stop value for last energy bin in TeV [100.0]
29 28 Number of energy bins [20]
30   - Output counts cube [cntcube.fits]
  29 + Output counts cube file [cntcube.fits]
31 30  
32   -We now have a stacked counts cube ``cntcube.fits`` on disk.
33   -Before we can use that counts cube in a maximum likelihood
34   -analysis, we have to compute the instrument response and the
  31 +You now have a stacked counts cube ``cntcube.fits`` on disk.
  32 +Before you can use that counts cube in a maximum likelihood
  33 +analysis, you have to compute the instrument response and the
35 34 background model that are needed to describe the stacked data.
36 35  
37   -For the former, we have to compute the total exposure for the stacked
  36 +For the former, you have to compute the total exposure for the stacked
38 37 cube (i.e. the sum of the effective areas for each observation multiplied
39 38 by the corresponding livetimes) and an effective point spread function
40 39 (i.e. the point spread function of the different observations weighted by
41 40 the corresponding exposures).
42   -To get both informations we use the :ref:`ctexpcube` and
  41 +To get both informations you use the :ref:`ctexpcube` and
43 42 :ref:`ctpsfcube` tools:
44 43  
45 44 .. code-block:: bash
46 45  
47 46 $ ctexpcube
48   - Event list or observation definition file [NONE] obs.xml
  47 + Input event list or observation definition XML file [NONE] obs.xml
49 48 Calibration database [prod2]
50   - Instrument response function [South_50h]
51   - Counts cube for exposure cube definition [NONE] cntcube.fits
  49 + Instrument response function [South_0.5h]
  50 + Input counts cube file to extract exposure cube definition [NONE] cntcube.fits
52 51 Output exposure cube file [expcube.fits]
53 52  
54 53 .. code-block:: bash
55 54  
56 55 $ ctpsfcube
57   - Event list or observation definition file [NONE] obs.xml
  56 + Input event list or observation definition XML file [NONE] obs.xml
58 57 Calibration database [prod2]
59   - Instrument response function [South_50h]
60   - Counts cube for psf cube definition [NONE]
  58 + Instrument response function [South_0.5h]
  59 + Input counts cube file to extract PSF cube definition [NONE]
61 60 First coordinate of image center in degrees (RA or galactic l) (0-360) [83.63]
62 61 Second coordinate of image center in degrees (DEC or galactic b) (-90-90) [22.01]
63 62 Projection method (AIT|AZP|CAR|MER|MOL|STG|TAN) [CAR]
... ... @@ -68,42 +67,41 @@ To get both informations we use the :ref:`ctexpcube` and
68 67 Lower energy limit (TeV) [0.1]
69 68 Upper energy limit (TeV) [100.0]
70 69 Number of energy bins [20]
71   - Output psf cube file [psfcube.fits]
72   -
73   -We provide the ``obs.xml`` file on input to inform both tools which
74   -observations have been combined.
75   -For :ref:`ctexpcube` we further provide the counts cube so that the
76   -tool can copy the exposure cube definition (number of spatial pixels
77   -and pixel size, number of energy bins) from the counts cube.
78   -This minimises the number of further user parameters that need to be
79   -provided and assures an exposure cube that is compatible with the counts
80   -cube.
81   -For :ref:`ctpsfcube` we do not use the counts cube for the PSF cube
82   -definition as this would lead to a hugh file owing to the fine spatial
  70 + Output PSF cube file [psfcube.fits]
  71 +
  72 +The ``obs.xml`` file has been provided on input to specify for both tools
  73 +which observations have been combined.
  74 +You further provided the counts cube on input so that :ref:`ctexpcube` can
  75 +read the cub definition from that file and apply it to the exposure cube.
  76 +This is a trick to reduce the number of user parameters that you need to
  77 +provide.
  78 +
  79 +You do not apply this trick when using :ref:`ctpsfcube` as this
  80 +would lead to a hugh output file owing to the fine spatial
83 81 pixelisation of the counts cube.
84   -Since the PSF evolves only slowly over the field of fiew, we provide a
85   -rather coarse spatial binning of 1 degree covering a grid of 10 x 10
86   -degrees around the centre of the counts cube.
87   -For the energy binning, we use the same logarithmic binning that has
88   -also been used for the counts cube.
  82 +Such a fine binning is not needed for the PSF cube, as the PSF evolves
  83 +only slowly over the field of view.
  84 +It is thus sufficient to compute a PSF cube with a rather coarse spatial
  85 +binning; here you used a spatial binning of 1 degree covering a grid of
  86 +10 x 10 degrees.
89 87  
90   -As final step of the analysis preparation, we need to generate a
  88 +As final step of the analysis preparation, you need to generate a
91 89 background cube using the :ref:`ctbkgcube` tool:
92 90  
93 91 .. code-block:: bash
94 92  
95 93 $ ctbkgcube
96   - Input event list or observation definition file [NONE] obs.xml
  94 + Input event list or observation definition XML file [NONE] obs.xml
97 95 Calibration database [prod2]
98   - Instrument response function [South_50h]
99   - Counts cube for background cube definition [NONE] cntcube.fits
  96 + Instrument response function [South_0.5h]
  97 + Input counts cube file to extract background cube definition [NONE] cntcube.fits
100 98 Input model XML file [NONE] $CTOOLS/share/models/crab.xml
101 99 Output background cube file [bkgcube.fits]
102 100 Output model XML file [NONE] model.xml
103 101  
104 102 The usage of :ref:`ctbkgcube` is very similar to that of :ref:`ctexpcube`,
105 103 yet it takes the model XML file as an additional input parameter.
106   -We here use the usual ``$CTOOLS/share/models/crab.xml`` model
  104 +You used here the usual ``$CTOOLS/share/models/crab.xml`` model
107 105 file that is shipped with the ctools.
108 106 :ref:`ctbkgcube` provides on output the background cube file
109 107 ``bkgcube.fits`` and the model XML file ``model.xml`` that can
... ... @@ -115,7 +113,7 @@ modelling works:
115 113  
116 114 <?xml version="1.0" encoding="UTF-8" standalone="no"?>
117 115 <source_library title="source library">
118   - <source name="Crab" type="PointSource" tscalc="0">
  116 + <source name="Crab" type="PointSource">
119 117 <spectrum type="PowerLaw">
120 118 <parameter name="Prefactor" value="5.7" error="0" scale="1e-16" min="1e-07" max="1000" free="1" />
121 119 <parameter name="Index" value="2.48" error="0" scale="-1" min="0" max="5" free="1" />
... ... @@ -157,88 +155,88 @@ as an appropriate multiplicator to the background cube.
157 155 Using the same binning for the exposure cube, the background cube and
158 156 the counts cube is only a convenience.
159 157  
160   -Now we have all files at hand to launch a stacked maximum likelihood
  158 +Now you have all files at hand to perform a stacked maximum likelihood
161 159 analysis using the :ref:`ctlike` tool:
162 160  
163 161 .. code-block:: bash
164 162  
165 163 $ ctlike
166   - Event list, counts cube or observation definition file [obs.xml] cntcube.fits
167   - Exposure cube file (only needed for stacked analysis) [NONE] expcube.fits
168   - PSF cube file (only needed for stacked analysis) [NONE] psfcube.fits
169   - Background cube file (only needed for stacked analysis) [NONE] bkgcube.fits
170   - Source model [$CTOOLS/share/models/crab.xml] model.xml
171   - Source model output file [crab_results.xml]
  164 + Input event list, counts cube or observation definition XML file [obs.xml] cntcube.fits
  165 + Input exposure cube file (only needed for stacked analysis) [NONE] expcube.fits
  166 + Input PSF cube file (only needed for stacked analysis) [NONE] psfcube.fits
  167 + Input background cube file (only needed for stacked analysis) [NONE] bkgcube.fits
  168 + Input model XML file [$CTOOLS/share/models/crab.xml] model.xml
  169 + Output model XML file [crab_results.xml]
172 170  
173 171 :ref:`ctlike` recognises that a counts cube should be analysed and queries
174 172 for the exposure cube, the PSF cube, and the background cube file names.
175   -We specified the names of the files produced by the :ref:`ctexpcube`,
  173 +You specified here the names of the files produced by the :ref:`ctexpcube`,
176 174 the :ref:`ctpsfcube` and the :ref:`ctbkgcube` tools.
177   -Furthermore we provided as model the ``model.xml`` file that has been
  175 +Furthermore you provided as model the ``model.xml`` file that has been
178 176 generated by the :ref:`ctbkgcube` tool.
179 177  
180 178 The log file of the :ref:`ctlike` run is shown below.
181 179 Note that the spectral model that is multiplied with the background
182   -cube has a Prefactor of 1.09 +/- 0.02 and an Index of 0.03 +/- 0.01,
  180 +cube has a Prefactor of 0.998 +/- 0.011 and an Index of 0.006 +/- 0.007,
183 181 indicating a very small correction to the actual spectrum of the background
184 182 cube.
185 183 Real life situations may of course require larger correction factors.
186 184  
187 185 .. code-block:: xml
188 186  
189   - 2015-05-22T21:10:09: +=================================+
190   - 2015-05-22T21:10:09: | Maximum likelihood optimisation |
191   - 2015-05-22T21:10:09: +=================================+
192   - 2015-05-22T21:10:10: >Iteration 0: -logL=60663.798, Lambda=1.0e-03
193   - 2015-05-22T21:10:11: >Iteration 1: -logL=60642.413, Lambda=1.0e-03, delta=21.385, max(|grad|)=120.031102 [Index:7]
194   - 2015-05-22T21:10:13: >Iteration 2: -logL=60642.233, Lambda=1.0e-04, delta=0.180, max(|grad|)=1.139187 [Index:7]
195   - 2015-05-22T21:10:14: >Iteration 3: -logL=60642.233, Lambda=1.0e-05, delta=0.000, max(|grad|)=-0.001247 [Index:7]
196   - 2015-05-22T21:10:16:
197   - 2015-05-22T21:10:16: +=========================================+
198   - 2015-05-22T21:10:16: | Maximum likelihood optimization results |
199   - 2015-05-22T21:10:16: +=========================================+
200   - 2015-05-22T21:10:16: === GOptimizerLM ===
201   - 2015-05-22T21:10:16: Optimized function value ..: 60642.233
202   - 2015-05-22T21:10:16: Absolute precision ........: 0.005
203   - 2015-05-22T21:10:16: Acceptable value decrease .: 2
204   - 2015-05-22T21:10:16: Optimization status .......: converged
205   - 2015-05-22T21:10:16: Number of parameters ......: 10
206   - 2015-05-22T21:10:16: Number of free parameters .: 4
207   - 2015-05-22T21:10:16: Number of iterations ......: 3
208   - 2015-05-22T21:10:16: Lambda ....................: 1e-06
209   - 2015-05-22T21:10:16: Maximum log likelihood ....: -60642.233
210   - 2015-05-22T21:10:16: Observed events (Nobs) ...: 25963.000
211   - 2015-05-22T21:10:16: Predicted events (Npred) ..: 25963.000 (Nobs - Npred = 1.5749e-05)
212   - 2015-05-22T21:10:16: === GModels ===
213   - 2015-05-22T21:10:16: Number of models ..........: 2
214   - 2015-05-22T21:10:16: Number of parameters ......: 10
215   - 2015-05-22T21:10:16: === GModelSky ===
216   - 2015-05-22T21:10:16: Name ......................: Crab
217   - 2015-05-22T21:10:16: Instruments ...............: all
218   - 2015-05-22T21:10:16: Instrument scale factors ..: unity
219   - 2015-05-22T21:10:16: Observation identifiers ...: all
220   - 2015-05-22T21:10:16: Model type ................: PointSource
221   - 2015-05-22T21:10:16: Model components ..........: "SkyDirFunction" * "PowerLaw" * "Constant"
222   - 2015-05-22T21:10:16: Number of parameters ......: 6
223   - 2015-05-22T21:10:16: Number of spatial par's ...: 2
224   - 2015-05-22T21:10:16: RA .......................: 83.6331 [-360,360] deg (fixed,scale=1)
225   - 2015-05-22T21:10:16: DEC ......................: 22.0145 [-90,90] deg (fixed,scale=1)
226   - 2015-05-22T21:10:16: Number of spectral par's ..: 3
227   - 2015-05-22T21:10:16: Prefactor ................: 5.8499e-16 +/- 8.02289e-18 [1e-23,1e-13] ph/cm2/s/MeV (free,scale=1e-16,gradient)
228   - 2015-05-22T21:10:16: Index ....................: -2.49909 +/- 0.0118976 [-0,-5] (free,scale=-1,gradient)
229   - 2015-05-22T21:10:16: PivotEnergy ..............: 300000 [10000,1e+09] MeV (fixed,scale=1e+06,gradient)
230   - 2015-05-22T21:10:16: Number of temporal par's ..: 1
231   - 2015-05-22T21:10:16: Normalization ............: 1 (relative value) (fixed,scale=1,gradient)
232   - 2015-05-22T21:10:16: === GCTAModelCubeBackground ===
233   - 2015-05-22T21:10:16: Name ......................: BackgroundModel
234   - 2015-05-22T21:10:16: Instruments ...............: CTA, HESS, MAGIC, VERITAS
235   - 2015-05-22T21:10:16: Instrument scale factors ..: unity
236   - 2015-05-22T21:10:16: Observation identifiers ...: all
237   - 2015-05-22T21:10:16: Model type ................: "PowerLaw" * "Constant"
238   - 2015-05-22T21:10:16: Number of parameters ......: 4
239   - 2015-05-22T21:10:16: Number of spectral par's ..: 3
240   - 2015-05-22T21:10:16: Prefactor ................: 1.08781 +/- 0.0212678 [0,infty[ ph/cm2/s/MeV (free,scale=1,gradient)
241   - 2015-05-22T21:10:16: Index ....................: 0.0269681 +/- 0.0111532 [-10,10] (free,scale=1,gradient)
242   - 2015-05-22T21:10:16: PivotEnergy ..............: 1e+06 MeV (fixed,scale=1e+06,gradient)
243   - 2015-05-22T21:10:16: Number of temporal par's ..: 1
244   - 2015-05-22T21:10:16: Normalization ............: 1 (relative value) (fixed,scale=1,gradient)
  187 + 2015-12-07T21:37:45: +=================================+
  188 + 2015-12-07T21:37:45: | Maximum likelihood optimisation |
  189 + 2015-12-07T21:37:45: +=================================+
  190 + 2015-12-07T21:37:46: >Iteration 0: -logL=83748.453, Lambda=1.0e-03
  191 + 2015-12-07T21:37:47: >Iteration 1: -logL=83736.039, Lambda=1.0e-03, delta=12.413, max(|grad|)=15.134616 [Index:3]
  192 + 2015-12-07T21:37:48: >Iteration 2: -logL=83736.021, Lambda=1.0e-04, delta=0.018, max(|grad|)=0.108613 [Index:3]
  193 + 2015-12-07T21:37:49: >Iteration 3: -logL=83736.021, Lambda=1.0e-05, delta=0.000, max(|grad|)=0.000570 [Index:3]
  194 + ...
  195 + 2015-12-07T21:37:51: +=========================================+
  196 + 2015-12-07T21:37:51: | Maximum likelihood optimisation results |
  197 + 2015-12-07T21:37:51: +=========================================+
  198 + 2015-12-07T21:37:51: === GOptimizerLM ===
  199 + 2015-12-07T21:37:51: Optimized function value ..: 83736.021
  200 + 2015-12-07T21:37:51: Absolute precision ........: 0.005
  201 + 2015-12-07T21:37:51: Acceptable value decrease .: 2
  202 + 2015-12-07T21:37:51: Optimization status .......: converged
  203 + 2015-12-07T21:37:51: Number of parameters ......: 10
  204 + 2015-12-07T21:37:51: Number of free parameters .: 4
  205 + 2015-12-07T21:37:51: Number of iterations ......: 3
  206 + 2015-12-07T21:37:51: Lambda ....................: 1e-06
  207 + 2015-12-07T21:37:51: Maximum log likelihood ....: -83736.021
  208 + 2015-12-07T21:37:51: Observed events (Nobs) ...: 35198.000
  209 + 2015-12-07T21:37:51: Predicted events (Npred) ..: 35198.000 (Nobs - Npred = 7.6773e-07)
  210 + 2015-12-07T21:37:51: === GModels ===
  211 + 2015-12-07T21:37:51: Number of models ..........: 2
  212 + 2015-12-07T21:37:51: Number of parameters ......: 10
  213 + 2015-12-07T21:37:51: === GModelSky ===
  214 + 2015-12-07T21:37:51: Name ......................: Crab
  215 + 2015-12-07T21:37:51: Instruments ...............: all
  216 + 2015-12-07T21:37:51: Instrument scale factors ..: unity
  217 + 2015-12-07T21:37:51: Observation identifiers ...: all
  218 + 2015-12-07T21:37:51: Model type ................: PointSource
  219 + 2015-12-07T21:37:51: Model components ..........: "SkyDirFunction" * "PowerLaw" * "Constant"
  220 + 2015-12-07T21:37:51: Number of parameters ......: 6
  221 + 2015-12-07T21:37:51: Number of spatial par's ...: 2
  222 + 2015-12-07T21:37:51: RA .......................: 83.6331 [-360,360] deg (fixed,scale=1)
  223 + 2015-12-07T21:37:51: DEC ......................: 22.0145 [-90,90] deg (fixed,scale=1)
  224 + 2015-12-07T21:37:51: Number of spectral par's ..: 3
  225 + 2015-12-07T21:37:51: Prefactor ................: 5.75289e-16 +/- 7.24749e-18 [1e-23,1e-13] ph/cm2/s/MeV (free,scale=1e-16,gradient)
  226 + 2015-12-07T21:37:51: Index ....................: -2.53122 +/- 0.0113068 [-0,-5] (free,scale=-1,gradient)
  227 + 2015-12-07T21:37:51: PivotEnergy ..............: 300000 [10000,1e+09] MeV (fixed,scale=1e+06,gradient)
  228 + 2015-12-07T21:37:51: Number of temporal par's ..: 1
  229 + 2015-12-07T21:37:51: Normalization ............: 1 (relative value) (fixed,scale=1,gradient)
  230 + 2015-12-07T21:37:51: === GCTAModelCubeBackground ===
  231 + 2015-12-07T21:37:51: Name ......................: BackgroundModel
  232 + 2015-12-07T21:37:51: Instruments ...............: CTA, HESS, MAGIC, VERITAS
  233 + 2015-12-07T21:37:51: Instrument scale factors ..: unity
  234 + 2015-12-07T21:37:51: Observation identifiers ...: all
  235 + 2015-12-07T21:37:51: Model type ................: "PowerLaw" * "Constant"
  236 + 2015-12-07T21:37:51: Number of parameters ......: 4
  237 + 2015-12-07T21:37:51: Number of spectral par's ..: 3
  238 + 2015-12-07T21:37:51: Prefactor ................: 0.998055 +/- 0.0114979 [0.01,100] ph/cm2/s/MeV (free,scale=1,gradient)
  239 + 2015-12-07T21:37:51: Index ....................: 0.00648796 +/- 0.00697365 [-5,5] (free,scale=1,gradient)
  240 + 2015-12-07T21:37:51: PivotEnergy ..............: 1e+06 MeV (fixed,scale=1e+06,gradient)
  241 + 2015-12-07T21:37:51: Number of temporal par's ..: 1
  242 + 2015-12-07T21:37:51: Normalization ............: 1 (relative value) (fixed,scale=1,gradient)
... ...
doc/source/user_manual/getting_started/beyond_tsmap.rst
  View file @14f9d87
... ... @@ -3,13 +3,14 @@
3 3 Generating a Test Statistic map
4 4 ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
5 5  
6   -In the above examples we were always considering that we knew exactly
  6 +In the above examples you have always considering that you knew exactly
7 7 where the source is located, but in real life situations this may not
8 8 necessarily be the case.
