def run_iteration(self):
""" Note: cobyla controls the looping."""
try:
self.iact, self.error_code, self.nfvals = \
cobyla(self._func, self.nparam, self.ncon, self.x,
self.rhobeg, self.rhoend, self.iprint, self.maxfun,
self.work_vector, self.iact, self.error_code, self.nfvals,
self.iout, self.output_filename, self.ff, self.gg)
except Exception as err:
self._logger.error(str(err))
raise
if self.iprint > 0:
closeunit(self.iout)
# Log any errors
if self.error_code != 0:
self._logger.warning(self.error_messages[self.error_code])
# Iteration is complete
self._continue = False
def run_iteration(self):
""" Note: cobyla controls the looping."""
try:
self.iact, self.error_code, self.nfvals = \
cobyla(self._func, self.nparam, self.ncon, self.x,
self.rhobeg, self.rhoend, self.iprint, self.maxfun,
self.work_vector, self.iact, self.error_code, self.nfvals,
self.iout, self.output_filename, self.ff, self.gg)
except Exception as err:
self._logger.error(str(err))
raise
if self.iprint > 0:
closeunit(self.iout)
# Log any errors
if self.error_code != 0:
self._logger.warning(self.error_messages[self.error_code])
# Iteration is complete
self._continue = False
class COBYLAdriver(Driver):
"""Minimize a function using the Constrained Optimization BY Linear
Approximation (COBYLA) method.
COBYLA is gradient-free and can handle inequality constraints.
Note: Constraints should be added using the OpenMDAO convention
(positive = violated).
"""
implements(IHasParameters, IHasIneqConstraints, IHasObjective, IOptimizer)
# pylint: disable-msg=E1101
rhobeg = Float(1.0, iotype='in',
desc = 'Reasonable initial changes to the variables.')
rhoend = Float(1e-4, iotype='in',
desc = 'Final accuracy in the optimization (not precisely guaranteed).')
iprint = Enum(1, [0, 1, 2, 3], iotype='in',
desc = 'Controls the frequency of output: 0 (no output),1,2,3.')
maxfun = Int(1000, iotype='in',
desc = 'Maximum number of function evaluations.')
iout = Int(6, iotype='in',
desc = 'Fortran output unit. Leave this at 6 for STDOUT.')
output_filename = Str('cobyla.out', iotype='in',
desc = 'Name of output file (if iout not 6).')
error_code = Int(0, iotype='out',
desc = 'Error code returned from COBYLA.')
def __init__(self):
super(COBYLAdriver, self).__init__()
self.error_messages = {
1 : 'Max. number of function evaluations reached',
2 : 'Rounding errors are becoming damaging'
}
self.x = zeros(0,'d')
self.work_vector = zeros(0,'d')
self.gg = zeros(0,'d')
self.iact = zeros(0,'d')
self.ff = 0
self.nfvals = 0
def start_iteration(self):
"""Perform initial setup before iteration loop begins."""
self.nparam = len(self.get_parameters().values())
self.ncon = len(self.get_ineq_constraints())
self.ncon += 2*self.nparam
self.x = zeros(self.nparam,'d')
self.g = zeros(self.ncon,'d')
self.work_vector = zeros(self.ncon,'d')
# get the initial values of the parameters
params = self.get_parameters().values()
for i, val in enumerate(params):
self.x[i] = val.evaluate(self.parent)
n = self.nparam
m = self.ncon
self.work_vector = zeros([n*(3*n+2*m+11)+4*m+6],'d')
self.iact = zeros([m+1],'i')
self.gg = zeros([m],'d')
self._continue = True
def run_iteration(self):
""" Note: cobyla controls the looping."""
try:
self.iact, self.error_code, self.nfvals = \
cobyla(self._func, self.nparam, self.ncon, self.x, \
self.rhobeg, self.rhoend, self.iprint, self.maxfun, \
self.work_vector, self.iact, self.error_code, self.nfvals, \
self.iout, self.output_filename, self.ff, self.gg)
except Exception, err:
self._logger.error(str(err))
raise
if self.iprint > 0 :
closeunit(self.iout)
# Log any errors
if self.error_code != 0 :
self._logger.warning(self.error_messages[self.error_code])
# Iteration is complete
self._continue = False