def __call__(self, optimizer, options=None):
""" Run optimization """
system = self._system
variables = self._variables
opt_prob = OptProblem('Optimization', self.obj_func)
for dv_name in variables['dv'].keys():
dv = variables['dv'][dv_name]
dv_id = dv['ID']
value = dv['value']
lower = dv['lower']
upper = dv['upper']
size = system.vec['u'](dv_id).shape[0]
opt_prob.addVarGroup(dv_name, size, value=value,
lower=lower, upper=upper)
opt_prob.finalizeDesignVariables()
for func_name in variables['func'].keys():
func = variables['func'][func_name]
func_id = func['ID']
lower = func['lower']
upper = func['upper']
linear = func['linear']
get_jacs = func['get_jacs']
size = system.vec['u'](func_id).shape[0]
if lower is None and upper is None:
opt_prob.addObj(func_name)
else:
if func['get_jacs'] is None:
opt_prob.addConGroup(func_name, size,
lower=lower, upper=upper)
else:
jacs_var = get_jacs()
dv_names = []
jacs = {}
for dv_var in jacs_var:
dv_id = self._system.get_id(dv_var)
dv_name = self._get_name(dv_id)
dv_names.append(dv_name)
jacs[dv_name] = jacs_var[dv_var]
opt_prob.addConGroup(func_name, size,
wrt=dv_names,
jac=jacs, linear=linear,
lower=lower, upper=upper)
if options is None:
options = {}
opt = Optimizer(optimizer, options=options)
opt.setOption('Iterations limit', int(1e6))
#opt.setOption('Verify level', 3)
sol = opt(opt_prob, sens=self.sens_func, storeHistory='hist.hst')
print sol
def __call__(self, optimizer, options=None):
""" Run optimization """
system = self._system
variables = self._variables
opt_prob = OptProblem('Optimization', self.obj_func)
for dv_name in variables['dv'].keys():
dv = variables['dv'][dv_name]
dv_id = dv['ID']
value = dv['value']
lower = dv['lower']
upper = dv['upper']
size = system.vec['u'](dv_id).shape[0]
opt_prob.addVarGroup(dv_name,
size,
value=value,
lower=lower,
upper=upper)
opt_prob.finalizeDesignVariables()
for func_name in variables['func'].keys():
func = variables['func'][func_name]
func_id = func['ID']
lower = func['lower']
upper = func['upper']
linear = func['linear']
get_jacs = func['get_jacs']
size = system.vec['u'](func_id).shape[0]
if lower is None and upper is None:
opt_prob.addObj(func_name)
else:
if func['get_jacs'] is None:
opt_prob.addConGroup(func_name,
size,
lower=lower,
upper=upper)
else:
jacs_var = get_jacs()
dv_names = []
jacs = {}
for dv_var in jacs_var:
dv_id = self._system.get_id(dv_var)
dv_name = self._get_name(dv_id)
dv_names.append(dv_name)
jacs[dv_name] = jacs_var[dv_var]
opt_prob.addConGroup(func_name,
size,
wrt=dv_names,
jac=jacs,
linear=linear,
lower=lower,
upper=upper)
if options is None:
options = {}
opt = Optimizer(optimizer, options=options)
opt.setOption('Iterations limit', int(1e6))
#opt.setOption('Verify level', 3)
sol = opt(opt_prob, sens=self.sens_func, storeHistory='hist.hst')
print sol
optProb.finalizeDesignVariables()
if constrained:
optProb.addCon("con", upper=0, scale=1.0)
optProb.addObj("obj")
# Create optimizer
opt = OPT(args.opt, options=optOptions)
if testHist == "no":
# Just run a normal run
sol = opt(optProb, sens=sens, sensMode=sensMode)
# print(sol.fStar)
print(sol)
else:
# First call just does 10 iterations
if args.opt.lower() == "snopt":
opt.setOption("Major iterations limit", 10)
solSnopt1 = opt(optProb,
sens=sens,
sensMode="pgc",
storeHistory="opt_hist")
# Now we are allowed to do 50
opt.setOption("Major iterations limit", 50)
if testHist == "hot":
solSnopt2 = opt(optProb,
sens=sens,
sensMode=sensMode,
hotStart="opt_hist",
storeHistory="opt_hist")
else:
solSnopt2 = opt(optProb,
optProb.finalizeDesignVariables()
if constrained:
optProb.addCon('con', upper=0, scale=1.0)
optProb.addObj('obj')
# Create optimizer
opt = OPT(args.opt, options=optOptions)
if testHist == 'no':
# Just run a normal run
sol = opt(optProb, sens=sens, sensMode=sensMode)
# print(sol.fStar)
print(sol)
else:
# First call just does 10 iterations
if args.opt.lower() == 'snopt':
opt.setOption('Major iterations limit', 10)
solSnopt1 = opt(optProb,
sens=sens,
sensMode='pgc',
storeHistory='opt_hist')
# Now we are allowed to do 50
opt.setOption('Major iterations limit', 50)
if testHist == 'hot':
solSnopt2 = opt(optProb,
sens=sens,
sensMode=sensMode,
hotStart='opt_hist',
storeHistory='opt_hist')
else:
solSnopt2 = opt(optProb,
def __call__(self, optimizer, options=None):
""" Run optimization """
system = self._system
variables = self._variables
opt_prob = OptProblem('Optimization', self.obj_func)
for dv_name in variables['dv'].keys():
dv = variables['dv'][dv_name]
dv_id = dv['ID']
if dv['value'] is not None:
value = dv['value']
else:
value = system.vec['u'](dv_id)
scale = dv['scale']
lower = dv['lower']
upper = dv['upper']
size = system.vec['u'](dv_id).shape[0]
opt_prob.addVarGroup(dv_name, size, value=value, scale=scale,
lower=lower, upper=upper)
opt_prob.finalizeDesignVariables()
for func_name in variables['func'].keys():
func = variables['func'][func_name]
func_id = func['ID']
lower = func['lower']
upper = func['upper']
linear = func['linear']
get_jacs = func['get_jacs']
sys = func['sys']
size = system.vec['u'](func_id).shape[0]
if lower is None and upper is None:
opt_prob.addObj(func_name)
else:
if get_jacs is not None:
jacs_var = get_jacs()
dv_names = []
jacs = {}
for dv_var in jacs_var:
dv_id = self._system.get_id(dv_var)
dv_name = self._get_name(dv_id)
dv_names.append(dv_name)
jacs[dv_name] = jacs_var[dv_var]
opt_prob.addConGroup(func_name, size,
wrt=dv_names,
jac=jacs, linear=linear,
lower=lower, upper=upper)
elif sys is not None:
dv_names = []
for dv_name in variables['dv'].keys():
dv_id = variables['dv'][dv_name]['ID']
if dv_id in sys.vec['u']:
dv_names.append(dv_name)
opt_prob.addConGroup(func_name, size,
wrt=dv_names,
lower=lower, upper=upper)
else:
opt_prob.addConGroup(func_name, size,
lower=lower, upper=upper)
if options is None:
options = {}
opt = Optimizer(optimizer, options=options)
opt.setOption('Iterations limit', int(1e6))
#opt.setOption('Verify level', 3)
sol = opt(opt_prob, sens=self.sens_func, storeHistory='hist.hst')
print sol
try:
exit_status = sol.optInform['value']
self.exit_flag = 1
if exit_status > 2: # bad
self.exit_flag = 0
except KeyError: #nothing is here, so something bad happened!
self.exit_flag = 0