9   -We thus need a means to search for significant excess emission in our data.
  9 +You thus need a means to search for significant excess emission in your data.
10 10 One possibility to accomplish this task is to compute the Test Statistic
11 11 for a specific source at a grid of trial positions.
12 12 The :ref:`cttsmap` tool will exactly do that job.
  13 +
13 14 The Test Statistic is defined as twice the log-likelihood difference
14 15 between fitting a source at a given position on top of a model or fitting
15 16 no source.
... ... @@ -18,7 +19,7 @@ the source detection significance in Gaussian sigmas, although the
18 19 exact relation depends somewhat on the formulation of the statistical
19 20 problem.
20 21  
21   -Here an example where we apply the :ref:`cttsmap` tool to our two
  22 +Here an example of how to apply the :ref:`cttsmap` tool to the two
22 23 simulated observations of the Crab in unbinned mode.
23 24 On input we provide a source model XML file and the name of the source
24 25 in the XML file that should be moved on a grid of test positions.
... ... @@ -31,11 +32,11 @@ nominal position of the Crab nebula with a grid spacing of 0.02 degrees.
31 32 .. code-block:: bash
32 33  
33 34 $ cttsmap
34   - Input event list, counts cube or observation definition file [events.fits] obs.xml
  35 + Input event list, counts cube or observation definition XML file [events.fits] obs.xml
35 36 Calibration database [prod2]
36   - Instrument response function [South_50h]
37   - Source model [$CTOOLS/share/models/crab.xml]
38   - Test source [Crab]
  37 + Instrument response function [South_0.5h]
  38 + Input model XML file [$CTOOLS/share/models/crab.xml]
  39 + Test source name [Crab]
39 40 First coordinate of image center in degrees (RA or galactic l) (0-360) [83.63]
40 41 Second coordinate of image center in degrees (DEC or galactic b) (-90-90) [22.01]
41 42 Projection method (AIT|AZP|CAR|MER|MOL|STG|TAN) [CAR]
... ... @@ -43,14 +44,14 @@ nominal position of the Crab nebula with a grid spacing of 0.02 degrees.
43 44 Image scale (in degrees/pixel) [0.02]
44 45 Size of the X axis in pixels [200] 10
45 46 Size of the Y axis in pixels [200] 10
46   - Output Test Statistic map [tsmap.fits]
  47 + Output Test Statistic map file [tsmap.fits]
47 48  
48 49 :ref:`cttsmap` writes the Test Statistic map in the ``tsmap.fits`` file
49 50 that contains one extension for the Test Statistic value and further
50 51 extensions for the spectral parameters that have been fitted for the
51 52 source at each position of the grid.
52 53 The figure below show the Test Statistic map which reaches a maximum
53   -value of 37484 near the centre of the map.
  54 +value of 40733 near the centre of the map.
54 55  
55 56 .. figure:: tsmap-crab.png
56 57 :height: 400px
... ...
doc/source/user_manual/getting_started/binning.rst 0 → 100644
  View file @14f9d87
  1 +.. _sec_binning_cta:
  2 +
  3 +Binning CTA data
  4 +~~~~~~~~~~~~~~~~
  5 +
  6 +As next analysis step you will bin the data in a counts cube using
  7 +:ref:`ctbin`.
  8 +A counts cube is a 3 dimensional data cube, spanned by
  9 +Right Ascension (or Galactic longitude), Declination (or Galactic latitude),
  10 +and energy (typically logarithmically spaced, but this is under user
  11 +control).
  12 +
  13 +:ref:`ctbin` is executed by typing:
  14 +
  15 +.. code-block:: bash
  16 +
  17 + $ ctbin
  18 + Input event list or observation definition XML file [events.fits]
  19 + First coordinate of image center in degrees (RA or galactic l) (0-360) [83.63]
  20 + Second coordinate of image center in degrees (DEC or galactic b) (-90-90) [22.01]
  21 + Projection method (AIT|AZP|CAR|MER|MOL|STG|TAN) [CAR]
  22 + Coordinate system (CEL - celestial, GAL - galactic) (CEL|GAL) [CEL]
  23 + Image scale (in degrees/pixel) [0.02]
  24 + Size of the X axis in pixels [200]
  25 + Size of the Y axis in pixels [200]
  26 + Algorithm for defining energy bins (FILE|LIN|LOG) [LOG]
  27 + Start value for first energy bin in TeV [0.1]
  28 + Stop value for last energy bin in TeV [100.0]
  29 + Number of energy bins [20]
  30 + Output counts cube file [cntcube.fits]
  31 +
  32 +The counts cube will be centred on the location of the Crab (Right Ascension
  33 +83.63 degrees, Declination 22.01 degrees) and will be aligned in celestial
  34 +coordinates. A cartesian projection has been selected. The counts cube has
  35 +200 x 200 spatial pixels of 0.02 x 0.02 degrees in size, hence it covers a
  36 +total area of 4 x 4 degrees.
  37 +
  38 +The counts cube will contain 20 maps, which are logarithmically spaced
  39 +in energy, and which cover the energy range from 0.1 TeV to 100 TeV. In this
  40 +example, the counts cube will be saved as ``cntcube.fits`` in the working
  41 +directory. In addition to the counts cube, that is stored as the primary
  42 +image extension, the FITS file also contains an extension named ``EBOUNDS``
  43 +that defines the energy boundaries that were used, and an extension ``GTI``
  44 +that defines the Good Time Intervals that have been used. The following
  45 +image shows the resulting FITS file. The ``EBOUNDS`` table has 20 rows, one
  46 +for each energy bin, while the ``GTI`` table has just a single row, indicating
  47 +the start and stop time of the simulated data.
  48 +
  49 +.. figure:: cntmap-fits.jpg
  50 + :width: 600px
  51 + :align: center
  52 +
  53 + *Counts cube FITS file*
  54 +
  55 +
  56 +An image of the first bin, covering the energy range 100 - 141 GeV, is
  57 +shown below:
  58 +
  59 +.. figure:: cntmap-map.jpg
  60 + :height: 400px
  61 + :align: center
  62 +
  63 + *Counts cube for first energy bin*
  64 +
  65 +For illustration, the last few lines of the log file ``ctbin.log`` are
  66 +reproduced below:
  67 +
  68 +.. code-block:: xml
  69 +
  70 + 2015-12-07T20:52:41: +=================+
  71 + 2015-12-07T20:52:41: | Bin observation |
  72 + 2015-12-07T20:52:41: +=================+
  73 + 2015-12-07T20:52:41: === CTA observation ===
  74 + 2015-12-07T20:52:41: Events in list ............: 22685
  75 + 2015-12-07T20:52:41: Events in cube ............: 18195
  76 + 2015-12-07T20:52:41: Event bins outside RoI ....: 0
  77 + 2015-12-07T20:52:41: Events outside cube area ..: 4490
  78 + 2015-12-07T20:52:41: Events outside energy bins : 0
  79 +
  80 +From the 22685 events that have been simulated and stored in the
  81 +``events.fits`` file, 18195 lie within the cube boundaries and are thus put
  82 +into the resulting counts cube. The counts cube is stored in a cartesian
  83 +projection in a World Coordinate System (WCS) compliant format.
... ...
doc/source/user_manual/getting_started/butterfly.rst 0 → 100644
  View file @14f9d87
  1 +.. _sec_butterfly_cta:
  2 +
  3 +Calculating and visualising a butterfly diagram
  4 +~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
  5 +
  6 +To visualise the analysis results you can compute a butterfly diagram
  7 +which shows the confidence band of the spectral fit using the
  8 +:ref:`ctbutterfly` tool.
  9 +The butterfly diagram is the envelope of all power law models
  10 +that are within a given confidence limit compatible with the data.
  11 +By default a confidence level of 68% is used, but the level can be adjusted
  12 +using the hidden ``confidence`` parameter.
  13 +:ref:`ctbutterfly` computes this envelope by evaluating for each energy the
  14 +minimum and maximum intensity of all power law models that fall within the
  15 +error ellipse of the prefactor and index parameters.
  16 +The error ellipse is derived from the covariance matrix of a maximum
  17 +likelihood fit.
  18 +
  19 +The following example illustrates how you can use the :ref:`ctbutterfly`
  20 +tool:
  21 +
  22 +.. code-block:: bash
  23 +
  24 + $ ctbutterfly
  25 + Input event list, counts cube or observation definition XML file [events.fits]
  26 + Calibration database [prod2]
  27 + Instrument response function [South_0.5h]
  28 + Input model XML file [$CTOOLS/share/models/crab.xml] crab_results.xml
  29 + Source of interest [Crab]
  30 + Start value for first energy bin in TeV [0.1]
  31 + Stop value for last energy bin in TeV [100.0]
  32 + Output ASCII file [butterfly.txt]
  33 +
  34 +Now that you have computed the confidence band of the spectral fit and
  35 +that you will have an ASCII file named ``butterfly.txt`` on disk you can
  36 +visualise the butterfly using the script ``show_butterfly.py`` that is
  37 +in the ctools ``example`` folder. You will need matplotlib on your system
  38 +to make this work. To launch the script, type:
  39 +
  40 +.. code-block:: bash
  41 +
  42 + python $CTOOLS/share/examples/python/show_butterfly.py butterfly.txt
  43 +
  44 +This will result in a canvas which should look like the following:
  45 +
  46 +.. figure:: butterfly.jpg
  47 + :height: 400px
  48 + :align: center
  49 +
  50 + *Confidence band of the fit*
  51 +
0 52 \ No newline at end of file
... ...
doc/source/user_manual/getting_started/fitting.rst 0 → 100644
  View file @14f9d87
  1 +.. _sec_fitting_cta:
  2 +
  3 +Fitting CTA data
  4 +~~~~~~~~~~~~~~~~
  5 +
  6 +Now we are ready to fit the simulated data with a model. For simplicity
  7 +we use in this example the same model that we used to simulate the data
  8 +with :ref:`ctobssim`. Model fitting is done using the :ref:`ctlike` tool,
  9 +and we do the fit by typing:
  10 +
  11 +.. code-block:: bash
  12 +
  13 + $ ctlike
  14 + Input event list, counts cube or observation definition XML file [events.fits] cntcube.fits
  15 + Input exposure cube file (only needed for stacked analysis) [NONE]
  16 + Input PSF cube file (only needed for stacked analysis) [NONE]
  17 + Input background cube file (only needed for stacked analysis) [NONE]
  18 + Calibration database [prod2]
  19 + Instrument response function [South_0.5h]
  20 + Input model XML file [$CTOOLS/share/models/crab.xml]
  21 + Output model XML file [crab_results.xml]
  22 +
  23 +The data are fitted in *binned* mode, which means that the events
  24 +have been binned into a counts cube and the fit computes the log-likelihood
  25 +function by summing over all 200 x 200 x 20 bins of the counts cube. There is
  26 +an alternative method, the so called *unbinned* mode, where the events are
  27 +not binned into a counts cube and the log-likelihood is computed directly by
  28 +summing over all events. We will explore the *unbinned* mode later.
  29 +
  30 +One of the parameters of :ref:`ctlike` is a source model output file
  31 +(we specified ``crab_results.xml`` in the example), and this file will be
  32 +a copy of the source model input XML file where the parameter values have
  33 +been replaced by the fit results. In addition, the statistical uncertainties
  34 +are added for each fitted parameter using the attribute ``error``.
  35 +Below we show the XML result file that has been produced by the run:
  36 +
  37 +.. code-block:: xml
  38 +
  39 + <?xml version="1.0" encoding="UTF-8" standalone="no"?>
  40 + <source_library title="source library">
  41 + <source name="Crab" type="PointSource">
  42 + <spectrum type="PowerLaw">
  43 + <parameter name="Prefactor" value="5.78443" error="0.101348" scale="1e-16" min="1e-07" max="1000" free="1" />
  44 + <parameter name="Index" value="2.50664" error="0.0153631" scale="-1" min="0" max="5" free="1" />
  45 + <parameter name="Scale" value="0.3" scale="1e+06" min="0.01" max="1000" free="0" />
  46 + </spectrum>
  47 + <spatialModel type="SkyDirFunction">
  48 + <parameter name="RA" value="83.6331" scale="1" min="-360" max="360" free="0" />
  49 + <parameter name="DEC" value="22.0145" scale="1" min="-90" max="90" free="0" />
  50 + </spatialModel>
  51 + </source>
  52 + <source name="CTABackgroundModel" type="CTAIrfBackground" instrument="CTA">
  53 + <spectrum type="PowerLaw">
  54 + <parameter name="Prefactor" value="0.993018" error="0.0160113" scale="1" min="0.001" max="1000" free="1" />
  55 + <parameter name="Index" value="0.00269761" error="0.00973921" scale="1" min="-5" max="5" free="1" />
  56 + <parameter name="Scale" value="1" scale="1e+06" min="0.01" max="1000" free="0" />
  57 + </spectrum>
  58 + </source>
  59 + </source_library>
  60 +
  61 +In this example, the ``Prefactor`` and ``Index`` of the spectral model for the
  62 +Crab as well as the ``Prefactor`` and ``Index`` of the background spectral
  63 +model have been fitted (all parameters having the attribute ``free="1"`` are
  64 +fitted). Now we see also the effect of having multiplied the background
  65 +model with a power law. In that way, the amplitude of the background as
  66 +well as it's spectral slope is adjusted by the fit. Obviously, in this
  67 +example the adjustment compensates only for the statistical fluctuations
  68 +of the background, but with real data, the adjustment may account also for
  69 +some of the systematic uncertainties.
  70 +
  71 +.. warning::
  72 +
  73 + As good practice, the amplitude of the background model should always be
  74 + left as a free parameter of the fit. Otherwise, any uncertainty in the
  75 + background rate will immediately propagate into the flux estimate of the
  76 + source.
  77 +
  78 +To get more details about the model fitting you can inspect the log file.
  79 +Below the last lines of the ctlike.log log file that has been produced by
  80 +this run:
  81 +
  82 +.. code-block:: xml
  83 +
  84 + 2015-12-07T20:55:32: +=================================+
  85 + 2015-12-07T20:55:32: | Maximum likelihood optimisation |
  86 + 2015-12-07T20:55:32: +=================================+
  87 + 2015-12-07T20:55:33: >Iteration 0: -logL=54877.412, Lambda=1.0e-03
  88 + 2015-12-07T20:55:35: >Iteration 1: -logL=54875.025, Lambda=1.0e-03, delta=2.387, max(|grad|)=1.856683 [Index:7]
  89 + 2015-12-07T20:55:36: >Iteration 2: -logL=54875.024, Lambda=1.0e-04, delta=0.001, max(|grad|)=-0.024661 [Index:3]
  90 + 2015-12-07T20:55:36:
  91 + ...
