def prob(self):
# type: () -> LEGOProblem
"""Create the problem instance of the subdriver component."""
return LEGOProblem(cmdows_path=self.options['cmdows_path'],
kb_path=self.options['kb_path'],
data_folder=self.options['data_folder'], # Output directory
base_xml_file=self.options['base_xml_file'],
driver_uid=self.options['driver_uid'])
def setup(self):
"""Setup of the explicit component object with a nested LEGOProblem as subdriver."""
# Set subproblem
from openlego.core.problem import LEGOProblem
p = self.prob = LEGOProblem(
cmdows_path=self.options['cmdows_path'],
kb_path=self.options['kb_path'],
data_folder=self.options['data_folder'], # Output directory
base_xml_file=self.options['base_xml_file'],
driver_uid=self.options['driver_uid'])
# p.driver.options['debug_print'] = ['desvars', 'nl_cons', 'ln_cons', 'objs'] # Set printing of debug info
# Add inputs
for input_name, shape in p.model.model_constants.items():
self.add_input(input_name, shape=shape)
for input_name, attrbs in p.model.model_super_inputs.items():
self.add_input(input_name, val=attrbs['val'])
# Add outputs
for output_name, value in p.model.model_super_outputs.items():
self.add_output(output_name, val=value)
# Declare partials
self.declare_partials('*',
'*',
method='fd',
step=1e-4,
step_calc='abs')
# Setup
p.setup()
p.final_setup()
# Store (and view?) model
if self.options['show_model']:
p.store_model_view(open_in_browser=self.options['show_model'])
def run_openlego(analyze_mdao_definitions, cmdows_dir=None, initial_file_path=None,
data_folder=None, run_type='test', approx_totals=False, driver_debug_print=False):
# Check and analyze inputs
mdao_defs_loop = get_loop_items(analyze_mdao_definitions)
file_dir = os.path.dirname(__file__)
if not cmdows_dir:
cmdows_dir = os.path.join(file_dir, 'cmdows_files')
if not initial_file_path:
initial_file_path = os.path.join(file_dir, 'sellar-input.xml')
if not data_folder:
data_folder = ''
for mdao_def in mdao_defs_loop:
print('\n-----------------------------------------------')
print('Running the OpenLEGO of Mdao_{}.xml...'.format(mdao_def))
print('------------------------------------------------')
"""Solve the Sellar problem using the given CMDOWS file."""
# 1. Create Problem
prob = LEGOProblem(cmdows_path=os.path.join(cmdows_dir, 'Mdao_{}.xml'.format(mdao_def)),
kb_path=os.path.join(file_dir, 'kb'),
data_folder=data_folder, # Output directory
base_xml_file='sellar-output.xml') # Output file
if driver_debug_print:
prob.driver.options['debug_print'] = ['desvars', 'nl_cons', 'ln_cons', 'objs']
prob.set_solver_print(0) # Set printing of solver information
if approx_totals:
prob.model.approx_totals()
# 2. Initialize the Problem and export N2 chart
prob.store_model_view(open_in_browser=False)
prob.initialize_from_xml(initial_file_path)
# 3. Run the Problem
prob.run_driver() # Run the driver (optimization, DOE, or convergence)
# 4. Read out the case reader
prob.collect_results()
if run_type == 'test':
# 5. Collect test results for test assertions
if '/dataSchema/variables/x0' in prob.model._outputs:
x = [prob['/dataSchema/variables/x0']]
y = [prob['/dataSchema/analyses/y1'], prob['/dataSchema/analyses/y2']]
z = [prob['/dataSchema/variables/z1'], prob['/dataSchema/variables/z2']]
f = [prob['/dataSchema/analyses/f']]
g = [prob['/dataSchema/analyses/g1'], prob['/dataSchema/analyses/g2']]
elif '/dataSchema/architectureNodes/copyDesignVariables/dataSchemaCopy/variables/x0' in prob.model._outputs:
x = [prob['/dataSchema/architectureNodes/copyDesignVariables/dataSchemaCopy/variables/x0']]
y = [prob['/dataSchema/architectureNodes/copyDesignVariables/dataSchemaCopy/analyses/y1'],
prob['/dataSchema/architectureNodes/copyDesignVariables/dataSchemaCopy/analyses/y2']]
z = [prob['/dataSchema/variables/z1'], prob['/dataSchema/variables/z2']]
f = [prob['/dataSchema/analyses/f']]
g = [prob.model.SubOptimizer0.prob['/dataSchema/analyses/g1'],
prob.model.SubOptimizer1.prob['/dataSchema/analyses/g2']]
# 6. Cleanup and invalidate the Problem afterwards
prob.invalidate()
return x, y, z, f, g
elif run_type == 'validation':
return prob
def run_openlego(analyze_mdao_definitions, cmdows_dir=None, initial_file_path=None,
data_folder=None, run_type='test', approx_totals=False, driver_debug_print=False):
# type: (Union[int, list, str], Optional[str], Optional[str], Optional[str], Optional[str], Optional[bool], Optional[bool]) -> Union[tuple, LEGOProblem]
"""Run OpenLEGO for a list of MDAO definitions.
