def prepare_weighted_spans(targets,  # type: List[TargetExplanation]
                           preserve_density=None,  # type: Optional[bool]
                           ):
    # type: (...) -> List[Optional[List[PreparedWeightedSpans]]]
    """ Return weighted spans prepared for rendering.
    Calculate a separate weight range for each different weighted
    span (for each different index): each target has the same number
    of weighted spans.
    """
    targets_char_weights = [
        [get_char_weights(ws, preserve_density=preserve_density)
         for ws in t.weighted_spans.docs_weighted_spans]
         if t.weighted_spans else None
         for t in targets]  # type: List[Optional[List[np.ndarray]]]
    max_idx = max_or_0(len(ch_w or []) for ch_w in targets_char_weights)

    targets_char_weights_not_None = [
        cw for cw in targets_char_weights
        if cw is not None]  # type: List[List[np.ndarray]]

    spans_weight_ranges = [
        max_or_0(
            abs(x) for char_weights in targets_char_weights_not_None
            for x in char_weights[idx])
        for idx in range(max_idx)]
    return [
        [PreparedWeightedSpans(ws, char_weights, weight_range)
         for ws, char_weights, weight_range in zip(
            t.weighted_spans.docs_weighted_spans,  # type: ignore
            t_char_weights,
            spans_weight_ranges)]
        if t_char_weights is not None else None
        for t, t_char_weights in zip(targets, targets_char_weights)]