  92 + 2015-12-07T20:55:38: +=========================================+
  93 + 2015-12-07T20:55:38: | Maximum likelihood optimisation results |
  94 + 2015-12-07T20:55:38: +=========================================+
  95 + 2015-12-07T20:55:38: === GOptimizerLM ===
  96 + 2015-12-07T20:55:38: Optimized function value ..: 54875.024
  97 + 2015-12-07T20:55:38: Absolute precision ........: 0.005
  98 + 2015-12-07T20:55:38: Acceptable value decrease .: 2
  99 + 2015-12-07T20:55:38: Optimization status .......: converged
  100 + 2015-12-07T20:55:38: Number of parameters ......: 10
  101 + 2015-12-07T20:55:38: Number of free parameters .: 4
  102 + 2015-12-07T20:55:38: Number of iterations ......: 2
  103 + 2015-12-07T20:55:38: Lambda ....................: 1e-05
  104 + 2015-12-07T20:55:38: Maximum log likelihood ....: -54875.024
  105 + 2015-12-07T20:55:38: Observed events (Nobs) ...: 18195.000
  106 + 2015-12-07T20:55:38: Predicted events (Npred) ..: 18194.999 (Nobs - Npred = 0.00146383)
  107 + 2015-12-07T20:55:38: === GModels ===
  108 + 2015-12-07T20:55:38: Number of models ..........: 2
  109 + 2015-12-07T20:55:38: Number of parameters ......: 10
  110 + 2015-12-07T20:55:38: === GModelSky ===
  111 + 2015-12-07T20:55:38: Name ......................: Crab
  112 + 2015-12-07T20:55:38: Instruments ...............: all
  113 + 2015-12-07T20:55:38: Instrument scale factors ..: unity
  114 + 2015-12-07T20:55:38: Observation identifiers ...: all
  115 + 2015-12-07T20:55:38: Model type ................: PointSource
  116 + 2015-12-07T20:55:38: Model components ..........: "SkyDirFunction" * "PowerLaw" * "Constant"
  117 + 2015-12-07T20:55:38: Number of parameters ......: 6
  118 + 2015-12-07T20:55:38: Number of spatial par's ...: 2
  119 + 2015-12-07T20:55:38: RA .......................: 83.6331 [-360,360] deg (fixed,scale=1)
  120 + 2015-12-07T20:55:38: DEC ......................: 22.0145 [-90,90] deg (fixed,scale=1)
  121 + 2015-12-07T20:55:38: Number of spectral par's ..: 3
  122 + 2015-12-07T20:55:38: Prefactor ................: 5.78443e-16 +/- 1.01348e-17 [1e-23,1e-13] ph/cm2/s/MeV (free,scale=1e-16,gradient)
  123 + 2015-12-07T20:55:38: Index ....................: -2.50664 +/- 0.0153631 [-0,-5] (free,scale=-1,gradient)
  124 + 2015-12-07T20:55:38: PivotEnergy ..............: 300000 [10000,1e+09] MeV (fixed,scale=1e+06,gradient)
  125 + 2015-12-07T20:55:38: Number of temporal par's ..: 1
  126 + 2015-12-07T20:55:38: Normalization ............: 1 (relative value) (fixed,scale=1,gradient)
  127 + 2015-12-07T20:55:38: === GCTAModelIrfBackground ===
  128 + 2015-12-07T20:55:38: Name ......................: CTABackgroundModel
  129 + 2015-12-07T20:55:38: Instruments ...............: CTA
  130 + 2015-12-07T20:55:38: Instrument scale factors ..: unity
  131 + 2015-12-07T20:55:38: Observation identifiers ...: all
  132 + 2015-12-07T20:55:38: Model type ................: "PowerLaw" * "Constant"
  133 + 2015-12-07T20:55:38: Number of parameters ......: 4
  134 + 2015-12-07T20:55:38: Number of spectral par's ..: 3
  135 + 2015-12-07T20:55:38: Prefactor ................: 0.993018 +/- 0.0160113 [0.001,1000] ph/cm2/s/MeV (free,scale=1,gradient)
  136 + 2015-12-07T20:55:38: Index ....................: 0.00269761 +/- 0.00973921 [-5,5] (free,scale=1,gradient)
  137 + 2015-12-07T20:55:38: PivotEnergy ..............: 1e+06 [10000,1e+09] MeV (fixed,scale=1e+06,gradient)
  138 + 2015-12-07T20:55:38: Number of temporal par's ..: 1
  139 + 2015-12-07T20:55:38: Normalization ............: 1 (relative value) (fixed,scale=1,gradient)
  140 +
  141 +The maximum likelihood optimizer required 2 iterations to converge. This
  142 +is pretty fast, but recall that we used the same model file for the simulation
  143 +and for fitting, hence the initial parameter values were already very close
  144 +to the best fitting values. To see the impact of the initial parameters on
  145 +the fit result, you may re-run :ref:`ctlike` using another copy of the model
  146 +XML file where you change the value attributes of the parameters that should be
  147 +fitted. You will see that the optimizer requires a couple of more iterations,
  148 +but it should converge to the same solution (provided that the initial values
  149 +are not too far from the best fitting values).
  150 +
  151 +.. note::
  152 +
  153 + As sanity check you should verify that the predicted number of events
  154 + (Npred) is equal to the observed number of events (Nobs). To facilitate
  155 + this comparison, :ref:`ctlike` provides the difference Nobs - Npred in
  156 + the log file. In real life situations, this difference may not always be
  157 + small, in particular if the source model is too constrained. You may
  158 + then free some of the model parameters so that the fit can correctly
  159 + describe the data.
  160 +
  161 +.. note::
  162 +
  163 + The :ref:`ctlike` tool has the ability to estimate the detection
  164 + significance for sources in the XML model. This is done by computing
  165 + the Test Statistic value which is defined as twice the log-likelihood
  166 + difference between fitting a source at a given position on top of a
  167 + (background) model or fitting no source. Roughly speaken, the square
  168 + root of the Test Statistic value gives the source detection significance
  169 + in Gaussian sigmas, although the exact relation depends somewhat on
  170 + the formulation of the statistical problem.
  171 +
  172 + To instruct :ref:`ctlike` to compute the Test Statistic value for a
  173 + given source you need to add the attribute ``tscalc="1"`` to the XML
  174 + file:
  175 +
  176 + .. code-block:: xml
  177 +
  178 + <source name="Crab" type="PointSource" tscalc="1">
  179 +
  180 + :ref:`ctlike` will then compute the Test Statistic value for that
  181 + source and dump the result in the log file:
  182 +
  183 + .. code-block:: xml
  184 +
  185 + 2015-12-07T20:58:45: === GModelSky ===
  186 + 2015-12-07T20:58:45: Name ......................: Crab
  187 + 2015-12-07T20:58:45: Instruments ...............: all
  188 + 2015-12-07T20:58:45: Test Statistic ............: 21164.4
  189 +
  190 + The Test Statistic value will also be added as new attribute
  191 + ``ts`` to the XML result file:
  192 +
  193 + .. code-block:: xml
  194 +
  195 + <source name="Crab" type="PointSource" ts="21164.384" tscalc="1">
... ...
doc/source/user_manual/getting_started/quickstart.rst
  View file @14f9d87
1 1 .. _quickstart:
2 2  
3   -A quick ctools tutorial
4   ------------------------
5   -
6 3 First steps with ctools
7   -~~~~~~~~~~~~~~~~~~~~~~~
8   -
9   -This section provides a step-by-step description of the CTA data analysis
10   -procedure implemented in ctools. In this example we will simulate data for
11   -the Crab nebula, observed on-axis, as a single source in the CTA field of
12   -view.
13   -
14   -The example consists of the following analysis steps:
15   -
16   -- :ref:`sec_simulating_cta`
17   -
18   -- :ref:`sec_binning_cta`
19   -
20   -- :ref:`sec_fitting_cta`
21   -
22   -- :ref:`sec_unbinned_cta`
23   -
24   -- :ref:`sec_butterfly_cta`
25   -
26   -
27   -.. _sec_simulating_cta:
28   -
29   -Simulating CTA data
30   -~~~~~~~~~~~~~~~~~~~
31   -
32   -CTA data are simulated using the :ref:`ctobssim` tool. To invoke the tool,
33   -type :ref:`ctobssim` at the console prompt (which is denoted by ``$``).
34   -:ref:`ctobssim` will query for a number of parameters:
35   -
36   -.. code-block:: bash
37   -
38   - $ ctobssim
39   - RA of pointing (degrees) (0-360) [83.63]
40   - Dec of pointing (degrees) (-90-90) [22.01]
41   - Radius of FOV (degrees) (0-180) [5.0]
42   - Start time (MET in s) [0.0]
43   - End time (MET in s) [1800.0]
44   - Lower energy limit (TeV) [0.1]
45   - Upper energy limit (TeV) [100.0]
46   - Calibration database [prod2]
47   - Instrument response function [South_50h]
48   - Model [$CTOOLS/share/models/crab.xml]
49   - Output event data file or observation definition file [events.fits]
50   -
51   -Each line represents a query for one parameter value.
52   -The line starts with a short description of the parameter, followed by
53   -the default value proposed by ctobssim in squared brackets ``[ ]``.
54   -**If no parameter is entered the default value will be used**
55   -(which is the case for all parameters shown here).
56   -Otherwise, the specified value will overwrite the default value.
57   -The round brackets ``( )`` indicate the range of possible parameter
58   -values (if applicable).
59   -
60   -
61   -You may have recognised that the environment variable ``$CTOOLS`` has
62   -been used in the path name of the model. ctools will automatically expand
63   -the environment variables in parameter inputs.
64   -
65   -The CTA instrument properties (effective area, PSF width) are taken from
66   -the prod2 database. The response for the southern array using the cuts
67   -optimised for 50 hours of observing time are used.
68   -
69   -.. note::
70   -
71   - ctools comes bundled with CTA response functions for the northern and
72   - the southern array. The response functions are based on a Prod2
73   - analysis with cuts optimised for 0.5 hours, 5 hours and 50 hours of
74   - observing time. The following Instrument Response Functions
75   - (IRFs) are available: ``North_0.5h``, ``North_5h``, ``North_50h``,
76   - ``South_0.5h``, ``South_5h``, and ``South_50h``.
77   -
78   -Events are simulated based on the instrument properties and based on a
79   -source and background model. Only events that fall within the specified
80   -region of interest (ROI), defined as a circle around a sky position in
81   -Right Ascension and Declination (in degrees), will be stored in the output
82   -event data file. The duration of the simulation is taken here to 30 minutes
83   -(or 1800 seconds). Events are simulated for energies between 0.1 and 100 TeV.
84   -
85   -The source and background model is defined by the XML file
86   -``$CTOOLS/share/models/crab.xml``:
87   -
88   -.. code-block:: xml
89   -
90   - <?xml version="1.0" standalone="no"?>
91   - <source_library title="source library">
92   - <source name="Crab" type="PointSource">
93   - <spectrum type="PowerLaw">
94   - <parameter name="Prefactor" scale="1e-16" value="5.7" min="1e-07" max="1000.0" free="1"/>
95   - <parameter name="Index" scale="-1" value="2.48" min="0.0" max="+5.0" free="1"/>
96   - <parameter name="Scale" scale="1e6" value="0.3" min="0.01" max="1000.0" free="0"/>
97   - </spectrum>
98   - <spatialModel type="SkyDirFunction">
99   - <parameter name="RA" scale="1.0" value="83.6331" min="-360" max="360" free="0"/>
100   - <parameter name="DEC" scale="1.0" value="22.0145" min="-90" max="90" free="0"/>
101   - </spatialModel>
102   - </source>
103   - <source name="CTABackgroundModel" type="CTAIrfBackground" instrument="CTA">
104   - <spectrum type="PowerLaw">
105   - <parameter name="Prefactor" scale="1.0" value="1.0" min="1e-3" max="1e+3" free="1"/>
106   - <parameter name="Index" scale="1.0" value="0.0" min="-5.0" max="+5.0" free="1"/>
107   - <parameter name="Scale" scale="1e6" value="1.0" min="0.01" max="1000.0" free="0"/>
108   - </spectrum>
109   - </source>
110   - </source_library>
111   -
112   -The model consists of a source library that contains two components:
113   -the Crab nebula and an instrumental background model.
114   -
115   -The Crab nebula is modelled by a factorized sky model that has a spectral
116   -and a spatial component (tags ``<spectrum>`` and ``<spatialModel>``,
117   -respectively). The spectrum is modelled by a power law, which is defined by
118   -three parameters: the ``Prefactor``, the ``Index`` and the ``Scale``.
119   -The spatial model has two parameters: Right Ascension in degrees (``RA``), and
120   -Declination in degrees (``DEC``). Each parameter has a value and a scale factor,
121   -the real value of the parameter being the product ``value * scale``. Typically,
122   -``scale`` is chosen so that ``value`` is of the order of 1 (this is relevant for
123   -model fitting). In addition, ``value`` is bound by a minimum (``min``) and
124   -maximum (``max``) value, and a parameter may be free (``free="1"``) or fixed
125   -(``free="0"``). The ``min``, ``max``, and ``free`` attributes are not
126   -relevant here for the simulations, but they will be important for the model
127   -fitting later.
128   -
129   -The spectral intensity I(E) (in units of photons/cm2/s/MeV) of the power
130   -law is given by
131   -
132   -.. math::
133   - \frac{dN}{dE} = N_0 \left( \frac{E}{E_0} \right)^{\gamma}
134   -
135   -where the parameters in the XML definition have the following mappings:
136   -
137   -* :math:`N_0` = ``Prefactor``
138   -* :math:`\gamma` = ``Index``
139   -* :math:`E_0` = ``Scale``
140   -
141   -.. warning::
142   -
143   - Energies are given in the XML file in MeV units. This is a GammaLib
144   - convention that can not be modified. **So make sure you always use
145   - MeV as energy unit in an XML file.**
146   -
147   -The instrumental background of CTA is modelled using the background
148   -information provided in the IRF (``CTAIrfBackground``) multipled
149   -by a power law. As it is defined here, the power law represents a
150   -constant of 1, hence the background IRF will be used without any
151   -modification. The power law will become active when fitting the data
152   -later and allows a spectral adjustment of the background model that
153   -may account for uncertainties in the background information provided
154   -in the IRF.
155   -
156   -:ref:`ctobssim` has a couple of hidden parameters, the most important one being
157   -certainly ``seed``. ``seed`` is an integer that specifies the seed value
158   -for the random number generator, and changing this parameter will allow to
159   -generate statistically independent Monte Carlo samples of CTA event data.
160   -To use for example a seed value of 41 you should type:
161   -
162   -.. code-block:: bash
163   -
164   - $ ctobssim seed=41
165   -
166   -:ref:`ctobssim` will write 2 files in the working directory: ``events.fits``
167   -and ``ctobssim.log``. The first file contains the simulated events in FITS
168   -format and can be inspected using ``fv`` or ``ds9``. The FITS file will
169   -contain three extensions: an empty primary image, a binary table named
170   -``EVENTS`` that holds the events (one row per event), and a binary table
171   -named ``GTI`` holding the Good Time Intervals (for the moment a single row
172   -with 2 columns providing the start and the stop time of the simulated time
173   -interval).
174   -
175   -The second file produced by :ref:`ctobssim` is a human readable log file that
176   -contains information about the job execution. As example, the last lines
177   -from this file are shown here:
178   -
179   -.. code-block:: xml
180   -
181   - 2015-05-22T19:24:53: +======================+
182   - 2015-05-22T19:24:53: | Simulate observation |
183   - 2015-05-22T19:24:53: +======================+
184   - 2015-05-22T19:24:53: === Observation ===
185   - 2015-05-22T19:24:53: Simulation area ...........: 1.9635e+11 cm2
186   - 2015-05-22T19:24:53: Simulation cone ...........: RA=83.63 deg, Dec=22.01 deg, r=5.5 deg
187   - 2015-05-22T19:24:53: Time interval .............: 0 - 1800 s
188   - 2015-05-22T19:24:53: Photon energy range .......: 100 GeV - 100 TeV
189   - 2015-05-22T19:24:53: Event energy range ........: 100 GeV - 100 TeV
190   - 2015-05-22T19:24:53: MC source photons .........: 207547 [Crab]
191   - 2015-05-22T19:24:53: MC source events ..........: 2961 [Crab]
192   - 2015-05-22T19:24:53: MC source events ..........: 2961 (all source models)
193   - 2015-05-22T19:24:55: MC background events ......: 13003
194   - 2015-05-22T19:24:55: MC events .................: 15964 (all models)
195   -
196   -Each line starts with the UTC time at which the line has been written. In
197   -this run, 207547 Crab photons have been thrown over an area of 19.6 square
198   -kilometres during a time interval of 1800 seconds. 2961 of these photons have
199   -been registered by CTA as events. In the same time interval, 13003 background
200   -events have been registred by CTA.
201   -
202   -You may change the name of the log file using the hidden parameter
203   -``logfile``:
204   -
205   -.. code-block:: bash
206   -
207   - $ ctobssim logfile=my-private-log-file
208   -
209   -Furthermore, you may decide on the amount of information provided in the
210   -log file (the chattiness of the executable) using the hidden parameter
211   -``chatter``:
212   -
213   -.. code-block:: bash
214   -
215   - $ ctobssim chatter=4
216   -
217   -``chatter`` can vary between 0 and 4, 0 providing no information while 4
218   -provides the most detailed information. **By default, all ctools have a
219   -chatter level of 2.**
220   -
221   -You may also duplicate the log file information into the console by setting
222   -the hidden ``debug`` parameter to yes:
223   -
224   -.. code-block:: bash
225   -
226   - $ ctobssim debug=yes
227   -
228   -
229   -.. _sec_binning_cta:
230   -
231   -Binning CTA data
232   -~~~~~~~~~~~~~~~~
233   -
234   -As next analysis step you will bin the data in a counts cube using
235   -:ref:`ctbin`.
236   -A counts cube is a 3 dimensional data cube, spanned by
237   -Right Ascension (or Galactic longitude), Declination (or Galactic latitude),
238   -and energy (typically logarithmically spaced, but this is under user
239   -control).
