class Driver(Component):
""" A Driver iterates over a workflow of Components until some condition
is met. """
implements(IDriver, IHasEvents)
recorders = List(Slot(ICaseRecorder, required=False),
desc='Case recorders for iteration data.')
# Extra variables for printing
printvars = List(
Str,
iotype='in',
desc='List of extra variables to output in the recorders.')
# set factory here so we see a default value in the docs, even
# though we replace it with a new Dataflow in __init__
workflow = Slot(Workflow,
allow_none=True,
required=True,
factory=Dataflow,
hidden=True)
def __init__(self, doc=None):
self._iter = None
super(Driver, self).__init__(doc=doc)
self.workflow = Dataflow(self)
self.force_execute = True
# This flag is triggered by adding or removing any parameters,
# constraints, or objectives.
self._invalidated = False
def _workflow_changed(self, oldwf, newwf):
if newwf is not None:
newwf._parent = self
def get_expr_scope(self):
"""Return the scope to be used to evaluate ExprEvaluators."""
return self.parent
def _invalidate(self):
""" Method for delegates to declare that the driver is in an invalid
state so that isvalid() returns false. Presently, this is called when
a constraint/objective/parameter is set, removed, or cleared.
"""
self._invalidated = True
self._set_exec_state('INVALID')
def is_valid(self):
"""Return False if any Component in our workflow(s) is invalid,
or if any of our variables is invalid, or if the parameters,
constraints, or objectives have changed.
"""
if super(Driver, self).is_valid() is False:
return False
# force exection if any param, obj, or constraint has changed.
if self._invalidated:
return False
# force execution if any component in the workflow is invalid
for comp in self.workflow.get_components():
if not comp.is_valid():
return False
return True
def check_config(self):
"""Verify that our workflow is able to resolve all of its components."""
# workflow will raise an exception if it can't resolve a Component
super(Driver, self).check_config()
self._update_workflow()
def _update_workflow(self):
"""Updates workflow contents based on driver dependencies."""
# if workflow is not defined, or if it contains only Drivers, try to
# use parameters, objectives and/or constraint expressions to
# determine the necessary workflow members
try:
iterset = set(c.name for c in self.iteration_set())
alldrivers = all([
isinstance(c, Driver) for c in self.workflow.get_components()
])
if len(self.workflow) == 0:
pass
elif alldrivers is True:
reqcomps = self._get_required_compnames()
self.workflow.add(
[name for name in reqcomps if name not in iterset])
# calling get_components() here just makes sure that all of the
# components can be resolved
comps = self.workflow.get_components()
except Exception as err:
self.raise_exception(str(err), type(err))
def iteration_set(self):
"""Return a set of all Components in our workflow(s) and
recursively in any workflow in any Driver in our workflow(s).
"""
allcomps = set()
if len(self.workflow) == 0:
for compname in self._get_required_compnames():
self.workflow.add(compname)
for child in self.workflow.get_components():
allcomps.add(child)
if has_interface(child, IDriver):
allcomps.update(child.iteration_set())
return allcomps
@rbac(('owner', 'user'))
def get_expr_depends(self):
"""Returns a list of tuples of the form (src_comp_name,
dest_comp_name) for each dependency introduced by any ExprEvaluators
in this Driver, ignoring any dependencies on components that are
inside of this Driver's iteration set.
"""
iternames = set([c.name for c in self.iteration_set()])
conn_list = super(Driver, self).get_expr_depends()
new_list = []
for src, dest in conn_list:
if src not in iternames and dest not in iternames:
new_list.append((src, dest))
return new_list
def _get_required_compnames(self):
"""Returns a set of names of components that are required by
this Driver in order to evaluate parameters, objectives
and constraints. This list will include any intermediate
components in the data flow between components referenced by
parameters and those referenced by objectives and/or constraints.
"""
setcomps = set()
getcomps = set()
if hasattr(self, '_delegates_'):
for name, dclass in self._delegates_.items():
inst = getattr(self, name)
if isinstance(inst, HasParameters):
setcomps = inst.get_referenced_compnames()
elif isinstance(
inst,
(HasConstraints, HasEqConstraints, HasIneqConstraints,
HasObjective, HasObjectives)):
getcomps.update(inst.get_referenced_compnames())
full = set(setcomps)
if self.parent:
graph = self.parent._depgraph
for end in getcomps:
for start in setcomps:
full.update(graph.find_all_connecting(start, end))
return full
def get_references(self, name):
"""Return parameter, constraint, and objective references to component
`name` in preparation for subsequent :meth:`restore_references` call.
name: string
Name of component being removed.
"""
refs = {}
if hasattr(self, '_delegates_'):
for dname, dclass in self._delegates_.items():
inst = getattr(self, dname)
if isinstance(
inst,
(HasParameters, HasConstraints, HasEqConstraints,
HasIneqConstraints, HasObjective, HasObjectives)):
refs[inst] = inst.get_references(name)
return refs
def remove_references(self, name):
"""Remove parameter, constraint, and objective references to component
`name`.
name: string
Name of component being removed.
"""
if hasattr(self, '_delegates_'):
for dname, dclass in self._delegates_.items():
inst = getattr(self, dname)
if isinstance(
inst,
(HasParameters, HasConstraints, HasEqConstraints,
HasIneqConstraints, HasObjective, HasObjectives)):
inst.remove_references(name)
def restore_references(self, refs, name):
"""Restore parameter, constraint, and objective references to component
`name` from `refs`.
name: string
Name of component being removed.
refs: object
Value returned by :meth:`get_references`.
"""
if hasattr(self, '_delegates_'):
for dname, dclass in self._delegates_.items():
inst = getattr(self, dname)
if isinstance(
inst,
(HasParameters, HasConstraints, HasEqConstraints,
HasIneqConstraints, HasObjective, HasObjectives)):
inst.restore_references(refs[inst], name)
@rbac('*', 'owner')
def run(self, force=False, ffd_order=0, case_id=''):
"""Run this object. This should include fetching input variables if necessary,
executing, and updating output variables. Do not override this function.
force: bool
If True, force component to execute even if inputs have not
changed. (Default is False)
ffd_order: int
Order of the derivatives to be used when finite differncing (1 for first
derivatives, 2 for second derivativse). During regular execution,
ffd_order should be 0. (Default is 0)
case_id: str
Identifier for the Case that is associated with this run. (Default is '')
If applied to the top-level assembly, this will be prepended to
all iteration coordinates.
"""
for recorder in self.recorders:
recorder.startup()
# Override just to reset the workflow :-(
self.workflow.reset()
super(Driver, self).run(force, ffd_order, case_id)
self._invalidated = False
def execute(self):
""" Iterate over a workflow of Components until some condition
is met. If you don't want to structure your driver to use *pre_iteration*,
*post_iteration*, etc., just override this function. As a result, none
of the ``<start/pre/post/continue>_iteration()`` functions will be called.
"""
self._iter = None
self.start_iteration()
while self.continue_iteration():
self.pre_iteration()
self.run_iteration()
self.post_iteration()
def step(self):
"""Similar to the 'execute' function, but this one only
executes a single Component from the workflow each time
it's called.
"""
if self._iter is None:
self.start_iteration()
self._iter = self._step()
try:
self._iter.next()
except StopIteration:
self._iter = None
raise
raise RunStopped('Step complete')
def _step(self):
while self.continue_iteration():
self.pre_iteration()
for junk in self._step_workflow():
yield
self.post_iteration()
self._iter = None
raise StopIteration()
def _step_workflow(self):
while True:
try:
self.workflow.step()
except RunStopped:
pass
yield
def stop(self):
self._stop = True
self.workflow.stop()
def start_iteration(self):
"""Called just prior to the beginning of an iteration loop. This can
be overridden by inherited classes. It can be used to perform any
necessary pre-iteration initialization.
"""
self._continue = True
def continue_iteration(self):
"""Return False to stop iterating."""
return self._continue
def pre_iteration(self):
"""Called prior to each iteration. This is where iteration events are set."""
self.set_events()
def run_iteration(self):
"""Runs workflow."""
wf = self.workflow
if len(wf) == 0:
self._logger.warning("'%s': workflow is empty!" %
self.get_pathname())
wf.run(ffd_order=self.ffd_order, case_id=self._case_id)
def calc_derivatives(self, first=False, second=False):
""" Calculate derivatives and save baseline states for all components
in this workflow."""
self.workflow.calc_derivatives(first, second)
def check_derivatives(self, order, driver_inputs, driver_outputs):
""" Check derivatives for all components in this workflow."""
self.workflow.check_derivatives(order, driver_inputs, driver_outputs)
def post_iteration(self):
"""Called after each iteration."""
self._continue = False # by default, stop after one iteration
def config_changed(self, update_parent=True):
"""Call this whenever the configuration of this Component changes,
for example, children are added or removed or dependencies may have
changed.
"""
super(Driver, self).config_changed(update_parent)
if self.workflow is not None:
self.workflow.config_changed()
def record_case(self):
""" A driver can call this function to record the current state of the
current iteration as a Case into all slotted case recorders. Generally,
the driver should call this function once per iteration and may also
need to call it at the conclusion.
All paramters, objectives, and constraints are included in the Case
output, along with all extra variables listed in self.printvars.
"""
if not self.recorders:
return
case_input = []
case_output = []
# Parameters
if hasattr(self, 'get_parameters'):
for name, param in self.get_parameters().iteritems():
if isinstance(name, tuple):
name = name[0]
case_input.append([name, param.evaluate(self.parent)])
# Objectives
if hasattr(self, 'eval_objective'):
case_output.append(["Objective", self.eval_objective()])
# Constraints
if hasattr(self, 'get_ineq_constraints'):
for name, con in self.get_ineq_constraints().iteritems():
val = con.evaluate(self.parent)
if '>' in val[2]:
case_output.append(
["Constraint ( %s )" % name, val[0] - val[1]])
else:
case_output.append(
["Constraint ( %s )" % name, val[1] - val[0]])
if hasattr(self, 'get_eq_constraints'):
for name, con in self.get_eq_constraints().iteritems():
val = con.evaluate(self.parent)
case_output.append(
["Constraint ( %s )" % name, val[1] - val[0]])
# Additional user-requested variables
for printvar in self.printvars:
if '*' in printvar:
printvars = self._get_all_varpaths(printvar)
else:
printvars = [printvar]
for var in printvars:
iotype = self.parent.get_metadata(var, 'iotype')
if iotype == 'in':
val = ExprEvaluator(var, scope=self.parent).evaluate()
case_input.append([var, val])
elif iotype == 'out':
val = ExprEvaluator(var, scope=self.parent).evaluate()
case_output.append([var, val])
else:
msg = "%s is not an input or output" % var
self.raise_exception(msg, ValueError)
# Pull iteration coord from workflow
coord = self.workflow._iterbase('')
case = Case(case_input,
case_output,
label=coord,
parent_uuid=self._case_id)
for recorder in self.recorders:
recorder.record(case)
def _get_all_varpaths(self, pattern, header=''):
''' Return a list of all varpaths in the driver's workflow that
match the specified pattern.
