heuristics

calculate_distance

calculate_distance(
    q0_index: int,
    q1_index: int,
    num_columns: int,
    distance_metric: DistanceMetric,
) -> float

Calculate the distance between two qubits based on the specified distance metric.

Parameters:

Name	Type	Description	Default
q0_index	int	The index of the first qubit.	required
q1_index	int	The index of the second qubit.	required
num_columns	int	The number of columns in the grid.	required
distance_metric	DistanceMetric	Distance metric to be used (Manhattan, Euclidean, or Chebyshev).	required

Returns:

Type	Description
float	The distance between the two qubits.

Source code in opensquirrel/passes/router/heuristics.py

def calculate_distance(q0_index: int, q1_index: int, num_columns: int, distance_metric: DistanceMetric) -> float:
    """Calculate the distance between two qubits based on the specified distance metric.

    Args:
        q0_index (int): The index of the first qubit.
        q1_index (int): The index of the second qubit.
        num_columns (int): The number of columns in the grid.
        distance_metric (DistanceMetric): Distance metric to be used (Manhattan, Euclidean, or Chebyshev).

    Returns:
        The distance between the two qubits.

    """
    x1, y1 = divmod(q0_index, num_columns)
    x2, y2 = divmod(q1_index, num_columns)

    match distance_metric:
        case DistanceMetric.MANHATTAN:
            return abs(x1 - x2) + abs(y1 - y2)

        case DistanceMetric.EUCLIDEAN:
            return float(((x1 - x2) ** 2 + (y1 - y2) ** 2) ** 0.5)

        case DistanceMetric.CHEBYSHEV:
            return max(abs(x1 - x2), abs(y1 - y2))

        case _:
            msg = f"invalid distance metric {distance_metric!r}: choose Manhattan, Euclidean, or Chebyshev"
            raise ValueError(msg)