240   -
241   -:ref:`ctbin` is executed by typing:
242   -
243   -.. code-block:: bash
244   -
245   - $ ctbin
246   - Event list or observation definition file [events.fits]
247   - First coordinate of image center in degrees (RA or galactic l) (0-360) [83.63]
248   - Second coordinate of image center in degrees (DEC or galactic b) (-90-90) [22.01]
249   - Projection method (AIT|AZP|CAR|MER|MOL|STG|TAN) [CAR]
250   - Coordinate system (CEL - celestial, GAL - galactic) (CEL|GAL) [CEL]
251   - Image scale (in degrees/pixel) [0.02]
252   - Size of the X axis in pixels [200]
253   - Size of the Y axis in pixels [200]
254   - Algorithm for defining energy bins (FILE|LIN|LOG) [LOG]
255   - Start value for first energy bin in TeV [0.1]
256   - Stop value for last energy bin in TeV [100.0]
257   - Number of energy bins [20]
258   - Output counts cube [cntcube.fits]
259   -
260   -The counts cube will be centred on the location of the Crab (Right Ascension
261   -83.63 degrees, Declination 22.01 degrees) and will be aligned in celestial
262   -coordinates. A cartesian projection has been selected. The counts cube has
263   -200 x 200 spatial pixels of 0.02 x 0.02 degrees in size, hence it covers a
264   -total area of 4 x 4 degrees.
265   -
266   -The counts cube will contain 20 maps, which are logarithmically spaced
267   -in energy, and which cover the energy range from 0.1 TeV to 100 TeV. In this
268   -example, the counts cube will be saved as ``cntcube.fits`` in the working
269   -directory. In addition to the counts cube, that is stored as the primary
270   -image extension, the FITS file also contains an extension named ``EBOUNDS``
271   -that defines the energy boundaries that were used, and an extension ``GTI``
272   -that defines the Good Time Intervals that have been used. The following
273   -image shows the resulting FITS file. The ``EBOUNDS`` table has 20 rows, one
274   -for each energy bin, while the ``GTI`` table has just a single row, indicating
275   -the start and stop time of the simulated data.
276   -
277   -.. figure:: cntmap-fits.jpg
278   - :width: 600px
279   - :align: center
280   -
281   - *Counts cube FITS file*
282   -
283   -
284   -An image of the first bin, covering the energy range 100 - 141 GeV, is
285   -shown below:
286   -
287   -.. figure:: cntmap-map.jpg
288   - :height: 400px
289   - :align: center
290   -
291   - *Counts cube for first energy bin*
292   -
293   -
294   -For illustration, the last few lines of the log file ``ctbin.log`` are
295   -reproduced below:
296   -
297   -.. code-block:: xml
298   -
299   - 2015-05-22T19:40:30: +=================+
300   - 2015-05-22T19:40:30: | Bin observation |
301   - 2015-05-22T19:40:30: +=================+
302   - 2015-05-22T19:40:30: === Observation ===
303   - 2015-05-22T19:40:30: Events in list ............: 15964
304   - 2015-05-22T19:40:30: Events in cube ............: 13360
305   - 2015-05-22T19:40:30: Event bins outside RoI ....: 0
306   - 2015-05-22T19:40:30: Events outside cube area ..: 2604
307   - 2015-05-22T19:40:30: Events outside energy bins : 0
308   -
309   -From the 15964 events that have been simulated and stored in the
310   -``events.fits`` file, 13360 lie within the cube boundaries and are thus put
311   -into the resulting counts cube. The counts cube is stored in a cartesian
312   -projection in a World Coordinate System (WCS) compliant format.
313   -
314   -
315   -.. _sec_fitting_cta:
316   -
317   -Fitting CTA data
318   -~~~~~~~~~~~~~~~~
319   -
320   -Now we are ready to fit the simulated data with a model. For simplicity
321   -we use in this example the same model that we used to simulate the data
322   -with :ref:`ctobssim`. Model fitting is done using the :ref:`ctlike` tool,
323   -and we do the fit by typing:
324   -
325   -.. code-block:: bash
326   -
327   - $ ctlike
328   - Event list, counts cube or observation definition file [events.fits] cntcube.fits
329   - Exposure cube file (only needed for stacked analysis) [NONE]
330   - PSF cube file (only needed for stacked analysis) [NONE]
331   - Background cube file (only needed for stacked analysis) [NONE]
332   - Calibration database [prod2]
333   - Instrument response function [South_50h]
334   - Source model [$CTOOLS/share/models/crab.xml]
335   - Source model output file [crab_results.xml]
336   -
337   -The data are fitted in *binned* mode, which means that the events
338   -have been binned into a counts cube and the fit computes the log-likelihood
339   -function by summing over all 200 x 200 x 20 bins of the counts cube. There is
340   -an alternative method, the so called *unbinned* mode, where the events are
341   -not binned into a counts cube and the log-likelihood is computed directly by
342   -summing over all events. We will explore the *unbinned* mode later.
343   -
344   -One of the parameters of :ref:`ctlike` is a source model output file
345   -(we specified ``crab_results.xml`` in the example), and this file will be
346   -a copy of the source model input XML file where the parameter values have
347   -been replaced by the fit results. In addition, the statistical uncertainties
348   -are added for each fitted parameter using the attribute ``error``.
349   -Below we show the XML result file that has been produced by the run:
350   -
351   -.. code-block:: xml
352   -
353   - <?xml version="1.0" encoding="UTF-8" standalone="no"?>
354   - <source_library title="source library">
355   - <source name="Crab" type="PointSource">
356   - <spectrum type="PowerLaw">
357   - <parameter name="Prefactor" value="5.78197" error="0.110889" scale="1e-16" min="1e-07" max="1000" free="1" />
358   - <parameter name="Index" value="2.49174" error="0.0164369" scale="-1" min="0" max="5" free="1" />
359   - <parameter name="Scale" value="0.3" scale="1e+06" min="0.01" max="1000" free="0" />
360   - </spectrum>
361   - <spatialModel type="SkyDirFunction">
362   - <parameter name="RA" value="83.6331" scale="1" min="-360" max="360" free="0" />
363   - <parameter name="DEC" value="22.0145" scale="1" min="-90" max="90" free="0" />
364   - </spatialModel>
365   - </source>
366   - <source name="CTABackgroundModel" type="CTAIrfBackground" instrument="CTA">
367   - <spectrum type="PowerLaw">
368   - <parameter name="Prefactor" value="1.02048" error="0.0280684" scale="1" min="0.001" max="1000" free="1" />
369   - <parameter name="Index" value="0.0197856" error="0.0156686" scale="1" min="-5" max="5" free="1" />
370   - <parameter name="Scale" value="1" scale="1e+06" min="0.01" max="1000" free="0" />
371   - </spectrum>
372   - </source>
373   - </source_library>
374   -
375   -In this example, the ``Prefactor`` and ``Index`` of the spectral model for the
376   -Crab as well as the ``Prefactor`` and ``Index`` of the background spectral
377   -model have been fitted (all parameters having the attribute ``free="1"`` are
378   -fitted). Now we see also the effect of having multiplied the background
379   -model with a power law. In that way, the amplitude of the background as
380   -well as it's spectral slope is adjusted by the fit. Obviously, in this
381   -example the adjustment compensates only for the statistical fluctuations
382   -of the background, but with real data, the adjustment may account also for
383   -some of the systematic uncertainties.
384   -
385   -.. warning::
386   -
387   - As good practice, the amplitude of the background model should always be
388   - left as a free parameter of the fit. Otherwise, any uncertainty in the
389   - background rate will immediately propagate into the flux estimate of the
390   - source.
391   -
392   -To get more details about the model fitting you can inspect the log file.
393   -Below the last lines of the ctlike.log log file that has been produced by
394   -this run:
395   -
396   -.. code-block:: xml
397   -
398   - 2015-05-22T19:45:15: +=================================+
399   - 2015-05-22T19:45:15: | Maximum likelihood optimisation |
400   - 2015-05-22T19:45:15: +=================================+
401   - 2015-05-22T19:45:16: >Iteration 0: -logL=39910.748, Lambda=1.0e-03
402   - 2015-05-22T19:45:18: >Iteration 1: -logL=39908.788, Lambda=1.0e-03, delta=1.960, max(|grad|)=6.701856 [Index:7]
403   - 2015-05-22T19:45:19: >Iteration 2: -logL=39908.787, Lambda=1.0e-04, delta=0.001, max(|grad|)=-0.057041 [Index:3]
404   - 2015-05-22T19:45:21:
405   - 2015-05-22T19:45:21: +=========================================+
406   - 2015-05-22T19:45:21: | Maximum likelihood optimization results |
407   - 2015-05-22T19:45:21: +=========================================+
408   - 2015-05-22T19:45:21: === GOptimizerLM ===
409   - 2015-05-22T19:45:21: Optimized function value ..: 39908.787
410   - 2015-05-22T19:45:21: Absolute precision ........: 0.005
411   - 2015-05-22T19:45:21: Acceptable value decrease .: 2
412   - 2015-05-22T19:45:21: Optimization status .......: converged
413   - 2015-05-22T19:45:21: Number of parameters ......: 10
414   - 2015-05-22T19:45:21: Number of free parameters .: 4
415   - 2015-05-22T19:45:21: Number of iterations ......: 2
416   - 2015-05-22T19:45:21: Lambda ....................: 1e-05
417   - 2015-05-22T19:45:21: Maximum log likelihood ....: -39908.787
418   - 2015-05-22T19:45:21: Observed events (Nobs) ...: 13360.000
419   - 2015-05-22T19:45:21: Predicted events (Npred) ..: 13359.998 (Nobs - Npred = 0.00180799)
420   - 2015-05-22T19:45:21: === GModels ===
421   - 2015-05-22T19:45:21: Number of models ..........: 2
422   - 2015-05-22T19:45:21: Number of parameters ......: 10
423   - 2015-05-22T19:45:21: === GModelSky ===
424   - 2015-05-22T19:45:21: Name ......................: Crab
425   - 2015-05-22T19:45:21: Instruments ...............: all
426   - 2015-05-22T19:45:21: Instrument scale factors ..: unity
427   - 2015-05-22T19:45:21: Observation identifiers ...: all
428   - 2015-05-22T19:45:21: Model type ................: PointSource
429   - 2015-05-22T19:45:21: Model components ..........: "SkyDirFunction" * "PowerLaw" * "Constant"
430   - 2015-05-22T19:45:21: Number of parameters ......: 6
431   - 2015-05-22T19:45:21: Number of spatial par's ...: 2
432   - 2015-05-22T19:45:21: RA .......................: 83.6331 [-360,360] deg (fixed,scale=1)
433   - 2015-05-22T19:45:21: DEC ......................: 22.0145 [-90,90] deg (fixed,scale=1)
434   - 2015-05-22T19:45:21: Number of spectral par's ..: 3
435   - 2015-05-22T19:45:21: Prefactor ................: 5.78197e-16 +/- 1.10889e-17 [1e-23,1e-13] ph/cm2/s/MeV (free,scale=1e-16,gradient)
436   - 2015-05-22T19:45:21: Index ....................: -2.49174 +/- 0.0164369 [-0,-5] (free,scale=-1,gradient)
437   - 2015-05-22T19:45:21: PivotEnergy ..............: 300000 [10000,1e+09] MeV (fixed,scale=1e+06,gradient)
438   - 2015-05-22T19:45:21: Number of temporal par's ..: 1
439   - 2015-05-22T19:45:21: Normalization ............: 1 (relative value) (fixed,scale=1,gradient)
440   - 2015-05-22T19:45:21: === GCTAModelIrfBackground ===
441   - 2015-05-22T19:45:21: Name ......................: CTABackgroundModel
442   - 2015-05-22T19:45:21: Instruments ...............: CTA
443   - 2015-05-22T19:45:21: Instrument scale factors ..: unity
444   - 2015-05-22T19:45:21: Observation identifiers ...: all
445   - 2015-05-22T19:45:21: Model type ................: "PowerLaw" * "Constant"
446   - 2015-05-22T19:45:21: Number of parameters ......: 4
447   - 2015-05-22T19:45:21: Number of spectral par's ..: 3
448   - 2015-05-22T19:45:21: Prefactor ................: 1.02048 +/- 0.0280684 [0.001,1000] ph/cm2/s/MeV (free,scale=1,gradient)
449   - 2015-05-22T19:45:21: Index ....................: 0.0197856 +/- 0.0156686 [-5,5] (free,scale=1,gradient)
450   - 2015-05-22T19:45:21: PivotEnergy ..............: 1e+06 [10000,1e+09] MeV (fixed,scale=1e+06,gradient)
451   - 2015-05-22T19:45:21: Number of temporal par's ..: 1
452   - 2015-05-22T19:45:21: Normalization ............: 1 (relative value) (fixed,scale=1,gradient)
453   -
454   -The maximum likelihood optimizer required 2 iterations to converge. This
455   -is pretty fast, but recall that we used the same model file for the simulation
456   -and for fitting, hence the initial parameter values were already very close
457   -to the best fitting values. To see the impact of the initial parameters on
458   -the fit result, you may re-run :ref:`ctlike` using another copy of the model
459   -XML file where you change the value attributes of the parameters that should be
460   -fitted. You will see that the optimizer requires a couple of more iterations,
461   -but it should converge to the same solution (provided that the initial values
462   -are not too far from the best fitting values).
463   -
464   -.. note::
465   -
466   - As sanity check you should verify that the predicted number of events
467   - (Npred) is equal to the observed number of events (Nobs). To facilitate
468   - this comparison, :ref:`ctlike` provides the difference Nobs - Npred in
469   - the log file. In real life situations, this difference may not always be
470   - small, in particular if the source model is too constrained. You may
471   - then free some of the model parameters so that the fit can correctly
472   - describe the data.
473   -
474   -.. note::
475   -
476   - The :ref:`ctlike` tool has the ability to estimate the detection
477   - significance for sources in the XML model. This is done by computing
478   - the Test Statistic value which is defined as twice the log-likelihood
479   - difference between fitting a source at a given position on top of a
480   - (background) model or fitting no source. Roughly speaken, the square
481   - root of the Test Statistic value gives the source detection significance
482   - in Gaussian sigmas, although the exact relation depends somewhat on
483   - the formulation of the statistical problem.
484   -
485   - To instruct :ref:`ctlike` to compute the Test Statistic value for a
486   - given source you need to add the attribute ``tscalc="1"`` to the XML
487   - file:
488   -
489   - .. code-block:: xml
490   -
491   - <source name="Crab" type="PointSource" tscalc="1">
492   -
493   - :ref:`ctlike` will then compute the Test Statistic value for that
494   - source and dump the result in the log file:
495   -
496   - .. code-block:: xml
497   -
498   - 2015-05-22T19:58:43: === GModelSky ===
499   - 2015-05-22T19:58:43: Name ......................: Crab
500   - 2015-05-22T19:58:43: Instruments ...............: all
501   - 2015-05-22T19:58:43: Test Statistic ............: 18662.6
502   -
503   - The Test Statistic value will also be added as new attribute
504   - ``ts`` to the XML result file:
505   -
506   - .. code-block:: xml
507   -
508   - <source name="Crab" type="PointSource" ts="18662.576" tscalc="1">
509   -
510   -
511   -.. _sec_unbinned_cta:
512   -
513   -Doing an unbinned analysis
514   -~~~~~~~~~~~~~~~~~~~~~~~~~~
515   -
516   -As gamma-ray events are rare, the counts cubes generated by :ref:`ctbin`
517   -will in general be sparsly populated, having many empty pixels, in
518   -particular at high energies.
519   -An alternative analysis technique consists of working directly on the event
520   -list without binning the events in a counts cube. We will see the benefit of
521   -such an analysis later once you re-run :ref:`ctlike` in unbinned mode.
522   -
523   -For unbinned analysis you first have to define the data space region over
524   -which the analysis is done. This is similiar to the :ref:`ctbin` step for
525   -a binned analysis where you defined the size of the counts cube, the energy
526   -range, and the time interval. For unbinned analysis you have no such thing
527   -as a counts cube, but you have to define over which region of the data space
528   -the selected events are spread (because the ctools have to integrate over
529   -this region to compute the total number of predicted events in the data space
530   -that you analyse). Furthermore, you have to define what energy range is
531   -covered, and what time interval is spanned by the data. All this is done
532   -by the :ref:`ctselect` tool, which replaces the :ref:`ctbin` step in an
533   -unbinned analysis.
534   -
535   -:ref:`ctselect` performs an event selection by choosing only events within
536   -a given region-of-interest (ROI), within a given energy band, and within a
537   -given time interval from the input event list. The ROI is a circular region on
538   -the sky, for which you define the centre (in celestial coordinates) and the
539   -radius. Such a circular ROI is sometimes also called an acceptance cone. The
540   -following example shows how to run ctselect:
541   -
542   -.. code-block:: bash
543   -
544   - $ ctselect
545   - Input event list or observation definition file [events.fits]
546   - RA for ROI centre (degrees) (0-360) [83.63]
547   - Dec for ROI centre (degrees) (-90-90) [22.01]
548   - Radius of ROI (degrees) (0-180) [3.0]
549   - Start time (CTA MET in seconds) [0.0]
550   - End time (CTA MET in seconds) [0.0]
551   - Lower energy limit (TeV) [0.1]
552   - Upper energy limit (TeV) [100.0]
553   - Output event list or observation definition file [selected_events.fits]
554   -
555   -:ref:`ctselect` takes the input event list ``events.fits``, performs an
556   -event selection, and writes the selected event into the file
557   -``selected_events.fits``. The parameters it will query for are the centre
558   -of the ROI, the radius of the ROI, the start and stop time (in seconds),
559   -and the energy lower and upper limits (in TeV). The event selection information
560   -is also written as a set of data selection keywords to the output events
561   -file ``selected_events.fits``, by respecting the same syntax that has been
562   -implemented for Fermi/LAT. The following image is a screen dump of the data
563   -selection keywords that have been written to the ``EVENTS`` header in the
564   -file ``selected_events.fits``:
565   -
566   -.. figure:: dskeys.jpg
567   - :width: 400px
568   - :align: center
569   -
570   - *Data selection keywords*
571   -
572   -**It is mandatory for an unbinned analysis that these data selection keywords
573   -exist in the FITS file.**
574   -If they don't exist, :ref:`ctlike` will not execute in unbinned mode.
