fastoad.openmdao.variables.variable_list module

Class for managing a list of OpenMDAO variables.

class fastoad.openmdao.variables.variable_list.VariableList(iterable=(), /)[source]

Bases: list

Class for storing OpenMDAO variables.

A list of Variable instances, but items can also be accessed through variable names. It also has utilities to be converted from/to some other data structures (python dict, OpenMDAO IndepVarComp, pandas DataFrame)

See documentation of Variable to see how to manipulate each element.

There are several ways for adding variables:

# Assuming these Python variables are ready...
var_1 = Variable('var/1', value=0.)
metadata_2 = {'value': 1., 'units': 'm'}

# ... a VariableList instance can be populated like this:
vars_A = VariableList()
vars_A.append(var_1)              # Adds directly a Variable instance
vars_A['var/2'] = metadata_2      # Adds the variable with given name and given metadata

Note

Adding a Variable instance with a name that is already in the VariableList instance will replace the previous Variable instance instead of adding a new one.

# It is also possible to instantiate a VariableList instance from another VariableList
# instance or a simple list of Variable instances
vars_B = VariableList(vars_A)
vars_C = VariableList([var_1])

# An existing VariableList instance can also receive the content of another VariableList
# instance.
vars_C.update(vars_A)             # variables in vars_A will overwrite variables with same
                                  # name in vars_C

After that, following equalities are True:

print( var_1 in vars_A )
print( 'var/1' in vars_A.names() )
print( 'var/2' in vars_A.names() )

names() → List[str][source]

Returns: names of variables

metadata_keys() → List[str][source]

Returns: the metadata keys that are common to all variables in the list

append(var: fastoad.openmdao.variables.variable.Variable) → None[source]: Append var to the end of the list, unless its name is already used. In that case, var will replace the previous Variable instance with the same name.

update(other_var_list: list, add_variables: bool = True)[source]

Uses variables in other_var_list to update the current VariableList instance.

For each Variable instance in other_var_list:

if a Variable instance with same name exists, it is replaced by the one in other_var_list (special case: if one in other_var_list has an empty description, the original description is kept)
if not, Variable instance from other_var_list will be added only if add_variables==True

Parameters

other_var_list – source for new Variable data
add_variables – if True, unknown variables are also added

to_ivc() → openmdao.core.indepvarcomp.IndepVarComp[source]

Returns: an OpenMDAO IndepVarComp instance with all variables from current list

to_dataframe() → pandas.core.frame.DataFrame[source]

Creates a DataFrame instance from a VariableList instance.

Column names are “name” + the keys returned by Variable.get_openmdao_keys(). Values in Series “value” are floats or lists (numpy arrays are converted).

Returns: a pandas DataFrame instance with all variables from current list

classmethod from_dict(var_dict: Union[Mapping[str, dict], Iterable[Tuple[str, dict]]]) → fastoad.openmdao.variables.variable_list.VariableList[source]

Creates a VariableList instance from a dict-like object.

Parameters: var_dict –
Returns: a VariableList instance

classmethod from_ivc(ivc: openmdao.core.indepvarcomp.IndepVarComp) → fastoad.openmdao.variables.variable_list.VariableList[source]

Creates a VariableList instance from an OpenMDAO IndepVarComp instance

Parameters: ivc – an IndepVarComp instance
Returns: a VariableList instance

classmethod from_dataframe(df: pandas.core.frame.DataFrame) → fastoad.openmdao.variables.variable_list.VariableList[source]

Creates a VariableList instance from a pandas DataFrame instance.

The DataFrame instance is expected to have column names “name” + some keys among the ones given by Variable.get_openmdao_keys().

Parameters: df – a DataFrame instance
Returns: a VariableList instance

classmethod from_problem(problem: openmdao.core.problem.Problem, use_initial_values: bool = False, get_promoted_names: bool = True, promoted_only: bool = True, io_status: str = 'all') → fastoad.openmdao.variables.variable_list.VariableList[source]

Creates a VariableList instance containing inputs and outputs of an OpenMDAO Problem.

The inputs (is_input=True) correspond to the variables of IndepVarComp components and all the unconnected input variables.

Note

Variables from _auto_ivc are ignored.

Parameters

problem – OpenMDAO Problem instance to inspect
use_initial_values – if True, or if problem has not been run, returned instance will contain values before computation
get_promoted_names – if True, promoted names will be returned instead of absolute ones (if no promotion, absolute name will be returned)
promoted_only – if True, only promoted variable names will be returned
io_status – to choose with type of variable we return (“all”, “inputs, “outputs”)

Returns

VariableList instance

classmethod from_unconnected_inputs(problem: openmdao.core.problem.Problem, with_optional_inputs: bool = False) → fastoad.openmdao.variables.variable_list.VariableList[source]

Creates a VariableList instance containing unconnected inputs of an OpenMDAO Problem.

Warning

problem.setup() must have been run.

If optional_inputs is False, only inputs that have numpy.nan as default value (hence considered as mandatory) will be in returned instance. Otherwise, all unconnected inputs will be in returned instance.

Parameters

problem – OpenMDAO Problem instance to inspect
with_optional_inputs – If True, returned instance will contain all unconnected inputs. Otherwise, it will contain only mandatory ones.

Returns

VariableList instance