def run_iteration(self):
""" The CONMIN driver iteration."""
#self._logger.debug('iter_count = %d' % self.iter_count)
#self._logger.debug('objective = %f' % self.cnmn1.obj)
#self._logger.debug('design vals = %s' % self.design_vals[:-2])
# TODO: 'step around' ill-behaved cases.
self._load_common_blocks()
#print "Iteration %s: " % self.get_pathname(), self.iter_count
#print "Before"
#print self.design_vals
try:
(self.design_vals,
self._scal, self.d_const, self.s,
self.g1, self.g2, self._b, self._c,
self._cons_is_linear,
self.cons_active_or_violated, self._ms1) = \
conmin.conmin(self.design_vals,
self._lower_bounds, self._upper_bounds,
self.constraint_vals,
self._scal, self.d_obj,
self.d_const,
self.s, self.g1, self.g2, self._b, self._c,
self._cons_is_linear,
self.cons_active_or_violated, self._ms1)
except Exception, err:
self._logger.error(str(err))
raise
def run_iteration(self):
""" The CONMIN driver iteration."""
#self._logger.debug('iter_count = %d' % self.iter_count)
#self._logger.debug('objective = %f' % self.cnmn1.obj)
#self._logger.debug('design vals = %s' % self.design_vals[:-2])
# TODO: 'step around' ill-behaved cases.
self._load_common_blocks()
#print "Iteration %s: " % self.get_pathname(), self.iter_count
#print "Before"
#print self.design_vals
try:
(self.design_vals,
self._scal, self.d_const, self.s,
self.g1, self.g2, self._b, self._c,
self._cons_is_linear,
self.cons_active_or_violated, self._ms1) = \
conmin.conmin(self.design_vals,
self._lower_bounds, self._upper_bounds,
self.constraint_vals,
self._scal, self.d_obj,
self.d_const,
self.s, self.g1, self.g2, self._b, self._c,
self._cons_is_linear,
self.cons_active_or_violated, self._ms1)
except Exception, err:
self._logger.error(str(err))
raise
def run_iteration(self):
""" The CONMIN driver iteration."""
#self._logger.debug('iter_count = %d' % self.iter_count)
#self._logger.debug('objective = %f' % self.cnmn1.obj)
#self._logger.debug('design vals = %s' % self.design_vals[:-2])
# TODO: 'step around' ill-behaved cases.
self._load_common_blocks()
#print "Iteration %s: " % self.get_pathname(), self.iter_count
#print "Before"
#print self.design_vals
try:
(self.design_vals,
self._scal, self.d_const, self.s,
self.g1, self.g2, self._b, self._c,
self._cons_is_linear,
self.cons_active_or_violated, self._ms1) = \
conmin.conmin(self.design_vals,
self._lower_bounds, self._upper_bounds,
self.constraint_vals,
self._scal, self.d_obj,
self.d_const,
self.s, self.g1, self.g2, self._b, self._c,
self._cons_is_linear,
self.cons_active_or_violated, self._ms1)
except Exception as err:
self._logger.error(str(err))
raise
self._save_common_blocks()
# calculate objective and constraints
if self.cnmn1.info == 1:
# Note. CONMIN is driving the finite difference estimation of the
# gradient. However, we still take advantage of a component's
# user-defined gradients via Fake Finite Difference.
if self.cnmn1.igoto == 3:
# update the parameters in the model
self.set_parameters(self.design_vals[:-2])
# Run model under Fake Finite Difference
self.calc_derivatives(first=True, savebase=True)
self.ffd_order = 1
super(CONMINdriver, self).run_iteration()
self.ffd_order = 0
else:
# update the parameters in the model
self.set_parameters(self.design_vals[:-2])
# Run the model for this step
super(CONMINdriver, self).run_iteration()
# calculate objective
self.cnmn1.obj = self.eval_objective()
# update constraint value array
self.constraint_vals[0:self.total_ineq_constraints()] = \
self.eval_ineq_constraints()
#self._logger.debug('constraints = %s' % self.constraint_vals)
