def _preprocess_inputs(durations, event_observed, timeline, entry, weights):
    """
    Cleans and confirms input to what lifelines expects downstream
    """

    n = len(durations)
    durations = np.asarray(pass_for_numeric_dtypes_or_raise_array(durations)).reshape((n,))

    # set to all observed if event_observed is none
    if event_observed is None:
        event_observed = np.ones(n, dtype=int)
    else:
        event_observed = np.asarray(event_observed).reshape((n,)).copy().astype(int)

    if entry is not None:
        entry = np.asarray(entry).reshape((n,))

    event_table = survival_table_from_events(durations, event_observed, entry, weights=weights)
    if timeline is None:
        timeline = event_table.index.values
    else:
        timeline = np.asarray(timeline)

    return (durations, event_observed, timeline.astype(float), entry, event_table)
Cleans and confirms input to what lifelines expects downstream