Use obsutils module and adapt to Python 3.

Jürgen Knödlseder
1 parent 5003e285
Showing 1 changed file with 35 additions and 220 deletions
test/example_survey.py
@@ -3,7 +3,7 @@
 # This script simulates CTA surveys. It can be considered as the master
 # script for CTA science simulations. Please modify as needed.
 #
-# Copyright (C) 2011 Jurgen Knodlseder
+# Copyright (C) 2011-2012 Jurgen Knodlseder
 #
 # This program is free software: you can redistribute it and/or modify
 # it under the terms of the GNU General Public License as published by
@@ -25,6 +25,7 @@ from math import *
 import os
 import glob
 import sys
+import obsutils
 # =========== #
@@ -47,9 +48,9 @@ def plot_counts(obs):
 		styles = ['b-', 'g-', 'y-', 'n-']
 		# Dump header
-		print ""
-		print "Make plots (using matplotlib):"
-		print "=============================="
+		print("")
+		print("Make plots (using matplotlib):")
+		print("==============================")
 		# Create figure 1
 		plt.figure(1,figsize=(12,6))
@@ -63,7 +64,7 @@ def plot_counts(obs):
 		for run in obs:
 			# Get event list
-			list = cast_GCTAEventList(run.events())
+			list = run.events()
 			# Create energy axis
 			ebounds = GEbounds()
@@ -75,9 +76,9 @@ def plot_counts(obs):
 			energy = [ebounds.elogmean(i).TeV() for i in range(ebounds.size())]
 			# Create spectrum
-			print "Extract data:"
+			print("Extract data:")
 			counts = [0.0 for i in range(ebounds.size())]
-			print list.size()
+			print(list.size())
 			for atom in list:
 				index         = ebounds.index(atom.energy())
 				counts[index] = counts[index] + 1.0
@@ -90,10 +91,10 @@ def plot_counts(obs):
 			#plt.errorbar(energy, counts, error, fmt=None, ecolor='r')
 			# Extract models
-			print "Extract models:"
+			print("Extract models:")
 			sum_model = [0.0 for i in range(ebounds.size())]
 			for k, m in enumerate(obs.models()):
-				print "- "+m.name()
+				print("- "+m.name())
 				model = [0.0 for i in range(ebounds.size())]
 				for atom in list:
 					index        = ebounds.index(atom.energy())
@@ -120,11 +121,11 @@ def plot_counts(obs):
 		# Loop over observations
 		for run in obs:
-			# Get event cube
-			list = cast_GCTAEventList(run.events())
+			# Get event list
+			list = run.events()
 			# Create offset histogram
-			print "Extract data:"
+			print("Extract data:")
 			nx       = 30
 			doffset2 = 0.01
 			offset2  = [(i+0.5)*doffset2 for i in range(nx)]
@@ -143,10 +144,10 @@ def plot_counts(obs):
 			#plt.semilogy(offset2, counts, 'ro', label='data')
 			# Extract models
-			print "Extract models:"
+			print("Extract models:")
 			sum_model = [0.0 for i in range(nx)]
 			for k, m in enumerate(obs.models()):
-				print "- "+m.name()
+				print("- "+m.name())
 				model = [0.0 for i in range(nx)]
 				for atom in list:
 					off   = atom.dir().dist_deg(crab)
@@ -170,200 +171,12 @@ def plot_counts(obs):
 		plt.show()
 	except ImportError:
-		print "Matplotlib is not (correctly) installed on your system."
+		print("Matplotlib is not (correctly) installed on your system.")
 	# Return
 	return
-# ===================== #
-# Simulate observations #
-# ===================== #
-def sim_obs(obs):
-	"""
-	Simulate events for all observations in the container.
