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 _delete(self, event=None):
firstIndex = self.listBox.curselection()[0]
self.selected_list = [self.listBox.get(i) for i in self.listBox.curselection()]
aeromap_uid = self.selected_list[0]
apm.delete_aeromap(self.tixi,aeromap_uid)
self._update()
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 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