def test_basics(self):
# Try a few different values of order and form
# Forward with order 1
self.model.driver.distribution_generator = FiniteDifferenceGenerator(
self.model.driver)
self.results = ListCaseRecorder()
self.model.driver.recorders = [self.results]
self.order = 1
self.model.driver.distribution_generator.form = "FORWARD"
self.model.driver.distribution_generator.order = self.order
self.model.run()
self.verify_results()
# reset driven component values
self.model.driven.x0 = self.model.driven.x1 = self.model.driven.x2 = self.model.driven.x3 = 1.0
# Backward with order 2
self.model.driver.distribution_generator = FiniteDifferenceGenerator(
self.model.driver)
self.results = ListCaseRecorder()
self.model.driver.recorders = [self.results]
self.order = 2
self.model.driver.distribution_generator.form = "BACKWARD"
self.model.driver.distribution_generator.order = self.order
self.model.run()
self.verify_results()
# reset driven component values
self.model.driven.x0 = self.model.driven.x1 = self.model.driven.x2 = self.model.driven.x3 = 1.0
# Central with order 2
self.model.driver.distribution_generator = FiniteDifferenceGenerator(
self.model.driver)
self.results = ListCaseRecorder()
self.model.driver.recorders = [self.results]
self.order = 2
self.model.driver.distribution_generator.form = "CENTRAL"
self.model.driver.distribution_generator.order = self.order
self.model.run()
self.verify_results()
# reset driven component values
self.model.driven.x0 = self.model.driven.x1 = self.model.driven.x2 = self.model.driven.x3 = 1.0
# Central with order 3
self.model.driver.distribution_generator = FiniteDifferenceGenerator(
self.model.driver)
self.results = ListCaseRecorder()
self.model.driver.recorders = [self.results]
self.order = 3
self.model.driver.distribution_generator.form = "CENTRAL"
self.model.driver.distribution_generator.order = self.order
self.model.run()
self.verify_results()
def test_super_simple_backward(self):
model = Assembly()
model.add('driver', DistributionCaseDriver())
model.add('driven', SimpleComponent())
model.driver.workflow.add('driven')
model.driver.distribution_generator = FiniteDifferenceGenerator(model.driver)
model.driver.case_outputs = ['driven.y']
model.driver.add_parameter("driven.x", low=-10., high=10., fd_step = 0.1 )
results = ListCaseRecorder()
model.driver.recorders = [results]
model.driver.distribution_generator.form = "BACKWARD"
model.driver.distribution_generator.order = 2
model.run()
self.assertAlmostEqual( results.cases[0][ 'driven.x' ], 1.0, places = 6 )
self.assertAlmostEqual( results.cases[0][ 'driven.y' ], 2.0, places = 6 )
self.assertAlmostEqual( results.cases[1][ 'driven.x' ], 0.8, places = 6 )
self.assertAlmostEqual( results.cases[1][ 'driven.y' ], 1.6, places = 6 )
self.assertAlmostEqual( results.cases[2][ 'driven.x' ], 0.9, places = 6 )
self.assertAlmostEqual( results.cases[2][ 'driven.y' ], 1.8, places = 6 )
def test_super_simple_forward(self):
model = Assembly()
model.add('driver', DistributionCaseDriver())
model.add('driven', SimpleComponent())
model.driver.workflow.add('driven')
# Forward
model.driver.distribution_generator = FiniteDifferenceGenerator(
model.driver)
model.driver.add_response('driven.y')
model.driver.add_parameter("driven.x", low=-10., high=10., fd_step=0.1)
model.driver.distribution_generator.form = "FORWARD"
model.driver.distribution_generator.order = 2
model.run()
x = model.driver.case_inputs.driven.x
y = model.driver.case_outputs.driven.y
self.assertAlmostEqual(x[0], 1.0, places=6)
self.assertAlmostEqual(y[0], 2.0, places=6)
self.assertAlmostEqual(x[1], 1.1, places=6)
self.assertAlmostEqual(y[1], 2.2, places=6)
self.assertAlmostEqual(x[2], 1.2, places=6)
self.assertAlmostEqual(y[2], 2.4, places=6)
def configure(self):
driver = self.add('driver', DistributionCaseDriver())
self.add('driven', ArrayRosenSuzuki())
driver.workflow.add('driven')
