def compute(self, inputs, outputs):
"""Launches the module"""
# Updating inputs in CPACS file
cpacs_path = mif.get_toolinput_file_path(self.module_name)
tixi = cpsf.open_tixi(cpacs_path)
for name in inputs:
if name in optim_var_dict:
xpath = optim_var_dict[name][4]
cpsf.add_float_vector(tixi, xpath, inputs[name])
cpsf.close_tixi(tixi, cpacs_path)
# Running the module
wkf.run_subworkflow([self.module_name])
# Feeding CPACS file restults to outputs
cpacs_path = mif.get_tooloutput_file_path(self.module_name)
tixi = cpsf.open_tixi(cpacs_path)
for name in outputs:
if name in optim_var_dict:
xpath = optim_var_dict[name][4]
outputs[name] = cpsf.get_value(tixi, xpath)
# Copy CPACS to input folder of next module
index = Rt.modules.index(self.module_name) + 1
if index != len(Rt.modules):
cpacs_path = mif.get_toolinput_file_path(Rt.modules[index])
else:
cpacs_path = mif.get_toolinput_file_path(Rt.modules[0])
cpsf.close_tixi(tixi, cpacs_path)
def first_run(Rt):
"""Run subworkflow once for the optimisation problem.
This function runs a first loop to ensure that all problem variables
are created an can be fed to the optimisation setup program.
Args:
Rt (Routine object): Class that contains the routine informations.
"""
log.info('Launching initialization workflow')
Rt.modules.insert(0, 'Optimisation')
# Settings needed for CFD calculation
if 'SettingsGUI' in Rt.modules:
Rt.modules.remove('SettingsGUI')
Rt.modules.insert(0, 'SettingsGUI')
# First iteration to create aeromap results if no pre-workflow
if Rt.modules[0] == 'Optimisation':
wkf.copy_module_to_module('Optimisation', 'in', Rt.modules[1], 'in')
else:
wkf.copy_module_to_module('Optimisation', 'in', Rt.modules[0], 'in')
wkf.run_subworkflow(Rt.modules)
wkf.copy_module_to_module(Rt.modules[-1], 'out', 'Optimisation', 'in')
# SettingsGUI only needed at the first iteration
if 'SettingsGUI' in Rt.modules: #and added_gui:
Rt.modules.remove('SettingsGUI')
# Optimisation parameters only needed for the first run
Rt.modules.remove('Optimisation')
def one_iteration():
"""
Compute the objective function.
Function 'one_iteration' will exectute in order all the module contained
in '...' and extract the ... value from the last CPACS file, this value will
be returned to the optimizer CPACSUpdater....
"""
global counter
counter += 1
# Create the parameter in CPACS with 'CPACSUpdater' module
cpacs_path = mi.get_toolinput_file_path('CPACSUpdater')
cpacs_out_path = mi.get_tooloutput_file_path('CPACSUpdater')
tixi = cpsf.open_tixi(cpacs_path)
wkdir_path = ceaf.create_new_wkdir(Rt.date)
WKDIR_XPATH = '/cpacs/toolspecific/CEASIOMpy/filesPath/wkdirPath'
tixi.updateTextElement(WKDIR_XPATH, wkdir_path)
# TODO: improve this part! (maybe move somewhere else)
# To delete coef from previous iter
if opf.get_aeromap_path(Rt.modules) != 'None':
xpath = opf.get_aeromap_path(Rt.modules)
aeromap_uid = cpsf.get_value(tixi, xpath + '/aeroMapUID')
Coef = apmf.get_aeromap(tixi, aeromap_uid)
apmf.delete_aeromap(tixi, aeromap_uid)
apmf.create_empty_aeromap(tixi, aeromap_uid, 'test_optim')
apmf.save_parameters(tixi, aeromap_uid, Coef)
cpsf.close_tixi(tixi, cpacs_path)
# Update the CPACS file with the parameters contained in design_var_dict
update_cpacs_file(cpacs_path, cpacs_out_path, design_var_dict)
# Save the CPACS file
if counter % 1 == 0:
file_copy_from = mi.get_tooloutput_file_path('CPACSUpdater')
shutil.copy(
file_copy_from,
optim_dir_path + '/Geometry/' + 'iter_{}.xml'.format(counter))
