本文整理汇总了Python中openmdao.core.Problem.driver方法的典型用法代码示例。如果您正苦于以下问题：Python Problem.driver方法的具体用法？Python Problem.driver怎么用？Python Problem.driver使用的例子？那么恭喜您, 这里精选的方法代码示例或许可以为您提供帮助。您也可以进一步了解该方法所在类openmdao.core.Problem的用法示例。
在下文中一共展示了Problem.driver方法的2个代码示例，这些例子默认根据受欢迎程度排序。您可以为喜欢或者感觉有用的代码点赞，您的评价将有助于系统推荐出更棒的Python代码示例。
示例1: setUp
# 需要导入模块: from openmdao.core import Problem [as 别名]
# 或者: from openmdao.core.Problem import driver [as 别名]
def setUp(self):
if SKIP:
raise unittest.SkipTest('Could not import pyOptSparseDriver. Is pyoptsparse installed?')
prob = Problem(impl=impl)
root = prob.root = Group()
#root.ln_solver = lin_solver()
root.ln_solver = LinearGaussSeidel()
par = root.add('par', ParallelGroup())
par.ln_solver = LinearGaussSeidel()
ser1 = par.add('ser1', Group())
ser1.ln_solver = LinearGaussSeidel()
ser1.add('p1', IndepVarComp('x', np.zeros([2])))
ser1.add('comp', SimpleArrayComp())
ser1.add('con', ExecComp('c = y - 20.0', c=np.array([0.0, 0.0]),
y=np.array([0.0, 0.0])))
ser1.add('obj', ExecComp('o = y[0]', y=np.array([0.0, 0.0])))
ser2 = par.add('ser2', Group())
ser2.ln_solver = LinearGaussSeidel()
ser2.add('p1', IndepVarComp('x', np.zeros([2])))
ser2.add('comp', SimpleArrayComp())
ser2.add('con', ExecComp('c = y - 30.0', c=np.array([0.0, 0.0]),
y=np.array([0.0, 0.0])))
ser2.add('obj', ExecComp('o = y[0]', y=np.array([0.0, 0.0])))
root.add('total', ExecComp('obj = x1 + x2'))
ser1.connect('p1.x', 'comp.x')
ser1.connect('comp.y', 'con.y')
ser1.connect('comp.y', 'obj.y')
root.connect('par.ser1.obj.o', 'total.x1')
ser2.connect('p1.x', 'comp.x')
ser2.connect('comp.y', 'con.y')
ser2.connect('comp.y', 'obj.y')
root.connect('par.ser2.obj.o', 'total.x2')
prob.driver = pyOptSparseDriver()
prob.driver.add_desvar('par.ser1.p1.x', low=-50.0, high=50.0)
prob.driver.add_desvar('par.ser2.p1.x', low=-50.0, high=50.0)
prob.driver.add_objective('total.obj')
prob.driver.add_constraint('par.ser1.con.c', equals=0.0)
prob.driver.add_constraint('par.ser2.con.c', equals=0.0)
self.prob = prob示例2: openmdao_sellar_converged
# 需要导入模块: from openmdao.core import Problem [as 别名]
# 或者: from openmdao.core.Problem import driver [as 别名]
def openmdao_sellar_converged():
from openmdao.core import Problem
from openmdao.drivers import ScipyOptimizer
top = Problem()
top.root = SellarDerivatives()
top.driver = ScipyOptimizer()
top.driver.options['optimizer'] = 'SLSQP'
top.driver.options['tol'] = 1.0e-8
top.driver.options['disp'] = False
top.driver.add_desvar('z', low=np.array([-10.0, 0.0]),
high=np.array([10.0, 10.0]))
top.driver.add_desvar('x', low=0.0, high=10.0)
top.driver.add_objective('obj')
top.driver.add_constraint('con1', upper=0.0)
top.driver.add_constraint('con2', upper=0.0)
top.setup(check=False)
top.run()
return top