7685876d31bc74dc9e1a3426c337d0c55c3d87da,paderbox/speech_enhancement/beamformer.py,,get_pca_vector,#,171

Before Change

        with shape (..., sensors, sensors)
    :return: Set of beamforming vectors with shape (..., sensors)
    
    return get_pca(target_psd_matrix)[0]


// TODO: Possible test case: Assert W^H * H = 1.
// TODO: Make function more stable for badly conditioned noise matrices.

After Change

    
    eigenvectors, eigenvalues = get_pca(target_psd_matrix)
    if scaling is None:
        scale = 1
    elif scaling == "trace":
        // ToDo: check whether this improves bf results
        scale = np.sqrt(
            np.trace(target_psd_matrix, axis1=-1, axis2=-2)
        ) / np.linalg.norm(eigenvectors, axis=-1)
        scale = scale[..., None]
        print(scale.shape)
    elif scaling == "eigenvalue":
        // ToDo: check whether this improves bf results
        scale = eigenvalues / np.linalg.norm(
            eigenvectors, axis=-1)
        scale = scale[..., None]
    else:
        raise ValueError
    return eigenvectors * scale


// TODO: Possible test case: Assert W^H * H = 1.
// TODO: Make function more stable for badly conditioned noise matrices.

Instances