Veronika Vodeb / ctools

Commit 892c9f419f6168faa5c8bd92ba39d0624acccbda

Authored by Jürgen Knödlseder 2014-07-24 23:55:43 +0200

Add stacked cube analysis script.

The purpose of the make_cube_analysis.py script is to provide an end-to-end test fur stacked cube analysis. It uses 4 CTA observations to illustrate the usage of stacked cube analysis and to demonstrate that the fitting results are okay.

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	1	+#! /usr/bin/env python
	2	+# ==========================================================================
	3	+# This script illustrates how to perform a stacked cube analysis.
	4	+#
	5	+# Copyright (C) 2014 Juergen Knoedlseder
	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 ctools
	22	+import gammalib
	23	+
	24	+
	25	+# ================= #
	26	+# Analysis pipeline #
	27	+# ================= #
	28	+def pipeline(caldb = "dummy", \
	29	+ irf = "cta_dummy_irf", \
	30	+ model = "$CTOOLS/share/models/crab.xml"):
	31	+ """
	32	+ Analysis pipeline for a stacked cube analysis. The pipeline writes
	33	+ intermediate results to FITS files on disk. Also log files of all
	34	+ individual ctools will be written.
	35	+
	36	+ Keywords:
	37	+ caldb - Calibration database repository
	38	+ irf - Name of instrument response
	39	+ model - Source model
	40	+ """
	41	+ # Set pointing pattern (4 pointings)
	42	+ pointings = ctools.obsutils.set_obs_patterns("four", offset=2.0)
	43	+
	44	+ # Set CTA observations (default: 1800 sec per pointing)
	45	+ obs = ctools.obsutils.set_obs_list(pointings, caldb=caldb, irf=irf)
	46	+
	47	+ # Load models
	48	+ models = gammalib.GModels(model)
	49	+ obs.models(models)
	50	+
	51	+ # Run ctobssim (simulates 4 event lists)
	52	+ sim = ctools.ctobssim(obs)
	53	+ sim.logFileOpen()
	54	+ sim.run()
	55	+
	56	+ # Run ctbin (builds stacked event cube)
	57	+ bin = ctools.ctbin(sim.obs())
	58	+ bin.logFileOpen()
	59	+ bin["outfile"].filename("cntmap.fits")
	60	+ bin["ebinalg"].string("LOG")
	61	+ bin["emin"].real(0.1)
	62	+ bin["emax"].real(100.0)
	63	+ bin["enumbins"].integer(20)
	64	+ bin["usepnt"].boolean(False)
	65	+ bin["nxpix"].integer(300)
	66	+ bin["nypix"].integer(300)
	67	+ bin["binsz"].real(0.02)
	68	+ bin["coordsys"].string("CEL")
	69	+ bin["proj"].string("CAR")
	70	+ bin["xref"].real(83.6331)
	71	+ bin["yref"].real(22.0145)
	72	+ bin.execute()
	73	+
	74	+ # Run ctexpcube (builds exposure cube)
	75	+ expcube = ctools.ctexpcube(sim.obs())
	76	+ expcube.logFileOpen()
	77	+ expcube["cntmap"].filename("cntmap.fits")
	78	+ expcube["outfile"].filename("expcube.fits")
	79	+ expcube["caldb"].string(caldb)
	80	+ expcube["irf"].string(irf)
	81	+ expcube.execute()
	82	+
	83	+ # Run ctpsfcube (builds PSF cube)
	84	+ psfcube = ctools.ctpsfcube(sim.obs())
	85	+ psfcube.logFileOpen()
	86	+ psfcube["cntmap"].filename("NONE")
	87	+ psfcube["outfile"].filename("psfcube.fits")
	88	+ psfcube["caldb"].string(caldb)
	89	+ psfcube["irf"].string(irf)
	90	+ psfcube["ebinalg"].string("LOG")
	91	+ psfcube["emin"].real(0.1)
	92	+ psfcube["emax"].real(100.0)
	93	+ psfcube["enumbins"].integer(20)
	94	+ psfcube["nxpix"].integer(5)
	95	+ psfcube["nypix"].integer(5)
	96	+ psfcube["binsz"].real(2.0)
	97	+ psfcube["coordsys"].string("CEL")
	98	+ psfcube["proj"].string("CAR")
	99	+ psfcube["xref"].real(83.6331)
	100	+ psfcube["yref"].real(22.0145)
	101	+ psfcube["amax"].real(0.3)
	102	+ psfcube["anumbins"].integer(60)
	103	+ psfcube.execute()
	104	+
	105	+ # Run ctbkgcube (builds background cube)
	106	+ bkgcube = ctools.ctbkgcube(sim.obs())
	107	+ bkgcube.logFileOpen()
	108	+ bkgcube["cntmap"].filename("cntmap.fits")
	109	+ bkgcube["bkgmdl"].filename(model)
	110	+ bkgcube["outfile"].filename("bkgcube.fits")
	111	+ bkgcube.execute()
	112	+
	113	+ # Create observation container for stacked cube analysis
	114	+ obs.clear()
	115	+ cta = gammalib.GCTAObservation("cntmap.fits", "expcube.fits", "psfcube.fits")
	116	+ obs.append(cta)
	117	+
	118	+ # Create model for stacked cube analysis
	119	+ models = gammalib.GModels(model)
	120	+ models.remove("Background")
	121	+ spatial = gammalib.GModelSpatialDiffuseCube("bkgcube.fits")
	122	+ spectral = gammalib.GModelSpectralConst()
	123	+ background = gammalib.GCTAModelCubeBackground(spatial, spectral)
	124	+ models.append(background)
	125	+ models.save("cube_model.xml")
	126	+
	127	+ # Append model to observation container
	128	+ obs.models(models)
	129	+
	130	+ # Run ctlike
	131	+ like = ctools.ctlike(obs)
	132	+ like.logFileOpen()
	133	+ like["debug"].boolean(True)
	134	+ like["outmdl"].filename("cube_results.xml")
	135	+ like.execute()
	136	+
	137	+ # Return
	138	+ return
	139	+
	140	+
	141	+#==========================#
	142	+# Main routine entry point #
	143	+#==========================#
	144	+if __name__ == '__main__':
	145	+ """
	146	+ """
	147	+ # Dump header
	148	+ print("*************************************")
	149	+ print("* CTA stacked cube analysis *")
	150	+ print("*************************************")
	151	+
	152	+ # Run pipeline
	153	+ pipeline()
	154	+
0	155	\ No newline at end of file
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