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Solve the following problem using Python, implementing the functions described below, one line at a time
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Description:
 def qubo_to_ising(Q, offset=0.0):
 """Convert a QUBO problem to an Ising problem. Map a quadratic unconstrained binary optimization (QUBO) problem :math:`x' Q x` defined over binary variables (0 or 1 values), where the linear term is contained along the diagonal of Q, to an Ising model defined on spins (variables with {-1, +1} values). Return h and J that define the Ising model as well as the offset in energy between the two problem formulations: .. math:: x' Q x = offset + s' J s + h' s See :meth:`~dimod.utilities.ising_to_qubo` for the inverse function. Args: Q (dict[(variable, variable), coefficient]):
 are 2-tuples of variables of the model and values are biases associated with the pair of variables. Tuples (u, v) represent interactions and (v, v) linear biases. offset (numeric, optional, default=0):
 Constant offset to be applied to the energy. Default 0. Returns: (dict, dict, float):
 A 3-tuple containing: dict: Linear coefficients of the Ising problem. dict: Quadratic coefficients of the Ising problem. float: New energy offset. Examples: This example converts a QUBO problem of two variables that have positive biases of value 1 and are positively coupled with an interaction of value 1 to an Ising problem. ({1: 0.75, 2: 0.75}, {(1, 2):
 0.25}, 1.75) """

    h = {}
    J = {}
    linear_offset = 0.0
    quadratic_offset = 0.0

    for (u, v), bias in iteritems(Q):
        if u == v:
            if u in h:
                h[u] += .5 * bias
            else:
                h[u] = .5 * bias
            linear_offset += bias

        else:
            if bias != 0.0:
                J[(u, v)] = .25 * bias

            if u in h:
                h[u] += .25 * bias
            else:
                h[u] = .25 * bias

            if v in h:
                h[v] += .25 * bias
            else:
                h[v] = .25 * bias

            quadratic_offset += bias

    offset += .5 * linear_offset + .25 * quadratic_offset

    return h, J, offset