pyrc.core.network

class RCNetwork(save_to_pickle: bool = True, load_from_pickle: bool = True, load_solution: bool = True, num_cores_jacobian: int = 1, settings: ~pyrc.core.settings.Settings = <pyrc.core.settings.Settings object>, rc_objects: ~pyrc.core.components.templates.RCObjects = <pyrc.core.components.templates.RCObjects object>, rc_solution: ~pyrc.core.components.templates.RCSolution = <pyrc.core.components.templates.RCSolution object>, continue_canceled: bool = True)

Bases: object

Parameters:

• save_to_pickle

• load_from_pickle

• load_solution

• num_cores_jacobian

• settings

• rc_objects

• rc_solution

• continue_canceled (bool, optional) – If True, continue canceled simulations. Overwrites load_solution

__init__(save_to_pickle: bool = True, load_from_pickle: bool = True, load_solution: bool = True, num_cores_jacobian: int = 1, settings: ~pyrc.core.settings.Settings = <pyrc.core.settings.Settings object>, rc_objects: ~pyrc.core.components.templates.RCObjects = <pyrc.core.components.templates.RCObjects object>, rc_solution: ~pyrc.core.components.templates.RCSolution = <pyrc.core.components.templates.RCSolution object>, continue_canceled: bool = True)

Parameters:

• save_to_pickle

• load_from_pickle

• load_solution

• num_cores_jacobian

• settings

• rc_objects

• rc_solution

• continue_canceled (bool, optional) – If True, continue canceled simulations. Overwrites load_solution

property all_objects: list

change_static_dynamic(calculate_static: bool | str)

check_courant(time_step: float)

Calculates the Courant number for the whole network and raises an error if its larger than 1.

Parameters:

time_step (float) – The maximum time step in seconds.

Raises:

HighCourantNumberError : – If the courant number is greater than 1 the network will calculate shit.

copy_dict()

create_network(*args, **kwargs)

get_node_by_id(_id: str | int)

Returns the node with the given id.

Parameters:

_id (str | int) – The id of the node.

Return type:

TemperatureNode | InternalHeatSource

get_symbols()

Returns a list with all symbols, except time dependent symbols.

Returns:

All symbols, except time dependent symbols.

Return type:

list

get_symbols_and_values() → tuple[list, list]

Return two lists of first: all symbols and second: all associated values of all rc objects.

Return type:

tuple[list, list]

get_time_dependent_symbols() → list

A list with all time dependent symbols but each of it is only added once.

Returns:

The time dependent symbols.

Return type:

list

get_values()

Returns a list with all values, except of time dependent symbols.

Returns:

All values, except of time dependent symbols.

Return type:

list

property hash

Compute a deterministic hash for the RCNetwork where node identity (class name + obj.id) and topology matter.

For Capacitor instances, an optional internal_heat_source (identified by its id) is encoded as a node attribute.

For Cell subclass instances, position and delta arrays are encoded.

Returns:

SHA-256 hex digest of the canonical edge and node representation.

Return type:

str

property inhomogeneous_system: bool

Returns True if inputs are existing and the network is inhomogeneous. False otherwise.

Return type:

bool

property input_matrix: SparseMatrix | ImmutableSparseMatrix | spmatrix | sparray

property input_matrix_function: Callable

property input_matrix_symbol: MutableSparseMatrix | ImmutableSparseMatrix

property input_vector: ndarray

property input_vector_symbol: ndarray

property inputs: list[EquationItemInput]

load_initial_values(return_bool: bool = False, pickle_path_single_solution: str = None) → bool

Loads the last time step solution (temperature vector) and sets it as initial values.

load_matrices()

make_system_matrices()

Creates the Jacobian matrices of the RC Network.

If self.load_from_pickle the whole network will be loaded from pickle file if it exists to prevent heavy calculations.

Returns:

The system matrix as sympy expression.