-	"""
-	# Simulate events
-	sim = ctobssim(obs)
-	sim.logFileOpen()  # We need this to explicitely open the log file in Python mode
-	sim.run()
-	
-	# Extract copy of observations (we need a copy here as sim goes out of
-	# scope once we leave the function)
-	obs = sim.obs().copy()
-	
-	# Return observations
-	return obs
-
-
-# ================ #
-# Fit observations #
-# ================ #
-def fit_obs(obs):
-	"""
-	Perform maximum likelihood fitting of observations.
-	"""
-	# Perform maximum likelihood fitting
-	like = ctlike(obs)
-	like.logFileOpen()  # We need this to explicitely open the log file in Python mode
-	like.run()
-	
-	# Extract copy of observations (we need a copy here as like goes out of
-	# scope once we leave the function)
-	#obs = like.obs().copy()
-	
-	#print like.opt()
-	
-	# Return observations
-	return like
-
-
-# ================= #
-# Create counts map #
-# ================= #
-def make_counts_map(obs):
-	"""
-	Make counts map by combining the events of all observations.
-	"""
-	# Allocate counts map
-	nxpix  = 600
-	nypix  = 200
-	cntmap = GSkymap("CAR", "GAL", 0.0, 0.0, -0.05, 0.05, nxpix, nypix, 1)
-	
-	# Fill all observations
-	for run in obs:
-		
-		# Loop over all events
-		for event in run.events():
-			
-			# Cast to CTA event
-			event = cast_GCTAEventAtom(event)
-			
-			# Determine sky pixel
-			skydir = event.dir().skydir()
-			pixel  = cntmap.dir2pix(skydir)
-			
-			# Set pixel
-			cntmap[pixel] += 1.0
-	
-	# Save sky map
-	cntmap.save("survey_cntmap.fits", True)
-	
-	# Return counts map
-	return cntmap
-
-
-# ================ #
-# Create model map #
-# ================ #
-def make_model_map(obs):
-	"""
-	Make model map by combining all observations. The map will
-	be in units of [counts/(sr MeV s)].
-	"""
-	# Allocate model map
-	nxpix  = 600
-	nypix  = 200
-	modmap = GSkymap("CAR", "GAL", 0.0, 0.0, -0.05, 0.05, nxpix, nypix, 1)
-	
-	# Set energy and time
-	energy  = GEnergy()
-	time    = GTime()
-	instdir = GCTAInstDir()
-	energy.TeV(0.1)
-	
-	# Loop over all map pixels
-	for pixel in range(modmap.npix()):
-		
-		# Get sky direction
-		skydir = modmap.pix2dir(pixel)
-		instdir.skydir(skydir)
-		
-		# Create event atom for map pixel
-		atom = GCTAEventAtom()
-		atom.dir(instdir)
-		atom.energy(energy)
-		atom.time(time)
-		
-		# Initialise model value
-		value = 0.0
-		
-		# Loop over all observations
-		for run in obs:
-			value += obs.models().eval(atom, run)
-		
-		# Set map value
-		modmap[pixel] = value
-	
-	# Save sky map
-	modmap.save("survey_modmap.fits", True)
-	
-	# Return model map
-	return modmap
-
-
-# ======================= #
-# Set one CTA observation #
-# ======================= #
-def set_one_obs(pntdir, tstart=0.0, duration=1800.0, emin=0.1, emax=100.0, rad=3.0, \
-                irf="kb_E_50h_v3", caldb="irf"):
-	"""
-	Parameters:
-	 pntdir   - Pointing direction
-	Keywords:
-	 tstart   - Start time (seconds)
-	 duration - Duration of observation (seconds)
-	 emin     - Minimum event energy (TeV)
-	 emax     - Maximum event energy (TeV)
-	 rad      - ROI radius (deg)
-	 irf      - Instrument response function
-	 caldb    - Calibration database path
-	"""
-	# Allocate CTA observation
-	obs = GCTAObservation()
-	
-	# Set pointing direction