Used by record_case.'''
# assume we don't want this in driver's imports
from openmdao.main.assembly import Assembly
# Start with our driver's settings
all_vars = []
for var in self.list_vars():
all_vars.append('%s.%s' % (self.name, var))
for comp in self.workflow.__iter__():
# All variables from components in workflow
for var in comp.list_vars():
all_vars.append('%s%s.%s' % (header, comp.name, var))
# Recurse into assemblys
if isinstance(comp, Assembly):
assy_header = '%s%s.' % (header, comp.name)
assy_vars = comp.driver._get_all_varpaths(pattern, assy_header)
all_vars = all_vars + assy_vars
# Match pattern in our var names
matched_vars = []
if pattern == '*':
matched_vars = all_vars
else:
matched_vars = fnmatch.filter(all_vars, pattern)
return matched_vars
def get_workflow(self):
""" Get the driver info and the list of components that make up the
driver's workflow; recurse on nested drivers.
"""
from openmdao.main.assembly import Assembly
ret = {}
ret['pathname'] = self.get_pathname()
ret['type'] = type(self).__module__ + '.' + type(self).__name__
ret['workflow'] = []
ret['valid'] = self.is_valid()
for comp in self.workflow:
pathname = comp.get_pathname()
if is_instance(comp, Assembly) and comp.driver:
ret['workflow'].append({
'pathname':
pathname,
'type':
type(comp).__module__ + '.' + type(comp).__name__,
'driver':
comp.driver.get_workflow(),
'valid':
comp.is_valid()
})
elif is_instance(comp, Driver):
ret['workflow'].append(comp.get_workflow())
else:
ret['workflow'].append({
'pathname':
pathname,
'type':
type(comp).__module__ + '.' + type(comp).__name__,
'valid':
comp.is_valid()
})
return ret
class Driver(Component):
""" A Driver iterates over a workflow of Components until some condition
is met. """
implements(IDriver, IHasEvents)
# set factory here so we see a default value in the docs, even
# though we replace it with a new Dataflow in __init__
workflow = Slot(Workflow, allow_none=True, required=True,
factory=Dataflow, hidden=True)
gradient_options = VarTree(GradientOptions(), iotype='in',
framework_var=True)
def __init__(self):
self._iter = None
super(Driver, self).__init__()
self.workflow = Dataflow(self)
self._required_compnames = None
# clean up unwanted trait from Component
self.remove_trait('missing_deriv_policy')
def __deepcopy__(self, memo):
"""For some reason `missing_deriv_policy` gets resurrected."""
result = super(Driver, self).__deepcopy__(memo)
result.remove_trait('missing_deriv_policy')
return result
def _workflow_changed(self, oldwf, newwf):
"""callback when new workflow is slotted"""
if newwf is not None:
newwf.parent = self
def get_expr_scope(self):
"""Return the scope to be used to evaluate ExprEvaluators."""
return self.parent
def check_config(self, strict=False):
"""Verify that our workflow is able to resolve all of its components."""
# workflow will raise an exception if it can't resolve a Component
super(Driver, self).check_config(strict=strict)
self.workflow.check_config(strict=strict)
def iteration_set(self, solver_only=False):
"""Return a set of all Components in our workflow and
recursively in any workflow in any Driver in our workflow.
solver_only: Bool
Only recurse into solver drivers. These are the only kinds
of drivers whose derivatives get absorbed into the parent
driver's graph.
"""
allcomps = set()
for child in self.workflow.get_components(full=True):
allcomps.add(child)
if has_interface(child, IDriver):
if solver_only and not has_interface(child, ISolver):
continue
allcomps.update(child.iteration_set())
return allcomps
@rbac(('owner', 'user'))
def get_expr_depends(self):
"""Returns a list of tuples of the form (src_comp_name,
dest_comp_name) for each dependency introduced by any ExprEvaluators
in this Driver, ignoring any dependencies on components that are
inside of this Driver's iteration set.
"""
iternames = set([c.name for c in self.iteration_set()])
conn_list = super(Driver, self).get_expr_depends()
new_list = []
for src, dest in conn_list:
if src not in iternames and dest not in iternames:
new_list.append((src, dest))
return new_list
@rbac(('owner', 'user'))
def get_expr_var_depends(self, recurse=True):
"""Returns a tuple of sets of the form (src_set, dest_set)
containing all dependencies introduced by any parameters,
objectives, or constraints in this Driver. If recurse is True,
include any refs from subdrivers.
"""
srcset = set()
destset = set()
if hasattr(self, '_delegates_'):
for dname in self._delegates_:
delegate = getattr(self, dname)
if isinstance(delegate, HasParameters):
destset.update(delegate.get_referenced_varpaths())
elif isinstance(delegate, (HasConstraints,
HasEqConstraints, HasIneqConstraints,
HasObjective, HasObjectives)):
srcset.update(delegate.get_referenced_varpaths())
if recurse:
for sub in self.subdrivers():
srcs, dests = sub.get_expr_var_depends(recurse)
srcset.update(srcs)
destset.update(dests)
return srcset, destset
@rbac(('owner', 'user'))
def subdrivers(self):
"""Returns a generator of of subdrivers of this driver."""
for d in self.iteration_set():
if has_interface(d, IDriver):
yield d
def _get_required_compnames(self):
"""Returns a set of names of components that are required by
this Driver in order to evaluate parameters, objectives
and constraints. This list will include any intermediate
components in the data flow between components referenced by
parameters and those referenced by objectives and/or constraints.
"""
if self._required_compnames is None:
conns = super(Driver, self).get_expr_depends()
getcomps = set([u for u, v in conns if u != self.name])
setcomps = set([v for u, v in conns if v != self.name])
full = set(setcomps)
full.update(getcomps)
full.update(self.list_pseudocomps())
compgraph = self.parent._depgraph.component_graph()
for end in getcomps:
for start in setcomps:
full.update(find_all_connecting(compgraph, start, end))
self._required_compnames = full
return self._required_compnames
@rbac(('owner', 'user'))
def list_pseudocomps(self):
"""Return a list of names of pseudocomps resulting from
our objectives, and constraints.
"""
pcomps = []
if hasattr(self, '_delegates_'):
for name in self._delegates_:
delegate = getattr(self, name)
if hasattr(delegate, 'list_pseudocomps'):
pcomps.extend(delegate.list_pseudocomps())
return pcomps
def get_references(self, name):
"""Return a dict of parameter, constraint, and objective
references to component `name` in preparation for
subsequent :meth:`restore_references` call.
name: string
Name of component being referenced.
"""
refs = {}
if hasattr(self, '_delegates_'):
for dname in self._delegates_:
inst = getattr(self, dname)
if isinstance(inst, (HasParameters, HasConstraints,
HasEqConstraints, HasIneqConstraints,
HasObjective, HasObjectives)):
refs[inst] = inst.get_references(name)
return refs
def remove_references(self, name):
"""Remove parameter, constraint, objective and workflow
references to component `name`.
name: string
Name of component being removed.
"""
if hasattr(self, '_delegates_'):
for dname in self._delegates_:
inst = getattr(self, dname)
if isinstance(inst, (HasParameters, HasConstraints,
HasEqConstraints, HasIneqConstraints,
HasObjective, HasObjectives)):
inst.remove_references(name)
self.workflow.remove(name)
def restore_references(self, refs):
"""Restore parameter, constraint, and objective references to component
`name` from `refs`.
refs: object
Value returned by :meth:`get_references`.
"""
for inst, inst_refs in refs.items():
inst.restore_references(inst_refs)
@rbac('*', 'owner')
def run(self, force=False, ffd_order=0, case_uuid=''):
"""Run this object. This should include fetching input variables if
necessary, executing, and updating output variables. Do not override
this function.
force: bool
If True, force component to execute even if inputs have not
changed. (Default is False)
ffd_order: int
Order of the derivatives to be used when finite differencing (1
for first derivatives, 2 for second derivatives). During regular
execution, ffd_order should be 0. (Default is 0)
case_uuid: str
Identifier for the Case that is associated with this run.
"""
# (Re)configure parameters.
if hasattr(self, 'config_parameters'):
self.config_parameters()
# force param pseudocomps to get updated values to start
# KTM1 - probably don't need this anymore
self.update_parameters()
# Reset the workflow.
self.workflow.reset()
super(Driver, self).run(ffd_order, case_uuid)
@rbac(('owner', 'user'))
def configure_recording(self, includes, excludes):
"""Called at start of top-level run to configure case recording.
Returns set of paths for changing inputs."""
return self.workflow.configure_recording(includes, excludes)
def update_parameters(self):
if hasattr(self, 'get_parameters'):
for param in self.get_parameters().values():
param.initialize(self.get_expr_scope())
def execute(self):
""" Iterate over a workflow of Components until some condition
is met. If you don't want to structure your driver to use
*pre_iteration*, *post_iteration*, etc., just override this function.
As a result, none of the ``<start/pre/post/continue>_iteration()``
functions will be called.
"""
self._iter = None
self.start_iteration()
while self.continue_iteration():
self.pre_iteration()
self.run_iteration()
self.post_iteration()
def stop(self):
"""Stop the workflow."""
self._stop = True
self.workflow.stop()
def start_iteration(self):
"""Called just prior to the beginning of an iteration loop. This can
be overridden by inherited classes. It can be used to perform any
necessary pre-iteration initialization.
"""
self._continue = True
def continue_iteration(self):
"""Return False to stop iterating."""
return self._continue
def pre_iteration(self):
"""Called prior to each iteration.
