def _add_variable(self, name, val, **kwargs):
""" Contruct metadata for new variable.
Args
----
name : string
Name of the variable.
val : float or ndarray or object
Initial value for the variable.
**kwargs
Arbitrary keyword arguments to be added to metadata.
Raises
------
RuntimeError
If name is already in use or if setup has already been performed.
NameError
If name is not valid.
ValueError
If a valid value or shape is not specified.
"""
shape = kwargs.get('shape')
self._check_name(name)
meta = kwargs.copy()
if isinstance(val, FileRef):
val._set_meta(kwargs)
meta['val'] = val = self._get_initial_val(val, shape)
if is_differentiable(val) and not meta.get('pass_by_obj'):
if isinstance(val, np.ndarray):
meta['size'] = val.size
meta['shape'] = val.shape
else:
meta['size'] = 1
meta['shape'] = 1
else:
if not meta.get('pass_by_obj'):
self._pbo_warns.append((name, val))
meta['size'] = 0
meta['pass_by_obj'] = True
if isinstance(shape, int) and shape > 1:
meta['shape'] = (shape, )
return meta
def _add_variable(self, name, val, **kwargs):
""" Contruct metadata for new variable.
Args
----
name : string
Name of the variable.
val : float or ndarray or object
Initial value for the variable.
**kwargs
Arbitrary keyword arguments to be added to metadata.
Raises
------
RuntimeError
If name is already in use or if setup has already been performed.
NameError
If name is not valid.
ValueError
If a valid value or shape is not specified.
"""
shape = kwargs.get('shape')
self._check_varname(name)
meta = kwargs.copy()
if isinstance(val, FileRef):
val._set_meta(kwargs)
meta['val'] = val = self._get_initial_val(val, shape)
if is_differentiable(val) and not meta.get('pass_by_obj'):
if isinstance(val, np.ndarray):
meta['size'] = val.size
meta['shape'] = val.shape
else:
meta['size'] = 1
meta['shape'] = 1
else:
if not meta.get('pass_by_obj'):
self._pbo_warns.append((name, val))
meta['size'] = 0
meta['pass_by_obj'] = True
if isinstance(shape, int) and shape > 1:
meta['shape'] = (shape,)
return meta
def _add_variable(self, name, val, var_type, **kwargs):
""" Contruct metadata for new variable.
Args
----
name : string
Name of the variable.
val : float or ndarray or object
Initial value for the variable.
var_type : 'param' or 'output'
Type of variable.
**kwargs
Arbitrary keyword arguments to be added to metadata.
Raises
------
RuntimeError
If name is already in use or if setup has already been performed.
NameError
If name is not valid.
ValueError
If a valid value or shape is not specified.
"""
shape = kwargs.get("shape")
self._check_val(name, var_type, val, shape)
self._check_name(name)
meta = kwargs.copy()
meta["promoted_name"] = name
meta["val"] = val = self._get_initial_val(val, shape)
if is_differentiable(val) and not meta.get("pass_by_obj"):
if isinstance(val, np.ndarray):
meta["size"] = val.size
meta["shape"] = val.shape
else:
meta["size"] = 1
meta["shape"] = 1
else:
meta["size"] = 0
meta["pass_by_obj"] = True
if isinstance(shape, int) and shape > 1:
meta["shape"] = (shape,)
return meta
def _setup_var_meta(self, name, meta):
"""
Populate the metadata dict for the named variable.
Args
----
name : str
The name of the variable to add.
meta : dict
Starting metadata for the variable, collected from components
in an earlier stage of setup.
"""
vmeta = meta.copy()
val = meta['val']
if not is_differentiable(val) or meta.get('pass_by_obj'):
vmeta['val'] = _ByObjWrapper(val)
return vmeta
def _add_variable(self, name, val, **kwargs):
""" Contruct metadata for new variable.
Args
----
name : string
Name of the variable.
val : float or ndarray or object
Initial value for the variable.
**kwargs
Arbitrary keyword arguments to be added to metadata.
Raises
------
RuntimeError
If name is already in use or if setup has already been performed.
NameError
If name is not valid.
ValueError
If a valid value or shape is not specified.
