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heuristics

calculate_distance(a, b, num_columns, distance_metric)

Calculate the distance between two qubits based on the specified distance metric. Args: a: The index of the first qubit. b: The index of the second qubit. num_columns: The number of columns in the grid. distance_metric: 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(a: int, b: int, num_columns: int, distance_metric: DistanceMetric) -> float:
    """
    Calculate the distance between two qubits based on the specified distance metric.
    Args:
        a: The index of the first qubit.
        b: The index of the second qubit.
        num_columns: The number of columns in the grid.
        distance_metric: Distance metric to be used (Manhattan, Euclidean, or Chebyshev).
    Returns:
        float: The distance between the two qubits.
    """
    x1, y1 = divmod(a, num_columns)
    x2, y2 = divmod(b, num_columns)

    if distance_metric == DistanceMetric.MANHATTAN:
        return abs(x1 - x2) + abs(y1 - y2)
    if distance_metric == DistanceMetric.EUCLIDEAN:
        return float(((x1 - x2) ** 2 + (y1 - y2) ** 2) ** 0.5)
    if distance_metric == DistanceMetric.CHEBYSHEV:
        return max(abs(x1 - x2), abs(y1 - y2))
    msg = "Invalid distance metric. Choose Manhattan, Euclidean, or Chebyshev."
    raise ValueError(msg)