def classical_bcr(riskinputs, riskmodel, param, monitor):
    """
    Compute and return the average losses for each asset.

    :param riskinputs:
        :class:`openquake.risklib.riskinput.RiskInput` objects
    :param riskmodel:
        a :class:`openquake.risklib.riskinput.CompositeRiskModel` instance
    :param param:
        dictionary of extra parameters
    :param monitor:
        :class:`openquake.baselib.performance.Monitor` instance
    """
    R = riskinputs[0].hazard_getter.num_rlzs
    result = AccumDict(accum=numpy.zeros((R, 3), F32))
    for ri in riskinputs:
        for out in riskmodel.gen_outputs(ri, monitor):
            for asset, (eal_orig, eal_retro, bcr) in zip(
                    ri.assets, out['structural']):
                aval = asset['value-structural']
                result[asset['ordinal']][out.rlzi] = numpy.array([
                    eal_orig * aval, eal_retro * aval, bcr])
    return {'bcr_data': result}
Compute and return the average losses for each asset.

    :param riskinputs:
        :class:`openquake.risklib.riskinput.RiskInput` objects
    :param riskmodel:
        a :class:`openquake.risklib.riskinput.CompositeRiskModel` instance
    :param param:
        dictionary of extra parameters
    :param monitor:
        :class:`openquake.baselib.performance.Monitor` instance