Solver

entities

CableType

Bases: Enum

Defines the type of the cable.

HeatEquationType

Bases: Enum

Defines all the possible heat equation types and their string values. * WITH_ONE_TEMPERATURE: computes a single temperature for the cable * WITH_THREE_TEMPERATURES: computes three temperatures for the cable (core, surface and average) * WITH_THREE_TEMPERATURES_LEGACY: computes three temperatures for the cable (core, surface and average), with specifications

ModelType

Bases: Enum

All the models available in thermohl. * cigre : model published by CIGRE * ieee : model published by IEEE * olla : model developed by RTE's R&D team * rte : model developed by RTE

PowerType

Bases: Enum

All the powers involved in the cable heating and cooling. * Joule heating : the way the electricity heats the cable (+ magnetic effect for core-metal cables) * Solar heating : the way the sun heats the cable * Convective cooling : the way the air cools the cable * Radiative cooling : the way the cable is cooled down by the radiations it emits * Precipitation : the way the rain cools the cable

TargetType

Bases: Enum

Defines the locations in the cable of the reference temperature * SURFACE: the reference temperature is at the surface of the cable * AVERAGE: the reference temperature is at an average thickness of the cable * CORE: the reference temperature is at the core of the cable

TemperatureType

Bases: Enum

Defines all the possible temperature locations for the cable. * SURFACE: the temperature at the surface of the cable * AVERAGE: the average temperature of the cable * CORE: the temperature at the core of the cable

VariableType

Bases: Enum

Defines the different types of variables that can be used in a solver. * ERROR: used to retrieve the error of the solver * TIME: the moment associated with TRANSIT and TEMPERATURE predictions * TRANSIT: the electric transit used in the solver * TEMPERATURE: the temperature used in the solver

solver

Base class to build a solver for heat equation.

Solver

Solver(
    dic: Optional[dict[str, Any]] = None,
    joule: Type[PowerTerm] = PowerTerm,
    solar: Type[PowerTerm] = PowerTerm,
    convective: Type[PowerTerm] = PowerTerm,
    radiative: Type[PowerTerm] = PowerTerm,
    precipitation: Type[PowerTerm] = PowerTerm,
)

Bases: ABC

Object to solve a temperature problem.

The temperature of a conductor is driven by four power terms, two heating terms (joule and solar heating) and three cooling terms (convective, radiative and precipitation cooling). This class is used to solve a temperature problem with the heating and cooling terms passed to its init function.

Parameters:

Name	Type	Description	Default
dic	dict[str, Any] | None	Input values used in power terms. If there is a missing value, a default is used.	None
joule	Type[PowerTerm]	Joule heating term class.	PowerTerm
solar	Type[PowerTerm]	Solar heating term class.	PowerTerm
convective	Type[PowerTerm]	Convective cooling term class.	PowerTerm
radiative	Type[PowerTerm]	Radiative cooling term class.	PowerTerm
precipitation	Type[PowerTerm]	Precipitation cooling term class.	PowerTerm

Returns:

Type	Description
None	None

Source code in src/thermohl/solver/solver.py

def __init__(
    self,
    dic: Optional[dict[str, Any]] = None,
    joule: Type[PowerTerm] = PowerTerm,
    solar: Type[PowerTerm] = PowerTerm,
    convective: Type[PowerTerm] = PowerTerm,
    radiative: Type[PowerTerm] = PowerTerm,
    precipitation: Type[PowerTerm] = PowerTerm,
) -> None:
    """Create a Solver object.

    Args:
        dic (dict[str, Any] | None): Input values used in power terms. If there is a missing value, a default is used.
        joule (Type[PowerTerm]): Joule heating term class.
        solar (Type[PowerTerm]): Solar heating term class.
        convective (Type[PowerTerm]): Convective cooling term class.
        radiative (Type[PowerTerm]): Radiative cooling term class.
        precipitation (Type[PowerTerm]): Precipitation cooling term class.

