def METHOD_NAME(
    weights: pd.DataFrame, costs_dict: dict
) -> pd.DataFrame:
    asset_names = list(weights.columns)
    SR_list = [costs_dict[asset] for asset in asset_names]
    # doesn't really matter but we need a figure
    PSEUDO_CORRELATION_FOR_COSTS = 0.5
    # very high as costs are 'certain'
    ASSUMED_LENGTH_OF_DATA_IN_YEARS_FOR_COSTS = 100
    adj_weights = adjust_dataframe_of_weights_for_SR(
        weights,
        SR_list=SR_list,
        years_of_data=ASSUMED_LENGTH_OF_DATA_IN_YEARS_FOR_COSTS,
        avg_correlation=PSEUDO_CORRELATION_FOR_COSTS,
    )
    return adj_weights