From 557ef70ec55523369fd1759a77e76ae4ffd61ed4 Mon Sep 17 00:00:00 2001
From: knodlseder <>
Date: Thu, 24 Feb 2011 00:30:52 +0000
Subject: [PATCH] initial version

---
 test/example_models.py | 128 ++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++
 1 file changed, 128 insertions(+), 0 deletions(-)
 create mode 100755 test/example_models.py

diff --git a/test/example_models.py b/test/example_models.py
new file mode 100755
index 0000000..a05bc9f
--- /dev/null
+++ b/test/example_models.py
@@ -0,0 +1,128 @@
+#! /usr/bin/env python
+# ===========================================================================================#
+# This script illustrates how to build a unbinned analysis chain using CTAtools.
+# ===========================================================================================#
+from ctatools import *
+from gammalib import *
+from math import *
+import os
+import glob
+import sys
+
+
+# ================= #
+# Analysis pipeline #
+# ================= #
+def pipeline(model_name):
+	"""
+	Unbinned analysis pipeline - keep intermediate results in memory.
+    
+    This function implements an analysis pipeline that successively calls
+    ctobssim, ctselect and ctlike without saving the intermediate results as
+	FITS files on disk. All data is only hold in memory.
+	"""
+	# Set script parameters
+	caldb       = "irf"
+	irf         = "kb_E_50h_v3"
+	ra          =   83.63
+	dec         =   22.01
+	rad_sim     =   10.0
+	tstart      =    0.0
+	tstop       = 1800.0
+	emin        =    0.1
+	emax        =  100.0
+	rad_select  =    3.0
+
+	# Write model name
+	print "Model: "+model_name
+
+	# Initialise timing
+	wall_seconds = 0.0
+	cpu_seconds  = 0.0
+
+	# Simulate events
+	sim = ctobssim()
+	sim["infile"].filename(model_name)
+	sim["caldb"].string(caldb)
+	sim["irf"].string(irf)
+	sim["ra"].real(ra)
+	sim["dec"].real(dec)
+	sim["rad"].real(rad_sim)
+	sim["tmin"].real(tstart)
+	sim["tmax"].real(tstop)
+	sim["emin"].real(emin)
+	sim["emax"].real(emax)
+	sim.run()
+
+	# Select events
+	select = ctselect(sim.obs())
+	select["ra"].real(ra)
+	select["dec"].real(dec)
+	select["rad"].real(rad_select)
+	select["tmin"].real(tstart)
+	select["tmax"].real(tstop)
+	select["emin"].real(emin)
+	select["emax"].real(emax)
+	select.run()
+
+	# Perform maximum likelihood fitting
+	like = ctlike(select.obs())
+	like.run()
+
+	# Show model fitting results
+	print like.obs().models()[0]
+	
+	# Return
+	return
+
+
+#==========================#
+# Main routine entry point #
+#==========================#
+if __name__ == '__main__':
+	"""
+	Perform unbinned analyses for various models.
+	
+	This script implements the analysis steps to perform an unbinned analysis.
+	The steps include:
+	- Event simulation
+	- Event selection
+	- Binned maximum likelihood fitting
+	"""
+	# Initialise flags
+	need_help = False
+	show_data = True
+	
+	# Test for command line arguments
+	print sys.argv[0]
+	if (len(sys.argv) > 1):
+		if sys.argv[1] == "-h":
+			need_help = True
+		elif sys.argv[1] == "-noshow":
+			show_data = False
+		else:
+			need_help = True			
+
+	# Print help if needed and exit
+	if need_help:
+		print "Usage: example_models.py [OPTIONS]"
+		print "     -h       Display this usage message"
+		print "     -noshow  Do not show data using matplotlib"
+		sys.exit()
+
+	# Dump header
+	print "********************************"
+	print "* CTA unbinned analysis script *"
+	print "********************************"
+		
+	# Perform analysis for Crab model
+	pipeline("data/crab.xml")
+
+	# Perform analysis for disk model
+	pipeline("data/disk.xml")
+
+	# Perform analysis for Gaussian model
+	pipeline("data/gauss.xml")
+	
+	# Perform analysis for shell model
+	pipeline("data/shell.xml")
--
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