librosa/util/utils.py
def valid_intervals(intervals):
    '''Ensure that an array is a valid representation of time intervals:

        - intervals.ndim == 2
        - intervals.shape[1] == 2
        - intervals[i, 0] <= intervals[i, 1] for all i

    Parameters
    ----------
    intervals : np.ndarray [shape=(n, 2)]
        set of time intervals

    Returns
    -------
    valid : bool
        True if `intervals` passes validation.
    '''

    if intervals.ndim != 2 or intervals.shape[-1] != 2:
        raise ParameterError('intervals must have shape (n, 2)')

    if np.any(intervals[:, 0] > intervals[:, 1]):
        raise ParameterError('intervals={} must have non-negative durations'.format(intervals))

    return True
def valid_intervals(intervals):
    '''Ensure that an array is a valid representation of time intervals:

        - intervals.ndim == 2
        - intervals.shape[1] == 2
        - intervals[i, 0] <= intervals[i, 1] for all i

    Parameters
    ----------
    intervals : np.ndarray [shape=(n, 2)]
        set of time intervals

    Returns
    -------
    valid : bool
        True if `intervals` passes validation.
    '''

    if intervals.ndim != 2 or intervals.shape[-1] != 2:
        raise ParameterError('intervals must have shape (n, 2)')

    if np.any(intervals[:, 0] > intervals[:, 1]):
        raise ParameterError('intervals={} must have non-negative durations'.format(intervals))

    return True
Ensure that an array is a valid representation of time intervals:

        - intervals.ndim == 2
        - intervals.shape[1] == 2
        - intervals[i, 0] <= intervals[i, 1] for all i

    Parameters
    ----------
    intervals : np.ndarray [shape=(n, 2)]
        set of time intervals

    Returns
    -------
    valid : bool
        True if `intervals` passes validation.