Parameters
----------
analyze_mdao_definitions : list
List of MDAO definitions to be analyzed.
cmdows_dir : str
Path to directory with CMDOWS files
initial_file_path : str
Path to file containing initial values
data_folder : str
Path to directory where results will be stored
run_type : str
Option to indicate the type of run, as this changes the return statement used
approx_totals : bool
Setting on whether to use approx_totals on the model
driver_debug_print : bool
Setting on whether to print debug information in the log
Returns
-------
Union[Tuple[float], LEGOProblem]
"""
# Check and analyze inputs
mdao_defs_loop = get_loop_items(analyze_mdao_definitions)
file_dir = os.path.dirname(__file__)
if not cmdows_dir:
cmdows_dir = os.path.join(file_dir, 'cmdows_files')
if not initial_file_path:
initial_file_path = os.path.join(file_dir, 'SSBJ-base.xml')
if not data_folder:
data_folder = ''
# Run the
for mdao_def in mdao_defs_loop:
print('\n-----------------------------------------------')
print('Running the OpenLEGO of Mdao_{}.xml...'.format(mdao_def))
print('------------------------------------------------')
"""Solve the SSBJ problem using the given CMDOWS file."""
# 1. Create Problem
prob = LEGOProblem(cmdows_path=os.path.join(cmdows_dir, 'Mdao_{}.xml'.format(mdao_def)),
kb_path=os.path.join(file_dir, 'kb'), # Knowledge base path
data_folder=data_folder, # Output directory
base_xml_file=os.path.join(data_folder,
'ssbj-output-{}.xml'.format(mdao_def)))
if driver_debug_print:
prob.driver.options['debug_print'] = ['desvars', 'nl_cons', 'ln_cons', 'objs']
prob.set_solver_print(0) # Set printing of solver information
if approx_totals:
prob.model.approx_totals()
# 2. Initialize the Problem and export N2 chart
prob.store_model_view()
prob.initialize_from_xml(initial_file_path) # Set the initial values from an XML file
# 3. Run the Problem
test_distributed = mdao_def in ['CO', 'BLISS-2000'] and run_type == 'test'
if test_distributed:
prob.run_model()
else:
prob.run_driver() # Run the driver (optimization, DOE, or convergence)
# 4. Read out the case reader
if not test_distributed:
prob.collect_results()
if run_type == 'test':
# 5. Collect test results for test assertions
tc = prob['/dataSchema/aircraft/geometry/tc'][0]
h = prob['/dataSchema/reference/h'][0]
M = prob['/dataSchema/reference/M'][0]
AR = prob['/dataSchema/aircraft/geometry/AR'][0]
Lambda = prob['/dataSchema/aircraft/geometry/Lambda'][0]
Sref = prob['/dataSchema/aircraft/geometry/Sref'][0]
if mdao_def not in ['CO', 'BLISS-2000']:
lambda_ = prob['/dataSchema/aircraft/geometry/lambda'][0]
section = prob['/dataSchema/aircraft/geometry/section'][0]
Cf = prob['/dataSchema/aircraft/other/Cf'][0]
T = prob['/dataSchema/aircraft/other/T'][0]
R = prob['/dataSchema/scaledData/R/value'][0]
extra = prob['/dataSchema/aircraft/weight/WT'][0]
elif mdao_def == 'CO':
lambda_ = prob.model.SubOptimizer0.prob['/dataSchema/aircraft/geometry/lambda'][0]
section = prob.model.SubOptimizer0.prob['/dataSchema/aircraft/geometry/section'][0]
Cf = prob.model.SubOptimizer1.prob['/dataSchema/aircraft/other/Cf'][0]
T = prob.model.SubOptimizer2.prob['/dataSchema/aircraft/other/T'][0]
R = prob['/dataSchema/scaledData/R/value'][0]
extra = (prob['/dataSchema/distributedArchitectures/group0/objective'],
