def frames_to_time(frames, sr=<NUM_LIT>, hop_length=<NUM_LIT>, n_fft=None):
samples = frames_to_samples(frames,<EOL>hop_length=hop_length,<EOL>n_fft=n_fft)<EOL>return samples_to_time(samples, sr=sr)<EOL>
Converts frame counts to time (seconds).

    Parameters
    ----------
    frames     : np.ndarray [shape=(n,)]
        frame index or vector of frame indices

    sr         : number > 0 [scalar]
        audio sampling rate

    hop_length : int > 0 [scalar]
        number of samples between successive frames

    n_fft : None or int > 0 [scalar]
        Optional: length of the FFT window.
        If given, time conversion will include an offset of `n_fft / 2`
        to counteract windowing effects when using a non-centered STFT.

    Returns
    -------
    times : np.ndarray [shape=(n,)]
        time (in seconds) of each given frame number:
        `times[i] = frames[i] * hop_length / sr`

    See Also
    --------
    time_to_frames : convert time values to frame indices
    frames_to_samples : convert frame indices to sample indices

    Examples
    --------
    >>> y, sr = librosa.load(librosa.util.example_audio_file())
    >>> tempo, beats = librosa.beat.beat_track(y, sr=sr)
    >>> beat_times = librosa.frames_to_time(beats, sr=sr)