This is where iteration events are set."""
self.set_events()
def run_iteration(self):
"""Runs workflow."""
wf = self.workflow
if len(wf) == 0:
self._logger.warning("'%s': workflow is empty!"
% self.get_pathname())
wf.run(ffd_order=self.ffd_order)
def calc_derivatives(self, first=False, second=False, savebase=False,
required_inputs=None, required_outputs=None):
""" Calculate derivatives and save baseline states for all components
in this workflow."""
self.workflow.calc_derivatives(first, second, savebase,
required_inputs, required_outputs)
def calc_gradient(self, inputs=None, outputs=None):
"""Returns the gradient of the passed outputs with respect to
all passed inputs. The basic driver behavior is to call calc_gradient
on its workflow. However, some driver (optimizers in particular) may
want to define their own behavior.
"""
return self.workflow.calc_gradient(inputs, outputs, upscope=True)
def post_iteration(self):
"""Called after each iteration."""
self._continue = False # by default, stop after one iteration
def config_changed(self, update_parent=True):
"""Call this whenever the configuration of this Component changes,
for example, children are added or removed or dependencies may have
changed.
"""
super(Driver, self).config_changed(update_parent)
self._required_compnames = None
if self.workflow is not None:
self.workflow.config_changed()
def get_workflow(self):
""" Get the driver info and the list of components that make up the
driver's workflow; recurse on nested drivers.
"""
from openmdao.main.assembly import Assembly
ret = {}
ret['pathname'] = self.get_pathname()
ret['type'] = type(self).__module__ + '.' + type(self).__name__
ret['workflow'] = []
comps = [comp for comp in self.workflow]
for comp in comps:
# Skip pseudo-comps
if hasattr(comp, '_pseudo_type'):
continue
pathname = comp.get_pathname()
if is_instance(comp, Assembly) and comp.driver:
inames = [cls.__name__
for cls in list(implementedBy(comp.__class__))]
ret['workflow'].append({
'pathname': pathname,
'type': type(comp).__module__ + '.' + type(comp).__name__,
'interfaces': inames,
'driver': comp.driver.get_workflow(),
})
elif is_instance(comp, Driver):
ret['workflow'].append(comp.get_workflow())
else:
inames = [cls.__name__
for cls in list(implementedBy(comp.__class__))]
ret['workflow'].append({
'pathname': pathname,
'type': type(comp).__module__ + '.' + type(comp).__name__,
'interfaces': inames,
})
return ret
class Driver(Component):
""" A Driver iterates over a workflow of Components until some condition
is met. """
implements(IDriver, IHasEvents)
recorders = List(Slot(ICaseRecorder, required=False),
desc='Case recorders for iteration data.')
# Extra variables for adding to CaseRecorders
printvars = List(
Str,
iotype='in',
framework_var=True,
desc='List of extra variables to output in the recorders.')
# set factory here so we see a default value in the docs, even
# though we replace it with a new Dataflow in __init__
workflow = Slot(Workflow,
allow_none=True,
required=True,
factory=Dataflow,
hidden=True)
gradient_options = VarTree(GradientOptions(),
iotype='in',
framework_var=True)
def __init__(self):
self._iter = None
super(Driver, self).__init__()
self.workflow = Dataflow(self)
self.force_execute = True
self._required_compnames = None
# This flag is triggered by adding or removing any parameters,
# constraints, or objectives.
self._invalidated = False
# clean up unwanted trait from Component
self.remove_trait('missing_deriv_policy')
def _workflow_changed(self, oldwf, newwf):
"""callback when new workflow is slotted"""
if newwf is not None:
newwf._parent = self
def get_expr_scope(self):
"""Return the scope to be used to evaluate ExprEvaluators."""
return self.parent
def _invalidate(self):
""" Method for delegates to declare that the driver is in an invalid
state so that isvalid() returns false. Presently, this is called when
a constraint/objective/parameter is set, removed, or cleared.
"""
self._invalidated = True
self._set_exec_state('INVALID')
def is_valid(self):
"""Return False if any Component in our workflow(s) is invalid,
if any of our variables is invalid, or if the parameters,
constraints, or objectives have changed.
"""
if super(Driver, self).is_valid() is False:
return False
# force exection if any param, obj, or constraint has changed.
if self._invalidated:
return False
# force execution if any component in the workflow is invalid
for comp in self.workflow.get_components():
if not comp.is_valid():
return False
return True
def check_config(self):
"""Verify that our workflow is able to resolve all of its components."""
# workflow will raise an exception if it can't resolve a Component
super(Driver, self).check_config()
self.workflow.check_config()
def iteration_set(self, solver_only=False):
"""Return a set of all Components in our workflow and
recursively in any workflow in any Driver in our workflow.
solver_only: Bool
Only recurse into solver drivers. These are the only kinds
of drivers whose derivatives get absorbed into the parent
driver's graph.
"""
allcomps = set()
for child in self.workflow.get_components(full=True):
allcomps.add(child)
if has_interface(child, IDriver):
if solver_only and not has_interface(child, ISolver):
continue
allcomps.update(child.iteration_set())
return allcomps
@rbac(('owner', 'user'))
def get_expr_depends(self):
"""Returns a list of tuples of the form (src_comp_name,
dest_comp_name) for each dependency introduced by any ExprEvaluators
in this Driver, ignoring any dependencies on components that are
inside of this Driver's iteration set.
"""
iternames = set([c.name for c in self.iteration_set()])
conn_list = super(Driver, self).get_expr_depends()
new_list = []
for src, dest in conn_list:
if src not in iternames and dest not in iternames:
new_list.append((src, dest))
return new_list
@rbac(('owner', 'user'))
def get_expr_var_depends(self, recurse=True):
"""Returns a tuple of sets of the form (src_set, dest_set)
containing all dependencies introduced by any parameters,
objectives, or constraints in this Driver. If recurse is True,
include any refs from subdrivers.
"""
srcset = set()
destset = set()
if hasattr(self, '_delegates_'):
for dname, dclass in self._delegates_.items():
delegate = getattr(self, dname)
if isinstance(delegate, HasParameters):
destset.update(delegate.get_referenced_varpaths())
elif isinstance(
delegate,
(HasConstraints, HasEqConstraints, HasIneqConstraints,
HasObjective, HasObjectives)):
srcset.update(delegate.get_referenced_varpaths())
if recurse:
for sub in self.subdrivers():
srcs, dests = sub.get_expr_var_depends(recurse)
srcset.update(srcs)
destset.update(dests)
return srcset, destset
@rbac(('owner', 'user'))
def subdrivers(self):
"""Returns a generator of of subdrivers of this driver."""
for d in self.iteration_set():
if has_interface(d, IDriver):
yield d
def _get_required_compnames(self):
"""Returns a set of names of components that are required by
this Driver in order to evaluate parameters, objectives
and constraints. This list will include any intermediate
components in the data flow between components referenced by
parameters and those referenced by objectives and/or constraints.
"""
if self._required_compnames is None:
conns = super(Driver, self).get_expr_depends()
getcomps = set([u for u, v in conns if u != self.name])
setcomps = set([v for u, v in conns if v != self.name])
full = set(setcomps)
compgraph = self.parent._depgraph.component_graph()
for end in getcomps:
for start in setcomps:
full.update(find_all_connecting(compgraph, start, end))
self._required_compnames = full
return self._required_compnames
@rbac(('owner', 'user'))
def list_pseudocomps(self):
"""Return a list of names of pseudocomps resulting from
our objectives, and constraints.
"""
pcomps = []
if hasattr(self, '_delegates_'):
for name, dclass in self._delegates_.items():
delegate = getattr(self, name)
if hasattr(delegate, 'list_pseudocomps'):
pcomps.extend(delegate.list_pseudocomps())
return pcomps
def get_references(self, name):
"""Return a dict of parameter, constraint, and objective
references to component `name` in preparation for
subsequent :meth:`restore_references` call.
name: string
Name of component being referenced.
"""
refs = {}
if hasattr(self, '_delegates_'):
for dname, dclass in self._delegates_.items():
inst = getattr(self, dname)
if isinstance(
inst,
(HasParameters, HasConstraints, HasEqConstraints,
HasIneqConstraints, HasObjective, HasObjectives)):
refs[inst] = inst.get_references(name)
return refs
def remove_references(self, name):
"""Remove parameter, constraint, objective and workflow
references to component `name`.
name: string
Name of component being removed.
"""
if hasattr(self, '_delegates_'):
for dname, dclass in self._delegates_.items():
inst = getattr(self, dname)
if isinstance(
inst,
(HasParameters, HasConstraints, HasEqConstraints,
HasIneqConstraints, HasObjective, HasObjectives)):
inst.remove_references(name)
self.workflow.remove(name)
def restore_references(self, refs):
"""Restore parameter, constraint, and objective references to component
`name` from `refs`.
refs: object
Value returned by :meth:`get_references`.
"""
for inst, inst_refs in refs.items():
inst.restore_references(inst_refs)
@rbac('*', 'owner')
def run(self, force=False, ffd_order=0, case_id=''):
"""Run this object. This should include fetching input variables if
necessary, executing, and updating output variables. Do not override
this function.
force: bool
If True, force component to execute even if inputs have not
changed. (Default is False)
ffd_order: int
Order of the derivatives to be used when finite differencing (1
for first derivatives, 2 for second derivatives). During regular
execution, ffd_order should be 0. (Default is 0)
case_id: str
Identifier for the Case that is associated with this run.
If applied to the top-level assembly, this will be prepended to
all iteration coordinates. (Default is '')
"""
# (Re)configure parameters.
if hasattr(self, 'config_parameters'):
self.config_parameters()
for recorder in self.recorders:
recorder.startup()
# force param pseudocomps to get updated values to start
# KTM1 - probably don't need this anymore
self.update_parameters()
# Override just to reset the workflow :-(
self.workflow.reset()
super(Driver, self).run(force, ffd_order, case_id)
self._invalidated = False
def update_parameters(self):
if hasattr(self, 'get_parameters'):
for param in self.get_parameters().values():
param.initialize(self.get_expr_scope())
def execute(self):
""" Iterate over a workflow of Components until some condition
is met. If you don't want to structure your driver to use *pre_iteration*,
*post_iteration*, etc., just override this function. As a result, none
of the ``<start/pre/post/continue>_iteration()`` functions will be called.
