librosa/core/audio.py
def clicks(times=None, frames=None, sr=22050, hop_length=512,
           click_freq=1000.0, click_duration=0.1, click=None, length=None):
    """Returns a signal with the signal `click` placed at each specified time

    Parameters
    ----------
    times : np.ndarray or None
        times to place clicks, in seconds

    frames : np.ndarray or None
        frame indices to place clicks

    sr : number > 0
        desired sampling rate of the output signal

    hop_length : int > 0
        if positions are specified by `frames`, the number of samples between frames.

    click_freq : float > 0
        frequency (in Hz) of the default click signal.  Default is 1KHz.

    click_duration : float > 0
        duration (in seconds) of the default click signal.  Default is 100ms.

    click : np.ndarray or None
        optional click signal sample to use instead of the default blip.

    length : int > 0
        desired number of samples in the output signal


    Returns
    -------
    click_signal : np.ndarray
        Synthesized click signal


    Raises
    ------
    ParameterError
        - If neither `times` nor `frames` are provided.
        - If any of `click_freq`, `click_duration`, or `length` are out of range.


    Examples
    --------
    >>> # Sonify detected beat events
    >>> y, sr = librosa.load(librosa.util.example_audio_file())
    >>> tempo, beats = librosa.beat.beat_track(y=y, sr=sr)
    >>> y_beats = librosa.clicks(frames=beats, sr=sr)

    >>> # Or generate a signal of the same length as y
    >>> y_beats = librosa.clicks(frames=beats, sr=sr, length=len(y))

    >>> # Or use timing instead of frame indices
    >>> times = librosa.frames_to_time(beats, sr=sr)
    >>> y_beat_times = librosa.clicks(times=times, sr=sr)

    >>> # Or with a click frequency of 880Hz and a 500ms sample
    >>> y_beat_times880 = librosa.clicks(times=times, sr=sr,
    ...                                  click_freq=880, click_duration=0.5)

    Display click waveform next to the spectrogram

    >>> import matplotlib.pyplot as plt
    >>> plt.figure()
    >>> S = librosa.feature.melspectrogram(y=y, sr=sr)
    >>> ax = plt.subplot(2,1,2)
    >>> librosa.display.specshow(librosa.power_to_db(S, ref=np.max),
    ...                          x_axis='time', y_axis='mel')
    >>> plt.subplot(2,1,1, sharex=ax)
    >>> librosa.display.waveplot(y_beat_times, sr=sr, label='Beat clicks')
    >>> plt.legend()
    >>> plt.xlim(15, 30)
    >>> plt.tight_layout()
    """

    # Compute sample positions from time or frames
    if times is None:
        if frames is None:
            raise ParameterError('either "times" or "frames" must be provided')

        positions = frames_to_samples(frames, hop_length=hop_length)
    else:
        # Convert times to positions
        positions = time_to_samples(times, sr=sr)

    if click is not None:
        # Check that we have a well-formed audio buffer
        util.valid_audio(click, mono=True)

    else:
        # Create default click signal
        if click_duration <= 0:
            raise ParameterError('click_duration must be strictly positive')

        if click_freq <= 0:
            raise ParameterError('click_freq must be strictly positive')

        angular_freq = 2 * np.pi * click_freq / float(sr)

        click = np.logspace(0, -10,
                            num=int(np.round(sr * click_duration)),
                            base=2.0)

        click *= np.sin(angular_freq * np.arange(len(click)))

    # Set default length
    if length is None:
        length = positions.max() + click.shape[0]
    else:
        if length < 1:
            raise ParameterError('length must be a positive integer')

        # Filter out any positions past the length boundary
        positions = positions[positions < length]

    # Pre-allocate click signal
    click_signal = np.zeros(length, dtype=np.float32)

    # Place clicks
    for start in positions:
        # Compute the end-point of this click
        end = start + click.shape[0]

        if end >= length:
            click_signal[start:] += click[:length - start]
        else:
            # Normally, just add a click here
            click_signal[start:end] += click

    return click_signal
def clicks(times=None, frames=None, sr=22050, hop_length=512,
           click_freq=1000.0, click_duration=0.1, click=None, length=None):
    # Compute sample positions from time or frames
    if times is None:
        if frames is None:
            raise ParameterError('either "times" or "frames" must be provided')

        positions = frames_to_samples(frames, hop_length=hop_length)
    else:
        # Convert times to positions
        positions = time_to_samples(times, sr=sr)

    if click is not None:
        # Check that we have a well-formed audio buffer
        util.valid_audio(click, mono=True)

    else:
        # Create default click signal
        if click_duration <= 0:
            raise ParameterError('click_duration must be strictly positive')

        if click_freq <= 0:
            raise ParameterError('click_freq must be strictly positive')

        angular_freq = 2 * np.pi * click_freq / float(sr)

        click = np.logspace(0, -10,
                            num=int(np.round(sr * click_duration)),
                            base=2.0)

        click *= np.sin(angular_freq * np.arange(len(click)))