575   -
576   -Below some lines of the ``ctselect.log`` file that show the data selection
577   -part:
578   -
579   -.. code-block:: xml
580   -
581   - 2015-05-22T20:01:46: +=================+
582   - 2015-05-22T20:01:46: | Event selection |
583   - 2015-05-22T20:01:46: +=================+
584   - 2015-05-22T20:01:46: === Observation ===
585   - 2015-05-22T20:01:47: Selected energy range .....: 0.1 - 100 TeV
586   - 2015-05-22T20:01:47: Requested ROI .............: Centre(RA,DEC)=(83.63, 22.01) deg, Radius=3 deg
587   - 2015-05-22T20:01:47: ROI of data ...............: Centre(RA,DEC)=(83.63, 22.01) deg, Radius=5 deg
588   - 2015-05-22T20:01:47: Selected ROI ..............: Centre(RA,DEC)=(83.63, 22.01) deg, Radius=3 deg
589   - 2015-05-22T20:01:47: cfitsio selection .........: ENERGY >= 0.10000000 && ENERGY <= 100.00000000 && ANGSEP(83.630000,22.010000,RA,DEC) <= 3.000000
590   - 2015-05-22T20:01:47: FITS filename .............: /var/tmp/tmp.0.rRgLpO[EVENTS][ENERGY >= 0.10000000 && ENERGY <= 100.00000000 && ANGSEP(83.630000,22.010000,RA,DEC) <= 3.000000]
591   -
592   -.. note::
593   -
594   - :ref:`ctobssim` will also write data selection keywords in the event
595   - list FITS file, hence you can run :ref:`ctlike` directly on a FITS file
596   - produced by :ref:`ctobssim`. Any selection performed by :ref:`ctselect`
597   - needs to be fully enclosed within any previous selection, e.g. the ROI
598   - needs to be fully enclosed in the acceptance cone used for event
599   - simulation, the energy selection must be fully comprised in the
600   - range of simulated energies, the same applies for the temporal selection.
601   - :ref:`ctselect` will automatically adjust
602   - the selection parameters to guarantee full enclosure. To keep track of
603   - this adjustment, the :ref:`ctselect` log file quotes the requested
604   - selection, any existing selections, and the selection that was finally
605   - applied.
606   -
607   -.. warning::
608   -
609   - :ref:`ctselect` may of course also be used for event selection prior to
610   - binned analysis, for example to select events for a given period in
611   - time. **If you use** :ref:`ctselect` **however to make a spatial or energy
612   - selection, make sure that the counts cube is fully enclosed in the
613   - selection intervals.** Otherwise you will get empty zones in the counts
614   - cube of which the ctools are not aware of, and the subsequent analysis
615   - results will be wrong.
616   -
617   -Now that you have selected the events of interest, you can run ctlike in
618   -unbinned mode. To do this you have to specify the selected event list
619   -instead of the counts cube:
620   -
621   -.. code-block:: bash
622   -
623   - $ ctlike
624   - Event list, counts cube or observation definition file [cntcube.fits] selected_events.fits
625   - Calibration database [prod2]
626   - Instrument response function [South_50h]
627   - Source model [$CTOOLS/share/models/crab.xml]
628   - Source model output file [crab_results.xml]
629   -
630   -You will recognise that :ref:`ctlike` runs much faster in unbinned mode
631   -compared to binned mode.
632   -This is understandable as the selected event list contains
633   -only 15312 events, while the binned counts cube we used before had
634   -200 x 200 x 20 = 800000 pixels. As unbinned maximum likelihood fitting loops
635   -over the events (while binned maximum likelihood loops over the pixels),
636   -there are much less operations to perform in unbinned than in binned mode
637   -(there is some additional overhead in unbinned mode that comes from
638   -integrating the models over the region of interest, yet this is negligible
639   -compared to the operations needed when looping over all pixels). So as long
640   -as you work with small event lists, unbinned mode is faster (this
641   -typically holds up to 100 hours of observing time).
642   -Unbinned :ref:`ctlike` should also be more precise as no binning is performed,
643   -hence there is no loss of information due to histogramming.
644   -
645   -Below you see the corresponding output from the ctlike.log file. The fitted
646   -parameters are essentially identical to the ones found in binned mode.
647   -The slight difference with respect to the binned analysis may be explained
648   -by the different event sample that has been used for the analysis: while
649   -binned likelihood works on rectangular counts cubes, unbinned likelihood works
650   -on circular event selection regions. It is thus not possible to select exactly
651   -the same events for both analyses.
652   -
653   -.. code-block:: xml
654   -
655   - 2015-05-22T20:05:54: +=================================+
656   - 2015-05-22T20:05:54: | Maximum likelihood optimisation |
657   - 2015-05-22T20:05:54: +=================================+
658   - 2015-05-22T20:05:54: >Iteration 0: -logL=93854.543, Lambda=1.0e-03
659   - 2015-05-22T20:05:54: >Iteration 1: -logL=93848.595, Lambda=1.0e-03, delta=5.948, max(|grad|)=22.480581 [Index:7]
660   - 2015-05-22T20:05:54: >Iteration 2: -logL=93848.587, Lambda=1.0e-04, delta=0.008, max(|grad|)=-0.081846 [Index:3]
661   - 2015-05-22T20:05:54: >Iteration 3: -logL=93848.587, Lambda=1.0e-05, delta=0.000, max(|grad|)=-0.003485 [Index:3]
662   - 2015-05-22T20:05:54:
663   - 2015-05-22T20:05:54: +=========================================+
664   - 2015-05-22T20:05:54: | Maximum likelihood optimization results |
665   - 2015-05-22T20:05:54: +=========================================+
666   - 2015-05-22T20:05:54: === GOptimizerLM ===
667   - 2015-05-22T20:05:54: Optimized function value ..: 93848.587
668   - 2015-05-22T20:05:54: Absolute precision ........: 0.005
669   - 2015-05-22T20:05:54: Acceptable value decrease .: 2
670   - 2015-05-22T20:05:54: Optimization status .......: converged
671   - 2015-05-22T20:05:54: Number of parameters ......: 10
672   - 2015-05-22T20:05:54: Number of free parameters .: 4
673   - 2015-05-22T20:05:54: Number of iterations ......: 3
674   - 2015-05-22T20:05:54: Lambda ....................: 1e-06
675   - 2015-05-22T20:05:54: Maximum log likelihood ....: -93848.587
676   - 2015-05-22T20:05:54: Observed events (Nobs) ...: 15312.000
677   - 2015-05-22T20:05:54: Predicted events (Npred) ..: 15312.000 (Nobs - Npred = 3.03823e-06)
678   - 2015-05-22T20:05:54: === GModels ===
679   - 2015-05-22T20:05:54: Number of models ..........: 2
680   - 2015-05-22T20:05:54: Number of parameters ......: 10
681   - 2015-05-22T20:05:54: === GModelSky ===
682   - 2015-05-22T20:05:54: Name ......................: Crab
683   - 2015-05-22T20:05:54: Instruments ...............: all
684   - 2015-05-22T20:05:54: Instrument scale factors ..: unity
685   - 2015-05-22T20:05:54: Observation identifiers ...: all
686   - 2015-05-22T20:05:54: Model type ................: PointSource
687   - 2015-05-22T20:05:54: Model components ..........: "SkyDirFunction" * "PowerLaw" * "Constant"
688   - 2015-05-22T20:05:54: Number of parameters ......: 6
689   - 2015-05-22T20:05:54: Number of spatial par's ...: 2
690   - 2015-05-22T20:05:54: RA .......................: 83.6331 [-360,360] deg (fixed,scale=1)
691   - 2015-05-22T20:05:54: DEC ......................: 22.0145 [-90,90] deg (fixed,scale=1)
692   - 2015-05-22T20:05:54: Number of spectral par's ..: 3
693   - 2015-05-22T20:05:54: Prefactor ................: 5.80619e-16 +/- 1.11149e-17 [1e-23,1e-13] ph/cm2/s/MeV (free,scale=1e-16,gradient)
694   - 2015-05-22T20:05:54: Index ....................: -2.49282 +/- 0.0163467 [-0,-5] (free,scale=-1,gradient)
695   - 2015-05-22T20:05:54: PivotEnergy ..............: 300000 [10000,1e+09] MeV (fixed,scale=1e+06,gradient)
696   - 2015-05-22T20:05:54: Number of temporal par's ..: 1
697   - 2015-05-22T20:05:54: Normalization ............: 1 (relative value) (fixed,scale=1,gradient)
698   - 2015-05-22T20:05:54: === GCTAModelIrfBackground ===
699   - 2015-05-22T20:05:54: Name ......................: CTABackgroundModel
700   - 2015-05-22T20:05:54: Instruments ...............: CTA
701   - 2015-05-22T20:05:54: Instrument scale factors ..: unity
702   - 2015-05-22T20:05:54: Observation identifiers ...: all
703   - 2015-05-22T20:05:54: Model type ................: "PowerLaw" * "Constant"
704   - 2015-05-22T20:05:54: Number of parameters ......: 4
705   - 2015-05-22T20:05:54: Number of spectral par's ..: 3
706   - 2015-05-22T20:05:54: Prefactor ................: 1.03511 +/- 0.024311 [0.001,1000] ph/cm2/s/MeV (free,scale=1,gradient)
707   - 2015-05-22T20:05:54: Index ....................: 0.0333176 +/- 0.0134386 [-5,5] (free,scale=1,gradient)
708   - 2015-05-22T20:05:54: PivotEnergy ..............: 1e+06 [10000,1e+09] MeV (fixed,scale=1e+06,gradient)
709   - 2015-05-22T20:05:54: Number of temporal par's ..: 1
710   - 2015-05-22T20:05:54: Normalization ............: 1 (relative value) (fixed,scale=1,gradient)
711   -
712   -
713   -.. _sec_butterfly_cta:
714   -
715   -Calculating and visualising a butterfly
716   -~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
717   -
718   -To visualise the analysis results retrieved above, one can calculate the
719   -confidence band of the spectral fit.
720   -The :ref:`ctbutterfly` tool takes the optimised source model as input.
721   -It takes the covariance matrix from the fit to conduct a
722   -Gaussian error propagation for each energy value. It will write the
723   -butterfly information into an ASCII file.
724   -The following example shows how to compute such a butterfly from the command
725   -line.
726   -
727   -.. code-block:: bash
728   -
729   - $ ctbutterfly
730   - Input event list, counts cube or observation definition file [events.fits]
731   - Calibration database [prod2]
732   - Instrument response function [South_50h]
733   - Source model [$CTOOLS/share/models/crab.xml]
734   - Source of interest [Crab]
735   - Start value for first energy bin in TeV [0.1]
736   - Stop value for last energy bin in TeV [100.0]
737   - Output ascii file [butterfly.txt]
738   -
739   -Now that you have computed the confidence band of the spectral fit and
740   -that you will have an ASCII file named ``butterfly.txt`` on disk you can
741   -visualise the butterfly using the script ``show_butterfly.py`` that is
742   -in the ctools ``example`` folder. You will need matplotlib on your system
743   -to make this work. To launch the script, type:
744   -
745   -.. code-block:: bash
746   -
747   - python $CTOOLS/share/examples/python/show_butterfly.py butterfly.txt
748   -
749   -This will result in a canvas which should look like the following:
750   -
751   -.. figure:: butterfly.jpg
752   - :height: 400px
753   - :align: center
  4 +-----------------------
754 5  
755   - *Confidence band of the fit*
756   -
757 6 \ No newline at end of file
  7 +This section provides a step-by-step description of a simple CTA data
  8 +analysis example using the ctools. In this example we will simulate a
  9 +half an hour long CTA observation of the Crab nebula as the single
  10 +point source within the CTA field of view. You will learn how to bin the
  11 +event data into a counts cube and how to fit a spatial and spectral model
  12 +to the data. You will also learn how to analyse directly event lists
  13 +without binning the events into a counts cube. Finally we will show how
  14 +you can create a butterfly diagram that shows the confidence band of the
  15 +fitted spectral model.
  16 +
  17 +.. toctree::
  18 + :maxdepth: 2
  19 +
  20 + simulating
  21 + binning
  22 + fitting
  23 + unbinned
  24 + butterfly
... ...
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... ... @@ -99,7 +99,7 @@ Specifying the response function as input parameters
99 99 ctools that require instrument response functions have two parameters
100 100 to specify the calibration database name and the response function name.
101 101 The following example shows a ``ctobssim`` run using the ``prod2``
102   -calibration database and the ``South_50h`` response function:
  102 +calibration database and the ``South_0.5h`` response function:
103 103  
104 104 .. code-block:: bash
105 105  
... ... @@ -112,8 +112,9 @@ calibration database and the ``South_50h`` response function:
112 112 Lower energy limit (TeV) [0.1]
113 113 Upper energy limit (TeV) [100.0]
114 114 Calibration database [prod2]
115   - Instrument response function [South_50h]
116   - Model [$CTOOLS/share/models/crab.xml]
  115 + Instrument response function [South_0.5h]
  116 + Input model XML file [$CTOOLS/share/models/crab.xml]
  117 + Output event data file or observation definition XML file [events.fits]
117 118  
118 119 Running the other tools is equivalent.
119 120  
... ... @@ -131,7 +132,7 @@ definition file:
131 132 <observation_list title="observation library">
132 133 <observation name="Crab" id="00001" instrument="CTA">
133 134 <parameter name="EventList" file="events.fits"/>
134   - <parameter name="Calibration" database="prod2" response="South_50h"/>
  135 + <parameter name="Calibration" database="prod2" response="South_0.5h"/>
135 136 </observation>
136 137 </observation_list>
137 138  
... ... @@ -141,9 +142,9 @@ response name. You can then pass this file directly to, e.g., ``ctlike``:
141 142 .. code-block:: bash
142 143  
143 144 $ ctlike
144   - Event list, counts cube or observation definition file [events.fits] obs_irf.xml
145   - Source model [$CTOOLS/share/models/crab.xml]
146   - Source model output file [crab_results.xml]
  145 + Input event list, counts cube or observation definition XML file [events.fits] obs_irf.xml
  146 + Input model XML file [$CTOOLS/share/models/crab.xml]
  147 + Output model XML file [crab_results.xml]
147 148  
148 149 Note that ``ctlike`` does not ask for the calibration database and
149 150 response name as it found the relevant information in the XML file.
... ... @@ -181,11 +182,11 @@ and response name from within Python:
181 182 import gammalib
182 183 obs = gammalib.GCTAObservation()
183 184 caldb = gammalib.GCaldb("cta", "prod2")
184   - irf = "South_50h"
  185 + irf = "South_0.5h"
185 186 obs.response(irf, caldb)
186 187  
187 188 The calibration database is set by creating a ``GCaldb`` object. The
188 189 constructor takes as argument the mission (always ``cta``) and the
189 190 database name, in our case ``prod2``. The response function is then set
190   -by passing the response name (here ``South_50h``) and the calibration
  191 +by passing the response name (here ``South_0.5h``) and the calibration
191 192 database object to the ``response`` method.
... ...
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  1 +.. _sec_simulating_cta:
  2 +
  3 +Simulating CTA data
  4 +~~~~~~~~~~~~~~~~~~~
  5 +
  6 +You can simulate a CTA observation with the :ref:`ctobssim` tool.
  7 +
  8 +To invoke the tool, type :ref:`ctobssim` at the console prompt
  9 +(which is denoted by ``$``).
  10 +:ref:`ctobssim` will query for a number of parameters:
  11 +
  12 +.. code-block:: bash
  13 +
  14 + $ ctobssim
  15 + RA of pointing (degrees) (0-360) [83.63]
  16 + Dec of pointing (degrees) (-90-90) [22.01]
  17 + Radius of FOV (degrees) (0-180) [5.0]
  18 + Start time (MET in s) [0.0]
  19 + End time (MET in s) [1800.0]
  20 + Lower energy limit (TeV) [0.1]
  21 + Upper energy limit (TeV) [100.0]
  22 + Calibration database [prod2]
  23 + Instrument response function [South_0.5h]
  24 + Input model XML file [$CTOOLS/share/models/crab.xml]
  25 + Output event data file or observation definition XML file [events.fits]
  26 +
  27 +Each line represents a query for one parameter value.
  28 +The line starts with a short description of the parameter, followed by
  29 +the default value proposed by ctobssim in squared brackets ``[ ]``.
  30 +
  31 +**If no parameter is entered the default value will be used**
  32 +(which is the case for all parameters shown here).
  33 +Otherwise, the specified value will overwrite the default value.
  34 +The round brackets ``( )`` indicate the range of possible parameter
  35 +values (if applicable).
  36 +
  37 +
  38 +You may have recognised that the environment variable ``$CTOOLS`` has
  39 +been used in the path name of the model. ctools will automatically expand
  40 +the environment variables in parameter inputs.
