mqt.qudits.core.dfs_tree¶

Module Contents¶

class Node(key: int, rotation: R | CustomOne, u_of_level: numpy.typing.NDArray[numpy.complex128], graph_current: LevelGraph, current_cost: float, current_decomp_cost: float, max_cost: tuple[float, float], pi_pulses: list[R], parent_key: int | None = None, children: list[Node] | None = None)[source]¶

key¶

children: list[Node] = None¶

rotation¶

u_of_level¶

finished: bool = False¶

current_cost¶

current_decomp_cost¶

max_cost¶

size = 0¶

parent_key = None¶

graph¶

PI_PULSES¶

add(new_key: int, rotation: R | CustomOne, u_of_level: numpy.typing.NDArray[numpy.complex128], graph_current: LevelGraph, current_cost: float, current_decomp_cost: float, max_cost: tuple[float, float], pi_pulses: list[R]) → None[source]¶

__str__() → str[source]¶

__bool__() → bool[source]¶

class NAryTree[source]¶

size: int = 0¶

global_id_counter: int = 0¶

add(new_key: int, rotation: R | CustomOne, u_of_level: numpy.typing.NDArray[numpy.complex128], graph_current: LevelGraph, current_cost: float, current_decomp_cost: float, max_cost: tuple[float, float], pi_pulses: list[R], parent_key: int | None = None) → None[source]¶

find_node(node: Node, key: int) → Node | None[source]¶

depth(key: int) → int[source]¶

max_depth(node: Node) → int[source]¶

size_refresh(node: Node) → int[source]¶

found_checker(node: Node) → bool[source]¶

min_cost_decomp(node: Node) → tuple[list[Node], tuple[float, float], LevelGraph][source]¶

retrieve_decomposition(node: Node) → tuple[list[Node], tuple[float, float], LevelGraph][source]¶

is_empty() → bool[source]¶

property total_size: int¶

print_tree(node: Node, str_aux: str) → str[source]¶

__str__() → str[source]¶