"""
self._iter = None
self.start_iteration()
while self.continue_iteration():
self.pre_iteration()
self.run_iteration()
self.post_iteration()
def step(self):
"""Similar to the 'execute' function, but this one only
executes a single Component from the workflow each time
it's called.
"""
if self._iter is None:
self.start_iteration()
self._iter = self._step()
try:
self._iter.next()
except StopIteration:
self._iter = None
raise
raise RunStopped('Step complete')
def _step(self):
'''Step through a single workflow comp and then return control'''
while self.continue_iteration():
self.pre_iteration()
for junk in self._step_workflow():
yield
self.post_iteration()
self._iter = None
raise StopIteration()
def _step_workflow(self):
while True:
try:
self.workflow.step()
except RunStopped:
pass
yield
def stop(self):
"""Stop the workflow."""
self._stop = True
self.workflow.stop()
def start_iteration(self):
"""Called just prior to the beginning of an iteration loop. This can
be overridden by inherited classes. It can be used to perform any
necessary pre-iteration initialization.
"""
self._continue = True
def continue_iteration(self):
"""Return False to stop iterating."""
return self._continue
def pre_iteration(self):
"""Called prior to each iteration. This is where iteration events are set."""
self.set_events()
def run_iteration(self):
"""Runs workflow."""
wf = self.workflow
if len(wf) == 0:
self._logger.warning("'%s': workflow is empty!" %
self.get_pathname())
wf.run(ffd_order=self.ffd_order, case_id=self._case_id)
def calc_derivatives(self,
first=False,
second=False,
savebase=False,
required_inputs=None,
required_outputs=None):
""" Calculate derivatives and save baseline states for all components
in this workflow."""
self.workflow.calc_derivatives(first, second, savebase,
required_inputs, required_outputs)
def calc_gradient(self, inputs=None, outputs=None):
"""Returns the gradient of the passed outputs with respect to
all passed inputs. The basic driver behavior is to call calc_gradient
on its workflow. However, some driver (optimizers in particular) may
want to define their own behavior.
"""
return self.workflow.calc_gradient(inputs, outputs, upscope=True)
def post_iteration(self):
"""Called after each iteration."""
self._continue = False # by default, stop after one iteration
def config_changed(self, update_parent=True):
"""Call this whenever the configuration of this Component changes,
for example, children are added or removed or dependencies may have
changed.
"""
super(Driver, self).config_changed(update_parent)
self._required_compnames = None
self._invalidate()
if self.workflow is not None:
self.workflow.config_changed()
def record_case(self):
""" A driver can call this function to record the current state of the
current iteration as a Case into all slotted case recorders. Generally,
the driver should call this function once per iteration and may also
need to call it at the conclusion.
All parameters, objectives, and constraints are included in the Case
output, along with all extra variables listed in self.printvars.
"""
if not self.recorders:
return
case_input = []
case_output = []
iotypes = {}
# Parameters
if hasattr(self, 'get_parameters'):
for name, param in self.get_parameters().iteritems():
if isinstance(name, tuple):
name = name[0]
case_input.append([name, param.evaluate(self.parent)])
iotypes[name] = 'in'
# Objectives
if hasattr(self, 'eval_objective'):
case_output.append(["Objective", self.eval_objective()])
elif hasattr(self, 'eval_objectives'):
for j, obj in enumerate(self.eval_objectives()):
case_output.append(["Objective_%d" % j, obj])
# Constraints
if hasattr(self, 'get_ineq_constraints'):
for name, con in self.get_ineq_constraints().iteritems():
val = con.evaluate(self.parent)
case_output.append(["Constraint ( %s )" % name, val])
if hasattr(self, 'get_eq_constraints'):
for name, con in self.get_eq_constraints().iteritems():
val = con.evaluate(self.parent)
case_output.append(["Constraint ( %s )" % name, val])
tmp_printvars = self.printvars[:]
tmp_printvars.append('%s.workflow.itername' % self.name)
iotypes[tmp_printvars[-1]] = 'out'
# Additional user-requested variables
for printvar in tmp_printvars:
if '*' in printvar:
printvars = self._get_all_varpaths(printvar)
else:
printvars = [printvar]
for var in printvars:
iotype = iotypes.get(var)
if iotype is None:
iotype = self.parent.get_metadata(var, 'iotype')
iotypes[var] = iotype
if iotype == 'in':
val = ExprEvaluator(var, scope=self.parent).evaluate()
case_input.append([var, val])
elif iotype == 'out':
val = ExprEvaluator(var, scope=self.parent).evaluate()
case_output.append([var, val])
else:
msg = "%s is not an input or output" % var
self.raise_exception(msg, ValueError)
#case = Case(case_input, case_output, case_uuid=self.case_id , parent_uuid=self.parent_case_id)
case = Case(case_input, case_output, parent_uuid=self._case_id)
for recorder in self.recorders:
recorder.record(case)
def _get_all_varpaths(self, pattern, header=''):
''' Return a list of all varpaths in the driver's workflow that
match the specified pattern.
Used by record_case.
'''
# assume we don't want this in driver's imports
from openmdao.main.assembly import Assembly
# Start with our driver's settings
all_vars = []
for var in self.list_vars():
all_vars.append('%s.%s' % (self.name, var))
for comp in self.workflow.__iter__():
# The variables in pseudo-comps are not of interest.
if not hasattr(comp, 'list_vars'):
continue
# All variables from components in workflow
for var in comp.list_vars():
all_vars.append('%s%s.%s' % (header, comp.name, var))
# Recurse into assemblys
if isinstance(comp, Assembly):
assy_header = '%s%s.' % (header, comp.name)
assy_vars = comp.driver._get_all_varpaths(pattern, assy_header)
all_vars = all_vars + assy_vars
# Match pattern in our var names
matched_vars = []
if pattern == '*':
matched_vars = all_vars
else:
matched_vars = fnmatch.filter(all_vars, pattern)
return matched_vars
def get_workflow(self):
""" Get the driver info and the list of components that make up the
driver's workflow; recurse on nested drivers.
"""
from openmdao.main.assembly import Assembly
ret = {}
ret['pathname'] = self.get_pathname()
ret['type'] = type(self).__module__ + '.' + type(self).__name__
ret['workflow'] = []
ret['valid'] = self.is_valid()
comps = [comp for comp in self.workflow]
for comp in comps:
# Skip pseudo-comps
if hasattr(comp, '_pseudo_type'):
continue
pathname = comp.get_pathname()
if is_instance(comp, Assembly) and comp.driver:
inames = [
cls.__name__ for cls in list(implementedBy(comp.__class__))
]
ret['workflow'].append({
'pathname':
pathname,
'type':
type(comp).__module__ + '.' + type(comp).__name__,
'interfaces':
inames,
'driver':
comp.driver.get_workflow(),
'valid':
comp.is_valid()
})
elif is_instance(comp, Driver):
ret['workflow'].append(comp.get_workflow())
else:
inames = [
cls.__name__ for cls in list(implementedBy(comp.__class__))
]
ret['workflow'].append({
'pathname':
pathname,
'type':
type(comp).__module__ + '.' + type(comp).__name__,
'interfaces':
inames,
'valid':
comp.is_valid()
})
return ret
class Driver(Component):
""" A Driver iterates over a workflow of Components until some condition
is met. """
implements(IDriver, IHasEvents)
recorders = List(Slot(ICaseRecorder, required=False),
desc='Case recorders for iteration data.')
# Extra variables for printing
printvars = List(Str, iotype='in',
desc='List of extra variables to output in the recorders.')
# set factory here so we see a default value in the docs, even
# though we replace it with a new Dataflow in __init__
workflow = Slot(Workflow, allow_none=True, required=True,
factory=Dataflow, hidden=True)
def __init__(self, doc=None):
self._iter = None
super(Driver, self).__init__(doc=doc)
self.workflow = Dataflow(self)
self.force_execute = True
# This flag is triggered by adding or removing any parameters,
# constraints, or objectives.
self._invalidated = False
def _workflow_changed(self, oldwf, newwf):
if newwf is not None:
newwf._parent = self
def get_expr_scope(self):
"""Return the scope to be used to evaluate ExprEvaluators."""
return self.parent
def _invalidate(self):
""" Method for delegates to declare that the driver is in an invalid
state so that isvalid() returns false. Presently, this is called when
a constraint/objective/parameter is set, removed, or cleared.
"""
self._invalidated = True
self._set_exec_state('INVALID')
def is_valid(self):
"""Return False if any Component in our workflow(s) is invalid,
or if any of our variables is invalid, or if the parameters,
constraints, or objectives have changed.
"""
if super(Driver, self).is_valid() is False:
return False
# force exection if any param, obj, or constraint has changed.
if self._invalidated:
return False
# force execution if any component in the workflow is invalid
for comp in self.workflow.get_components():
if not comp.is_valid():
return False
return True
def check_config(self):
"""Verify that our workflow is able to resolve all of its components."""
# workflow will raise an exception if it can't resolve a Component
super(Driver, self).check_config()
self._update_workflow()
def _update_workflow(self):
"""Updates workflow contents based on driver dependencies."""
# if workflow is not defined, or if it contains only Drivers, try to
# use parameters, objectives and/or constraint expressions to
# determine the necessary workflow members
try:
iterset = set(c.name for c in self.iteration_set())
alldrivers = all([isinstance(c, Driver)
for c in self.workflow.get_components()])
if len(self.workflow) == 0:
pass
elif alldrivers is True:
reqcomps = self._get_required_compnames()
self.workflow.add([name for name in reqcomps
if name not in iterset])
# calling get_components() here just makes sure that all of the
# components can be resolved
comps = self.workflow.get_components()
except Exception as err:
self.raise_exception(str(err), type(err))
def iteration_set(self):
"""Return a set of all Components in our workflow(s) and
recursively in any workflow in any Driver in our workflow(s).
"""
allcomps = set()
if len(self.workflow) == 0:
for compname in self._get_required_compnames():
self.workflow.add(compname)
for child in self.workflow.get_components():
allcomps.add(child)
if has_interface(child, IDriver):
allcomps.update(child.iteration_set())
return allcomps
@rbac(('owner', 'user'))
def get_expr_depends(self):
"""Returns a list of tuples of the form (src_comp_name,
dest_comp_name) for each dependency introduced by any ExprEvaluators
in this Driver, ignoring any dependencies on components that are
inside of this Driver's iteration set.