  41 +
  42 +The CTA instrument properties (effective area, PSF width) are taken from
  43 +the prod2 database. The response for the southern array using the cuts
  44 +optimised for 50 hours of observing time are used.
  45 +
  46 +.. note::
  47 +
  48 + ctools comes bundled with CTA response functions for the northern and
  49 + the southern array. The response functions are based on a Prod2
  50 + analysis with cuts optimised for 0.5 hours, 5 hours and 50 hours of
  51 + observing time. The following Instrument Response Functions
  52 + (IRFs) are available: ``North_0.5h``, ``North_5h``, ``North_50h``,
  53 + ``South_0.5h``, ``South_5h``, and ``South_50h``.
  54 +
  55 +Events are simulated based on the instrument properties and based on a
  56 +source and background model. Only events that fall within the specified
  57 +region of interest (ROI), defined as a circle around a sky position in
  58 +Right Ascension and Declination (in degrees), will be stored in the output
  59 +event data file. The duration of the simulation is taken here to 30 minutes
  60 +(or 1800 seconds). Events are simulated for energies between 0.1 and 100 TeV.
  61 +
  62 +The source and background model is defined by the XML file
  63 +``$CTOOLS/share/models/crab.xml``:
  64 +
  65 +.. code-block:: xml
  66 +
  67 + <?xml version="1.0" standalone="no"?>
  68 + <source_library title="source library">
  69 + <source name="Crab" type="PointSource">
  70 + <spectrum type="PowerLaw">
  71 + <parameter name="Prefactor" scale="1e-16" value="5.7" min="1e-07" max="1000.0" free="1"/>
  72 + <parameter name="Index" scale="-1" value="2.48" min="0.0" max="+5.0" free="1"/>
  73 + <parameter name="Scale" scale="1e6" value="0.3" min="0.01" max="1000.0" free="0"/>
  74 + </spectrum>
  75 + <spatialModel type="SkyDirFunction">
  76 + <parameter name="RA" scale="1.0" value="83.6331" min="-360" max="360" free="0"/>
  77 + <parameter name="DEC" scale="1.0" value="22.0145" min="-90" max="90" free="0"/>
  78 + </spatialModel>
  79 + </source>
  80 + <source name="CTABackgroundModel" type="CTAIrfBackground" instrument="CTA">
  81 + <spectrum type="PowerLaw">
  82 + <parameter name="Prefactor" scale="1.0" value="1.0" min="1e-3" max="1e+3" free="1"/>
  83 + <parameter name="Index" scale="1.0" value="0.0" min="-5.0" max="+5.0" free="1"/>
  84 + <parameter name="Scale" scale="1e6" value="1.0" min="0.01" max="1000.0" free="0"/>
  85 + </spectrum>
  86 + </source>
  87 + </source_library>
  88 +
  89 +The model consists of a source library that contains two components:
  90 +the Crab nebula and an instrumental background model.
  91 +
  92 +The Crab nebula is modelled by a factorized sky model that has a spectral
  93 +and a spatial component (tags ``<spectrum>`` and ``<spatialModel>``,
  94 +respectively). The spectrum is modelled by a power law, which is defined by
  95 +three parameters: the ``Prefactor``, the ``Index`` and the ``Scale``.
  96 +The spatial model has two parameters: Right Ascension in degrees (``RA``), and
  97 +Declination in degrees (``DEC``). Each parameter has a value and a scale factor,
  98 +the real value of the parameter being the product ``value * scale``. Typically,
  99 +``scale`` is chosen so that ``value`` is of the order of 1 (this is relevant for
  100 +model fitting). In addition, ``value`` is bound by a minimum (``min``) and
  101 +maximum (``max``) value, and a parameter may be free (``free="1"``) or fixed
  102 +(``free="0"``). The ``min``, ``max``, and ``free`` attributes are not
  103 +relevant here for the simulations, but they will be important for the model
  104 +fitting later.
  105 +
  106 +The spectral intensity I(E) (in units of photons/cm2/s/MeV) of the power
  107 +law is given by
  108 +
  109 +.. math::
  110 + \frac{dN}{dE} = N_0 \left( \frac{E}{E_0} \right)^{\gamma}
  111 +
  112 +where the parameters in the XML definition have the following mappings:
  113 +
  114 +* :math:`N_0` = ``Prefactor``
  115 +* :math:`\gamma` = ``Index``
  116 +* :math:`E_0` = ``Scale``
  117 +
  118 +.. warning::
  119 +
  120 + Energies are given in the XML file in MeV units. This is a GammaLib
  121 + convention that can not be modified. **So make sure you always use
  122 + MeV as energy unit in an XML file.**
  123 +
  124 +The instrumental background of CTA is modelled using the background
  125 +information provided in the IRF (``CTAIrfBackground``) multipled
  126 +by a power law. As it is defined here, the power law represents a
  127 +constant of 1, hence the background IRF will be used without any
  128 +modification. The power law will become active when fitting the data
  129 +later and allows a spectral adjustment of the background model that
  130 +may account for uncertainties in the background information provided
  131 +in the IRF.
  132 +
  133 +:ref:`ctobssim` has a couple of hidden parameters, the most important one being
  134 +certainly ``seed``. ``seed`` is an integer that specifies the seed value
  135 +for the random number generator, and changing this parameter will allow to
  136 +generate statistically independent Monte Carlo samples of CTA event data.
  137 +To use for example a seed value of 41 you should type:
  138 +
  139 +.. code-block:: bash
  140 +
  141 + $ ctobssim seed=41
  142 +
  143 +:ref:`ctobssim` will write 2 files in the working directory: ``events.fits``
  144 +and ``ctobssim.log``. The first file contains the simulated events in FITS
  145 +format and can be inspected using ``fv`` or ``ds9``. The FITS file will
  146 +contain three extensions: an empty primary image, a binary table named
  147 +``EVENTS`` that holds the events (one row per event), and a binary table
  148 +named ``GTI`` holding the Good Time Intervals (for the moment a single row
  149 +with 2 columns providing the start and the stop time of the simulated time
  150 +interval).
  151 +
  152 +The second file produced by :ref:`ctobssim` is a human readable log file that
  153 +contains information about the job execution. As example, the last lines
  154 +from this file are shown here:
  155 +
  156 +.. code-block:: xml
  157 +
  158 + 2015-12-07T20:48:30: +======================+
  159 + 2015-12-07T20:48:30: | Simulate observation |
  160 + 2015-12-07T20:48:30: +======================+
  161 + 2015-12-07T20:48:30: === CTA observation ===
  162 + 2015-12-07T20:48:30: Simulation area ...........: 1.9635e+11 cm2
  163 + 2015-12-07T20:48:30: Simulation cone ...........: RA=83.63 deg, Dec=22.01 deg, r=5.5 deg
  164 + 2015-12-07T20:48:30: Time interval .............: 0 - 1800 s
  165 + 2015-12-07T20:48:30: Photon energy range .......: 100 GeV - 100 TeV
  166 + 2015-12-07T20:48:30: Event energy range ........: 100 GeV - 100 TeV
  167 + 2015-12-07T20:48:30: Use model .................: Crab
  168 + 2015-12-07T20:48:30: Normalization .............: 1 [Crab]
  169 + 2015-12-07T20:48:30: Flux ......................: 5.87297e-10 [Crab] photons/cm2/s
  170 + 2015-12-07T20:48:30: Normalized flux ...........: 5.87297e-10 [Crab] photons/cm2/s
  171 + 2015-12-07T20:48:30: Photon rate ...............: 115.316 photons/s [Crab]
  172 + 2015-12-07T20:48:31: MC source photons .........: 207547 [Crab]
  173 + 2015-12-07T20:48:31: MC source events ..........: 3646 [Crab]
  174 + 2015-12-07T20:48:31: MC source events ..........: 3646 (all source models)
  175 + 2015-12-07T20:48:33: MC events outside ROI .....: 0
  176 + 2015-12-07T20:48:33: MC background events ......: 19039
  177 + 2015-12-07T20:48:33: MC events .................: 22685 (all models)
  178 +
  179 +Each line starts with the UTC time at which the line has been written. In
  180 +this run, 207547 Crab photons have been thrown over an area of 19.6 square
  181 +kilometres during a time interval of 1800 seconds. 3646 of these photons have
  182 +been registered by CTA as events. In the same time interval, 19039 background
  183 +events have been registred by CTA.
  184 +
  185 +You may change the name of the log file using the hidden parameter
  186 +``logfile``:
  187 +
  188 +.. code-block:: bash
  189 +
  190 + $ ctobssim logfile=my-private-log-file
  191 +
  192 +Furthermore, you may decide on the amount of information provided in the
  193 +log file (the chattiness of the executable) using the hidden parameter
  194 +``chatter``:
  195 +
  196 +.. code-block:: bash
  197 +
  198 + $ ctobssim chatter=4
  199 +
  200 +``chatter`` can vary between 0 and 4, 0 providing no information while 4
  201 +provides the most detailed information.
  202 +
  203 +**By default, all ctools have a chatter level of 2.**
  204 +
  205 +You may also duplicate the log file information into the console by setting
  206 +the hidden ``debug`` parameter to yes:
  207 +
  208 +.. code-block:: bash
  209 +
  210 + $ ctobssim debug=yes
... ...
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  1 +.. _sec_unbinned_cta:
  2 +
  3 +Doing an unbinned analysis
  4 +~~~~~~~~~~~~~~~~~~~~~~~~~~
  5 +
  6 +As gamma-ray events are rare, the counts cubes generated by :ref:`ctbin`
  7 +will in general be sparsly populated, having many empty pixels, in
  8 +particular at high energies.
  9 +An alternative analysis technique consists of working directly on the event
  10 +list without binning the events in a counts cube. We will see the benefit of
  11 +such an analysis later once you re-run :ref:`ctlike` in unbinned mode.
  12 +
  13 +For unbinned analysis you first have to define the data space region over
  14 +which the analysis is done. This is similiar to the :ref:`ctbin` step for
  15 +a binned analysis where you defined the size of the counts cube, the energy
  16 +range, and the time interval. For unbinned analysis you have no such thing
  17 +as a counts cube, but you have to define over which region of the data space
  18 +the selected events are spread (because the ctools have to integrate over
  19 +this region to compute the total number of predicted events in the data space
  20 +that you analyse). Furthermore, you have to define what energy range is
  21 +covered, and what time interval is spanned by the data. All this is done
  22 +by the :ref:`ctselect` tool, which replaces the :ref:`ctbin` step in an
  23 +unbinned analysis.
  24 +
  25 +:ref:`ctselect` performs an event selection by choosing only events within
  26 +a given region-of-interest (ROI), within a given energy band, and within a
  27 +given time interval from the input event list. The ROI is a circular region on
  28 +the sky, for which you define the centre (in celestial coordinates) and the
  29 +radius. Such a circular ROI is sometimes also called an acceptance cone. The
  30 +following example shows how to run ctselect:
  31 +
  32 +.. code-block:: bash
  33 +
  34 + $ ctselect
  35 + Input event list or observation definition XML file [events.fits]
  36 + RA for ROI centre (degrees) (0-360) [83.63]
  37 + Dec for ROI centre (degrees) (-90-90) [22.01]
  38 + Radius of ROI (degrees) (0-180) [3.0]
  39 + Start time (CTA MET in seconds) [0.0]
  40 + End time (CTA MET in seconds) [0.0]
  41 + Lower energy limit (TeV) [0.1]
  42 + Upper energy limit (TeV) [100.0]
  43 + Output event list or observation definition XML file [selected_events.fits]
  44 +
  45 +:ref:`ctselect` takes the input event list ``events.fits``, performs an
  46 +event selection, and writes the selected event into the file
  47 +``selected_events.fits``. The parameters it will query for are the centre
  48 +of the ROI, the radius of the ROI, the start and stop time (in seconds),
  49 +and the energy lower and upper limits (in TeV). The event selection information
  50 +is also written as a set of data selection keywords to the output events
  51 +file ``selected_events.fits``, by respecting the same syntax that has been
  52 +implemented for Fermi/LAT. The following image is a screen dump of the data
  53 +selection keywords that have been written to the ``EVENTS`` header in the
  54 +file ``selected_events.fits``:
  55 +
  56 +.. figure:: dskeys.jpg
  57 + :width: 400px
  58 + :align: center
  59 +
  60 + *Data selection keywords*
  61 +
  62 +**It is mandatory for an unbinned analysis that these data selection keywords
  63 +exist in the FITS file.**
  64 +If they don't exist, :ref:`ctlike` will not execute in unbinned mode.
  65 +
  66 +Below some lines of the ``ctselect.log`` file that show the data selection
  67 +part:
  68 +
  69 +.. code-block:: xml
  70 +
  71 + 2015-12-06T23:44:52: +=================+
  72 + 2015-12-06T23:44:52: | Event selection |
  73 + 2015-12-06T23:44:52: +=================+
  74 + 2015-12-06T23:44:52: === CTA observation ===
  75 + 2015-12-06T23:44:52: Selected energy range .....: 0.1 - 100 TeV
  76 + 2015-12-06T23:44:52: Requested ROI .............: Centre(RA,DEC)=(83.63, 22.01) deg, Radius=3 deg
  77 + 2015-12-06T23:44:52: ROI of data ...............: Centre(RA,DEC)=(83.63, 22.01) deg, Radius=5 deg
  78 + 2015-12-06T23:44:52: Selected ROI ..............: Centre(RA,DEC)=(83.63, 22.01) deg, Radius=3 deg
  79 + 2015-12-06T23:44:52: cfitsio selection .........: ENERGY >= 0.10000000 && ENERGY <= 100.00000000 && ANGSEP(83.630000,22.010000,RA,DEC) <= 3.000000
  80 + 2015-12-06T23:44:52: FITS filename .............: /var/tmp/tmp.0.jHg5hJ[EVENTS][ENERGY >= 0.10000000 && ENERGY <= 100.00000000 && ANGSEP(83.630000,22.010000,RA,DEC) <= 3.000000]
  81 +
  82 +.. note::
  83 +
  84 + :ref:`ctobssim` will also write data selection keywords in the event
  85 + list FITS file, hence you can run :ref:`ctlike` directly on a FITS file
  86 + produced by :ref:`ctobssim`. Any selection performed by :ref:`ctselect`
  87 + needs to be fully enclosed within any previous selection, e.g. the ROI
  88 + needs to be fully enclosed in the acceptance cone used for event
  89 + simulation, the energy selection must be fully comprised in the
  90 + range of simulated energies, the same applies for the temporal selection.
  91 + :ref:`ctselect` will automatically adjust
  92 + the selection parameters to guarantee full enclosure. To keep track of
  93 + this adjustment, the :ref:`ctselect` log file quotes the requested
  94 + selection, any existing selections, and the selection that was finally
  95 + applied.
  96 +
  97 +.. warning::
  98 +
  99 + :ref:`ctselect` may of course also be used for event selection prior to
  100 + binned analysis, for example to select events for a given period in
  101 + time. **If you use** :ref:`ctselect` **however to make a spatial or energy
  102 + selection, make sure that the counts cube is fully enclosed in the
  103 + selection intervals.** Otherwise you will get empty zones in the counts
  104 + cube of which the ctools are not aware of, and the subsequent analysis
  105 + results will be wrong.
  106 +
  107 +Now that you have selected the events of interest, you can run ctlike in
  108 +unbinned mode. To do this you have to specify the selected event list
  109 +instead of the counts cube:
  110 +
  111 +.. code-block:: bash
  112 +
  113 + $ ctlike
  114 + Input event list, counts cube or observation definition XML file [cntcube.fits] selected_events.fits
  115 + Calibration database [prod2]
  116 + Instrument response function [South_0.5h]
  117 + Input model XML file [$CTOOLS/share/models/crab.xml]
  118 + Output model XML file [crab_results.xml]
  119 +
  120 +You will recognise that :ref:`ctlike` runs much faster in unbinned mode
  121 +compared to binned mode.
  122 +This is understandable as the selected event list contains
  123 +only 21203 events, while the binned counts cube we used before had
  124 +200 x 200 x 20 = 800000 pixels. As unbinned maximum likelihood fitting loops
  125 +over the events (while binned maximum likelihood loops over the pixels),
  126 +there are much less operations to perform in unbinned than in binned mode
  127 +(there is some additional overhead in unbinned mode that comes from
  128 +integrating the models over the region of interest, yet this is negligible
  129 +compared to the operations needed when looping over all pixels). So as long
  130 +as you work with small event lists, unbinned mode is faster (this
  131 +typically holds up to 100 hours of observing time).
  132 +Unbinned :ref:`ctlike` should also be more precise as no binning is performed,
  133 +hence there is no loss of information due to histogramming.
  134 +
  135 +Below you see the corresponding output from the ctlike.log file. The fitted
  136 +parameters are essentially identical to the ones found in binned mode.
  137 +The slight difference with respect to the binned analysis may be explained
  138 +by the different event sample that has been used for the analysis: while
  139 +binned likelihood works on rectangular counts cubes, unbinned likelihood works
  140 +on circular event selection regions. It is thus not possible to select exactly
  141 +the same events for both analyses.
  142 +
  143 +.. code-block:: xml
  144 +
  145 + 2015-12-07T21:02:17: +=================================+
  146 + 2015-12-07T21:02:17: | Maximum likelihood optimisation |
  147 + 2015-12-07T21:02:17: +=================================+
  148 + 2015-12-07T21:02:17: >Iteration 0: -logL=135278.644, Lambda=1.0e-03
  149 + 2015-12-07T21:02:17: >Iteration 1: -logL=135274.475, Lambda=1.0e-03, delta=4.168, max(|grad|)=5.806873 [Index:7]
  150 + 2015-12-07T21:02:17: >Iteration 2: -logL=135274.474, Lambda=1.0e-04, delta=0.001, max(|grad|)=-0.009463 [Index:7]
  151 + 2015-12-07T21:02:17:
  152 + ...
