clarity.enhancer.multiband_compressor.crossover module

Class compute crossover filter for one crossover frequency.

class clarity.enhancer.multiband_compressor.crossover.Crossover(freq_crossover: list | ndarray | int, sample_rate: float = 44100)

Bases: object

A class to compute crossover filter for two or more crossover frequencies. This is based on [1]

References: [1] D’Appolito, J. A. (1984, October). Active realization of multiway all-pass crossover systems. In Audio Engineering Society Convention 76. Audio Engineering Society.

Example: >>> xover_freqs = np.array( … [250, 500, 1000, 1500, 2000, 3000, 4000, 5000, 6000, 8000] …) * np.sqrt(2) >>> xover = Crossover(xover_freqs) >>> signal = np.random.randn(1000) >>> filtered_signal = xover(signal) >>> xover.plot_filter()

FILTER_ORDER = 4

plot_filter()

Method to plot the frequency response of the filter. This can help to validate the Class is generating the expected filters

xover_component(signal: ndarray, filter_idx: int, len_xover_freqs: int, axis: int = -1) → ndarray

Apply the crossover filter to the signal.

Parameters:

• signal (np.ndarray) – The input signal.

• filter_idx (int) – The index of the filter to apply.

• len_xover_freqs (int) – The number of crossover frequencies.

• axis (int) – The axis along which to apply the filter. Default is -1. `More information in scipy.signal.lfilter` documentation.

Returns:

The filtered signal.

Return type:

np.ndarray

clarity.enhancer.multiband_compressor.crossover.compute_coefficients(xover_freqs: ndarray, sample_rate: float = 44100, order: int = 4) → tuple[ndarray, ndarray, ndarray, ndarray]

Compute the filter coefficients. These are independent of the signal.

Parameters:

• xover_freqs (ndarray) – The crossover frequencies.

• sample_rate (float) – The sample rate of the signal.

• order (int) – The order of the filter.

Returns:

The numerator of the filter. astore (ndarray): The denominator of the filter. bstore_phi (ndarray): The phase correction for the numerator of the

all pass filter.

astore_phi (ndarray): The phase correction for the denominator of the

all pass filter.

Return type:

bsotre (ndarray)

clarity.enhancer.multiband_compressor.crossover.linkwitz_riley(xover_freqs: float, btype: str, order: int = 4) → tuple[ndarray, ndarray]

Compute the Linkwitz-Riley filter. Makes a filter that is equivalent to passing through butterworth twice to get linkwitz-riley

Parameters:

• xover_freqs – The crossover frequency.

• btype – The type of filter.

• order – The order of the filter.

Returns:

The numerator and denominator of the filter.

Return type:

np.ndarray

clarity.enhancer.multiband_compressor.crossover.make_all_pass(b1: ndarray, a1: ndarray, b2: ndarray, a2: ndarray) → tuple[ndarray, ndarray]

Take two filters [b1,a1] and [b2,a2] and calculate the coefficient of a filter that is equivalent to passing the input through each filter in parallel and summing the result

Parameters:

• b1 – Numerator of the first filter

• a1 – Denominator of the first filter

• b2 – Numerator of the second filter

• a2 – Denominator of the second filter

Returns:

The numerator and denominator of the all pass filter.

Return type:

np.ndarray