Return type:

sympy expression

matrix_to_latex_diag()

no_infinity(sp_matrix: SparseMatrix | spmatrix | sparray) → bool

Checks the given sparse matrix for infinity entries and symbolic singularities.

Notes

Saves a dict, which maps each free sympy symbol to a set of values at which at least one symbolic entry diverges. Empty if no symbolic entries exist.

Parameters:

sp_matrix (SparseMatrix | spmatrix | sparray) – A sparse matrix/vector to check, may contain numeric values or sympy expressions.

Returns:

bool : True if no numeric infinity was found.

Return type:

tuple[bool, dict]

property nodes

property objects_with_identical_symbols: list

Get all objects with symbols that are relevant for the system matrix.

You cannot just use every object, because some (e.g. Resistors) can be summarized in local groups with one symbol representing the whole group, like the equivalent resistance of multiple connected Resistors.

No InternalHeatSource s are returned, because their symbol is already represented in the corresponding Node.

Returns:

All network objects without the ones that are already taken into account by the symbols of another. The list has the same order every time it is created.

Return type:

list

property pickle_path: str

pickle_path_result(t_span, name_add_on=None)

property pickle_path_single_solution: str

pickle_path_solution(t_span, name_add_on=None) → str

reset_properties()

property save_folder_path

save_last_step_solution(pickle_path_single_solution: str = None)

Saves the last time step solution.

save_matrices()

solve_network(t_span: tuple | ~typing.Any = None, print_progress=False, name_add_on: str = '', check_courant: bool = True, time_dependent_function: ~typing.Callable = None, hook_function: ~typing.Callable = None, expected_solution_size_mb=5000, **kwargs: dict[slice(<class 'str'>, int | typing.Any, None)])

Solves the network at the given times.

If time_vector is None, one second is calculated.

Parameters:

• t_span (tuple | Any) – Interval of integration (t0, tf). The solver starts with t=t0 and integrates until it reaches t=tf. Both t0 and tf must be floats or values interpretable by the float conversion function.

• print_progress (bool, optional) – If True, some print outs are made during solving to get the time step that is currently simulated.

• name_add_on (str, optional) –

  Optional add-on to the name of in-between saves that is placed after the hash value (separated by “_”). Example save name:

  42395d3d9f07f06ce9c9cb609b406aa54fc2dc5e8c4d9cc75987d9a02541ad2f_nameAddOn_zw_000001080_h.pickle

• check_courant (bool, optional) – If True, self.check_courant(0.4) is run before simulating.

• time_dependent_function (Callable) – A function returning the values for all time dependent symbols that are in the matrices in the same order as self.get_time_dependent_symbols(). This function is required if time dependent symbols exist. It must return an iterable (e.g. list)

• hook_function (Callable, optional) – A function that is run before the network is solved using solve_ivp. Can be used to catch the time before the solving actually starts (e.g. used in PerformanceTest).

• expected_solution_size_mb (int | float, optional) – The expected solution size in Megabytes. Is used for RAM-Management in SystemHandler.solve(). The solution size depends on the size of the RC network and number of saved time steps.

• kwargs (dict[str: int | Any], optional) – Passed to SystemHandler.

Returns:

The solution of the network (time and temperatures of all nodes). See: https://docs.scipy.org/doc/scipy/reference/generated/scipy.integrate.solve_ivp.html#solve-ivp

Return type:

scipy.integrate._ivp.ivp.OdeResult

property system_handler_type

Returns the SystemHandler type depending on which system (in/homogeneous) is needed.

Returns:

The system handler type.

Return type:

type

property system_matrix: SparseMatrix | ImmutableSparseMatrix | spmatrix | sparray

property system_matrix_function: Callable

property system_matrix_symbol: MutableSparseMatrix | ImmutableSparseMatrix

property temperature_vector: ndarray

property temperature_vector_symbol: list

property time_steps: list

Returns a list with all time steps.

Returns:

The time steps.

Return type:

list