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Solve the following problem using Python, implementing the functions described below, one line at a time
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Description:
 def time_indices(npts, dt, start, end, index):
 """ Determine the new start and end indices of the time series. :param npts: Number of points in original time series :param dt: Time step of original time series :param start: int or float, optional, New start point :param end: int or float, optional, New end point :param index: bool, optional, if False then start and end are considered values in time. :return: tuple, start index, end index """

    if index is False:  # Convert time values into indices
        if end != -1:
            e_index = int(end / dt) + 1
        else:
            e_index = end
        s_index = int(start / dt)
    else:
        s_index = start
        e_index = end
    if e_index > npts:
        raise exceptions.ModelWarning("Cut point is greater than time series length")
    return s_index, e_index