driver.distribution_generator = FiniteDifferenceGenerator(driver)
driver.case_outputs = ['driven.rosen_suzuki']
driver.add_parameter('driven.x', low=-10., high=10.,
fd_step=[0.1, 0.01, 0.001, 0.0001])
def configure(self):
self.add('driver', DistributionCaseDriver())
self.add('driven', RosenSuzukiComponent())
self.driver.workflow.add('driven')
self.driver.distribution_generator = FiniteDifferenceGenerator(self.driver)
self.driver.case_outputs = ['driven.rosen_suzuki']
self.driver.add_parameter("driven.x0", low=-10., high=10., fd_step = 0.1 )
self.driver.add_parameter("driven.x1", low=-10., high=10., fd_step = 0.01 )
self.driver.add_parameter("driven.x2", low=-10., high=10., fd_step = 0.001 )
self.driver.add_parameter("driven.x3", low=-10., high=10., fd_step = 0.0001 )
def test_invalid_input(self):
model = Assembly()
model.add('driver', DistributionCaseDriver())
model.add('driven', SimpleComponent())
model.driver.workflow.add('driven')
model.driver.distribution_generator = FiniteDifferenceGenerator(model.driver)
try:
model.driver.add_parameter("driven.invalid", low=-10., high=10., fd_step = 0.1 )
except AttributeError as err:
self.assertEqual(str(err),
"driver: Can't add parameter 'driven.invalid' because it doesn't exist.")
def test_invalid_form(self):
model = Assembly()
model.add('driver', DistributionCaseDriver())
model.add('driven', SimpleComponent())
model.driver.workflow.add('driven')
model.driver.distribution_generator = FiniteDifferenceGenerator(
model.driver)
model.driver.add_response('driven.y')
model.driver.add_parameter("driven.x", low=-10., high=10., fd_step=0.1)
try:
model.driver.distribution_generator.form = "INVALID_FORM"
except ValueError, err:
msg = ": Variable 'form' must be in ['CENTRAL', 'FORWARD', 'BACKWARD'], " \
"but a value of INVALID_FORM <type 'str'> was specified."
self.assertEqual(str(err), msg)
def test_invalid_case_outputs(self):
model = Assembly()
model.add('driver', DistributionCaseDriver())
model.add('driven', SimpleComponent())
model.driver.workflow.add('driven')
model.driver.distribution_generator = FiniteDifferenceGenerator(
model.driver)
try:
model.driver.add_response('driven.invalid')
except ValueError as err:
self.assertEqual(
str(err), "driver: Can't add response "
"'driven.invalid' because of invalid variables"
" 'driven.invalid'")
else:
self.fail('Expected ValueError')
def test_invalid_case_outputs(self):
model = Assembly()
model.add('driver', DistributionCaseDriver())
model.add('driven', SimpleComponent())
model.driver.workflow.add('driven')
model.driver.distribution_generator = FiniteDifferenceGenerator(model.driver)
model.driver.case_outputs = ['driven.invalid']
model.driver.add_parameter("driven.x", low=-10., high=10., fd_step = 0.1 )
model.driver.error_policy = 'RETRY'
results = ListCaseRecorder()
model.driver.recorders = [results]
model.driver.distribution_generator.form = "FORWARD"
model.driver.distribution_generator.order = 2
model.run()
self.assertEqual(results.cases[0].items()[1][1], _Missing )
def __init__(self, *args, **kwargs):
super(MyModel, self).__init__(*args, **kwargs)
self.add('driver', DistributionCaseDriver())
self.add('driven', RosenSuzukiComponent())
self.driver.workflow.add('driven')
self.driver.distribution_generator = FiniteDifferenceGenerator(
self.driver)
self.driver.case_outputs = ['driven.rosen_suzuki']
self.driver.add_parameter("driven.x0", low=-10., high=10., fd_step=0.1)
self.driver.add_parameter("driven.x1",
low=-10.,
high=10.,
fd_step=0.01)
self.driver.add_parameter("driven.x2",
low=-10.,
high=10.,
fd_step=0.001)
self.driver.add_parameter("driven.x3",
low=-10.,
high=10.,
fd_step=0.0001)
def __init__(self, model, comps, wrt, outs, stepsize=1.0e-6, order=1,
form='CENTRAL'):
''' Takes a model and a list of component names in that model. The
model is deepcopied to create a copy. All but the needed comps are
removed from the model.