# calculate gradient of constraints and gradient of objective
# We also have to determine which constraints are active/violated, and
# only return gradients of active/violated constraints.
elif self.cnmn1.info == 2 and self.cnmn1.nfdg == 1:
# Sometimes, CONMIN wants the derivatives at a different point.
self.set_parameters(self.design_vals[:-2])
super(CONMINdriver, self).run_iteration()
inputs = self.list_param_group_targets()
obj = self.list_objective_targets()
con = self.list_ineq_constraint_targets()
J = self.workflow.calc_gradient(inputs, obj + con)
nobj = len(obj)
self.d_obj[:-2] = J[0:nobj, :].ravel()
for i in range(len(self.cons_active_or_violated)):
self.cons_active_or_violated[i] = 0
self.cnmn1.nac = 0
for i in range(self.total_ineq_constraints()):
if self.constraint_vals[i] >= self.cnmn1.ct:
self.cons_active_or_violated[self.cnmn1.nac] = i+1
self.d_const[:-2, self.cnmn1.nac] = J[nobj+i, :]
self.cnmn1.nac += 1
else:
self.raise_exception('Unexpected value for flag INFO returned'
' from CONMIN.', RuntimeError)
def run_iteration(self):
""" The CONMIN driver iteration."""
#self._logger.debug('iter_count = %d' % self.iter_count)
#self._logger.debug('objective = %f' % self.cnmn1.obj)
#self._logger.debug('design vals = %s' % self.design_vals[:-2])
# TODO: 'step around' ill-behaved cases.
self._load_common_blocks()
#print "Iteration %s: " % self.get_pathname(), self.iter_count
#print "Before"
#print self.design_vals
try:
(self.design_vals,
self._scal, self.d_const, self.s,
self.g1, self.g2, self._b, self._c,
self._cons_is_linear,
self.cons_active_or_violated, self._ms1) = \
conmin.conmin(self.design_vals,
self._lower_bounds, self._upper_bounds,
self.constraint_vals,
self._scal, self.d_obj,
self.d_const,
self.s, self.g1, self.g2, self._b, self._c,
self._cons_is_linear,
self.cons_active_or_violated, self._ms1)
except Exception as err:
self._logger.error(str(err))
raise
self._save_common_blocks()
# calculate objective and constraints
if self.cnmn1.info == 1:
# Note. CONMIN is driving the finite difference estimation of the
# gradient.
if self.cnmn1.igoto == 3:
# update the parameters in the model
self.set_parameters(self.design_vals[:-2])
super(CONMINdriver, self).run_iteration()
else:
# update the parameters in the model
self.set_parameters(self.design_vals[:-2])
# Run the model for this step
super(CONMINdriver, self).run_iteration()
# calculate objective
self.cnmn1.obj = self.eval_objective()
# update constraint value array
self.constraint_vals[0:self.total_ineq_constraints()] = \
self.eval_ineq_constraints()
#self._logger.debug('constraints = %s' % self.constraint_vals)
# calculate gradient of constraints and gradient of objective
# We also have to determine which constraints are active/violated, and
# only return gradients of active/violated constraints.
elif self.cnmn1.info == 2 and self.cnmn1.nfdg == 1:
# Sometimes, CONMIN wants the derivatives at a different point.
self.set_parameters(self.design_vals[:-2])
super(CONMINdriver, self).run_iteration()
inputs = self.list_param_group_targets()
obj = self.list_objective_targets()
con = self.list_ineq_constraint_targets()
J = self.workflow.calc_gradient(inputs, obj + con)
nobj = len(obj)
self.d_obj[:-2] = J[0:nobj, :].ravel()
for i in range(len(self.cons_active_or_violated)):
self.cons_active_or_violated[i] = 0
self.cnmn1.nac = 0
for i in range(self.total_ineq_constraints()):
if self.constraint_vals[i] >= self.cnmn1.ct:
self.cons_active_or_violated[self.cnmn1.nac] = i + 1
self.d_const[:-2, self.cnmn1.nac] = J[nobj + i, :]
self.cnmn1.nac += 1
else:
self.raise_exception(
'Unexpected value for flag INFO returned'
' from CONMIN.', RuntimeError)