"""
iternames = set([c.name for c in self.iteration_set()])
conn_list = super(Driver, self).get_expr_depends()
new_list = []
for src, dest in conn_list:
if src not in iternames and dest not in iternames:
new_list.append((src, dest))
return new_list
def _get_required_compnames(self):
"""Returns a set of names of components that are required by
this Driver in order to evaluate parameters, objectives
and constraints. This list will include any intermediate
components in the data flow between components referenced by
parameters and those referenced by objectives and/or constraints.
"""
setcomps = set()
getcomps = set()
if hasattr(self, '_delegates_'):
for name, dclass in self._delegates_.items():
inst = getattr(self, name)
if isinstance(inst, HasParameters):
setcomps = inst.get_referenced_compnames()
elif isinstance(inst, (HasConstraints, HasEqConstraints,
HasIneqConstraints, HasObjective, HasObjectives)):
getcomps.update(inst.get_referenced_compnames())
full = set(setcomps)
if self.parent:
graph = self.parent._depgraph
for end in getcomps:
for start in setcomps:
full.update(graph.find_all_connecting(start, end))
return full
def get_references(self, name):
"""Return parameter, constraint, and objective references to component
`name` in preparation for subsequent :meth:`restore_references` call.
name: string
Name of component being removed.
"""
refs = {}
if hasattr(self, '_delegates_'):
for dname, dclass in self._delegates_.items():
inst = getattr(self, dname)
if isinstance(inst, (HasParameters, HasConstraints,
HasEqConstraints, HasIneqConstraints,
HasObjective, HasObjectives)):
refs[inst] = inst.get_references(name)
return refs
def remove_references(self, name):
"""Remove parameter, constraint, and objective references to component
`name`.
name: string
Name of component being removed.
"""
if hasattr(self, '_delegates_'):
for dname, dclass in self._delegates_.items():
inst = getattr(self, dname)
if isinstance(inst, (HasParameters, HasConstraints,
HasEqConstraints, HasIneqConstraints,
HasObjective, HasObjectives)):
inst.remove_references(name)
def restore_references(self, refs, name):
"""Restore parameter, constraint, and objective references to component
`name` from `refs`.
name: string
Name of component being removed.
refs: object
Value returned by :meth:`get_references`.
"""
if hasattr(self, '_delegates_'):
for dname, dclass in self._delegates_.items():
inst = getattr(self, dname)
if isinstance(inst, (HasParameters, HasConstraints,
HasEqConstraints, HasIneqConstraints,
HasObjective, HasObjectives)):
inst.restore_references(refs[inst], name)
@rbac('*', 'owner')
def run(self, force=False, ffd_order=0, case_id=''):
"""Run this object. This should include fetching input variables if necessary,
executing, and updating output variables. Do not override this function.
force: bool
If True, force component to execute even if inputs have not
changed. (Default is False)
ffd_order: int
Order of the derivatives to be used when finite differncing (1 for first
derivatives, 2 for second derivativse). During regular execution,
ffd_order should be 0. (Default is 0)
case_id: str
Identifier for the Case that is associated with this run. (Default is '')
If applied to the top-level assembly, this will be prepended to
all iteration coordinates.
"""
for recorder in self.recorders:
recorder.startup()
# Override just to reset the workflow :-(
self.workflow.reset()
super(Driver, self).run(force, ffd_order, case_id)
self._invalidated = False
def execute(self):
""" Iterate over a workflow of Components until some condition
is met. If you don't want to structure your driver to use *pre_iteration*,
*post_iteration*, etc., just override this function. As a result, none
of the ``<start/pre/post/continue>_iteration()`` functions will be called.
"""
self._iter = None
self.start_iteration()
while self.continue_iteration():
self.pre_iteration()
self.run_iteration()
self.post_iteration()
def step(self):
"""Similar to the 'execute' function, but this one only
executes a single Component from the workflow each time
it's called.
"""
if self._iter is None:
self.start_iteration()
self._iter = self._step()
try:
self._iter.next()
except StopIteration:
self._iter = None
raise
raise RunStopped('Step complete')
def _step(self):
while self.continue_iteration():
self.pre_iteration()
for junk in self._step_workflow():
yield
self.post_iteration()
self._iter = None
raise StopIteration()
def _step_workflow(self):
while True:
try:
self.workflow.step()
except RunStopped:
pass
yield
def stop(self):
self._stop = True
self.workflow.stop()
def start_iteration(self):
"""Called just prior to the beginning of an iteration loop. This can
be overridden by inherited classes. It can be used to perform any
necessary pre-iteration initialization.
"""
self._continue = True
def continue_iteration(self):
"""Return False to stop iterating."""
return self._continue
def pre_iteration(self):
"""Called prior to each iteration. This is where iteration events are set."""
self.set_events()
def run_iteration(self):
"""Runs workflow."""
wf = self.workflow
if len(wf) == 0:
self._logger.warning("'%s': workflow is empty!" % self.get_pathname())
wf.run(ffd_order=self.ffd_order, case_id=self._case_id)
def calc_derivatives(self, first=False, second=False):
""" Calculate derivatives and save baseline states for all components
in this workflow."""
self.workflow.calc_derivatives(first, second)
def check_derivatives(self, order, driver_inputs, driver_outputs):
""" Check derivatives for all components in this workflow."""
self.workflow.check_derivatives(order, driver_inputs, driver_outputs)
def post_iteration(self):
"""Called after each iteration."""
self._continue = False # by default, stop after one iteration
def config_changed(self, update_parent=True):
"""Call this whenever the configuration of this Component changes,
for example, children are added or removed or dependencies may have
changed.
"""
super(Driver, self).config_changed(update_parent)
if self.workflow is not None:
self.workflow.config_changed()
def record_case(self):
""" A driver can call this function to record the current state of the
current iteration as a Case into all slotted case recorders. Generally,
the driver should call this function once per iteration and may also
need to call it at the conclusion.
All paramters, objectives, and constraints are included in the Case
output, along with all extra variables listed in self.printvars.
"""
if not self.recorders:
return
case_input = []
case_output = []
# Parameters
if hasattr(self, 'get_parameters'):
for name, param in self.get_parameters().iteritems():
if isinstance(name, tuple):
name = name[0]
case_input.append([name, param.evaluate(self.parent)])
# Objectives
if hasattr(self, 'eval_objective'):
case_output.append(["Objective", self.eval_objective()])
# Constraints
if hasattr(self, 'get_ineq_constraints'):
for name, con in self.get_ineq_constraints().iteritems():
val = con.evaluate(self.parent)
if '>' in val[2]:
case_output.append(["Constraint ( %s )" % name,
val[0] - val[1]])
else:
case_output.append(["Constraint ( %s )" % name,
val[1] - val[0]])
if hasattr(self, 'get_eq_constraints'):
for name, con in self.get_eq_constraints().iteritems():
val = con.evaluate(self.parent)
case_output.append(["Constraint ( %s )" % name, val[1] - val[0]])
# Additional user-requested variables
for printvar in self.printvars:
if '*' in printvar:
printvars = self._get_all_varpaths(printvar)
else:
printvars = [printvar]
for var in printvars:
iotype = self.parent.get_metadata(var, 'iotype')
if iotype == 'in':
val = ExprEvaluator(var, scope=self.parent).evaluate()
case_input.append([var, val])
elif iotype == 'out':
val = ExprEvaluator(var, scope=self.parent).evaluate()
case_output.append([var, val])
else:
msg = "%s is not an input or output" % var
self.raise_exception(msg, ValueError)
# Pull iteration coord from workflow
coord = self.workflow._iterbase('')
case = Case(case_input, case_output, label=coord,
parent_uuid=self._case_id)
for recorder in self.recorders:
recorder.record(case)
def _get_all_varpaths(self, pattern, header=''):
''' Return a list of all varpaths in the driver's workflow that
match the specified pattern.
Used by record_case.'''
# assume we don't want this in driver's imports
from openmdao.main.assembly import Assembly
# Start with our driver's settings
all_vars = []
for var in self.list_vars():
all_vars.append('%s.%s' % (self.name, var))
for comp in self.workflow.__iter__():
# All variables from components in workflow
for var in comp.list_vars():
all_vars.append('%s%s.%s' % (header, comp.name, var))
# Recurse into assemblys
if isinstance(comp, Assembly):
assy_header = '%s%s.' % (header, comp.name)
assy_vars = comp.driver._get_all_varpaths(pattern, assy_header)
all_vars = all_vars + assy_vars
# Match pattern in our var names
matched_vars = []
if pattern == '*':
matched_vars = all_vars
else:
matched_vars = fnmatch.filter(all_vars, pattern)
return matched_vars
def get_workflow(self):
""" Get the driver info and the list of components that make up the
driver's workflow; recurse on nested drivers.
"""
from openmdao.main.assembly import Assembly
ret = {}
ret['pathname'] = self.get_pathname()
ret['type'] = type(self).__module__ + '.' + type(self).__name__
ret['workflow'] = []
ret['valid'] = self.is_valid()
for comp in self.workflow:
pathname = comp.get_pathname()
if is_instance(comp, Assembly) and comp.driver:
ret['workflow'].append({
'pathname': pathname,
'type': type(comp).__module__ + '.' + type(comp).__name__,
'driver': comp.driver.get_workflow(),
'valid': comp.is_valid()
})
elif is_instance(comp, Driver):
ret['workflow'].append(comp.get_workflow())
else:
ret['workflow'].append({
'pathname': pathname,
'type': type(comp).__module__ + '.' + type(comp).__name__,
'valid': comp.is_valid()
})
return ret
class Driver(Component):
""" A Driver iterates over a workflow of Components until some condition
is met. """
implements(IDriver, IHasEvents)
recorders = List(Slot(ICaseRecorder, required=False),
desc='Case recorders for iteration data.')
# Extra variables for adding to CaseRecorders
printvars = List(Str, iotype='in', framework_var=True,
desc='List of extra variables to output in the recorders.')
