diff --git a/examples/make_binned_analysis.py b/examples/make_binned_analysis.py
index 6cc0b3c..cd1d174 100755
--- a/examples/make_binned_analysis.py
+++ b/examples/make_binned_analysis.py
@@ -73,8 +73,8 @@ def pipeline_v1():
     # Simulate events
     sim = ctools.ctobssim()
     sim.logFileOpen()  # We need this to explicitely open the log file in Python mode
-    sim["infile"].filename(model_name)
-    sim["outfile"].filename(events_name)
+    sim["inmodel"].filename(model_name)
+    sim["outevents"].filename(events_name)
     sim["caldb"].string(caldb)
     sim["irf"].string(irf)
     sim["ra"].real(ra)
@@ -94,8 +94,8 @@ def pipeline_v1():
     # Bin events into counts map
     bin = ctools.ctbin()
     bin.logFileOpen()  # We need this to explicitely open the log file in Python mode
-    bin["evfile"].filename(events_name)
-    bin["outfile"].filename(cntmap_name)
+    bin["inobs"].filename(events_name)
+    bin["outcube"].filename(cntmap_name)
     bin["ebinalg"].string("LOG")
     bin["emin"].real(emin)
     bin["emax"].real(emax)
@@ -117,9 +117,9 @@ def pipeline_v1():
     # Perform maximum likelihood fitting
     like = ctools.ctlike()
     like.logFileOpen()  # We need this to explicitely open the log file in Python mode
-    like["infile"].filename(cntmap_name)
-    like["srcmdl"].filename(model_name)
-    like["outmdl"].filename(result_name)
+    like["inobs"].filename(cntmap_name)
+    like["inmodel"].filename(model_name)
+    like["outmodel"].filename(result_name)
     like["caldb"].string(caldb)
     like["irf"].string(irf)
     like.execute()
@@ -174,7 +174,7 @@ def pipeline_v2():
 
     # Simulate events
     sim = ctools.ctobssim()
-    sim["infile"].filename(model_name)
+    sim["inmodel"].filename(model_name)
     sim["caldb"].string(caldb)
     sim["irf"].string(irf)
     sim["ra"].real(ra)
diff --git a/examples/make_cube_analysis.py b/examples/make_cube_analysis.py
index b164e5e..f5d104c 100755
--- a/examples/make_cube_analysis.py
+++ b/examples/make_cube_analysis.py
@@ -20,6 +20,7 @@
 # ==========================================================================
 import ctools
 import gammalib
+from ctools import obsutils
 
 
 # ================= #
@@ -39,10 +40,10 @@ def pipeline(caldb = "dummy", \
      model - Source model
     """
     # Set pointing pattern (4 pointings)
-    pointings = ctools.obsutils.set_obs_patterns("four", offset=2.0)
+    pointings = obsutils.set_obs_patterns("four", offset=2.0)
 
     # Set CTA observations (default: 1800 sec per pointing)
-    obs = ctools.obsutils.set_obs_list(pointings, caldb=caldb, irf=irf)
+    obs = obsutils.set_obs_list(pointings, caldb=caldb, irf=irf)
 