-	pnt    = GCTAPointing()
-	pnt.dir(pntdir)
-	obs.pointing(pnt)
-	
-	# Set ROI
-	roi     = GCTARoi()
-	instdir = GCTAInstDir()
-	instdir.skydir(pntdir)
-	roi.centre(instdir)
-	roi.radius(rad)
-	
-	# Set GTI
-	gti   = GGti()
-	start = GTime()
-	stop  = GTime()
-	start.met(tstart)
-	stop.met(tstart+duration)
-	gti.append(start, stop)
-	
-	# Set energy boundaries
-	ebounds = GEbounds()
-	e_min   = GEnergy()
-	e_max   = GEnergy()
-	e_min.TeV(emin)
-	e_max.TeV(emax)
-	ebounds.append(e_min, e_max)
-
-	# Allocate event list
-	events = GCTAEventList()
-	events.roi(roi)
-	events.gti(gti)
-	events.ebounds(ebounds)
-	obs.events(events)
-	
-	# Set instrument response
-	obs.response(irf, caldb)
-	
-	# Return observation
-	return obs
-
-
 # ======================================== #
 # Add CTA background model to observations #
 # ======================================== #
@@ -428,7 +241,8 @@ def survey_single():
 	# Set single pointing at galactic centre
 	pntdir = GSkyDir()
 	pntdir.lb_deg(0.0, 0.0)
-	run = set_one_obs(pntdir)
+	#run = set_one_obs(pntdir)
+	run = obsutils.set(pntdir)
 	obs.append(run)
 	# Define single point source with Crab flux at galactic centre
@@ -468,7 +282,8 @@ def survey_gplane(lrange=10, lstep=2):
 		# Set pointing
 		pntdir = GSkyDir()
 		pntdir.lb_deg(l, 0.0)
-		run = set_one_obs(pntdir)
+		#run = set_one_obs(pntdir)
+		run = obsutils.set(pntdir)
 		obs.append(run)
 	# Define single point source with Crab flux at galactic centre
@@ -499,7 +314,7 @@ if __name__ == &#39;__main__&#39;:
 	need_help = False
 	# Test for command line arguments
-	print sys.argv[0]
+	print(sys.argv[0])
 	if (len(sys.argv) > 1):
 		if sys.argv[1] == "-h":
 			need_help = True
@@ -508,14 +323,14 @@ if __name__ == &#39;__main__&#39;:
 	# Print help if needed and exit
 	if need_help:
-		print "Usage: example_survey.py [OPTIONS]"
-		print "     -h       Display this usage message"
+		print("Usage: example_survey.py [OPTIONS]")
+		print("     -h       Display this usage message")
 		sys.exit()
 	# Dump header
-	print "**********************"
-	print "* Simulate CTA survey *"
-	print "**********************"
+	print("***********************")
+	print("* Simulate CTA survey *")
+	print("***********************")
 	# Remove any existing result files
 	list = [glob.glob("*.fits"), glob.glob("*.log"), glob.glob("*.xml")]
@@ -524,29 +339,29 @@ if __name__ == &#39;__main__&#39;:
 			os.remove(file)
 	# Setup single observation survey
-	obs = survey_single()
+	#obs = survey_single()
 	obs = survey_gplane()
 	# Add background model
 	obs = add_background_model(obs)
 	# Simulate events
-	print "Simulate events"
-	obs = sim_obs(obs)
+	print("Simulate events")
+	obs = obsutils.sim(obs)
 	# Make counts map
-	print "Make counts map"
-	cntmap = make_counts_map(obs)
+	print("Make counts map")
+	cntmap = obsutils.cntmap(obs)
 	# Fit observations
-	print "Fit observatins"
-	like = fit_obs(obs)
+	print("Fit observatins")
+	like = obsutils.fit(obs)
 	#print like.opt()
 	#print like.obs().models()
 	# Make model map
-	print "Make model map (this step will take some time)"
-	modmap = make_model_map(obs)
+	print("Make model map (this step will take some time)")
+	modmap = obsutils.modmap(obs)
 	# Show fit results
 	#plot_counts(like.obs())