model: Assembly
Parent assembly of the components we want to finite difference.
comps: list( string )
List of component names that we want to finite difference as a
group.
wrt: list( string )
List of variable paths to use as finite difference inputs.
outs: list( string )
List of variable paths to return as outputs.
stepsize: float
Default stepsize to use.
order: int
Finite Difference order. Only first order is supported right now.
form: string
Choose from 'CENTRAL', 'FORWARD', and "BACKWARD'. Default is central
differencing.
'''
# Copy model. We need to null out the reference to the parent before
# we copy.
save_parent = model.parent
model.parent = None
try:
self.model = deepcopy(model)
finally:
model.parent = save_parent
# Get rid of the comps we don't need
for item in self.model.list_containers():
if item not in comps + ['driver']:
self.model.remove(item)
# Remove all connections to the assembly boundary
bdy_inputs = self.model.list_inputs()
bdy_outputs = self.model.list_outputs()
for conn in self.model.list_connections():
if conn[0] in bdy_inputs or conn[1] in bdy_outputs:
self.model.disconnect(conn[0], conn[1])
# Distribution driver to drive the finite difference calculation
self.model.add('driver', DistributionCaseDriver())
gen = FiniteDifferenceGenerator(self.model.driver)
self.model.driver.distribution_generator = gen
self.model.driver.workflow.add(comps)
for item in wrt:
self.model.driver.add_parameter(item, low=-1e99, high=1e99,
fd_step=stepsize)
self.model.driver.case_outputs = outs
self.model.driver.ffd_order = 1
gen.num_parameters = len(wrt)
gen.form = form
gen.order = order
# Save a reference to the original model so that we can increment the
# execution counter as needed.
self.copy_source = model
# All execution counts should be reset to zero.
for comp in self.model.driver.workflow.__iter__():
comp.exec_count = 0
comp.derivative_exec_count = 0
def __init__(self,
model,
comps,
wrt,
outs,
stepsize=1.0e-6,
order=1,
form='CENTRAL'):
''' Takes a model and a list of component names in that model. The
model is deepcopied to create a copy. All but the needed comps are
removed from the model.
model: Assembly
Parent assembly of the components we want to finite difference.
comps: list( string )
List of component names that we want to finite difference as a
group.
wrt: list( string )
List of variable paths to use as finite difference inputs.
outs: list( string )
List of variable paths to return as outputs.
stepsize: float
Default stepsize to use.
order: int
Finite Difference order. Only first order is supported right now.
form: string
Choose from 'CENTRAL', 'FORWARD', and "BACKWARD'. Default is central
differencing.
'''
# Copy model. We need to null out the reference to the parent before
# we copy.
save_parent = model.parent
model.parent = None
try:
self.model = deepcopy(model)
finally:
model.parent = save_parent
# Get rid of the comps we don't need
for item in self.model.list_containers():
if item not in comps + ['driver']:
self.model.remove(item)
# Remove all connections to the assembly boundary
bdy_inputs = self.model.list_inputs()
bdy_outputs = self.model.list_outputs()
for conn in self.model.list_connections():
if conn[0] in bdy_inputs or conn[1] in bdy_outputs:
self.model.disconnect(conn[0], conn[1])
# Distribution driver to drive the finite difference calculation
self.model.add('driver', DistributionCaseDriver())
gen = FiniteDifferenceGenerator(self.model.driver)
self.model.driver.distribution_generator = gen
self.model.driver.workflow.add(comps)
for item in wrt:
self.model.driver.add_parameter(item,
low=-1e99,
high=1e99,
fd_step=stepsize)
self.model.driver.case_outputs = outs
self.model.driver.ffd_order = 1
gen.num_parameters = len(wrt)
gen.form = form
gen.order = order
# Save a reference to the original model so that we can increment the
# execution counter as needed.
self.copy_source = model
# All execution counts should be reset to zero.
for comp in self.model.driver.workflow.__iter__():
comp.exec_count = 0
comp.derivative_exec_count = 0
