def numpy_weighted_median(data, weights=None):
    """Calculate the weighted median of an array/list using numpy."""
    import numpy as np
    if weights is None:
        return np.median(np.array(data).flatten())
    data, weights = np.array(data).flatten(), np.array(weights).flatten()
    if any(weights > 0):
        sorted_data, sorted_weights = map(np.array, zip(*sorted(zip(data, weights))))
        midpoint = 0.5 * sum(sorted_weights)
        if any(weights > midpoint):
            return (data[weights == np.max(weights)])[0]
        cumulative_weight = np.cumsum(sorted_weights)
        below_midpoint_index = np.where(cumulative_weight <= midpoint)[0][-1]
        if cumulative_weight[below_midpoint_index] - midpoint < sys.float_info.epsilon:
            return np.mean(sorted_data[below_midpoint_index:below_midpoint_index+2])
        return sorted_data[below_midpoint_index+1]