    Returns:
        None

    """
    self.args = Parameters(dic)
    self.args.extend()
    self.joule_heating = joule(**self.args.__dict__)
    self.solar_heating = solar(**self.args.__dict__)
    self.convective_cooling = convective(**self.args.__dict__)
    self.radiative_cooling = radiative(**self.args.__dict__)
    self.precipitation_cooling = precipitation(**self.args.__dict__)
    self.args.compress()

reshape

reshape(
    input_array: numberArrayLike,
    nb_row: int,
    nb_columns: int,
) -> numberArray

Reshape the input array to the specified dimensions (nr, nc) if possible.

Parameters:

Name	Type	Description	Default
input_array	numberArrayLike	Input array to be reshaped.	required
nb_row	int	Desired number of rows for the reshaped array.	required
nb_columns	int	Desired number of columns for the reshaped array.	required

Returns:

Name	Type	Description
numberArray	numberArray	Reshaped array of size (nb_row, nb_columns). If reshaping is not possible, returns an array filled with the input_value repeated to fill the dimension (nb_row, nb_columns).

Raises:

Type	Description
AttributeError	If the input_array has an invalid shape that cannot be reshaped.

Source code in src/thermohl/solver/solver.py

def reshape(input_array: numberArrayLike, nb_row: int, nb_columns: int) -> numberArray:
    """
    Reshape the input array to the specified dimensions (nr, nc) if possible.

    Args:
        input_array (numberArrayLike): Input array to be reshaped.
        nb_row (int): Desired number of rows for the reshaped array.
        nb_columns (int): Desired number of columns for the reshaped array.

    Returns:
        numberArray: Reshaped array of size (nb_row, nb_columns). If reshaping is not possible,
            returns an array filled with the input_value repeated to fill the dimension (nb_row, nb_columns).

    Raises:
        AttributeError: If the input_array has an invalid shape that cannot be reshaped.
    """
    reshaped_array = ndarray
    try:
        input_shape = input_array.shape
        if len(input_shape) == 1:
            if nb_row == input_shape[0]:
                reshaped_array = np.column_stack(nb_columns * (input_array,))
            elif nb_columns == input_shape[0]:
                reshaped_array = np.vstack(nb_row * (input_array,))
        elif len(input_shape) == 0:
            raise AttributeError()
        else:
            reshaped_array = np.reshape(input_array, (nb_row, nb_columns))
    except AttributeError:
        reshaped_array = input_array * np.ones(
            (nb_row, nb_columns), dtype=type(input_array)
        )
    return reshaped_array

parameters

Parameters

Parameters(input_dict: Optional[dict[str, Any]] = None)

Object to store Solver args in a dict-like manner.

Source code in src/thermohl/solver/parameters.py

def __init__(self, input_dict: Optional[dict[str, Any]] = None):
    # add default values
    self._set_default_values()
    # use values from input dict
    if input_dict is None:
        return
    arg_keys = self.keys()
    for input_key, input_value in input_dict.items():
        if input_key in arg_keys and input_value is not None:
            self[input_key] = input_value

compress

compress() -> None

Compress the elements in the Args dictionary by replacing lists containing a unique value with this value.

Source code in src/thermohl/solver/parameters.py

def compress(self) -> None:
    """
    Compress the elements in the Args dictionary by replacing lists containing a unique value
    with this value.
    """
    for key in self.keys():
        u = np.unique(self[key])
        if len(u) == 1:
            self[key] = u[0]

extend

extend() -> None

Extend all compressed elements in the Args dictionary to the right length, ie the number of computations. If the element is a list, it already has the right length. If the element is a scalar, it is replaced with a list of the right length filled with the scalar value.

Source code in src/thermohl/solver/parameters.py

def extend(self) -> None:
    """
    Extend all compressed elements in the Args dictionary to the right length, ie the number of computations.
    If the element is a list, it already has the right length.
    If the element is a scalar, it is replaced with a list of the right length filled with the scalar value.
    """
    number_of_computations = self.get_number_of_computations()
    for key in self.keys():
        if not isinstance(self[key], Iterable):
            self[key] = np.array(number_of_computations * [self[key]])

keys

keys() -> KeysView[str]

Get list of members as dict keys.

Source code in src/thermohl/solver/parameters.py

def keys(self) -> KeysView[str]:
    """Get list of members as dict keys."""
    return self.__dict__.keys()