# Run optimisation sub workflow
wkf.copy_module_to_module('CPACSUpdater', 'out', Rt.modules[0], 'in')
wkf.run_subworkflow(Rt.modules)
wkf.copy_module_to_module(Rt.modules[-1], 'out', 'CPACSUpdater', 'in')
# Extract results TODO: improve this part
cpacs_results_path = mi.get_tooloutput_file_path(Rt.modules[-1])
log.info('Results will be extracted from:' + cpacs_results_path)
tixi = cpsf.open_tixi(cpacs_results_path)
# Update the constraints values
update_res_var_dict(tixi)
return compute_obj()
def compute(self, inputs, outputs):
"""Launches the module"""
# Updating inputs in CPACS file
cpacs_path = mif.get_toolinput_file_path(self.module_name)
tixi = cpsf.open_tixi(cpacs_path)
for name in inputs:
if name in optim_var_dict:
xpath = optim_var_dict[name][4]
# Change only the first vector value for aeromap param
if name in apmf.XSTATES:
size = tixi.getVectorSize(xpath)
v = list(tixi.getFloatVector(xpath, size))
v.pop(0)
v.insert(0, inputs[name])
tixi.updateFloatVector(xpath, v, size, '%g')
else:
cpsf.add_float_vector(tixi, xpath, inputs[name])
cpsf.close_tixi(tixi, cpacs_path)
# Running the module
wkf.run_subworkflow([self.module_name])
# Feeding CPACS file results to outputs
cpacs_path = mif.get_tooloutput_file_path(self.module_name)
tixi = cpsf.open_tixi(cpacs_path)
for name in outputs:
if name in optim_var_dict:
xpath = optim_var_dict[name][4]
if name in apmf.COEF_LIST:
val = cpsf.get_value(tixi, xpath)
if isinstance(val, str):
val = val.split(';')
outputs[name] = val[0]
else:
outputs[name] = val
else:
outputs[name] = cpsf.get_value(tixi, xpath)
# Copy CPACS to input folder of next module
index = Rt.modules.index(self.module_name) + 1
if index != len(Rt.modules):
cpacs_path = mif.get_toolinput_file_path(Rt.modules[index])
else:
cpacs_path = mif.get_toolinput_file_path(Rt.modules[0])
cpsf.close_tixi(tixi, cpacs_path)
def first_run(module_list, modules_pre_list=[]):
"""Run subworkflow once for the optimisation problem.
This function runs a first loop to ensure that all problem variables
are created an can be fed to the optimisation setup program.
Args:
module_list (lst) : List of modules to run.
module_pre_list (lst) : List of modules that were run in a previous
workflow.
Returns:
None.
"""
# Check if aeromap results already exists, else run workflow
global XPATH
global XPATH_PRE
log.info('Launching initialization workflow')
XPATH = tls.get_aeromap_path(module_list)
if 'PyTornado' in modules_pre_list or 'SU2Run' in modules_pre_list:
XPATH_PRE = tls.get_aeromap_path(modules_pre_list)
else:
XPATH_PRE = XPATH
# Settings needed for CFD calculation
if 'Optimisation' not in modules_pre_list:
module_list.insert(0, 'Optimisation')
if 'SettingsGUI' not in module_list or 'SettingsGUI' not in modules_pre_list:
module_list.insert(0, 'SettingsGUI')
# First iteration to create aeromap results if no pre-workflow
if XPATH != XPATH_PRE or modules_pre_list == []:
wkf.copy_module_to_module('Optimisation', 'in', module_list[0], 'in')
wkf.run_subworkflow(module_list)
wkf.copy_module_to_module(module_list[-1], 'out', 'Optimisation', 'in')
# SettingsGUI only needed at the first iteration
if 'SettingsGUI' in module_list:
module_list.pop(module_list.index('SettingsGUI'))
# Optimisation parameters only needed for the first run
module_list.pop(module_list.index('Optimisation'))
def init_dict(cpacs_path, module_list, modules_pre_list=[]):
"""
Create dictionnaries for the optimisation problem.