# set factory here so we see a default value in the docs, even
# though we replace it with a new Dataflow in __init__
workflow = Slot(Workflow, allow_none=True, required=True,
factory=Dataflow, hidden=True)
gradient_options = VarTree(GradientOptions(), iotype='in')
def __init__(self):
self._iter = None
super(Driver, self).__init__()
self.workflow = Dataflow(self)
self.force_execute = True
self._required_compnames = None
# This flag is triggered by adding or removing any parameters,
# constraints, or objectives.
self._invalidated = False
# clean up unwanted trait from Component
self.remove_trait('missing_deriv_policy')
def _workflow_changed(self, oldwf, newwf):
"""callback when new workflow is slotted"""
if newwf is not None:
newwf._parent = self
def get_expr_scope(self):
"""Return the scope to be used to evaluate ExprEvaluators."""
return self.parent
def _invalidate(self):
""" Method for delegates to declare that the driver is in an invalid
state so that isvalid() returns false. Presently, this is called when
a constraint/objective/parameter is set, removed, or cleared.
"""
self._invalidated = True
self._set_exec_state('INVALID')
def is_valid(self):
"""Return False if any Component in our workflow(s) is invalid,
if any of our variables is invalid, or if the parameters,
constraints, or objectives have changed.
"""
if super(Driver, self).is_valid() is False:
return False
# force exection if any param, obj, or constraint has changed.
if self._invalidated:
return False
# force execution if any component in the workflow is invalid
for comp in self.workflow.get_components():
if not comp.is_valid():
return False
return True
def check_config(self):
"""Verify that our workflow is able to resolve all of its components."""
# workflow will raise an exception if it can't resolve a Component
super(Driver, self).check_config()
self.workflow.check_config()
def iteration_set(self, solver_only=False):
"""Return a set of all Components in our workflow and
recursively in any workflow in any Driver in our workflow.
solver_only: Bool
Only recurse into solver drivers. These are the only kinds
of drivers whose derivatives get absorbed into the parent
driver's graph.
"""
allcomps = set()
for child in self.workflow.get_components(full=True):
allcomps.add(child)
if has_interface(child, IDriver):
if solver_only and not has_interface(child, ISolver):
continue
allcomps.update(child.iteration_set())
return allcomps
@rbac(('owner', 'user'))
def get_expr_depends(self):
"""Returns a list of tuples of the form (src_comp_name,
dest_comp_name) for each dependency introduced by any ExprEvaluators
in this Driver, ignoring any dependencies on components that are
inside of this Driver's iteration set.
"""
iternames = set([c.name for c in self.iteration_set()])
conn_list = super(Driver, self).get_expr_depends()
new_list = []
for src, dest in conn_list:
if src not in iternames and dest not in iternames:
new_list.append((src, dest))
return new_list
@rbac(('owner', 'user'))
def get_expr_var_depends(self, recurse=True):
"""Returns a tuple of sets of the form (src_set, dest_set)
containing all dependencies introduced by any parameters,
objectives, or constraints in this Driver. If recurse is True,
include any refs from subdrivers.
"""
srcset = set()
destset = set()
if hasattr(self, '_delegates_'):
for dname, dclass in self._delegates_.items():
delegate = getattr(self, dname)
if isinstance(delegate, HasParameters):
destset.update(delegate.get_referenced_varpaths())
elif isinstance(delegate, (HasConstraints,
HasEqConstraints, HasIneqConstraints,
HasObjective, HasObjectives)):
srcset.update(delegate.get_referenced_varpaths())
if recurse:
for sub in self.subdrivers():
srcs, dests = sub.get_expr_var_depends(recurse)
srcset.update(srcs)
destset.update(dests)
return srcset, destset
@rbac(('owner', 'user'))
def subdrivers(self):
"""Returns a generator of of subdrivers of this driver."""
for d in self.iteration_set():
if has_interface(d, IDriver):
yield d
def _get_required_compnames(self):
"""Returns a set of names of components that are required by
this Driver in order to evaluate parameters, objectives
and constraints. This list will include any intermediate
components in the data flow between components referenced by
parameters and those referenced by objectives and/or constraints.
"""
if self._required_compnames is None:
conns = super(Driver, self).get_expr_depends()
getcomps = set([u for u, v in conns if u != self.name])
setcomps = set([v for u, v in conns if v != self.name])
full = set(setcomps)
compgraph = self.parent._depgraph.component_graph()
for end in getcomps:
for start in setcomps:
full.update(find_all_connecting(compgraph, start, end))
self._required_compnames = full
return self._required_compnames
@rbac(('owner', 'user'))
def list_pseudocomps(self):
"""Return a list of names of pseudocomps resulting from
our objectives, and constraints.
"""
pcomps = []
if hasattr(self, '_delegates_'):
for name, dclass in self._delegates_.items():
delegate = getattr(self, name)
if hasattr(delegate, 'list_pseudocomps'):
pcomps.extend(delegate.list_pseudocomps())
return pcomps
def get_references(self, name):
"""Return a dict of parameter, constraint, and objective
references to component `name` in preparation for
subsequent :meth:`restore_references` call.
name: string
Name of component being referenced.
"""
refs = {}
if hasattr(self, '_delegates_'):
for dname, dclass in self._delegates_.items():
inst = getattr(self, dname)
if isinstance(inst, (HasParameters, HasConstraints,
HasEqConstraints, HasIneqConstraints,
HasObjective, HasObjectives)):
refs[inst] = inst.get_references(name)
return refs
def remove_references(self, name):
"""Remove parameter, constraint, objective and workflow
references to component `name`.
name: string
Name of component being removed.
"""
if hasattr(self, '_delegates_'):
for dname, dclass in self._delegates_.items():
inst = getattr(self, dname)
if isinstance(inst, (HasParameters, HasConstraints,
HasEqConstraints, HasIneqConstraints,
HasObjective, HasObjectives)):
inst.remove_references(name)
self.workflow.remove(name)
def restore_references(self, refs):
"""Restore parameter, constraint, and objective references to component
`name` from `refs`.
refs: object
Value returned by :meth:`get_references`.
"""
for inst, inst_refs in refs.items():
inst.restore_references(inst_refs)
@rbac('*', 'owner')
def run(self, force=False, ffd_order=0, case_id=''):
"""Run this object. This should include fetching input variables if
necessary, executing, and updating output variables. Do not override
this function.
force: bool
If True, force component to execute even if inputs have not
changed. (Default is False)
ffd_order: int
Order of the derivatives to be used when finite differencing (1
for first derivatives, 2 for second derivatives). During regular
execution, ffd_order should be 0. (Default is 0)
case_id: str
Identifier for the Case that is associated with this run.
If applied to the top-level assembly, this will be prepended to
all iteration coordinates. (Default is '')
"""
# (Re)configure parameters.
if hasattr(self, 'config_parameters'):
self.config_parameters()
for recorder in self.recorders:
recorder.startup()
# force param pseudocomps to get updated values to start
# KTM1 - probably don't need this anymore
self.update_parameters()
# Override just to reset the workflow :-(
self.workflow.reset()
super(Driver, self).run(force, ffd_order, case_id)
self._invalidated = False
def update_parameters(self):
if hasattr(self, 'get_parameters'):
for param in self.get_parameters().values():
param.initialize(self.get_expr_scope())
def execute(self):
""" Iterate over a workflow of Components until some condition
is met. If you don't want to structure your driver to use *pre_iteration*,
*post_iteration*, etc., just override this function. As a result, none
of the ``<start/pre/post/continue>_iteration()`` functions will be called.
"""
self._iter = None
self.start_iteration()
while self.continue_iteration():
self.pre_iteration()
self.run_iteration()
self.post_iteration()
def step(self):
"""Similar to the 'execute' function, but this one only
executes a single Component from the workflow each time
it's called.
"""
if self._iter is None:
self.start_iteration()
self._iter = self._step()
try:
self._iter.next()
except StopIteration:
self._iter = None
raise
raise RunStopped('Step complete')
def _step(self):
'''Step through a single workflow comp and then return control'''
while self.continue_iteration():
self.pre_iteration()
for junk in self._step_workflow():
yield
self.post_iteration()
self._iter = None
raise StopIteration()
def _step_workflow(self):
while True:
try:
self.workflow.step()
except RunStopped:
pass
yield
def stop(self):
"""Stop the workflow."""
self._stop = True
self.workflow.stop()
def start_iteration(self):
"""Called just prior to the beginning of an iteration loop. This can
be overridden by inherited classes. It can be used to perform any
necessary pre-iteration initialization.
"""
self._continue = True
def continue_iteration(self):
"""Return False to stop iterating."""
return self._continue
def pre_iteration(self):
"""Called prior to each iteration. This is where iteration events are set."""
self.set_events()
def run_iteration(self):
"""Runs workflow."""
wf = self.workflow
if len(wf) == 0:
self._logger.warning("'%s': workflow is empty!" % self.get_pathname())
wf.run(ffd_order=self.ffd_order, case_id=self._case_id)
def calc_derivatives(self, first=False, second=False, savebase=False,
required_inputs=None, required_outputs=None):
""" Calculate derivatives and save baseline states for all components
in this workflow."""
self.workflow.calc_derivatives(first, second, savebase,
required_inputs, required_outputs)
def calc_gradient(self, inputs=None, outputs=None):
"""Returns the gradient of the passed outputs with respect to
all passed inputs. The basic driver behavior is to call calc_gradient
on its workflow. However, some driver (optimizers in particular) may
want to define their own behavior.
"""
return self.workflow.calc_gradient(inputs, outputs, upscope=True)
def post_iteration(self):
"""Called after each iteration."""
self._continue = False # by default, stop after one iteration
def config_changed(self, update_parent=True):
"""Call this whenever the configuration of this Component changes,
for example, children are added or removed or dependencies may have
changed.
"""
super(Driver, self).config_changed(update_parent)
self._required_compnames = None
self._invalidate()
if self.workflow is not None:
self.workflow.config_changed()
def record_case(self):
""" A driver can call this function to record the current state of the
current iteration as a Case into all slotted case recorders. Generally,
the driver should call this function once per iteration and may also
need to call it at the conclusion.
All parameters, objectives, and constraints are included in the Case
output, along with all extra variables listed in self.printvars.
