diff --git a/examples/scripts/sellar_problem_dev_CO.py b/examples/scripts/sellar_problem_dev_CO.py
deleted file mode 100644
index f781b43d3586f7516037f5db61824e33c1d0cbe7..0000000000000000000000000000000000000000
--- a/examples/scripts/sellar_problem_dev_CO.py
+++ /dev/null
@@ -1,225 +0,0 @@
-# Imports
-import logging
-
-from collections import OrderedDict
-
-import networkx as nx
-
-from kadmos.graph import RepositoryConnectivityGraph, FundamentalProblemGraph, load
-from kadmos.utilities.general import get_mdao_setup
-
-
-# Settings for logging
-logging.basicConfig(format='%(levelname)s: %(message)s', level=logging.DEBUG)
-
-# Settings for scripting
-mdao_definitions_loop_all = True # Option for looping through all MDAO definitions
-mdao_definition_id = 13 # Option for selecting a MDAO definition (in case mdao_definitions_loop_all=False)
-
-# Settings for saving
-pdf_dir = 'sellar_problem/(X)DSM'
-cmdows_dir = 'sellar_problem/CMDOWS'
-kdms_dir = 'sellar_problem/KDMS'
-vistoms_dir = 'sellar_problem/VISTOMS'
-
-
-print 'Scripting RCG...'
-
-# A new repository connectivity graph is defined to describe the general problem
-rcg = RepositoryConnectivityGraph(name='Sellar problem graph')
-# A description is added to the graph
-rcg.graph['description'] = 'Repository graph of tools where a subset can be used to solve the Sellar problem'
-# All function nodes are defined
-rcg.add_node('A', category='function', instance=1)
-rcg.add_node('D1', category='function', instance=1)
-rcg.add_node('D2', category='function', instance=1)
-rcg.add_node('D3', category='function', instance=1)
-rcg.add_node('F1', category='function', instance=1)
-rcg.add_node('F2', category='function', instance=1)
-rcg.add_node('G1', category='function', instance=1)
-rcg.add_node('G2', category='function', instance=1)
-# All variable nodes are defined
-rcg.add_node('/data_schema/settings/a', category='variable', label='a', instance=1)
-rcg.add_node('/data_schema/settings/c', category='variable', label='c', instance=1)
-rcg.add_node('/data_schema/analyses/f', category='variable', label='f', instance=1)
-rcg.add_node('/data_schema/analyses/g1', category='variable', label='g1', instance=1)
-rcg.add_node('/data_schema/analyses/g2', category='variable', label='g2', instance=1)
-rcg.add_node('/data_schema/geometry/x1', category='variable', label='x1', instance=1)
-rcg.add_node('/data_schema/analyses/y1', category='variable', label='y1', instance=1)
-rcg.add_node('/data_schema/analyses/y2', category='variable', label='y2', instance=1)
-rcg.add_node('/data_schema/geometry/z1', category='variable', label='z1', instance=1)
-rcg.add_node('/data_schema/geometry/z2', category='variable', label='z2', instance=1)
-# The edges between the nodes are defined
-rcg.add_edge('A', '/data_schema/settings/c')
-rcg.add_edge('D1', '/data_schema/analyses/y1')
-rcg.add_edge('D2', '/data_schema/analyses/y2')
-rcg.add_edge('D3', '/data_schema/geometry/x1')
-rcg.add_edge('D3', '/data_schema/geometry/z1')
-rcg.add_edge('D3', '/data_schema/geometry/z2')
-rcg.add_edge('F1', '/data_schema/analyses/f')
-rcg.add_edge('F2', '/data_schema/analyses/f')
-rcg.add_edge('G1', '/data_schema/analyses/g1')
-rcg.add_edge('G2', '/data_schema/analyses/g2')
-rcg.add_edge('/data_schema/settings/a', 'A')
-rcg.add_edge('/data_schema/settings/c', 'D1')
-rcg.add_edge('/data_schema/settings/c', 'D2')
-rcg.add_edge('/data_schema/geometry/x1', 'D1')
-rcg.add_edge('/data_schema/geometry/x1', 'F1')
-rcg.add_edge('/data_schema/geometry/x1', 'F2')
-rcg.add_edge('/data_schema/analyses/y1', 'D2')
-rcg.add_edge('/data_schema/analyses/y1', 'D3')
-rcg.add_edge('/data_schema/analyses/y1', 'F1')
-rcg.add_edge('/data_schema/analyses/y1', 'G1')
-rcg.add_edge('/data_schema/analyses/y2', 'D1')
-rcg.add_edge('/data_schema/analyses/y2', 'D3')
-rcg.add_edge('/data_schema/analyses/y2', 'F1')
