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heuristics

calculate_distance(q0_index, q1_index, num_columns, distance_metric)

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: float: The distance between the two qubits.

Source code in opensquirrel/passes/router/heuristics.py 
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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:
        float: 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 = "Invalid distance metric. Choose Manhattan, Euclidean, or Chebyshev."
            raise ValueError(msg)