"""
if not self.recorders:
return
case_input = []
case_output = []
iotypes = {}
# Parameters
if hasattr(self, 'get_parameters'):
for name, param in self.get_parameters().iteritems():
if isinstance(name, tuple):
name = name[0]
case_input.append([name, param.evaluate(self.parent)])
iotypes[name] = 'in'
# Objectives
if hasattr(self, 'eval_objective'):
case_output.append(["Objective", self.eval_objective()])
elif hasattr(self, 'eval_objectives'):
for j, obj in enumerate(self.eval_objectives()):
case_output.append(["Objective_%d" % j, obj])
# Constraints
if hasattr(self, 'get_ineq_constraints'):
for name, con in self.get_ineq_constraints().iteritems():
val = con.evaluate(self.parent)
case_output.append(["Constraint ( %s )" % name, val])
if hasattr(self, 'get_eq_constraints'):
for name, con in self.get_eq_constraints().iteritems():
val = con.evaluate(self.parent)
case_output.append(["Constraint ( %s )" % name, val])
tmp_printvars = self.printvars[:]
tmp_printvars.append('%s.workflow.itername' % self.name)
iotypes[tmp_printvars[-1]] = 'out'
# Additional user-requested variables
for printvar in tmp_printvars:
if '*' in printvar:
printvars = self._get_all_varpaths(printvar)
else:
printvars = [printvar]
for var in printvars:
iotype = iotypes.get(var)
if iotype is None:
iotype = self.parent.get_metadata(var, 'iotype')
iotypes[var] = iotype
if iotype == 'in':
val = ExprEvaluator(var, scope=self.parent).evaluate()
case_input.append([var, val])
elif iotype == 'out':
val = ExprEvaluator(var, scope=self.parent).evaluate()
case_output.append([var, val])
else:
msg = "%s is not an input or output" % var
self.raise_exception(msg, ValueError)
case = Case(case_input, case_output, parent_uuid=self._case_id)
for recorder in self.recorders:
recorder.record(case)
def _get_all_varpaths(self, pattern, header=''):
''' Return a list of all varpaths in the driver's workflow that
match the specified pattern.
Used by record_case.
'''
# assume we don't want this in driver's imports
from openmdao.main.assembly import Assembly
# Start with our driver's settings
all_vars = []
for var in self.list_vars():
all_vars.append('%s.%s' % (self.name, var))
for comp in self.workflow.__iter__():
# The variables in pseudo-comps are not of interest.
if not hasattr(comp, 'list_vars'):
continue
# All variables from components in workflow
for var in comp.list_vars():
all_vars.append('%s%s.%s' % (header, comp.name, var))
# Recurse into assemblys
if isinstance(comp, Assembly):
assy_header = '%s%s.' % (header, comp.name)
assy_vars = comp.driver._get_all_varpaths(pattern, assy_header)
all_vars = all_vars + assy_vars
# Match pattern in our var names
matched_vars = []
if pattern == '*':
matched_vars = all_vars
else:
matched_vars = fnmatch.filter(all_vars, pattern)
return matched_vars
def get_workflow(self):
""" Get the driver info and the list of components that make up the
driver's workflow; recurse on nested drivers.
"""
from openmdao.main.assembly import Assembly
ret = {}
ret['pathname'] = self.get_pathname()
ret['type'] = type(self).__module__ + '.' + type(self).__name__
ret['workflow'] = []
ret['valid'] = self.is_valid()
comps = [comp for comp in self.workflow]
for comp in comps:
# Skip pseudo-comps
if hasattr(comp, '_pseudo_type'):
continue
pathname = comp.get_pathname()
if is_instance(comp, Assembly) and comp.driver:
inames = [cls.__name__
for cls in list(implementedBy(comp.__class__))]
ret['workflow'].append({
'pathname': pathname,
'type': type(comp).__module__ + '.' + type(comp).__name__,
'interfaces': inames,
'driver': comp.driver.get_workflow(),
'valid': comp.is_valid()
})
elif is_instance(comp, Driver):
ret['workflow'].append(comp.get_workflow())
else:
inames = [cls.__name__
for cls in list(implementedBy(comp.__class__))]
ret['workflow'].append({
'pathname': pathname,
'type': type(comp).__module__ + '.' + type(comp).__name__,
'interfaces': inames,
'valid': comp.is_valid()
})
return ret
class Driver(Component):
""" A Driver iterates over a workflow of Components until some condition
is met. """
implements(IDriver, IHasEvents)
recorders = List(Slot(ICaseRecorder, required=False),
desc='Case recorders for iteration data.')
# set factory here so we see a default value in the docs, even
# though we replace it with a new Dataflow in __init__
workflow = Slot(Workflow, allow_none=True, required=True, factory=Dataflow)
def __init__(self, doc=None):
self._iter = None
super(Driver, self).__init__(doc=doc)
self.workflow = Dataflow(self)
def _workflow_changed(self, oldwf, newwf):
if newwf is not None:
newwf._parent = self
def get_expr_scope(self):
"""Return the scope to be used to evaluate ExprEvaluators."""
return self.parent
def is_valid(self):
"""Return False if any Component in our workflow(s) is invalid,
or if any of our variables is invalid.
"""
if super(Driver, self).is_valid() is False:
return False
# force execution if any component in the workflow is invalid
for comp in self.workflow.get_components():
if not comp.is_valid():
return False
return True
def check_config (self):
"""Verify that our workflow is able to resolve all of its components."""
# workflow will raise an exception if it can't resolve a Component
super(Driver, self).check_config()
# if workflow is not defined, or if it contains only Drivers, try to
# use parameters, objectives and/or constraint expressions to
# determine the necessary workflow members
try:
iterset = set(c.name for c in self.iteration_set())
alldrivers = all([isinstance(c, Driver)
for c in self.workflow.get_components()])
reqcomps = self._get_required_compnames()
if len(self.workflow) == 0:
self.workflow.add(reqcomps)
elif alldrivers is True:
self.workflow.add([name for name in reqcomps
if name not in iterset])
else:
diff = reqcomps - iterset
if len(diff) > 0:
#raise RuntimeError("Expressions in this Driver require the following "
# "Components that are not part of the "
# "workflow: %s" % list(diff))
pass
# calling get_components() here just makes sure that all of the
# components can be resolved
comps = self.workflow.get_components()
except Exception as err:
self.raise_exception(str(err), type(err))
def iteration_set(self):
"""Return a set of all Components in our workflow(s), and
recursively in any workflow in any Driver in our workflow(s).
"""
allcomps = set()
if len(self.workflow) == 0:
for compname in self._get_required_compnames():
self.workflow.add(compname)
for child in self.workflow.get_components():
allcomps.add(child)
if has_interface(child, IDriver):
allcomps.update(child.iteration_set())
return allcomps
@rbac(('owner', 'user'))
def get_expr_depends(self):
"""Returns a list of tuples of the form (src_comp_name,
dest_comp_name) for each dependency introduced by any ExprEvaluators
in this Driver, ignoring any dependencies on components that are
inside of this Driver's iteration set.
"""
iternames = set([c.name for c in self.iteration_set()])
conn_list = super(Driver, self).get_expr_depends()
new_list = []
for src, dest in conn_list:
if src not in iternames and dest not in iternames:
new_list.append((src, dest))
return new_list
def _get_required_compnames(self):
"""Returns a set of names of components that are required by
this Driver in order to evaluate parameters, objectives
and constraints. This list will include any intermediate
components in the data flow between components referenced by
parameters and those referenced by objectives and/or constraints.
"""
setcomps = set()
getcomps = set()
if hasattr(self, '_delegates_'):
for name, dclass in self._delegates_.items():
inst = getattr(self, name)
if isinstance(inst, HasParameters):
setcomps = inst.get_referenced_compnames()
elif isinstance(inst, (HasConstraints, HasEqConstraints,
HasIneqConstraints, HasObjective, HasObjectives)):
getcomps.update(inst.get_referenced_compnames())
full = set(getcomps)
full.update(setcomps)
if self.parent:
graph = self.parent._depgraph
for end in getcomps:
for start in setcomps:
full.update(graph.find_all_connecting(start, end))
return full
def execute(self):
""" Iterate over a workflow of Components until some condition
is met. If you don't want to structure your driver to use *pre_iteration*,
*post_iteration*, etc., just override this function. As a result, none
of the <start/pre/post/continue>_iteration() functions will be called.
"""
self._iter = None
self.start_iteration()
while self.continue_iteration():
self.pre_iteration()
self.run_iteration()
self.post_iteration()
def step(self):
"""Similar to the 'execute' function, but this one only
executes a single Component from the workflow each time
it's called.
"""
if self._iter is None:
self.start_iteration()
self._iter = self._step()
try:
self._iter.next()
except StopIteration:
self._iter = None
raise
raise RunStopped('Step complete')
def _step(self):
while self.continue_iteration():
self.pre_iteration()
for junk in self._step_workflow():
yield
self.post_iteration()
self._iter = None
raise StopIteration()
def _step_workflow(self):
while True:
try:
self.workflow.step()
except RunStopped:
pass
yield
def stop(self):
self._stop = True
self.workflow.stop()
def start_iteration(self):
"""Called just prior to the beginning of an iteration loop. This can
be overridden by inherited classes. It can be used to perform any
necessary pre-iteration initialization.
"""
self._continue = True
def continue_iteration(self):
"""Return False to stop iterating."""
return self._continue
def pre_iteration(self):
"""Called prior to each iteration. This is where iteration events are set."""
self.set_events()
def run_iteration(self):
"""Runs workflow."""
wf = self.workflow
if len(wf) == 0:
self._logger.warning("'%s': workflow is empty!" % self.get_pathname())
wf.run(ffd_order=self.ffd_order, case_id=self._case_id)
def calc_derivatives(self, first=False, second=False):
""" Calculate derivatives and save baseline states for all components
in this workflow."""
self.workflow.calc_derivatives(first, second)
def check_derivatives(self, order, driver_inputs, driver_outputs):
""" Check derivatives for all components in this workflow."""
self.workflow.check_derivatives(order, driver_inputs, driver_outputs)
def post_iteration(self):
"""Called after each iteration."""
self._continue = False # by default, stop after one iteration
def config_changed(self, update_parent=True):
"""Call this whenever the configuration of this Component changes,
for example, children are added or removed or dependencies may have
changed.