-rcg.add_edge('/data_schema/analyses/y2', 'G2')
-rcg.add_edge('/data_schema/geometry/z1', 'D1')
-rcg.add_edge('/data_schema/geometry/z1', 'D2')
-rcg.add_edge('/data_schema/geometry/z1', 'F2')
-rcg.add_edge('/data_schema/geometry/z2', 'D1')
-rcg.add_edge('/data_schema/geometry/z2', 'D2')
-rcg.add_edge('/data_schema/geometry/z2', 'F1')
-rcg.add_edge('/data_schema/geometry/z2', 'F2')
-
-# Add some (optional) equations
-rcg.add_equation_labels(rcg.get_function_nodes())
-rcg.add_equation('A', 'a', 'Python')
-rcg.add_equation('A', 'a', 'LaTeX')
-rcg.add_equation('A', '<math xmlns="http://www.w3.org/1998/Math/MathML"><mi>a</mi></math>', 'MathML')
-rcg.add_equation('G1', 'y1/3.16-1', 'Python')
-rcg.add_equation('G1', 'y1/3.16-1', 'LaTeX')
-rcg.add_equation('G1', '<math xmlns="http://www.w3.org/1998/Math/MathML"><mi>y</mi><mn>1</mn><mo>/</mo><mn>3</mn><mo>.</mo><mn>16</mn><mo>-</mo><mn>1</mn></math>', 'MathML')
-rcg.add_equation('G2', '1-y2/24.0', 'Python')
-rcg.add_equation('G2', '1-y2/24.0', 'LaTeX')
-rcg.add_equation('G2', '<math xmlns="http://www.w3.org/1998/Math/MathML"><mn>1</mn><mo>-</mo><mi>y</mi><mn>2</mn><mo>/</mo><mn>24</mn><mo>.</mo><mn>0</mn></math>', 'MathML')
-rcg.add_equation('F1', 'x1**2+z2+y1+exp(-y2)', 'Python')
-rcg.add_equation('F1', 'x1^2+z2+y1+e^{-y2}', 'LaTeX')
-rcg.add_equation('F1', '<math xmlns="http://www.w3.org/1998/Math/MathML"><mi>x</mi><msup><mn>1</mn><mn>2</mn></msup><mo>+</mo><mi>z</mi><mn>2</mn><mo>+</mo><mi>y</mi><mn>1</mn><mo>+</mo><msup><mi>e</mi><mrow><mo>-</mo><mi>y</mi><mn>2</mn></mrow></msup></math>', 'MathML')
-# Add some (optional) organization information
-contacts = [{'attrib': {'uID': 'ivangent'}, 'name': 'Imco van Gent', 'email': 'i.vangent@tudelft.nl', 'company': 'TU Delft'},
- {'attrib': {'uID': 'lmuller'}, 'name': 'Lukas Muller', 'email': 'l.muller@student.tudelft.nl', 'company': 'TU Delft'}]
-architects = [{'contactUID': 'ivangent'}, {'contactUID': 'lmuller'}]
-integrators = [{'contactUID': 'lmuller'}]
-rcg.graph['organization'] = OrderedDict([('contacts', contacts),
- ('organigram', {'architects': architects,
- 'integrators': integrators})])
-# Add some (optional) ranges
-rcg.adj['/data_schema/geometry/z1']['D1']['valid_ranges'] = {'limit_range': {'minimum': -5, 'maximum': 5.},
- 'list_range': [('list_range_item', 7.5), ('list_range_item', 8)]}
-# Add some (optional) metadata
-rcg.node['F2']['general_info'] = {'description': 'dummy function that is not part of the original Sellar problem'}
-rcg.node['F2']['performance_info'] = {'precision': 20,
- 'fidelity_level': 2,
- 'run_time': 1.5}
-
-function_order = ['A', 'D1', 'D2', 'D3', 'F1', 'F2', 'G1', 'G2']
-
-# Create a DSM visualization of the RCG
-#rcg.create_dsm(file_name='RCG', function_order=function_order, include_system_vars=True, destination_folder=pdf_dir)
-# Create a VISTOMS visualization of the RCG
-#rcg.vistoms_create(vistoms_dir, function_order=function_order, compress=False)
-
-# Save the RCG as kdms
-#rcg.save('RCG', destination_folder=kdms_dir)
-# Save the RCG as cmdows (and do an integrity check)
-#rcg.save('RCG', file_type='cmdows', destination_folder=cmdows_dir,
-# description='RCG CMDOWS file of the well-known Sellar problem',
-# creator='Imco van Gent',
-# version='0.1',
-# pretty_print=True,
-# integrity=True)
-
-print 'Scripting initial FPG...'
-
-# A initial fundamental problem graph is created based on the rcg
-fpg_initial = rcg.deepcopy_as(FundamentalProblemGraph)
-# The dummy function nodes are removed
-fpg_initial.remove_function_nodes('D3', 'F2')
-# A new function order is defined
-function_order = fpg_initial.get_possible_function_order('single-swap')
-
-# On to the wrapping of the MDAO architectures
-# Get iterator (all or single one)
-mdao_definition = 'CO'
-
-print 'Scripting ' + str(mdao_definition) + '...'