"""
shape = kwargs.get('shape')
self._check_varname(name)
meta = kwargs.copy()
# Check for bad unit here
unit = meta.get('unit')
if unit:
try:
pq = PhysicalQuantity(1.0, unit)
except:
msg = "Unit '{}' is not a valid unit or combination of units."
raise RuntimeError(msg.format(unit))
if isinstance(val, FileRef):
val._set_meta(kwargs)
meta['val'] = val = self._get_initial_val(val, shape)
if is_differentiable(val) and not meta.get('pass_by_obj'):
if isinstance(val, np.ndarray):
meta['size'] = val.size
meta['shape'] = val.shape
else:
meta['size'] = 1
meta['shape'] = 1
else:
if not meta.get('pass_by_obj'):
self._pbo_warns.append((name, val))
meta['size'] = 0
meta['pass_by_obj'] = True
if isinstance(shape, int) and shape > 1:
meta['shape'] = (shape,)
if 'low' in kwargs:
raise TypeError("Used arg 'low' when adding variable '%s'. "
"Use 'lower' instead." % name)
if 'high' in kwargs:
raise TypeError("Used arg 'high' when adding variable '%s'. "
"Use 'upper' instead." % name)
return meta
def _add_variable(self, name, val, **kwargs):
""" Contruct metadata for new variable.
Args
----
name : string
Name of the variable.
val : float or ndarray or object
Initial value for the variable.
**kwargs
Arbitrary keyword arguments to be added to metadata.
Raises
------
RuntimeError
If name is already in use or if setup has already been performed.
NameError
If name is not valid.
ValueError
If a valid value or shape is not specified.
"""
shape = kwargs.get('shape')
self._check_varname(name)
meta = kwargs.copy()
# Check for bad unit here
unit = meta.get('unit')
if unit:
try:
pq = PhysicalQuantity(1.0, unit)
except:
msg = "Unit '{}' is not a valid unit or combination of units."
raise RuntimeError(msg.format(unit))
if isinstance(val, FileRef):
val._set_meta(kwargs)
meta['val'] = val = self._get_initial_val(val, shape)
if is_differentiable(val) and not meta.get('pass_by_obj'):
if isinstance(val, np.ndarray):
meta['size'] = val.size
meta['shape'] = val.shape
else:
meta['size'] = 1
meta['shape'] = 1
else:
if not meta.get('pass_by_obj'):
self._pbo_warns.append((name, val))
meta['size'] = 0
meta['pass_by_obj'] = True
if isinstance(shape, int) and shape > 1:
meta['shape'] = (shape, )
if 'low' in kwargs:
raise TypeError("Used arg 'low' when adding variable '%s'. "
"Use 'lower' instead." % name)
if 'high' in kwargs:
raise TypeError("Used arg 'high' when adding variable '%s'. "
"Use 'upper' instead." % name)
return meta
def __init__(self, name, mdao_config, root, subproblem_output_meta):
super(TestBenchComponent, self).__init__()
self.name = name
self.mdao_config = mdao_config
self.__directory = mdao_config['components'][name]['details'][
'directory']
self.original_testbench_manifest = self._read_testbench_manifest()
self.manifest_params = {
param['Name']: param
for param in self.original_testbench_manifest['Parameters']
}
self.manifest_fileinputs = {
param['Name']: param
for param in self.original_testbench_manifest.get(
'FileInputs', [])
}
self.manifest_metrics = {
param['Name']: param
for param in self.original_testbench_manifest['Metrics']
}
self.manifest_fileoutputs = {
param['Name']: param
for param in self.original_testbench_manifest.get(
'FileOutputs', {})
}
self.deriv_options['type'] = 'fd'
def get_meta(param):
units = param.get('units')
if units:
return {'units': str(units)}
else:
return {}
for param_name, param in six.iteritems(
mdao_config['components'][name].get('parameters', {})):
pass_by_obj = source_is_not_driver = param.get(
'source', [''])[0] not in mdao_config['drivers']
val = 0.0
manifest_fileinput = self.manifest_fileinputs.get(param_name)
if manifest_fileinput is not None:
val = FileRef(
os.path.join(
self.__directory,
manifest_fileinput.get('FileName', param_name)))
self.add_param(_get_param_name(param_name),
val=val,
binary=True,
pass_by_obj=True)
continue
elif source_is_not_driver and 'source' in param:
if len(param['source']) == 1:
# TODO: Single-element source must be a ProblemInput
problemInput = mdao_config['problemInputs'][param['source']