Parameters
----------
cpacs_path : String
Path to the CPACS file.
module_list : List
List of modules.
Returns
-------
Dict
All dictionnaries needed for the optimisation problem.
"""
# Check if aeromap results already exists, else run workflow
global XPATH
global XPATH_PRE
XPATH = optf.get_aeromap_path(module_list)
if 'PyTornado' in modules_pre_list or 'SU2Run' in modules_pre_list:
XPATH_PRE = optf.get_aeromap_path(modules_pre_list)
else:
XPATH_PRE = XPATH
# Settings needed for CFD calculation
if 'SettingsGUI' not in module_list or 'SettingsGUI' not in modules_pre_list:
module_list.insert(0, 'SettingsGUI')
# First iteration to create aeromap results if no pre-workflow
if XPATH != XPATH_PRE or modules_pre_list == []:
wkf.copy_module_to_module('Optimisation', 'in', module_list[0], 'in')
wkf.run_subworkflow(module_list)
wkf.copy_module_to_module(module_list[-1], 'out', 'Optimisation', 'in')
# If settingsGUI only needed at the first iteration
if 'SettingsGUI' in module_list:
module_list.pop(module_list.index('SettingsGUI'))
tixi = cpsf.open_tixi(cpacs_path)
return init_res_dict(tixi), init_design_var_dict(tixi)
Opt.module_post = []
# Copy ToolInput.xml in ToolInput dir if not already there
cpacs_path = mi.get_toolinput_file_path(MODULE_NAME)
if not Opt.cpacs_path == cpacs_path:
shutil.copy(Opt.cpacs_path, cpacs_path)
Opt.cpacs_path = cpacs_path
# Create a new wkdir
tixi = cpsf.open_tixi(Opt.cpacs_path)
wkdir = ceaf.get_wkdir_or_create_new(tixi)
cpsf.close_tixi(tixi, Opt.cpacs_path)
# Run Pre-otimisation workflow
if Opt.module_pre:
wkf.run_subworkflow(Opt.module_pre, Opt.cpacs_path)
if not Opt.module_optim and not Opt.module_post:
shutil.copy(mi.get_tooloutput_file_path(Opt.module_pre[-1]),
cpacs_path_out)
# Run Optimisation workflow
if Opt.module_optim:
if Opt.module_pre:
wkf.copy_module_to_module(Opt.module_pre[-1], 'out',
'Optimisation', 'in')
else:
wkf.copy_module_to_module('WorkflowCreator', 'in', 'Optimisation',
'in')
if Opt.optim_method != 'None':
def aeromap_case_gen(modules):
"""
Generate a CSV file containing a dataset generated with aeromap parameters
only.
Args:
modules (lst) : list of modules to execute.
Returns:
file (str) : Path to CSV file.
"""
file = MODULE_DIR + '/Aeromap_generated.csv'
infile = mi.get_toolinput_file_path('PredictiveTool')
outfile = mi.get_tooloutput_file_path('PredictiveTool')
tixi = cpsf.open_tixi(infile)
# Inputs
alt = [0, 0]
mach = [0.5, 0.5]
aoa = [-10, 10]
aos = [0, 0]
nt = 100
bounds = np.array([alt, mach, aoa, aos])
# Sort criterion : ‘center’, ‘maximin’, ‘centermaximin’, ‘correlation’
crit = 'corr'
# Generate sample points, LHS or FullFactorial
sampling = smp.LHS(xlimits=bounds, criterion=crit)
xd = sampling(nt)
xd = xd.transpose()
