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New Features and Important Changes in ctools 00-08-00
Author(s) : Juergen Knoedlseder
30 October 2014
1. Introduction
---------------
This document briefly summarizes executable by executable the most
important changes made since the last release of ctools.
For all ctools, the public method interface was cleaned up so that
only methods that are really useful for an outside client are
exposed. Low-level methods that are used by the application are now
protected, as improper usage of these methods may lead to
unpredictable results.
The ctool base class has been introduced and all tools now derive
from ctool instead of GApplication. This allows to avoid code
duplications and makes the code generally slimmer and more readable.
2. Configuration
-----------------
None
3. Python interface
-------------------
None
4. Support model
----------------
A support module has been introduced that will contain common classes
and functions. For the moment the only class in this module is the
ctool base class.
5. ctobssim - CTA observation simulation
----------------------------------------
ctobssim was not fully thread save as the models were shared among the
threads which led to concurrent memory access when evaluating the Monte
Carlo cache. The models are now copied within the parallel section,
avoiding concurrent memory access (#1258).
ctobssim now also supports the handling of energy dispersion. Energy
dispersion can be switched on or off using the hidden edisp parameter.
The memory needs for ctobssim have been reduced by first working on a
local copy of the CTA observation (this de-allocates properly and memory
cache associated to the response functions), and by saving and disposing
the event lists immediately if called using the execute() method (this
is the method called when the tool is run from the command line).
6. ctselect - CTA event selection
---------------------------------
The temporary file is now properly close to avoid file opening errors
when iterating over ctselect (#1149).
Non-CTA time references are now correctly handled by ctselect. While the
tmin and tmax parameters are given in CTA reference time, they are
internally converted to the reference time of the GTI before event
selection (#1329).
7. ctbin - CTA event binning
----------------------------
WARNING: The philosophy behind the ctbin tool changed fundamentally!
ctbin now always produces a single counts cube on output. If a single
event list is specified on input, the functionnality is basically
unchanged. If multiple event lists are specified, however, events are
now merged into a single counts cube file. No observation definition
XML file is written anymore!
So far, ctbin still writes pointing information in the counts cube,
although this is not necessarily meaningful if merging event lists
with different pointings. In the long run, pointing information will
be summarized in a pointings definition file, and will be removed
from the counts cube header. The logic is that the pointing definition
is set to the map centre. This is only identical to the pointing in
case of binning a single event list and using the usepnt=yes option
(or specifying the pointing manually as the xref and yref parameters).
Memory usage has been reduced by disposing the event lists after their
usage.
8. ctlike - Maximum likelihood fitting
--------------------------------------
ctlike now has full access to the calibration database, allowing
the use for 2D response functions in FITS files.
ctlike now also supports the handling of energy dispersion. Energy
dispersion can be switched on or off using the hidden edisp parameter.
9. cttsmap - Generation of Test Statistics map
----------------------------------------------
The cttsmap tool has been added that provides a test statistics map
for a given set of observations. This tool is not restricted to CTA
data and will work for all types of instruments.
cttsmap will move a test sources over a specified grid of positions
and compute the likelihood difference between having the source at
a given position and having not the source. Twice the likelihood
difference is called the Test Statistic. The computation is done for
a grid of positions, and the results is saved into a FITS file as
TS map. Also the value of the fitted parameters are stored as
extension in the FITS file.
10. ctskymap - CTA sky mapping
------------------------------
None
11. ctmodel - CTA counts cube modelling
---------------------------------------
WARNING: The philosophy behind the ctmodel tool changed fundamentally!
ctmodel now always produces a single model cube on output. There are
two important input parameters: "infile" and "obsfile". "infile"
specifies a counts or model cube that is used to define the binning
of the model cube. The functionnality for this parameter is as before.
If "infile=NONE", the cube will be defined according to task parameters
that specify the spatial and the energy binning. The "obsfile"
parameter is new and allows specifying the observation definition
for which the model cube should be computed. If an event list or a
counts cube is presented, the pointing and Good Time Intervals will
be extracted from the FITS file header. If an observation definition
XML file is presented, ctmodel will now loop over all CTA observations
in the file and add the model values to the model cube. If no
response information is associated to the "obsfile" (which is typically
the case for event lists or counts cubes), the "caldb" and "irf"
parameters will be used to identify the response.
ctmodel now has full access to the calibration database, allowing
the use for 2D response functions in FITS files.
ctmodel now also supports the handling of energy dispersion. Energy
dispersion can be switched on or off using the hidden edisp parameter.
Memory usage has been reduced by disposing the event lists after their
usage.
12. ctexpcube - CTA exposure cube generation
--------------------------------------------
The first version of the ctexpcube tool is included in the release.
ctexpcube computes the exposure cube for an observation definition
file. The cube definition may be taken from a counts cube or may be
specified by user parameters.
13. ctpsfcube - CTA point spread function cube generation
---------------------------------------------------------
The first version of the ctpsfcube tool is included in the release.
ctpsfcube computes the point spread function cube for an observation
definition file. The cube definition may be taken from a counts cube
or may be specified by user parameters.
14. ctbkgcube - CTA background cube generation
----------------------------------------------
The first version of the ctbkgcube tool is included in the release.
ctbkgcube computes the background cube for an observation definition
file. The cube definition may be taken from a counts cube or may be
specified by user parameters. The tools also updates the input model
by replacing all IACT background model components by a single
background cube background model with a power law as spectral
parameter. The model container is available to Python using the
models() method or can be written into an XML file on disk.
15. ctcubemask - CTA cube filtering
-----------------------------------
The first version of the ctcubemask tool is included in the release.
ctcubemask allows filtering of bins in a counts cube by setting the
bin content to -1. Filtering can be done by energy, for a circular
Region of Interest (ROI) or using ds9 exclusion regions.
16. ctbutterfly - Generate butterfly diagrams
=============================================
The first version of the ctbutterfly tool is included in the release.
This tools derives a butterfly diagram from the fitted model parameters
for one specified source. The result will be written into an ASCII
file.
17. Examples
------------
Added the following example scripts:
* pipeline_stacked.py (simulation and stacked analysis)
18. Scripts
-----------
Add logL and event statistics to cspull output file.
Convert all tabs into spaces.
The obsutils script has now been moved into the ctools module namespace.
The following functions have been added to obsutils:
* set_obs() replaces the now obsolete set() function
* set_obs_list() returns an observation container filled with a list of
observations
* set_obs_patterns() defines standard patterns of CTA observations.
Current options are:
- "single": single pointing
- "four": four pointings offset by specific angle around centre
* spectrum() generates spectral points by fitting a source model in
specified energy bins.
Add the csresmap script that uses ctbin and ctmodel to generate a
residual counts cube for a given model.
19. caldb
---------
None
20. models
----------
None