prob['/dataSchema/distributedArchitectures/group1/objective'],
prob['/dataSchema/distributedArchitectures/group2/objective'])
else:
lambda_, section, Cf, T, R, extra = None, None, None, None, None, None
# 6. Cleanup and invalidate the Problem afterwards
prob.invalidate()
return tc, h, M, AR, Lambda, Sref, lambda_, section, Cf, T, R, extra
elif run_type == 'validation':
return prob
else:
prob.invalidate()
def run_openlego(analyze_mdao_definitions):
# Check and analyze inputs
mdao_defs_loop = get_loop_items(analyze_mdao_definitions)
for mdao_def in mdao_defs_loop:
print('\n-----------------------------------------------')
print('Running the OpenLEGO of Mdao_{}.xml...'.format(mdao_def))
print('------------------------------------------------')
"""Solve the SSBJ problem using the given CMDOWS file."""
# 1. Create Problem
prob = LEGOProblem(cmdows_path=os.path.join('cmdows_files', 'Mdao_{}.xml'.format(mdao_def)), # CMDOWS file
kb_path='kb', # Knowledge base path
data_folder='', # Output directory
base_xml_file='ssbj-output-{}.xml'.format(mdao_def)) # Output file
# prob.driver.options['debug_print'] = ['desvars', 'nl_cons', 'ln_cons', 'objs'] # Set printing of debug info
prob.set_solver_print(0) # Set printing of solver information
# 2. Initialize the Problem and export N2 chart
prob.store_model_view()
prob.initialize_from_xml('SSBJ-base.xml') # Set the initial values from an XML file
# 3. Run the Problem
if mdao_def == 'CO':
prob.run_model()
else:
prob.run_driver() # Run the driver (optimization, DOE, or convergence)
# 4. Read out the case reader
if mdao_def != 'CO':
prob.collect_results()
# 5. Collect test results for test assertions
tc = prob['/dataSchema/aircraft/geometry/tc']
h = prob['/dataSchema/reference/h']
M = prob['/dataSchema/reference/M']
AR = prob['/dataSchema/aircraft/geometry/AR']
Lambda = prob['/dataSchema/aircraft/geometry/Lambda']
Sref = prob['/dataSchema/aircraft/geometry/Sref']
if mdao_def != 'CO':
lambda_ = prob['/dataSchema/aircraft/geometry/lambda']
section = prob['/dataSchema/aircraft/geometry/section']
Cf = prob['/dataSchema/aircraft/other/Cf']
T = prob['/dataSchema/aircraft/other/T']
R = prob['/dataSchema/scaledData/R/value']
extra = prob['/dataSchema/aircraft/weight/WT']
else:
lambda_ = prob.model.SubOptimizer0.prob['/dataSchema/aircraft/geometry/lambda']
section = prob.model.SubOptimizer0.prob['/dataSchema/aircraft/geometry/section']
Cf = prob.model.SubOptimizer1.prob['/dataSchema/aircraft/other/Cf']
T = prob.model.SubOptimizer2.prob['/dataSchema/aircraft/other/T']
R = prob['/dataSchema/scaledData/R/value']
extra = (prob['/dataSchema/distributedArchitectures/group0/objective'],
prob['/dataSchema/distributedArchitectures/group1/objective'],
prob['/dataSchema/distributedArchitectures/group2/objective'])
# 6. Cleanup and invalidate the Problem afterwards
prob.invalidate()
return tc, h, M, AR, Lambda, Sref, lambda_, section, Cf, T, R, extra
def run_openlego(cmdows_file,
data_folder=None,
driver_debug_print=False,
discipline_resolvers=None):
file_dir = os.path.dirname(__file__)
initial_file_path = os.path.join(file_dir, 'input.xml')
if not data_folder:
data_folder = ''
print('\n-----------------------------------------------')
print('Running the OpenLEGO of {}...'.format(cmdows_file))
print('------------------------------------------------')