-
-# Determine the three main settings: architecture, convergence type and unconverged coupling setting
-mdao_architecture, convergence_type, allow_unconverged_couplings = get_mdao_setup(mdao_definition)
-
-# Reset FPG
-fpg = fpg_initial.deepcopy()
-fpg.graph['name'] = 'FPG - ' + mdao_definition
-fpg.graph['description'] = 'Fundamental problem graph for solving the Sellar problem using the strategy: ' \
- + mdao_definition + '.'
-
-# Define settings of the problem formulation
-fpg.graph['problem_formulation'] = dict()
-fpg.graph['problem_formulation']['function_order'] = function_order
-fpg.graph['problem_formulation']['mdao_architecture'] = mdao_architecture
-fpg.graph['problem_formulation']['convergence_type'] = convergence_type
-fpg.graph['problem_formulation']['allow_unconverged_couplings'] = allow_unconverged_couplings
-fpg.graph['problem_formulation']['coupled_functions_groups'] = [['D1'],['D2']]
-if mdao_architecture in ['unconverged-DOE', 'converged-DOE']:
- fpg.graph['problem_formulation']['doe_settings'] = dict()
- fpg.graph['problem_formulation']['doe_settings']['doe_method'] = 'Custom design table'
- if fpg.graph['problem_formulation']['doe_settings']['doe_method'] in ['Latin hypercube design',
- 'Monte Carlo design']:
- fpg.graph['problem_formulation']['doe_settings']['doe_seed'] = 6
- fpg.graph['problem_formulation']['doe_settings']['doe_runs'] = 5
- elif fpg.graph['problem_formulation']['doe_settings']['doe_method'] in ['Full factorial design']:
- fpg.graph['problem_formulation']['doe_settings']['doe_runs'] = 5
-
-# Depending on the architecture, different additional node attributes have to be specified. This is automated here
-# to allow direct execution of all different options.
-fpg.mark_as_objective('/data_schema/analyses/f')
-fpg.mark_as_constraints(['/data_schema/analyses/g1','/data_schema/analyses/g2'], '>=', 0.0)
-fpg.mark_as_design_variables(['/data_schema/geometry/z1','/data_schema/geometry/z2','/data_schema/geometry/x1'],
- lower_bounds=[-10,0.0,0.0], upper_bounds=10, nominal_values=0.0)
-
-# Search for problem roles
-fpg.add_function_problem_roles()
-
-# Create a DSM visualization of the FPG
-#fpg.create_dsm(file_name='FPG_'+mdao_definition, function_order=function_order, include_system_vars=True,
-# destination_folder=pdf_dir)
-# Create a VISTOMS visualization of the FPG (and add it to the existing directory)
-#fpg.vistoms_add(vistoms_dir, function_order=function_order)
-
-# Save the FPG as kdms
-#fpg.save('FPG_'+mdao_definition, destination_folder=kdms_dir, graph_check_critical=False) # TODO: add graph check for CO
-# Save the FPG as cmdows (and do an integrity check)
-#fpg.save('FPG_'+mdao_definition, file_type='cmdows', destination_folder=cmdows_dir,
-# description='FPG CMDOWS file of the well-known Sellar problem',
-# creator='Imco van Gent',
-# version='0.1',
-# pretty_print=True,
-# integrity=True,
-# graph_check_critical=False) # TODO: add graph check for CO
-
-# Get Mdao graphs
-mdg = fpg.get_mdg(name='mdg Sellar problem')
-mpg = mdg.get_mpg(name='mpg Sellar problem')
-mdg.graph['name'] = 'XDSM - ' + mdao_definition
-mdg.graph['description'] = 'Solution strategy to solve the Sellar problem using the strategy: ' \
- + str(mdao_architecture) + ('_' + str(convergence_type) if convergence_type else '') + '.'
-
-# Create a DSM visualization of the Mdao
-mdg.create_dsm(file_name='Mdao_'+mdao_definition, include_system_vars=True, destination_folder=pdf_dir, mpg=mpg)
-# Create a VISTOMS visualization of the Mdao (and add it to the existing directory)
-#mdg.vistoms_add(vistoms_dir, mpg=mpg)
-
-# Save the Mdao as kdms
-mdg.save('Mdao_'+mdao_definition, destination_folder=kdms_dir, mpg=mpg)
-# Save the Mdao as cmdows (and do an integrity check)
-# mdg.save('Mdao_'+mdao_definition, file_type='cmdows', destination_folder=cmdows_dir,
-# mpg=mpg,
-# description='Mdao CMDOWS file of the well-known Sellar problem',
-# creator='Imco van Gent',
-# version='0.1',
-# pretty_print=True,
-# integrity=True,
-# convention=True)
-
-print 'Done!'