"""
super(Driver, self).config_changed(update_parent)
if self.workflow is not None:
self.workflow.config_changed()
class Driver(Component):
""" A Driver iterates over a workflow of Components until some condition
is met. """
implements(IDriver, IHasEvents)
# set factory here so we see a default value in the docs, even
# though we replace it with a new Dataflow in __init__
workflow = Slot(Workflow, allow_none=True, required=True,
factory=Dataflow, hidden=True)
gradient_options = VarTree(GradientOptions(), iotype='in',
framework_var=True)
def __init__(self):
self._iter = None
super(Driver, self).__init__()
self.workflow = Dataflow(self)
self._required_compnames = None
# clean up unwanted trait from Component
self.remove_trait('missing_deriv_policy')
def __deepcopy__(self, memo):
"""For some reason `missing_deriv_policy` gets resurrected."""
result = super(Driver, self).__deepcopy__(memo)
result.remove_trait('missing_deriv_policy')
return result
def _workflow_changed(self, oldwf, newwf):
"""callback when new workflow is slotted"""
if newwf is not None:
newwf.parent = self
def get_expr_scope(self):
"""Return the scope to be used to evaluate ExprEvaluators."""
return self.parent
def check_config(self, strict=False):
"""Verify that our workflow is able to resolve all of its components."""
# workflow will raise an exception if it can't resolve a Component
super(Driver, self).check_config(strict=strict)
self.workflow.check_config(strict=strict)
def iteration_set(self, solver_only=False):
"""Return a set of all Components in our workflow and
recursively in any workflow in any Driver in our workflow.
solver_only: Bool
Only recurse into solver drivers. These are the only kinds
of drivers whose derivatives get absorbed into the parent
driver's graph.
"""
allcomps = set()
for child in self.workflow.get_components(full=True):
allcomps.add(child)
if has_interface(child, IDriver):
if solver_only and not has_interface(child, ISolver):
continue
allcomps.update(child.iteration_set())
return allcomps
@rbac(('owner', 'user'))
def get_expr_depends(self):
"""Returns a list of tuples of the form (src_comp_name,
dest_comp_name) for each dependency introduced by any ExprEvaluators
in this Driver, ignoring any dependencies on components that are
inside of this Driver's iteration set.
"""
iternames = set([c.name for c in self.iteration_set()])
conn_list = super(Driver, self).get_expr_depends()
new_list = []
for src, dest in conn_list:
if src not in iternames and dest not in iternames:
new_list.append((src, dest))
return new_list
@rbac(('owner', 'user'))
def get_expr_var_depends(self, recurse=True):
"""Returns a tuple of sets of the form (src_set, dest_set)
containing all dependencies introduced by any parameters,
objectives, or constraints in this Driver. If recurse is True,
include any refs from subdrivers.
"""
srcset = set()
destset = set()
if hasattr(self, '_delegates_'):
for dname in self._delegates_:
delegate = getattr(self, dname)
if isinstance(delegate, HasParameters):
destset.update(delegate.get_referenced_varpaths())
elif isinstance(delegate, (HasConstraints,
HasEqConstraints, HasIneqConstraints,
HasObjective, HasObjectives)):
srcset.update(delegate.get_referenced_varpaths())
if recurse:
for sub in self.subdrivers():
srcs, dests = sub.get_expr_var_depends(recurse)
srcset.update(srcs)
destset.update(dests)
return srcset, destset
@rbac(('owner', 'user'))
def subdrivers(self):
"""Returns a generator of of subdrivers of this driver."""
for d in self.iteration_set():
if has_interface(d, IDriver):
yield d
def _get_required_compnames(self):
"""Returns a set of names of components that are required by
this Driver in order to evaluate parameters, objectives
and constraints. This list will include any intermediate
components in the data flow between components referenced by
parameters and those referenced by objectives and/or constraints.
"""
if self._required_compnames is None:
boundary_vars = self.parent.list_vars()
conns = super(Driver, self).get_expr_depends()
getcomps = set([u for u, v in conns if u != self.name \
if u not in boundary_vars and v not in boundary_vars])
setcomps = set([v for u, v in conns if v != self.name \
if u not in boundary_vars and v not in boundary_vars])
full = set(setcomps)
full.update(getcomps)
full.update(self.list_pseudocomps())
compgraph = self.parent._depgraph.component_graph()
for end in getcomps:
for start in setcomps:
full.update(find_all_connecting(compgraph, start, end))
self._required_compnames = full
return self._required_compnames
@rbac(('owner', 'user'))
def list_pseudocomps(self):
"""Return a list of names of pseudocomps resulting from
our objectives, and constraints.
"""
pcomps = []
if hasattr(self, '_delegates_'):
for name in self._delegates_:
delegate = getattr(self, name)
if hasattr(delegate, 'list_pseudocomps'):
pcomps.extend(delegate.list_pseudocomps())
return pcomps
def get_references(self, name):
"""Return a dict of parameter, constraint, and objective
references to component `name` in preparation for
subsequent :meth:`restore_references` call.
name: string
Name of component being referenced.
"""
refs = {}
if hasattr(self, '_delegates_'):
for dname in self._delegates_:
inst = getattr(self, dname)
if isinstance(inst, (HasParameters, HasConstraints,
HasEqConstraints, HasIneqConstraints,
HasObjective, HasObjectives)):
refs[inst] = inst.get_references(name)
return refs
def remove_references(self, name):
"""Remove parameter, constraint, objective and workflow
references to component `name`.
name: string
Name of component being removed.
"""
if hasattr(self, '_delegates_'):
for dname in self._delegates_:
inst = getattr(self, dname)
if isinstance(inst, (HasParameters, HasConstraints,
HasEqConstraints, HasIneqConstraints,
HasObjective, HasObjectives)):
inst.remove_references(name)
self.workflow.remove(name)
def restore_references(self, refs):
"""Restore parameter, constraint, and objective references to component
`name` from `refs`.
refs: object
Value returned by :meth:`get_references`.
"""
for inst, inst_refs in refs.items():
inst.restore_references(inst_refs)
@rbac('*', 'owner')
def run(self, force=False, ffd_order=0, case_uuid=''):
"""Run this object. This should include fetching input variables if
necessary, executing, and updating output variables. Do not override
this function.
force: bool
If True, force component to execute even if inputs have not
changed. (Default is False)
ffd_order: int
Order of the derivatives to be used when finite differencing (1
for first derivatives, 2 for second derivatives). During regular
execution, ffd_order should be 0. (Default is 0)
case_uuid: str
Identifier for the Case that is associated with this run.
"""
# (Re)configure parameters.
if hasattr(self, 'config_parameters'):
self.config_parameters()
# force param pseudocomps to get updated values to start
# KTM1 - probably don't need this anymore
self.update_parameters()
# Reset the workflow.
self.workflow.reset()
super(Driver, self).run(ffd_order, case_uuid)
@rbac(('owner', 'user'))
def configure_recording(self, recording_options=None):
"""Called at start of top-level run to configure case recording.
Returns set of paths for changing inputs."""
return self.workflow.configure_recording(recording_options)
def update_parameters(self):
if hasattr(self, 'get_parameters'):
for param in self.get_parameters().values():
param.initialize(self.get_expr_scope())
def execute(self):
""" Iterate over a workflow of Components until some condition
is met. If you don't want to structure your driver to use
*pre_iteration*, *post_iteration*, etc., just override this function.
As a result, none of the ``<start/pre/post/continue>_iteration()``
functions will be called.
"""
self._iter = None
self.start_iteration()
while self.continue_iteration():
self.pre_iteration()
self.run_iteration()
self.post_iteration()
def stop(self):
"""Stop the workflow."""
self._stop = True
self.workflow.stop()
def start_iteration(self):
"""Called just prior to the beginning of an iteration loop. This can
be overridden by inherited classes. It can be used to perform any
necessary pre-iteration initialization.
"""
self._continue = True
def continue_iteration(self):
"""Return False to stop iterating."""
return self._continue
def pre_iteration(self):
"""Called prior to each iteration.
This is where iteration events are set."""
self.set_events()
def run_iteration(self):
"""Runs workflow."""
wf = self.workflow
if len(wf) == 0:
self._logger.warning("'%s': workflow is empty!"
% self.get_pathname())
wf.run(ffd_order=self.ffd_order)
def calc_derivatives(self, first=False, second=False, savebase=False,
required_inputs=None, required_outputs=None):
""" Calculate derivatives and save baseline states for all components
in this workflow."""
self.workflow.calc_derivatives(first, second, savebase,
required_inputs, required_outputs)
def calc_gradient(self, inputs=None, outputs=None):
"""Returns the gradient of the passed outputs with respect to
all passed inputs. The basic driver behavior is to call calc_gradient
on its workflow. However, some driver (optimizers in particular) may
want to define their own behavior.
"""
return self.workflow.calc_gradient(inputs, outputs, upscope=True)
def post_iteration(self):
"""Called after each iteration."""
self._continue = False # by default, stop after one iteration
def config_changed(self, update_parent=True):
"""Call this whenever the configuration of this Component changes,
for example, children are added or removed or dependencies may have
changed.
"""
super(Driver, self).config_changed(update_parent)
self._required_compnames = None
if self.workflow is not None:
self.workflow.config_changed()
def get_workflow(self):
""" Get the driver info and the list of components that make up the
driver's workflow; recurse on nested drivers.
"""
from openmdao.main.assembly import Assembly
ret = {}
ret['pathname'] = self.get_pathname()
ret['type'] = type(self).__module__ + '.' + type(self).__name__
ret['workflow'] = []
comps = [comp for comp in self.workflow]
for comp in comps:
# Skip pseudo-comps
if hasattr(comp, '_pseudo_type'):
continue
pathname = comp.get_pathname()
if is_instance(comp, Assembly) and comp.driver:
inames = [cls.__name__
for cls in list(implementedBy(comp.__class__))]
ret['workflow'].append({
'pathname': pathname,
'type': type(comp).__module__ + '.' + type(comp).__name__,
'interfaces': inames,
'driver': comp.driver.get_workflow(),
})
elif is_instance(comp, Driver):
ret['workflow'].append(comp.get_workflow())
else:
inames = [cls.__name__
for cls in list(implementedBy(comp.__class__))]
ret['workflow'].append({
'pathname': pathname,
'type': type(comp).__module__ + '.' + type(comp).__name__,
'interfaces': inames,
})
return ret