     # Load models
     models = gammalib.GModels(model)
@@ -56,7 +57,7 @@ def pipeline(caldb = "dummy", \
     # Run ctbin (builds stacked event cube)
     bin = ctools.ctbin(sim.obs())
     bin.logFileOpen()
-    bin["outfile"].filename("cntmap.fits")
+    bin["outcube"].filename("cntmap.fits")
     bin["ebinalg"].string("LOG")
     bin["emin"].real(0.1)
     bin["emax"].real(100.0)
@@ -74,8 +75,8 @@ def pipeline(caldb = "dummy", \
     # Run ctexpcube (builds exposure cube)
     expcube = ctools.ctexpcube(sim.obs())
     expcube.logFileOpen()
-    expcube["cntmap"].filename("cntmap.fits")
-    expcube["outfile"].filename("expcube.fits")
+    expcube["incube"].filename("cntmap.fits")
+    expcube["outcube"].filename("expcube.fits")
     expcube["caldb"].string(caldb)
     expcube["irf"].string(irf)
     expcube.execute()
@@ -83,8 +84,8 @@ def pipeline(caldb = "dummy", \
     # Run ctpsfcube (builds PSF cube)
     psfcube = ctools.ctpsfcube(sim.obs())
     psfcube.logFileOpen()
-    psfcube["cntmap"].filename("NONE")
-    psfcube["outfile"].filename("psfcube.fits")
+    psfcube["incube"].filename("NONE")
+    psfcube["outcube"].filename("psfcube.fits")
     psfcube["caldb"].string(caldb)
     psfcube["irf"].string(irf)
     psfcube["ebinalg"].string("LOG")
@@ -105,33 +106,23 @@ def pipeline(caldb = "dummy", \
     # Run ctbkgcube (builds background cube)
     bkgcube = ctools.ctbkgcube(sim.obs())
     bkgcube.logFileOpen()
-    bkgcube["cntmap"].filename("cntmap.fits")
-    bkgcube["bkgmdl"].filename(model)
-    bkgcube["outfile"].filename("bkgcube.fits")
+    bkgcube["incube"].filename("cntmap.fits")
+    bkgcube["inmodel"].filename(model)
+    bkgcube["outcube"].filename("bkgcube.fits")
+    bkgcube["outmodel"].filename("bkgcube.xml")
     bkgcube.execute()
 
     # Create observation container for stacked cube analysis
     obs.clear()
     cta = gammalib.GCTAObservation("cntmap.fits", "expcube.fits", "psfcube.fits")
     obs.append(cta)
-
-    # Create model for stacked cube analysis
-    models = gammalib.GModels(model)
-    models.remove("Background")
-    spatial    = gammalib.GModelSpatialDiffuseCube("bkgcube.fits")
-    spectral   = gammalib.GModelSpectralConst()
-    background = gammalib.GCTAModelCubeBackground(spatial, spectral)
-    models.append(background)
-    models.save("cube_model.xml")
-
-    # Append model to observation container
-    obs.models(models)
+    obs.models(gammalib.GModels("bkgcube.xml"))
 
     # Run ctlike
     like = ctools.ctlike(obs)
     like.logFileOpen()
     like["debug"].boolean(True)
-    like["outmdl"].filename("cube_results.xml")
+    like["outmodel"].filename("cube_results.xml")
     like.execute()
 
     # Return
diff --git a/examples/make_spectrum.py b/examples/make_spectrum.py
index 83e8577..e18bc9e 100755
--- a/examples/make_spectrum.py
+++ b/examples/make_spectrum.py
@@ -20,6 +20,7 @@
 # ==========================================================================
 import gammalib
 import ctools
+from ctools import obsutils
 try:
 	import matplotlib.pyplot as plt
 	has_matplotlib = True
@@ -47,7 +48,7 @@ def make_spectrum():
 
     # Simulate events
     sim = ctools.ctobssim()
-    sim["infile"].filename(model_name)
+    sim["inmodel"].filename(model_name)
     sim["caldb"].string(caldb)
     sim["irf"].string(irf)
     sim["ra"].real(ra)
@@ -65,7 +66,7 @@ def make_spectrum():
     ebounds = gammalib.GEbounds(10, e_min, e_max)
 
     # Generate spectral points
-    spectrum = ctools.obsutils.spectrum(sim.obs(), "Crab", ebounds)
+    spectrum = obsutils.spectrum(sim.obs(), "Crab", ebounds)
 	