# Delete the other aeromaps... maybe conserve them ?
for uid in apmf.get_aeromap_uid_list(tixi):
apmf.delete_aeromap(tixi, uid)
# Create new aeromap
aeromap_uid = 'DoE_Aeromap'
am_xpath = tls.get_aeromap_path(modules)
apmf.create_empty_aeromap(tixi, aeromap_uid)
cpsf.add_string_vector(tixi, am_xpath + '/aeroMapUID', [aeromap_uid])
# Add parameters to aeromap
Param = apmf.AeroCoefficient()
for i in range(0, xd.shape[1]):
Param.add_param_point(xd[0][i], xd[1][i], xd[2][i], xd[3][i])
apmf.save_parameters(tixi, aeromap_uid, Param)
cpsf.close_tixi(tixi, infile)
wkf.run_subworkflow(modules, cpacs_path_in=infile, cpacs_path_out=outfile)
# Get Aerocoefficient
tixi = cpsf.open_tixi(outfile)
am_xpath = tls.get_aeromap_path(modules)
aeromap_uid = cpsf.get_value(tixi, am_xpath + '/aeroMapUID')
AeroCoefficient = apmf.get_aeromap(tixi, aeromap_uid)
cpsf.close_tixi(tixi, outfile)
dct = AeroCoefficient.to_dict()
# Write to CSV
df = pd.DataFrame(dct)
df = df.transpose()
var_type = [
'obj' if i in objectives else
'des' if i in ['alt', 'mach', 'aoa', 'aos'] else 'const'
for i in df.index
]
df.insert(0, 'type', var_type)
df.to_csv(file, index=True)
return file
def run_workflow(Otp):
""" Run the complete Worflow
Args:
Opt (class): Cl
cpacs_out_path (str): Path to the output CPACS file
module_list (list): List of module to inclue in the GUI
"""
# Copy ToolInput.xml in ToolInput dir if not already there
cpacs_path = mi.get_toolinput_file_path(MODULE_NAME)
if not os.path.abspath(Opt.cpacs_path) == os.path.abspath(cpacs_path):
shutil.copy(Opt.cpacs_path, cpacs_path)
Opt.cpacs_path = os.path.abspath(cpacs_path)
# Create a new wkdir
tixi = cpsf.open_tixi(Opt.cpacs_path)
wkdir = ceaf.get_wkdir_or_create_new(tixi)
cpsf.close_tixi(tixi, Opt.cpacs_path)
# Run Pre-otimisation workflow
if Opt.module_pre:
wkf.run_subworkflow(Opt.module_pre, Opt.cpacs_path)
if not Opt.module_optim and not Opt.module_post:
shutil.copy(mi.get_tooloutput_file_path(Opt.module_pre[-1]),
cpacs_path_out)
# Run Optimisation workflow
if Opt.module_optim:
if Opt.module_pre:
wkf.copy_module_to_module(Opt.module_pre[-1], 'out',
'Optimisation', 'in')
else:
wkf.copy_module_to_module('WorkflowCreator', 'in', 'Optimisation',
'in')
if Opt.optim_method != 'None':
routine_launcher(Opt)
else:
log.warning('No optimization method has been selected!')
log.warning('The modules will be run as a simple workflow')
wkf.run_subworkflow(Opt.module_optim)
if not Opt.module_post:
shutil.copy(mi.get_tooloutput_file_path(Opt.module_optim[-1]),
cpacs_path_out)
# Run Post-optimisation workflow
if Opt.module_post:
if Opt.module_optim:
wkf.copy_module_to_module(Opt.module_optim[-1], 'out',
Opt.module_post[0], 'in')
elif Opt.module_pre:
wkf.copy_module_to_module(Opt.module_pre[-1], 'out',
Opt.module_post[0], 'in')
else:
wkf.copy_module_to_module('WorkflowCreator', 'in',
Opt.module_post[0], 'in')
# wkf.copy_module_to_module('CPACSUpdater','out',Opt.module_post[0],'in') usefuel?
wkf.run_subworkflow(Opt.module_post)
shutil.copy(mi.get_tooloutput_file_path(Opt.module_post[-1]),
cpacs_path_out)
def one_optim_iter():
"""Function to evaluate the value to optimize.
Function 'one_optim_iter' will exectute in order all the module contained
in '...' and extract the ... value from the last CPACS file, this value will
be returned to the optimizer
CPACSUpdater....