    # Set default length
    if length is None:
        length = positions.max() + click.shape[0]
    else:
        if length < 1:
            raise ParameterError('length must be a positive integer')

        # Filter out any positions past the length boundary
        positions = positions[positions < length]

    # Pre-allocate click signal
    click_signal = np.zeros(length, dtype=np.float32)

    # Place clicks
    for start in positions:
        # Compute the end-point of this click
        end = start + click.shape[0]

        if end >= length:
            click_signal[start:] += click[:length - start]
        else:
            # Normally, just add a click here
            click_signal[start:end] += click

    return click_signal
def clicks ( times = None , frames = None , sr = 22050 , hop_length = 512 , click_freq = 1000.0 , click_duration = 0.1 , click = None , length = None ) : # Compute sample positions from time or frames if times is None : if frames is None : raise ParameterError ( 'either "times" or "frames" must be provided' ) positions = frames_to_samples ( frames , hop_length = hop_length ) else : # Convert times to positions positions = time_to_samples ( times , sr = sr ) if click is not None : # Check that we have a well-formed audio buffer util . valid_audio ( click , mono = True ) else : # Create default click signal if click_duration <= 0 : raise ParameterError ( 'click_duration must be strictly positive' ) if click_freq <= 0 : raise ParameterError ( 'click_freq must be strictly positive' ) angular_freq = 2 * np . pi * click_freq / float ( sr ) click = np . logspace ( 0 , - 10 , num = int ( np . round ( sr * click_duration ) ) , base = 2.0 ) click *= np . sin ( angular_freq * np . arange ( len ( click ) ) ) # Set default length if length is None : length = positions . max ( ) + click . shape [ 0 ] else : if length < 1 : raise ParameterError ( 'length must be a positive integer' ) # Filter out any positions past the length boundary positions = positions [ positions < length ] # Pre-allocate click signal click_signal = np . zeros ( length , dtype = np . float32 ) # Place clicks for start in positions : # Compute the end-point of this click end = start + click . shape [ 0 ] if end >= length : click_signal [ start : ] += click [ : length - start ] else : # Normally, just add a click here click_signal [ start : end ] += click return click_signal
Returns a signal with the signal `click` placed at each specified time

    Parameters
    ----------
    times : np.ndarray or None
        times to place clicks, in seconds

    frames : np.ndarray or None
        frame indices to place clicks

    sr : number > 0
        desired sampling rate of the output signal

    hop_length : int > 0
        if positions are specified by `frames`, the number of samples between frames.

    click_freq : float > 0
        frequency (in Hz) of the default click signal.  Default is 1KHz.

    click_duration : float > 0
        duration (in seconds) of the default click signal.  Default is 100ms.

    click : np.ndarray or None
        optional click signal sample to use instead of the default blip.

    length : int > 0
        desired number of samples in the output signal


    Returns
    -------
    click_signal : np.ndarray
        Synthesized click signal


    Raises
    ------
    ParameterError
        - If neither `times` nor `frames` are provided.
        - If any of `click_freq`, `click_duration`, or `length` are out of range.


    Examples
    --------
    >>> # Sonify detected beat events
    >>> y, sr = librosa.load(librosa.util.example_audio_file())
    >>> tempo, beats = librosa.beat.beat_track(y=y, sr=sr)
    >>> y_beats = librosa.clicks(frames=beats, sr=sr)

    >>> # Or generate a signal of the same length as y
    >>> y_beats = librosa.clicks(frames=beats, sr=sr, length=len(y))

    >>> # Or use timing instead of frame indices
    >>> times = librosa.frames_to_time(beats, sr=sr)
    >>> y_beat_times = librosa.clicks(times=times, sr=sr)

    >>> # Or with a click frequency of 880Hz and a 500ms sample
    >>> y_beat_times880 = librosa.clicks(times=times, sr=sr,
    ...                                  click_freq=880, click_duration=0.5)

    Display click waveform next to the spectrogram

    >>> import matplotlib.pyplot as plt
    >>> plt.figure()
    >>> S = librosa.feature.melspectrogram(y=y, sr=sr)
    >>> ax = plt.subplot(2,1,2)
    >>> librosa.display.specshow(librosa.power_to_db(S, ref=np.max),
    ...                          x_axis='time', y_axis='mel')
    >>> plt.subplot(2,1,1, sharex=ax)
    >>> librosa.display.waveplot(y_beat_times, sr=sr, label='Beat clicks')
    >>> plt.legend()
    >>> plt.xlim(15, 30)
    >>> plt.tight_layout()
Returns a signal with the signal click placed at each specified time