augly/audio/functional.py [353:395]:
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    audio: Union[str, np.ndarray],
    sample_rate: int = DEFAULT_SAMPLE_RATE,
    kernel_size: int = 31,
    power: float = 2.0,
    margin: float = 1.0,
    output_path: Optional[str] = None,
    metadata: Optional[List[Dict[str, Any]]] = None,
) -> Tuple[np.ndarray, int]:
    """
    Extracts the harmonic part of the audio

    @param audio: the path to the audio or a variable of type np.ndarray that
        will be augmented

    @param sample_rate: the audio sample rate of the inputted audio

    @param kernel_size: kernel size for the median filters

    @param power: exponent for the Wiener filter when constructing soft
        mask matrices

    @param margin: margin size for the masks

    @param output_path: the path in which the resulting audio will be stored. If None,
        the resulting np.ndarray will still be returned

    @param metadata: if set to be a list, metadata about the function execution
        including its name, the source & dest duration, sample rates, etc. will be
        appended to the inputted list. If set to None, no metadata will be appended

    @returns: the augmented audio array and sample rate
    """
    assert isinstance(kernel_size, int), "Expected 'kernel_size' to be an int"
    assert isinstance(power, (int, float)), "Expected 'power' to be a number"
    assert isinstance(margin, (int, float)), "Expected 'margin' to be a number"
    audio, sample_rate = audutils.validate_and_load_audio(audio, sample_rate)

    if metadata is not None:
        func_kwargs = deepcopy(locals())
        func_kwargs.pop("metadata")

    num_channels = 1 if audio.ndim == 1 else audio.shape[0]
    if num_channels == 1:
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augly/audio/functional.py [858:899]:
- - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
    audio: Union[str, np.ndarray],
    sample_rate: int = DEFAULT_SAMPLE_RATE,
    kernel_size: int = 31,
    power: float = 2.0,
    margin: float = 1.0,
    output_path: Optional[str] = None,
    metadata: Optional[List[Dict[str, Any]]] = None,
) -> Tuple[np.ndarray, int]:
    """
    Extracts the percussive part of the audio

    @param audio: the path to the audio or a variable of type np.ndarray that
        will be augmented

    @param sample_rate: the audio sample rate of the inputted audio

    @param kernel_size: kernel size for the median filters

    @param power: exponent for the Wiener filter when constructing soft mask matrices

    @param margin: margin size for the masks

    @param output_path: the path in which the resulting audio will be stored. If None,
        the resulting np.ndarray will still be returned

    @param metadata: if set to be a list, metadata about the function execution
        including its name, the source & dest duration, sample rates, etc. will be
        appended to the inputted list. If set to None, no metadata will be appended

    @returns: the augmented audio array and sample rate
    """
    assert isinstance(kernel_size, int), "Expected 'kernel_size' to be an int"
    assert isinstance(power, (int, float)), "Expected 'power' to be a number"
    assert isinstance(margin, (int, float)), "Expected 'margin' to be a number"
    audio, sample_rate = audutils.validate_and_load_audio(audio, sample_rate)

    if metadata is not None:
        func_kwargs = deepcopy(locals())
        func_kwargs.pop("metadata")

    num_channels = 1 if audio.ndim == 1 else audio.shape[0]
    if num_channels == 1:
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