  153 + 2015-12-07T21:02:17: +=========================================+
  154 + 2015-12-07T21:02:17: | Maximum likelihood optimisation results |
  155 + 2015-12-07T21:02:17: +=========================================+
  156 + 2015-12-07T21:02:17: === GOptimizerLM ===
  157 + 2015-12-07T21:02:17: Optimized function value ..: 135274.474
  158 + 2015-12-07T21:02:17: Absolute precision ........: 0.005
  159 + 2015-12-07T21:02:17: Acceptable value decrease .: 2
  160 + 2015-12-07T21:02:17: Optimization status .......: converged
  161 + 2015-12-07T21:02:17: Number of parameters ......: 10
  162 + 2015-12-07T21:02:17: Number of free parameters .: 4
  163 + 2015-12-07T21:02:17: Number of iterations ......: 2
  164 + 2015-12-07T21:02:17: Lambda ....................: 1e-05
  165 + 2015-12-07T21:02:17: Maximum log likelihood ....: -135274.474
  166 + 2015-12-07T21:02:17: Observed events (Nobs) ...: 21203.000
  167 + 2015-12-07T21:02:17: Predicted events (Npred) ..: 21202.998 (Nobs - Npred = 0.00198937)
  168 + 2015-12-07T21:02:17: === GModels ===
  169 + 2015-12-07T21:02:17: Number of models ..........: 2
  170 + 2015-12-07T21:02:17: Number of parameters ......: 10
  171 + 2015-12-07T21:02:17: === GModelSky ===
  172 + 2015-12-07T21:02:17: Name ......................: Crab
  173 + 2015-12-07T21:02:17: Instruments ...............: all
  174 + 2015-12-07T21:02:17: Instrument scale factors ..: unity
  175 + 2015-12-07T21:02:17: Observation identifiers ...: all
  176 + 2015-12-07T21:02:17: Model type ................: PointSource
  177 + 2015-12-07T21:02:17: Model components ..........: "SkyDirFunction" * "PowerLaw" * "Constant"
  178 + 2015-12-07T21:02:17: Number of parameters ......: 6
  179 + 2015-12-07T21:02:17: Number of spatial par's ...: 2
  180 + 2015-12-07T21:02:17: RA .......................: 83.6331 [-360,360] deg (fixed,scale=1)
  181 + 2015-12-07T21:02:17: DEC ......................: 22.0145 [-90,90] deg (fixed,scale=1)
  182 + 2015-12-07T21:02:17: Number of spectral par's ..: 3
  183 + 2015-12-07T21:02:17: Prefactor ................: 5.81583e-16 +/- 1.01727e-17 [1e-23,1e-13] ph/cm2/s/MeV (free,scale=1e-16,gradient)
  184 + 2015-12-07T21:02:17: Index ....................: -2.50611 +/- 0.0153542 [-0,-5] (free,scale=-1,gradient)
  185 + 2015-12-07T21:02:17: PivotEnergy ..............: 300000 [10000,1e+09] MeV (fixed,scale=1e+06,gradient)
  186 + 2015-12-07T21:02:17: Number of temporal par's ..: 1
  187 + 2015-12-07T21:02:17: Normalization ............: 1 (relative value) (fixed,scale=1,gradient)
  188 + 2015-12-07T21:02:17: === GCTAModelIrfBackground ===
  189 + 2015-12-07T21:02:17: Name ......................: CTABackgroundModel
  190 + 2015-12-07T21:02:17: Instruments ...............: CTA
  191 + 2015-12-07T21:02:17: Instrument scale factors ..: unity
  192 + 2015-12-07T21:02:17: Observation identifiers ...: all
  193 + 2015-12-07T21:02:17: Model type ................: "PowerLaw" * "Constant"
  194 + 2015-12-07T21:02:17: Number of parameters ......: 4
  195 + 2015-12-07T21:02:17: Number of spectral par's ..: 3
  196 + 2015-12-07T21:02:17: Prefactor ................: 0.990866 +/- 0.0136406 [0.001,1000] ph/cm2/s/MeV (free,scale=1,gradient)
  197 + 2015-12-07T21:02:17: Index ....................: 0.00536014 +/- 0.00839916 [-5,5] (free,scale=1,gradient)
  198 + 2015-12-07T21:02:17: PivotEnergy ..............: 1e+06 [10000,1e+09] MeV (fixed,scale=1e+06,gradient)
  199 + 2015-12-07T21:02:17: Number of temporal par's ..: 1
  200 + 2015-12-07T21:02:17: Normalization ............: 1 (relative value) (fixed,scale=1,gradient)
... ...
doc/source/user_manual/glossary.rst
  View file @14f9d87
1 1 Glossary
2 2 ========
3 3  
4   -- **GammaLib** (`<http://gammalib.sourceforge.net/>`_)
  4 +- **GammaLib** (`<http://cta.irap.omp.eu/gammalib/>`_)
5 5  
6 6 A versatile toolbox for scientific analysis of astronomical
7 7 gamma-ray data.
... ...
doc/source/user_manual/index.rst
  View file @14f9d87
... ... @@ -8,8 +8,6 @@ User Manual
8 8 introduction
9 9 getting
10 10 getting_started/index
11   - enhancing
12   - expert
13 11 plotting
14 12 glossary
15 13  
... ...
doc/source/user_manual/introduction.rst
  View file @14f9d87
... ... @@ -22,6 +22,13 @@ also be specified as arguments separated by a whitespace to the ctool:
22 22  
23 23 $ ctobssim ra=83.63 dec=22.01 rad=5.0 tmin=0 tmax=1800 emin=0.1 emax=100.0 caldb=prod2 irf=South_50h inmodel=$CTOOLS/share/models/crab.xml outevents=events.fits
24 24  
  25 +If you need help about the usage of a ctool or a cscript, type the name of
  26 +the ctool or cscript followed by the ``--help`` option:
  27 +
  28 +.. code-block:: bash
  29 +
  30 + $ ctobssim --help
  31 +
25 32 ctools includes also a Python module that declares every ctool as a
26 33 Python class. The following example illustrates the usage:
27 34  
... ... @@ -47,7 +54,7 @@ command line or used as Python classes, as illustrated below:
47 54  
48 55 In this User Manual you will now learn how to install and use the ctools
49 56 package.
50   -If you encounter any problems, please read the :ref:`issues` section.
51   -If you're desperate, you may need :ref:`help`.
  57 +If you encounter any problems, please read the :ref:`faq` and :ref:`issues`
  58 +sections. If you're desperate, you may need :ref:`help`.
52 59 And you should read the :ref:`develop` section if you would like to
53 60 contribute to the ctools developments.
... ...
doc/source/user_manual/plotting.rst
  View file @14f9d87
1 1 Plotting
2 2 ========
3 3  
4   -Gammalib and ctools currently do not include classes and scripts to make plots.
  4 +Gammalib and ctools do not include classes and scripts to make plots.
5 5  
6   -This is intentional because creating and maintaining plotting tools that work on most user's machines
7   -and cover most user's needs is a big project in itself, and deciding to support a
8   -plotting package that is popular now as part of the CTA science tools could become very problematic in the future.
  6 +This is intentional because creating and maintaining plotting tools that
  7 +work on most user's machines and cover most user's needs is a big project
  8 +in itself, and deciding to support a plotting package that is popular now
  9 +as part of the CTA science tools could become very problematic in the
  10 +future.
  11 +
  12 +But we realise that most ctools users need to create plots for their
  13 +high-level science results, so on this page we provide a few pointers
  14 +to external packages and tools.
9 15  
10   -But we realise that most ctools users need to create plots for their high-level science results,
11   -so on this page we provide a few pointers to external packages and tools.
12 16  
13 17 General
14 18 -------
15 19  
16   -The most common way to create publication-quality astronomy plots at the moment is to use the `matplotlib`_
17   -Python plotting package. As illustrated by the `matplotlib gallery`_, virtually any plot can be constructed,
18   -but matplotlib doesn't have built-in easy-to-use classes or functions to create the common plots for gamma-ray
19   -astronomy, which are sky maps and spectra, so in the sections below we give some specific pointers for those.
  20 +The most common way to create publication-quality astronomy plots at the
  21 +moment is to use the `matplotlib`_ Python plotting package. As illustrated
  22 +by the `matplotlib gallery`_, virtually any plot can be constructed,
  23 +but matplotlib doesn't have built-in easy-to-use classes or functions to
  24 +create the common plots for gamma-ray astronomy, which are sky maps and
  25 +spectra, so in the sections below we give some specific pointers for those.
  26 +
20 27  
21 28 Sky maps
22 29 --------
23 30  
24   -For creating publication quality sky map plots via a Python script a good choice is to use `APLPy`_, `WCSAxes`_
25   -or `kapteyn`_, which are all based on matplotlib.
  31 +For creating publication quality sky map plots via a Python script a good
  32 +choice is to use `APLPy`_, `WCSAxes`_ or `kapteyn`_, which are all based on
  33 +matplotlib.
26 34  
27   -You can also use interactive astronomy image viewers like `DS9`_, `Aladin`_ or `Ginga`_
28   -which allow you to save the image to a PNG or PDF file after customising it interactively,
29   -but also contain command line options to create the plot, i.e. you can write a bash or Python script
30   -to make the plot reproducible (DS9 and Ginga also feature direct communication with Python,
31   -but that is a bit harder to use and usually used for interactive image analysis, not plotting scripts).
  35 +You can also use interactive astronomy image viewers like `DS9`_, `Aladin`_
  36 +or `Ginga`_ which allow you to save the image to a PNG or PDF file after
  37 +customising it interactively, but also contain command line options to create
  38 +the plot, i.e. you can write a bash or Python script to make the plot
  39 +reproducible (DS9 and Ginga also feature direct communication with Python,
  40 +but that is a bit harder to use and usually used for interactive image
  41 +analysis, not plotting scripts).
32 42  
33 43  
34 44 Spectra and light curves
35 45 ------------------------
36 46  
37   -To plot spectra or spectral energy distributions (including flux model curves, flux model error bands,
38   -flux points and residuals) and light curves, you can use matplotlib directly,
39   -or use the classes and scripts in `Gammapy`_.
40   -
41   -Another option is to use virtual observatory interactive spectrum tools like `IRIS`_, `CASSIS`_ or `VOSpec`_
42   -which allow you to save the plot to a PNG or PDF file after creating it interactively.
  47 +To plot spectra or spectral energy distributions (including flux model curves,
  48 +flux model error bands, flux points and residuals) and light curves, you can
  49 +use matplotlib directly, or use the classes and scripts in `Gammapy`_.
43 50  
  51 +Another option is to use virtual observatory interactive spectrum tools
  52 +like `IRIS`_, `CASSIS`_ or `VOSpec`_ which allow you to save the plot to a
  53 +PNG or PDF file after creating it interactively.
44 54  
45 55 .. _DS9: http://ds9.si.edu/
46 56 .. _Aladin: http://aladin.u-strasbg.fr/
... ...
pyext/Makefile.am
  View file @14f9d87
... ... @@ -94,6 +94,15 @@ all-local: build
94 94 # this.
95 95 build: ctools/tools_wrap.cpp ctools/tools.py
96 96 $(PYTHON) setup.py build
  97 +if IS_ELCAPITAN
  98 + -for f in build/ctools/ctools/_*.so; do \
  99 + echo "Post process module "$$f; \
  100 + install_name_tool -change $(libdir)/libctools.1.dylib @rpath/libctools.1.dylib $$f; \
  101 + install_name_tool -change $(libdir)/libgamma.1.dylib @rpath/libgamma.1.dylib $$f; \
  102 + install_name_tool -add_rpath $(libdir) $$f; \
  103 + install_name_tool -add_rpath $(abs_top_srcdir)/src/.libs $$f; \
  104 + done
  105 +endif
97 106  
98 107 install-exec-local:
99 108 $(PYTHON) setup.py install --prefix=$(prefix)
... ...
pyext/ctool.i
  View file @14f9d87
... ... @@ -99,6 +99,8 @@ public:
99 99  
100 100 // Protected methods that check user parameters
101 101 void require_inobs(const std::string& method);
  102 + void require_inobs_nolist(const std::string& method);
  103 + void require_inobs_nocube(const std::string& method);
102 104  
103 105 // Protected support methods
104 106 void set_response(GObservations& obs);
... ...
pyext/ctools/__init__.py renamed to pyext/ctools/__init__.py.in
  View file @14f9d87
... ... @@ -34,3 +34,6 @@ del tools
34 34 del gammalib
35 35 del bad_entries
36 36 del entry
  37 +
  38 +# Add version
  39 +__version__ = '@PACKAGE_VERSION@'
37 40 \ No newline at end of file
... ...
pyext/setup.py.in
  View file @14f9d87
... ... @@ -114,6 +114,10 @@ else:
114 114 extra_compile_args = []
115 115 extra_link_args = []
116 116  
  117 +# Optionally add link flag for El Capitan post-processing of modules
  118 +if '@IS_ELCAPITAN_TRUE@' != '#':
  119 + extra_link_args.append('-headerpad_max_install_names')
  120 +
117 121 # Setup
118 122 setup(name='@PACKAGE_NAME@',
119 123 version='@PACKAGE_VERSION@',
... ...
src/Makefile.am
  View file @14f9d87
... ... @@ -46,6 +46,7 @@ libctools_la_LIBADD = support/libsupport.la \
46 46 ctbutterfly/libctbutterfly.la \
47 47 ctulimit/libctulimit.la \
48 48 cterror/libcterror.la
  49 +libctools_la_LDFLAGS = -version-info $(CTOOLS_LT_VERSION) @OPENMP_LIB_LDFLAGS@
49 50  
50 51 # Distribute scripts
51 52 EXTRA_DIST = $(scripts)
... ...
src/ctbin/Makefile.am
  View file @14f9d87
... ... @@ -12,6 +12,7 @@ sources = ctbin.cpp
12 12 # Libtool library
13 13 noinst_LTLIBRARIES = libctbin.la
14 14 libctbin_la_SOURCES = $(sources)
  15 +libctbin_la_LDFLAGS = -version-info $(CTOOLS_LT_VERSION) @OPENMP_LIB_LDFLAGS@
15 16  
16 17 # Program definition
17 18 ctbin_SOURCES = main.cpp
... ...
src/ctbin/ctbin.cpp
  View file @14f9d87
... ... @@ -434,6 +434,9 @@ void ctbin::get_parameters(void)
434 434 // Throw exception if no input observation file is given
435 435 require_inobs(G_GET_PARAMETERS);
436 436  
  437 + // Throw exception if counts cube is given
  438 + require_inobs_nocube(G_GET_PARAMETERS);
  439 +
437 440 // Get observation container without response (not needed)
438 441 m_obs = get_observations(false);
439 442  
... ...
src/ctbin/ctbin.par
  View file @14f9d87
... ... @@ -17,8 +17,9 @@
17 17 #
18 18 # General parameters
19 19 #===================
20   -inobs, f, a, "events.fits",,, "Event list or observation definition file"
21   -outcube, f, a, "cntcube.fits",,, "Output counts cube"
  20 +inobs, f, a, "events.fits",,, "Input event list or observation definition XML file"
  21 +outcube, f, a, "cntcube.fits",,, "Output counts cube file"
  22 +
22 23 #
23 24 # Energy binning parameters
24 25 #==========================
... ... @@ -27,6 +28,7 @@ emin, r, a, 0.1,,, &quot;Start value for first energy bin in TeV&quot;
27 28 emax, r, a, 100.0,,, "Stop value for last energy bin in TeV"
28 29 enumbins, i, a, 20,,, "Number of energy bins"
29 30 ebinfile, f, a, "NONE",,, "Name of the file containing the energy bin definition"
  31 +
30 32 #
31 33 # Spatial binning parameters
32 34 #===========================
... ... @@ -38,6 +40,7 @@ coordsys, s, a, &quot;CEL&quot;, CEL|GAL,,&quot;Coordinate system (CEL - celestial, GAL - galac
38 40 xref, r, a, 83.63,0,360, "First coordinate of image center in degrees (RA or galactic l)"
39 41 yref, r, a, 22.01,-90,90, "Second coordinate of image center in degrees (DEC or galactic b)"
40 42 proj, s, a, "CAR",AIT|AZP|CAR|MER|MOL|STG|TAN,, "Projection method"
  43 +
41 44 #
42 45 # Standard parameters
43 46 #====================
... ...
src/ctbkgcube/Makefile.am
  View file @14f9d87
... ... @@ -12,6 +12,7 @@ sources = ctbkgcube.cpp
12 12 # Libtool library
13 13 noinst_LTLIBRARIES = libctbkgcube.la
14 14 libctbkgcube_la_SOURCES = $(sources)
  15 +libctbkgcube_la_LDFLAGS = -version-info $(CTOOLS_LT_VERSION) @OPENMP_LIB_LDFLAGS@
15 16  
16 17 # Program definition
17 18 ctbkgcube_SOURCES = main.cpp
... ...
src/ctbkgcube/ctbkgcube.cpp
  View file @14f9d87
... ... @@ -450,6 +450,9 @@ void ctbkgcube::get_parameters(void)
450 450 // Throw exception if no input observation file is given
451 451 require_inobs(G_GET_PARAMETERS);
452 452  
  453 + // Throw exception if counts cube is given
  454 + require_inobs_nocube(G_GET_PARAMETERS);
  455 +
453 456 // Build observation container
454 457 m_obs = get_observations();
455 458  
... ...
