diff --git a/examples/sensitivity_pull.py b/examples/sensitivity_pull.py
deleted file mode 100755
index 5de9bda..0000000
--- a/examples/sensitivity_pull.py
+++ /dev/null
@@ -1,208 +0,0 @@
-#! /usr/bin/env python
-# ==========================================================================
-# This script generates pull distributions for a source at the 5 sigma
-# sensitivity limit. The script makes use of the "processing" Python module,
-# if available, that can be used for parallel computing on multiple
-# cores/CPUs.
-#
-# Required 3rd party modules:
-# - processing (optional)
-#
-# Copyright (C) 2011 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
-# the Free Software Foundation, either version 3 of the License, or
-# (at your option) any later version.
-#
-# This program is distributed in the hope that it will be useful,
-# but WITHOUT ANY WARRANTY; without even the implied warranty of
-# MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the
-# GNU General Public License for more details.
-#
-# You should have received a copy of the GNU General Public License
-# along with this program.  If not, see <http://www.gnu.org/licenses/>.
-#
-# ==========================================================================
-from ctatools import *
-from gammalib import *
-from cspull import *
-import sys
-import time
-
-# Try importing processing module
-has_processing = False
-try:
-	import processing
-	has_processing = True
-except:
-	pass
-
-
-# ======================== #
-# Create pull distribution #
-# ======================== #
-def create_pull(loge, emin, emax, models, ntrials=100, duration=180000.0, \
-                enumbins=0, log=False):
-	"""
-	Create pull distribution
-	
-	Parameters:
-	 emin - Minimum energy (TeV)
-	 emax - Maximum energy (TeV)
-	Keywords:
-	 log  - Create log file(s)
-	"""
-	# Generate output filename
-	outfile = "pull_"+loge+".dat"
-	
-	# Setup cspull tool
-	pull = cspull()
-	pull.models(models)
-	pull["outfile"]  = outfile
-	pull["ntrials"]  = ntrials
-	pull["caldb"]    = "$GAMMALIB/share/caldb/cta"
-	pull["irf"]      = "kb_E_50h_v3"
-	pull["ra"]       = 83.6331
-	pull["dec"]      = 22.0145
-	pull["emin"]     = emin
-	pull["emax"]     = emax
-	pull["enumbins"] = enumbins
-	pull["duration"] = duration
-		
-	# Optionally open the log file
-	if log:
-		pull.logFileOpen()
-	
-	# Run tool
-	pull.run()
-	
-	# Return
-	return
-
-
-# ============ #
-# Create model #
-# ============ #
-def create_model(flux, index=-2.48, fitidx=False):
-	"""
-	Add standard CTA background model to observations container.
-	We use a simple power law here, scaled to Konrad's E configuration
-	performance table.
-
-	Parameters:
-	 flux - Flux in Crab units
-	"""
-	# Define background model
-	bgd_radial   = GCTAModelRadialGauss(3.0)
-	bgd_spectrum = GModelSpectralPlaw(61.8, -1.85)
-	bgd_spectrum["Prefactor"].scale(1.0e-6)
-	bgd_spectrum["PivotEnergy"].value(1.0)
-	bgd_spectrum["PivotEnergy"].scale(1.0e6)
-	if fitidx:
-		bgd_spectrum["Index"].free()
-	else:
-		bgd_spectrum["Index"].fix()
-	bgd_model = GCTAModelRadialAcceptance(bgd_radial, bgd_spectrum)
-	bgd_model.name("Background")
-	bgd_model.instruments("CTA")
-	
-	# Define source spectrum
-	location = GSkyDir()
-	location.radec_deg(83.6331, 22.0145)
-	src_spatial  = GModelSpatialPtsrc(location)
-	src_spectrum = GModelSpectralPlaw(flux, index)
-	src_spectrum["Prefactor"].scale(5.7e-16)
-	src_spectrum["PivotEnergy"].value(0.3)
-	src_spectrum["PivotEnergy"].scale(1.0e6)
-	if fitidx:
-		src_spectrum["Index"].free()
-	else:
-		src_spectrum["Index"].fix()	
-	src_model = GModelPointSource(src_spatial, src_spectrum)
-	src_model.name("Test")
-
-	# Add models to container
-	models = GModels()
-	models.append(bgd_model)
-	models.append(src_model)
-	
-	# Return model container
-	return models
-
-
-# ======================== #
-# Main routine entry point #
-# ======================== #
-if __name__ == '__main__':
-	"""
-	Create pull distributions for the energy bands and fluxes given in the
-	file specified in the argument
-	"""
-	# Get input arguments
-	usage = "sensitivity_pull filename [max_threads]"
-	if len(sys.argv) < 2 or len(sys.argv) > 3:
-		print usage
-		sys.exit()
-
-	# Get sensitivity file
-	filename = sys.argv[1]
-	
-	# Set maximum number of threads
-	if len(sys.argv) > 2:
-		max_threads = int(sys.argv[2])
-	else:
-		max_threads = 1
-	
-	# Load sensitivity file
-	file = open(filename, 'r')
-	reader = csv.DictReader(file)
-	
-	# Loop over rows
-	for row in reader:
-	
-		# Get parameters
-		loge = float(row['loge'])
-		if loge < 0:
-			loge = "m"+str(abs(loge))
-		else:
-			loge = "p"+str(abs(loge))
-		emin = float(row['emin'])
-		emax = float(row['emax'])
-		flux = float(row['crab'])
-		
-		# Generate model
-		models = create_model(flux)
-
-		# Processing support?
-		if has_processing:
-
-			# Wait until one thread has finished
-			while len(processing.activeChildren()) >= max_threads:
-				time.sleep(60)
-
-			# Set arguments
-			args   = (loge, emin, emax, models)
-			kwargs = {}
-
-			# Generate pull distribution
-			p = processing.Process(target=create_pull, args=args, kwargs=kwargs)
-			p.start()
-			print "Process emin=%.4f emax=%.4f started." % (emin, emax)
-
-			# Wait some time
-			time.sleep(1)
-		
-		# ... no
-		else:
-			create_pull(loge, emin, emax, models)
-	
-	# Processing support
-	if has_processing:
-	
-		# Wait until all threads finished
-		while len(processing.activeChildren()) > 0:
-			time.sleep(60)
-
-	# Close file
-	file.close()