"""
# Create the parameter in CPACS with 'CPACSUpdater' module
cpacs_path = mi.get_toolinput_file_path('CPACSUpdater')
cpacs_out_path = mi.get_tooloutput_file_path('CPACSUpdater')
tixi = cpsf.open_tixi(cpacs_path)
wkdir_path = ceaf.create_new_wkdir()
WKDIR_XPATH = '/cpacs/toolspecific/CEASIOMpy/filesPath/wkdirPath'
tixi.updateTextElement(WKDIR_XPATH, wkdir_path)
# TODO: improve this part! (maybe move somewhere else)
# To delete coef from previous iter
aeromap_uid = cpsf.get_value(tixi, SU2_XPATH + '/aeroMapUID')
Coef = apmf.get_aeromap(tixi, aeromap_uid)
apmf.delete_aeromap(tixi, aeromap_uid)
apmf.create_empty_aeromap(tixi, aeromap_uid, 'test_optim')
apmf.save_parameters(tixi, aeromap_uid, Coef)
cpsf.close_tixi(tixi, cpacs_path)
# Update the CPACS file with the parameters contained in optim_var_dict
update_cpacs_file(cpacs_path, cpacs_out_path, optim_var_dict)
# Run optimisation sub workflow
wkf.copy_module_to_module('CPACSUpdater', 'out', module_optim[0], 'in')
wkf.run_subworkflow(module_optim)
wkf.copy_module_to_module(module_optim[-1], 'out', 'CPACSUpdater', 'in')
# Extract results TODO: improve this part
cpacs_results_path = mi.get_tooloutput_file_path(module_optim[-1])
log.info('Results will be extracted from:' + cpacs_results_path)
tixi = cpsf.open_tixi(cpacs_results_path)
mtom = cpsf.get_value(
tixi,
'/cpacs/vehicles/aircraft/model/analyses/massBreakdown/designMasses/mTOM/mass'
)
aeromap_uid = cpsf.get_value(tixi, SU2_XPATH + '/aeroMapUID')
Coef = apmf.get_aeromap(tixi, aeromap_uid)
cl = Coef.cl[0]
cd = Coef.cd[0]
cm = Coef.cms[0]
log.info('=========================')
for key, (name, listval, minval, maxval,
command) in optim_var_dict.items():
log.info(name, ': ', listval[-1])
log.info('Cl/Cd: ' + str(cl / cd))
log.info('Cl: ' + str(cl))
log.info('Cd: ' + str(cd))
log.info('Cd: ' + str(cm))
log.info('MTOM:' + str(mtom))
log.info('(Cl)/MTOM:' + str(cl / mtom))
log.info('=========================')
# TODO: add option to choose what will be returned
# return -mtom
# return -cl
# return cd
# return -cl/cd
return -cl / cd / mtom
# Settings: 'SettingsGUI'
# Geometry and mesh: 'CPACSCreator','CPACS2SUMO','SUMOAutoMesh'
# Weight and balance: 'WeightConventional','WeightUnconventional','BalanceConventional','BalanceUnconventional'
# Aerodynamics: 'CLCalculator','PyTornado','SkinFriction','PlotAeroCoefficients','SU2Run'
# Mission analysis: 'Range'
# Copy-Paste the module you want to execute, they will be run in order
module_pre = ['SettingsGUI','WeightConventional','SkinFriction','CLCalculator','Range']
module_optim = ['WeightConventional','PyTornado']
module_post = []
optim = True
doe = False
# Pre Workflow (only run once)------------------------
wkf.run_subworkflow(module_pre,cpacs_path)
# Optim Workflow ------------------------------------
if optim:
wkf.copy_module_to_module(module_pre[-1],'out','CPACSUpdater','in')
#run_optimizer()
optimize(module_optim)
# Post optim -------------------------------
if module_post:
wkf.copy_module_to_module('CPACSUpdater','out',module_post[0],'in')
wkf.run_subworkflow(module_post)
shutil.copy(mi.get_tooloutput_file_path(module_post[-1]),cpacs_path_out)
else:
shutil.copy(mi.get_tooloutput_file_path(module_optim[-1]),cpacs_path_out)