src/ctbkgcube/ctbkgcube.par
  View file @14f9d87
... ... @@ -15,15 +15,16 @@
15 15 # #
16 16 #############################################################################
17 17 #
18   -# Observational parameters
  18 +# General parameters
19 19 #===================
20   -inobs, f, a, "NONE",,, "Input event list or observation definition file"
  20 +inobs, f, a, "NONE",,, "Input event list or observation definition XML file"
21 21 inmodel, f, a, "NONE",,, "Input model XML file"
22   -incube, f, a, "NONE",,, "Counts cube for background cube definition"
  22 +incube, f, a, "NONE",,, "Input counts cube file to extract background cube definition"
  23 +caldb, s, a, "prod2",,, "Calibration database"
  24 +irf, s, a, "South_0.5h",,, "Instrument response function"
23 25 outcube, f, a, "bkgcube.fits",,, "Output background cube file"
24 26 outmodel, f, a, "NONE",,, "Output model XML file"
25   -caldb, s, a, "prod2",,, "Calibration database"
26   -irf, s, a, "South_50h",,, "Instrument response function"
  27 +
27 28 #
28 29 # Energy binning parameters
29 30 #==========================
... ... @@ -32,6 +33,7 @@ emin, r, a, 0.1,,, &quot;Lower energy limit (TeV)&quot;
32 33 emax, r, a, 100.0,,, "Upper energy limit (TeV)"
33 34 enumbins, i, a, 20,,, "Number of energy bins"
34 35 ebinfile, f, h, "NONE",,, "Name of the file containing the energy bin definition"
  36 +
35 37 #
36 38 # Spatial binning parameters
37 39 #===========================
... ... @@ -43,6 +45,7 @@ coordsys, s, a, &quot;CEL&quot;, CEL|GAL,,&quot;Coordinate system (CEL - celestial, GAL - galac
43 45 xref, r, a, 83.63,0,360, "First coordinate of image center in degrees (RA or galactic l)"
44 46 yref, r, a, 22.01,-90,90, "Second coordinate of image center in degrees (DEC or galactic b)"
45 47 proj, s, a, "CAR", AIT|AZP|CAR|MER|MOL|STG|TAN,, "Projection method"
  48 +
46 49 #
47 50 # Standard parameters
48 51 #====================
... ...
src/ctbutterfly/Makefile.am
  View file @14f9d87
... ... @@ -12,6 +12,7 @@ sources = ctbutterfly.cpp
12 12 # Libtool library
13 13 noinst_LTLIBRARIES = libctbutterfly.la
14 14 libctbutterfly_la_SOURCES = $(sources)
  15 +libctbutterfly_la_LDFLAGS = -version-info $(CTOOLS_LT_VERSION) @OPENMP_LIB_LDFLAGS@
15 16  
16 17 # Program definition
17 18 ctbutterfly_SOURCES = main.cpp
... ...
src/ctbutterfly/ctbutterfly.cpp
  View file @14f9d87
... ... @@ -241,8 +241,8 @@ void ctbutterfly::run(void)
241 241 log << m_obs << std::endl;
242 242 }
243 243  
244   - // If refit is selected then do maximum likelihood fit
245   - if (m_refit) {
  244 + // If fit is selected then do maximum likelihood fit
  245 + if (m_fit) {
246 246  
247 247 // Write header
248 248 if (logTerse()) {
... ... @@ -267,14 +267,14 @@ void ctbutterfly::run(void)
267 267 log << m_covariance << std::endl;
268 268 }
269 269  
270   - } // endif: refit selected
  270 + } // endif: fit selected
271 271  
272 272 // Get model instance for further computations
273 273 GModels models = m_obs.models();
274 274  
275   - // If no refit is selected and no covariance matrix has been specified
  275 + // If no fit is selected and no covariance matrix has been specified
276 276 // then compute now the covariance matrix
277   - if (!m_refit && m_covariance.size() == 0) {
  277 + if (!m_fit && m_covariance.size() == 0) {
278 278  
279 279 // Write header
280 280 if (logTerse()) {
... ... @@ -542,7 +542,7 @@ void ctbutterfly::init_members(void)
542 542 m_confidence = 0.68;
543 543 m_max_iter = 50;
544 544 m_apply_edisp = false;
545   - m_refit = false;
  545 + m_fit = false;
546 546 m_ebounds.clear();
547 547 m_outfile.clear();
548 548  
... ... @@ -576,7 +576,7 @@ void ctbutterfly::copy_members(const ctbutterfly&amp; app)
576 576 m_confidence = app.m_confidence;
577 577 m_max_iter = app.m_max_iter;
578 578 m_apply_edisp = app.m_apply_edisp;
579   - m_refit = app.m_refit;
  579 + m_fit = app.m_fit;
580 580 m_ebounds = app.m_ebounds;
581 581 m_outfile = app.m_outfile;
582 582  
... ... @@ -668,7 +668,7 @@ void ctbutterfly::get_parameters(void)
668 668  
669 669 // Read other parameters
670 670 m_confidence = (*this)["confidence"].real();
671   - m_refit = (*this)["refit"].boolean();
  671 + m_fit = (*this)["fit"].boolean();
672 672  
673 673 // Optionally read ahead parameters so that they get correctly
674 674 // dumped into the log file
... ...
src/ctbutterfly/ctbutterfly.hpp
  View file @14f9d87
... ... @@ -93,7 +93,7 @@ protected:
93 93 double m_confidence; //!< Confidence level
94 94 int m_max_iter; //!< Maximum number of iterations
95 95 bool m_apply_edisp; //!< Apply energy dispersion?
96   - bool m_refit; //!< Do refit?
  96 + bool m_fit; //!< Do fit?
97 97 GEbounds m_ebounds; //!< Energy binning definition
98 98 std::string m_outfile; //!< Output ascii file
99 99  
... ...
src/ctbutterfly/ctbutterfly.par
  View file @14f9d87
... ... @@ -17,17 +17,21 @@
17 17 #
18 18 # General parameters
19 19 #===================
20   -inobs, f, a, "events.fits",,,"Input event list, counts cube or observation definition file"
21   -inmodel, f, a, "$CTOOLS/share/models/crab.xml",,, "Source model"
  20 +inobs, f, a, "events.fits",,,"Input event list, counts cube or observation definition XML file"
  21 +inmodel, f, a, "$CTOOLS/share/models/crab.xml",,, "Input model XML file"
22 22 srcname, s, a, "Crab",,,"Source of interest"
23   -expcube, f, a, "NONE",,, "Exposure cube file (only needed for stacked analysis)"
24   -psfcube, f, a, "NONE",,, "PSF cube file (only needed for stacked analysis)"
25   -bkgcube, f, a, "NONE",,, "Background cube file (only needed for stacked analysis)"
  23 +expcube, f, a, "NONE",,, "Input exposure cube file (only needed for stacked analysis)"
  24 +psfcube, f, a, "NONE",,, "Input PSF cube file (only needed for stacked analysis)"
  25 +bkgcube, f, a, "NONE",,, "Input background cube file (only needed for stacked analysis)"
26 26 caldb, s, a, "prod2",,, "Calibration database"
27   -irf, s, a, "South_50h",,, "Instrument response function"
  27 +irf, s, a, "South_0.5h",,, "Instrument response function"
28 28 edisp, b, h, no,,, "Apply energy dispersion?"
29   -outfile, f, a, "butterfly.txt",,, "Output ascii file"
30   -refit, b, h, no,,, "Do refitting?"
  29 +outfile, f, a, "butterfly.txt",,, "Output ASCII file"
  30 +
  31 +#
  32 +# Butterfly parameters
  33 +#=====================
  34 +fit, b, h, no,,, "Perform maximum likelihood fitting?"
31 35 confidence, r, h, 0.68,0.0,1.0, "Confidence level"
32 36 matrix, f, h, "NONE",,, "Input covariance Matrix FITS file"
33 37  
... ...
src/ctcubemask/Makefile.am
  View file @14f9d87
... ... @@ -12,6 +12,7 @@ sources = ctcubemask.cpp
12 12 # Libtool library (only needed for python bindings)
13 13 noinst_LTLIBRARIES = libctcubemask.la
14 14 libctcubemask_la_SOURCES = $(sources)
  15 +libctcubemask_la_LDFLAGS = -version-info $(CTOOLS_LT_VERSION) @OPENMP_LIB_LDFLAGS@
15 16  
16 17 # Program definition
17 18 ctcubemask_SOURCES = main.cpp
... ...
src/ctcubemask/ctcubemask.cpp
  View file @14f9d87
... ... @@ -221,7 +221,7 @@ void ctcubemask::run(void)
221 221 // Write observation(s) into logger
222 222 if (logTerse()) {
223 223 log << std::endl;
224   - log.header1("Observations for applying mask");
  224 + log.header1("Observations");
225 225 log << m_obs << std::endl;
226 226 }
227 227  
... ... @@ -349,20 +349,19 @@ void ctcubemask::save(void)
349 349 ***************************************************************************/
350 350 void ctcubemask::get_parameters(void)
351 351 {
  352 + // Initialise selection flags
  353 + m_select_energy = true;
  354 + m_select_roi = true;
  355 +
352 356 // If there are no observations in container then load them via user
353 357 // parameters
354 358 if (m_obs.size() == 0) {
355 359  
356   - // Throw exception if no infile is given
357   - if ((*this)["inobs"].filename() == "NONE" ||
358   - (*this)["inobs"].filename() == "") {
359   - std::string msg = "A valid file needs to be specified for the "
360   - "\"inobs\" parameter, yet \""+
361   - (*this)["inobs"].filename()+"\" was given."
362   - " Specify a vaild observation definition or "
363   - "event list FITS file to proceed.";
364   - throw GException::invalid_value(G_GET_PARAMETERS, msg);
365   - }
  360 + // Throw exception if no input observation file is given
  361 + require_inobs(G_GET_PARAMETERS);
  362 +
  363 + // Throw exception if event list is given
  364 + require_inobs_nolist(G_GET_PARAMETERS);
366 365  
367 366 // Build observation container without response (not needed)
368 367 m_obs = get_observations(false);
... ... @@ -373,13 +372,36 @@ void ctcubemask::get_parameters(void)
373 372 m_regfile = (*this)["regfile"].filename();
374 373 m_usepnt = (*this)["usepnt"].boolean();
375 374 if (!m_usepnt) {
376   - m_ra = (*this)["ra"].real();
377   - m_dec = (*this)["dec"].real();
  375 +
  376 + // Check RA/DEC parameters for validity to read
  377 + if ((*this)["ra"].is_valid() && (*this)["dec"].is_valid()) {
  378 + m_ra = (*this)["ra"].real();
  379 + m_dec = (*this)["dec"].real();
  380 + m_select_roi = true;
  381 + }
  382 + else {
  383 + m_select_roi = false;
  384 + }
  385 + }
  386 +
  387 + // Check if radius is valid for a RoI selection
  388 + if (m_select_roi && (*this)["rad"].is_valid()) {
  389 + m_rad = (*this)["rad"].real();
378 390 }
379   - m_rad = (*this)["rad"].real();
380   - m_emin = (*this)["emin"].real();
381   - m_emax = (*this)["emax"].real();
382   -
  391 + else {
  392 + m_select_roi = false;
  393 + }
  394 +
  395 + // Check for sanity of energy selection parameters
  396 + if ((*this)["emin"].is_valid() && (*this)["emax"].is_valid()) {
  397 + m_emin = (*this)["emin"].real();
  398 + m_emax = (*this)["emax"].real();
  399 + m_select_energy = true;
  400 + }
  401 + else {
  402 + m_select_energy = false;
  403 + }
  404 +
383 405 // Optionally read ahead parameters so that they get correctly
384 406 // dumped into the log file
385 407 if (read_ahead()) {
... ... @@ -410,11 +432,28 @@ void ctcubemask::apply_mask(GCTAObservation* obs)
410 432 GSkyMap map = cube->map();
411 433 const GEbounds& ebounds = cube->ebounds();
412 434  
  435 + // If no energy selection is required set energy boundaries to cube boundaries
  436 + if (!m_select_energy) {
  437 + m_emin = ebounds.emin().TeV();
  438 + m_emax = ebounds.emax().TeV();
  439 + }
  440 +
413 441 // Initialise energy selection
  442 + int npix = map.npix();
414 443 int n_ebin = ebounds.size();
415 444 int e_idx1 = 0;
416 445 int e_idx2 = n_ebin;
417 446  
  447 + // Determine number of events before masking
  448 + double sum_before = 0.0;
  449 + for (int i = 0; i < n_ebin; ++i) {
  450 + for (int pixel = 0; pixel < npix; ++pixel) {
  451 + if (map(pixel, i) >= 0.0) {
  452 + sum_before += map(pixel, i);
  453 + }
  454 + }
  455 + }
  456 +
418 457 // Loop over ebounds to find the first valid energy band
419 458 for (int i = 0; i < n_ebin; ++i) {
420 459 double emin = ebounds.emin(i).TeV() + 1.0e-6; // Rounding tolerance
... ... @@ -434,7 +473,6 @@ void ctcubemask::apply_mask(GCTAObservation* obs)
434 473 }
435 474  
436 475 // Set all pixels outside the desired energy bands to -1.0
437   - int npix = map.npix();
438 476 for (int i = 0; i < e_idx1; ++i) {
439 477 for (int pixel = 0; pixel < npix; ++pixel) {
440 478 map(pixel,i) = -1.0;
... ... @@ -455,24 +493,26 @@ void ctcubemask::apply_mask(GCTAObservation* obs)
455 493 }
456 494  
457 495 // Set all pixels inside selected energy bands but outside ROI
458   - // to -1.0
459   - GSkyRegionCircle roi(m_ra, m_dec, m_rad);
460   - for (int i = e_idx1; i <= e_idx2; ++i) {
461   - for (int pixel = 0; pixel < npix; ++pixel) {
462   - GSkyDir dir = map.inx2dir(pixel);
463   - if (!roi.contains(dir)) {
464   - map(pixel,i) = -1.0;
  496 + // to -1.0 if requested
  497 + if (m_select_roi) {
  498 + GSkyRegionCircle roi(m_ra, m_dec, m_rad);
  499 + for (int i = e_idx1; i <= e_idx2; ++i) {
  500 + for (int pixel = 0; pixel < npix; ++pixel) {
  501 + GSkyDir dir = map.inx2dir(pixel);
  502 + if (!roi.contains(dir)) {
  503 + map(pixel,i) = -1.0;
  504 + }
465 505 }
466 506 }
467   - }
468 507  
469   - // Log selected energy band
470   - if (logTerse()) {
471   - log << gammalib::parformat("Selected ROI");
472   - log << "RA=" << m_ra << " deg, ";
473   - log << "DEC=" << m_dec << " deg, ";
474   - log << "Radius=" << m_rad << " deg";
475   - log << std::endl;
  508 + // Log selected energy band
  509 + if (logTerse()) {
  510 + log << gammalib::parformat("Selected ROI");
  511 + log << "RA=" << m_ra << " deg, ";
  512 + log << "DEC=" << m_dec << " deg, ";
  513 + log << "Radius=" << m_rad << " deg";
  514 + log << std::endl;
  515 + }
476 516 }
477 517  
478 518 // Set all pixels inside selected energy bands and inside exclusion
... ... @@ -503,6 +543,24 @@ void ctcubemask::apply_mask(GCTAObservation* obs)
503 543 }
504 544 }
505 545  
  546 + // Determine number of events after masking
  547 + double sum_after = 0.0;
  548 + for (int i = 0; i < n_ebin; ++i) {
  549 + for (int pixel = 0; pixel < npix; ++pixel) {
  550 + if (map(pixel, i) >= 0.0) {
  551 + sum_after += map(pixel, i);
  552 + }
  553 + }
  554 + }
  555 +
  556 + // Dump number of events before and after masking
  557 + if (logTerse()) {
  558 + log << gammalib::parformat("Events before masking");
  559 + log << sum_before << std::endl;
  560 + log << gammalib::parformat("Events after masking");
  561 + log << sum_after << std::endl;
  562 + }
  563 +
506 564 // Put back map into the event cube
507 565 cube->map(map);
508 566  
... ... @@ -538,6 +596,8 @@ void ctcubemask::init_members(void)
538 596 // Initialise protected members
539 597 m_obs.clear();
540 598 m_infiles.clear();
  599 + m_select_energy = true;
  600 + m_select_roi = true;
541 601  
542 602 // Return
543 603 return;
... ... @@ -563,8 +623,10 @@ void ctcubemask::copy_members(const ctcubemask&amp; app)
563 623 m_emax = app.m_emax;
564 624  
565 625 // Copy protected members
566   - m_obs = app.m_obs;
567   - m_infiles = app.m_infiles;
  626 + m_obs = app.m_obs;
  627 + m_infiles = app.m_infiles;
  628 + m_select_energy = app.m_select_energy;
  629 + m_select_roi = app.m_select_roi;
568 630  
569 631 // Return
570 632 return;
... ...
src/ctcubemask/ctcubemask.hpp
  View file @14f9d87
... ... @@ -90,8 +90,10 @@ protected:
90 90 double m_emax; //!< Upper energy
91 91  
92 92 // Protected members
93   - GObservations m_obs; //!< Observations container
94   - std::vector<std::string> m_infiles; //!< Input event filenames
  93 + GObservations m_obs; //!< Observations container
  94 + std::vector<std::string> m_infiles; //!< Input event filenames
  95 + bool m_select_energy; //!< Perform energy selection
  96 + bool m_select_roi; //!< Perform ROI selection
95 97 };
96 98  
97 99  
... ...