     # Return spectrum
     return spectrum
diff --git a/examples/make_ts_distributions.py b/examples/make_ts_distributions.py
index 3360a2a..ceb6893 100755
--- a/examples/make_ts_distributions.py
+++ b/examples/make_ts_distributions.py
@@ -12,7 +12,7 @@
 # Required 3rd party modules:
 # - processing (optional)
 #
-# Copyright (C) 2011 Jurgen Knodlseder
+# Copyright (C) 2011-2015 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
@@ -28,8 +28,6 @@
 # along with this program.  If not, see <http://www.gnu.org/licenses/>.
 #
 # ==========================================================================
-from ctools import *
-from gammalib import *
 from cstsdist import *
 import sys
 import time
diff --git a/examples/make_unbinned_analysis.py b/examples/make_unbinned_analysis.py
index 5011035..3859571 100755
--- a/examples/make_unbinned_analysis.py
+++ b/examples/make_unbinned_analysis.py
@@ -7,7 +7,7 @@
 # Required 3rd party modules:
 # None
 #
-# Copyright (C) 2011-2014 Jurgen Knodlseder
+# Copyright (C) 2011-2015 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
@@ -23,9 +23,6 @@
 # along with this program.  If not, see <http://www.gnu.org/licenses/>.
 #
 # ==========================================================================
-#from ctools import *
-#from gammalib import *
-#from math import *
 import gammalib
 import ctools
 import math
@@ -74,8 +71,8 @@ def pipeline_v1():
     # Simulate events
     sim = ctools.ctobssim()
     sim.logFileOpen()
-    sim["infile"].filename(model_name)
-    sim["outfile"].filename(events_name)
+    sim["inmodel"].filename(model_name)
+    sim["outevents"].filename(events_name)
     sim["caldb"].string(caldb)
     sim["irf"].string(irf)
     sim["ra"].real(ra)
@@ -95,8 +92,8 @@ def pipeline_v1():
     # Select events
     select = ctools.ctselect()
     select.logFileOpen()
-    select["infile"].filename(events_name)
-    select["outfile"].filename(selected_events_name)
+    select["inobs"].filename(events_name)
+    select["outobs"].filename(selected_events_name)
     select["ra"].real(ra)
     select["dec"].real(dec)
     select["rad"].real(rad_select)
@@ -114,9 +111,9 @@ def pipeline_v1():
     # Perform maximum likelihood fitting
     like = ctools.ctlike()
     like.logFileOpen()
-    like["infile"].filename(selected_events_name)
-    like["srcmdl"].filename(model_name)
-    like["outmdl"].filename(result_name)
+    like["inobs"].filename(selected_events_name)
+    like["inmodel"].filename(model_name)
+    like["outmodel"].filename(result_name)
     like["caldb"].string(caldb)
     like["irf"].string(irf)
     like.execute()
@@ -164,7 +161,7 @@ def pipeline_v2(show_data):
 
     # Simulate events
     sim = ctools.ctobssim()
-    sim["infile"].filename(model_name)
+    sim["inmodel"].filename(model_name)
     sim["caldb"].string(caldb)
     sim["irf"].string(irf)
     sim["ra"].real(ra)
@@ -210,9 +207,6 @@ def pipeline_v2(show_data):
     print("Total wall time elapsed: "+str(wall_seconds)+" seconds")
     print("Total CPU time used ...: "+str(cpu_seconds)+" seconds")
 
-    # Show model fitting results
-    #print like.obs().models()
-    
     # Optionally plot counts
     if show_data:
         if has_matplotlib:
diff --git a/examples/model_bgd.xml b/examples/model_bgd.xml
deleted file mode 100644
index b927387..0000000
--- a/examples/model_bgd.xml
+++ /dev/null
@@ -1,12 +0,0 @@
-<?xml version="1.0" standalone="no"?>
-<source_library title="source library">
-  <source name="Background" type="RadialAcceptance" instrument="CTA">
-    <spectrum type="FileFunction" file="$CTOOLS/share/models/bkg_dummy.txt">
-      <parameter scale="1.0" name="Normalization" min="0.0" max="1000.0" value="1.0" free="1"/>
-    </spectrum>
-    <radialModel type="Gaussian">
-       <parameter name="Sigma" scale="1.0" value="3.0" min="0.01" max="10.0" free="1"/>
-    </radialModel>
-  </source>
-</source_library>
-