本文整理汇总了Python中openmdao.core.Problem.check_partial_derivatives方法的典型用法代码示例。如果您正苦于以下问题：Python Problem.check_partial_derivatives方法的具体用法？Python Problem.check_partial_derivatives怎么用？Python Problem.check_partial_derivatives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.check_partial_derivatives方法的5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: test_derivatives
# 需要导入模块: from openmdao.core import Problem [as 别名]
# 或者: from openmdao.core.Problem import check_partial_derivatives [as 别名]
def test_derivatives(self):
meta = MetaModel()
meta.add_param('x', 0.)
meta.add_output('f', 0.)
meta.default_surrogate = FloatKrigingSurrogate()
prob = Problem(Group())
prob.root.add('meta', meta, promotes=['x'])
prob.root.add('p', IndepVarComp('x', 0.), promotes=['x'])
prob.setup(check=False)
prob['meta.train:x'] = [0., .25, .5, .75, 1.]
prob['meta.train:f'] = [1., .75, .5, .25, 0.]
prob['x'] = 0.125
prob.run()
Jf = prob.calc_gradient(['x'], ['meta.f'], mode='fwd')
Jr = prob.calc_gradient(['x'], ['meta.f'], mode='rev')
assert_rel_error(self, Jf[0][0], -1.00011, 1.0e-5)
assert_rel_error(self, Jr[0][0], -1.00011, 1.0e-5)
stream = cStringIO()
prob.check_partial_derivatives(out_stream=stream)
abs_errors = findall('Absolute Error \(.+\) : (.+)', stream.getvalue())
self.assertTrue(len(abs_errors) > 0)
for match in abs_errors:
abs_error = float(match)
self.assertTrue(abs_error < 1e-6)示例2: test_derivatives
# 需要导入模块: from openmdao.core import Problem [as 别名]
# 或者: from openmdao.core.Problem import check_partial_derivatives [as 别名]
def test_derivatives(self):
meta = MetaModel()
meta.add_param("x", 0.0)
meta.add_output("f", 0.0)
meta.default_surrogate = FloatKrigingSurrogate()
prob = Problem(Group())
prob.root.add("meta", meta, promotes=["x"])
prob.root.add("p", ParamComp("x", 0.0), promotes=["x"])
prob.setup(check=False)
prob["meta.train:x"] = [0.0, 0.25, 0.5, 0.75, 1.0]
prob["meta.train:f"] = [1.0, 0.75, 0.5, 0.25, 0.0]
prob["x"] = 0.125
prob.run()
stream = cStringIO()
prob.check_partial_derivatives(out_stream=stream)
abs_errors = findall("Absolute Error \(.+\) : (.+)", stream.getvalue())
self.assertTrue(len(abs_errors) > 0)
for match in abs_errors:
abs_error = float(match)
self.assertTrue(abs_error < 1e-6)示例3: test_derivatives
# 需要导入模块: from openmdao.core import Problem [as 别名]
# 或者: from openmdao.core.Problem import check_partial_derivatives [as 别名]
def test_derivatives(self):
meta = MetaModel()
meta.add_param('x', 0.)
meta.add_output('f', 0.)
meta.default_surrogate = FloatKrigingSurrogate()
prob = Problem(Group())
prob.root.add('meta', meta, promotes=['x'])
prob.root.add('p', ParamComp('x', 0.), promotes=['x'])
prob.setup(check=False)
prob['meta.train:x'] = [0., .25, .5, .75, 1.]
prob['meta.train:f'] = [1., .75, .5, .25, 0.]
prob['x'] = 0.125
prob.run()
stream = cStringIO()
prob.check_partial_derivatives(out_stream=stream)
abs_errors = findall('Absolute Error \(.+\) : (.+)', stream.getvalue())
self.assertTrue(len(abs_errors) > 0)
for match in abs_errors:
abs_error = float(match)
self.assertTrue(abs_error < 1e-6)示例4: test_simple_array_model2
# 需要导入模块: from openmdao.core import Problem [as 别名]
# 或者: from openmdao.core.Problem import check_partial_derivatives [as 别名]
def test_simple_array_model2(self):
prob = Problem()
prob.root = Group()
comp = prob.root.add('comp', ExecComp('y = mat.dot(x)',
x=np.zeros((2,)), y=np.zeros((2,)),
mat=np.array([[2.,7.],[5.,-3.]])))
p1 = prob.root.add('p1', ParamComp('x', np.ones([2])))
prob.root.connect('p1.x', 'comp.x')
prob.setup(check=False)
prob.run()
data = prob.check_partial_derivatives(out_stream=None)
assert_rel_error(self, data['comp'][('y','x')]['abs error'][0], 0.0, 1e-5)
assert_rel_error(self, data['comp'][('y','x')]['abs error'][1], 0.0, 1e-5)
assert_rel_error(self, data['comp'][('y','x')]['abs error'][2], 0.0, 1e-5)
assert_rel_error(self, data['comp'][('y','x')]['rel error'][0], 0.0, 1e-5)
assert_rel_error(self, data['comp'][('y','x')]['rel error'][1], 0.0, 1e-5)
assert_rel_error(self, data['comp'][('y','x')]['rel error'][2], 0.0, 1e-5)示例5: test_simple_array_model
# 需要导入模块: from openmdao.core import Problem [as 别名]
# 或者: from openmdao.core.Problem import check_partial_derivatives [as 别名]
def test_simple_array_model(self):
prob = Problem()
prob.root = Group()
prob.root.add('comp', ExecComp(['y[0]=2.0*x[0]+7.0*x[1]',
'y[1]=5.0*x[0]-3.0*x[1]'],
x=np.zeros([2]), y=np.zeros([2])))
prob.root.add('p1', ParamComp('x', np.ones([2])))
prob.root.connect('p1.x', 'comp.x')
prob.setup(check=False)
prob.run()
data = prob.check_partial_derivatives(out_stream=None)
assert_rel_error(self, data['comp'][('y','x')]['abs error'][0], 0.0, 1e-5)
assert_rel_error(self, data['comp'][('y','x')]['abs error'][1], 0.0, 1e-5)
assert_rel_error(self, data['comp'][('y','x')]['abs error'][2], 0.0, 1e-5)
assert_rel_error(self, data['comp'][('y','x')]['rel error'][0], 0.0, 1e-5)
assert_rel_error(self, data['comp'][('y','x')]['rel error'][1], 0.0, 1e-5)
assert_rel_error(self, data['comp'][('y','x')]['rel error'][2], 0.0, 1e-5)