# 1. Create Problem
prob = LEGOProblem(
cmdows_path=os.path.join(file_dir, 'cmdows', cmdows_file),
kb_path='',
data_folder=data_folder,
base_xml_file='sellar-output.xml',
discipline_resolvers=discipline_resolvers,
)
if driver_debug_print:
prob.driver.options['debug_print'] = [
'desvars', 'nl_cons', 'ln_cons', 'objs'
]
prob.set_solver_print(0) # Set printing of solver information
# 2. Initialize the Problem and export N2 chart
prob.store_model_view(open_in_browser=False)
prob.initialize_from_xml(initial_file_path)
# 3. Run the Problem
prob.run_driver() # Run the driver (optimization, DOE, or convergence)
# 4. Read out the case reader
prob.collect_results()
# 5. Collect test results for test assertions
x = [prob['/dataSchema/variables/x1']]
y = [prob['/dataSchema/analyses/y1'], prob['/dataSchema/analyses/y2']]
z = [prob['/dataSchema/variables/z1'], prob['/dataSchema/variables/z2']]
f = [prob['/dataSchema/output/f']]
g = [prob['/dataSchema/output/g1'], prob['/dataSchema/output/g2']]
# 6. Cleanup and invalidate the Problem afterwards
prob.invalidate()
return x, y, z, f, g
def run_openlego(analyze_mdao_definitions):
# Check and analyze inputs
mdao_defs_loop = get_loop_items(analyze_mdao_definitions)
for mdao_def in mdao_defs_loop:
print('\n-----------------------------------------------')
print('Running the OpenLEGO of Mdao_{}.xml...'.format(mdao_def))
print('------------------------------------------------')
"""Solve the Sellar problem using the given CMDOWS file."""
# 1. Create Problem
prob = LEGOProblem(
cmdows_path=os.path.join(
'cmdows_files', 'Mdao_{}.xml'.format(mdao_def)), # CMDOWS file
kb_path='kb',
data_folder='', # Output directory
base_xml_file='sellar-output.xml') # Output file
# prob.driver.options['debug_print'] = ['desvars', 'nl_cons', 'ln_cons', 'objs'] # Set printing of debug info
prob.set_solver_print(0) # Set printing of solver information
# 2. Initialize the Problem and export N2 chart
prob.store_model_view(open_in_browser=False)
prob.initialize_from_xml('sellar-input.xml')
# 3. Run the Problem
prob.run_driver() # Run the driver (optimization, DOE, or convergence)
# 4. Read out the case reader
prob.collect_results()
# 5. Collect test results for test assertions
if '/dataSchema/geometry/x1' in prob.model._outputs:
x = [prob['/dataSchema/geometry/x1']]
y = [
prob['/dataSchema/analyses/y1'],
prob['/dataSchema/analyses/y2']
]
z = [
prob['/dataSchema/geometry/z1'],
prob['/dataSchema/geometry/z2']
]
f = [prob['/dataSchema/analyses/f']]
g = [
prob['/dataSchema/analyses/g1'],
prob['/dataSchema/analyses/g2']
]
elif '/dataSchema/architectureNodes/copyDesignVariables/dataSchemaCopy/geometry/x1' in prob.model._outputs:
x = [
prob[
'/dataSchema/architectureNodes/copyDesignVariables/dataSchemaCopy/geometry/x1']
]
y = [
prob[
'/dataSchema/architectureNodes/copyDesignVariables/dataSchemaCopy/analyses/y1'],
prob[
'/dataSchema/architectureNodes/copyDesignVariables/dataSchemaCopy/analyses/y2']
]
z = [
prob['/dataSchema/geometry/z1'],
prob['/dataSchema/geometry/z2']
]
f = [prob['/dataSchema/analyses/f']]
g = [
prob.model.SubOptimizer0.prob['/dataSchema/analyses/g1'],
prob.model.SubOptimizer1.prob['/dataSchema/analyses/g2']
]
# 6. Cleanup and invalidate the Problem afterwards
prob.invalidate()
return x, y, z, f, g