[0]]
if 'innerSource' in problemInput and problemInput[
'innerSource'][0] in mdao_config['drivers']:
source_type = mdao_config['drivers'][
problemInput['innerSource'][0]]['designVariables'][
problemInput['innerSource'][1]].get('type')
if source_type == 'enum':
val = mdao_config['drivers'][problemInput[
'innerSource'][0]]['designVariables'][
problemInput['innerSource'][1]]['items'][0]
pass_by_obj = True
elif source_type == "int":
val = 0
else:
(val,
pass_by_obj) = get_problem_input_value(problemInput)
else:
if param['source'][0] in mdao_config.get(
'subProblems', {}):
# Source is a subproblem output; look up its real path, value, and pass_by_obj-ness
source_component = {
c.name: c
for c in root.components()
}[param['source'][0]]
output_name = subproblem_output_meta[
param['source'][0]][param['source'][1]]
meta = source_component._problem.root.unknowns._dat[
output_name].meta
val = meta['val']
pass_by_obj = meta.get('pass_by_obj', False)
else:
# Source is not a subproblem output; must be a component
source_component = {
c.name: c
for c in root.components()
}[param['source'][0]]
val = source_component._init_unknowns_dict[
param['source'][-1]]['val']
pass_by_obj = source_component._init_unknowns_dict[
param['source'][-1]].get('pass_by_obj', False)
elif 'source' in param:
source_type = mdao_config['drivers'][param['source'][0]][
'designVariables'][param['source'][-1]].get('type')
if source_type == 'enum':
val = mdao_config['drivers'][param['source'][0]][
'designVariables'][param['source'][-1]]['items'][0]
pass_by_obj = True
elif source_type == "int":
val = 0
else:
manifest_param = self.manifest_params.get(param_name)
if manifest_param is not None:
val = manifest_param['Value']
pass_by_obj = True
else:
raise ValueError(
'Could not find parameter or input file named {} in testbench_manifest.json'
.format(param_name))
self.add_param(_get_param_name(param_name),
val=val,
pass_by_obj=pass_by_obj,
**get_meta(param))
for metric_name, metric in six.iteritems(
mdao_config['components'][name].get('unknowns', {})):
manifest_metric = self.manifest_metrics.get(metric_name)
if manifest_metric is not None:
pass_by_obj = True
for driver in mdao_config['drivers'].values():
if driver.get('type') != 'optimizer':
continue
for objective in driver['objectives'].values():
if objective['source'][0] == name and objective[
'source'][1] == metric_name:
pass_by_obj = False
metric_meta = get_meta(metric)
metric_meta['val'] = 0.0
for mdao_component in root.components():
# TODO: metric is possibly connected to a subproblem problemOutput. We should handle this case (root.components() does not contain the desired component, nor is it created yet)
destination_component = mdao_config['components'].get(
mdao_component.name)
if destination_component is None:
# TODO: possibly connected to an input to a component in a subproblem. We should handle this case
# destination_component should possibly be an IndepVarComp from a ProblemInput. We don't need to handle this case
# destination_component should possibly be an IndepVarComp designVariable. We don't need to handle this case
continue
for parameter_name, parameter in six.iteritems(
destination_component['parameters']):
if parameter['source'] == [self.name, metric_name]:
mdao_parameter = mdao_component._init_params_dict[
_get_param_name(
parameter_name,
destination_component.get('type'))]
for key in ('val', 'shape'):
next_val = mdao_parameter.get(key, None)
if next_val is not None:
metric_meta.pop('val', None)
metric_meta[key] = next_val
if key == 'val':
pass_by_obj = pass_by_obj or not is_differentiable(
next_val)
break
self.add_output(metric_name,
pass_by_obj=pass_by_obj,
**metric_meta)
else:
manifest_fileoutput = self.manifest_fileoutputs.get(
metric_name)
if manifest_fileoutput is None:
raise ValueError(metric_name)
self.add_output(metric_name,
val=FileRef(
os.path.join(
self.__directory,
manifest_fileoutput.get(
'FileName', metric_name))),
binary=True,
pass_by_obj=True)
self.add_output('_ret_code', val=0, pass_by_obj=True)
