ssspy.bss.hva

Algorithms

class ssspy.bss.hva.MaskingPDSHVA(mu1=1, mu2=1, alpha=None, relaxation=1, attenuation=None, mask_iter=1, flooring_fn=functools.partial(<function max_flooring>, eps=1e-10), callbacks=None, scale_restoration=True, record_loss=None, reference_id=0)

Harmonic vector analysis proposed in [1].

Parameters:

  • mu1 (float) – Step size. Default: 1.

  • mu2 (float) – Step size. Default: 1.

  • alpha (float) – Relaxation parameter (deprecated). Set relaxation instead.

  • relaxation (float) – Relaxation parameter. Default: 1.

  • attenuation (float, optional) – Attenuation parameter in masking. Default: 1 / n_sources.

  • mask_iter (int) – Number of iterations in application of cosine shrinkage operator.

  • flooring_fn (callable, optional) – A flooring function for numerical stability. This function is expected to return the same shape tensor as the input. If you explicitly set flooring_fn=None, the identity function (lambda x: x) is used. Default: functools.partial(max_flooring, eps=1e-10).

  • callbacks (callable or list[callable], optional) – Callback functions. Each function is called before separation and at each iteration. Default: None.

  • scale_restoration (bool or str) – Technique to restore scale ambiguity. If scale_restoration=True, the projection back technique is applied to estimated spectrograms. You can also specify projection_back explicitly. Default: True.

  • record_loss (bool) – Record the loss at each iteration of the update algorithm if record_loss=True. Default: True.

  • reference_id (int) – Reference channel for projection back. Default: 0.

class ssspy.bss.hva.MaskingADMMHVA(rho=1, alpha=None, relaxation=1, attenuation=None, mask_iter=1, flooring_fn=functools.partial(<function max_flooring>, eps=1e-10), callbacks=None, scale_restoration=True, record_loss=None, reference_id=0)

Harmonic vector analysis using ADMM with masking.

Parameters:

  • rho (float) – Penalty parameter. Default: 1.

  • alpha (float) – Relaxation parameter (deprecated). Set relaxation instead.

  • relaxation (float) – Relaxation parameter. Default: 1.

  • attenuation (float, optional) – Attenuation parameter.

  • mask_iter (int) – Number of iterations in application of cosine shrinkage operator.

  • flooring_fn (callable, optional) – A flooring function for numerical stability. This function is expected to receive (n_channels, n_bins, n_frames) and return (n_channels, n_bins, n_frames). If you explicitly set flooring_fn=None, the identity function (lambda x: x) is used. Default: partial(max_flooring, eps=1e-10).

  • callbacks (callable or list[callable], optional) – Callback functions. Each function is called before separation and at each iteration. Default: None.

  • scale_restoration (bool or str) – Technique to restore scale ambiguity. If scale_restoration=True, the projection back technique is applied to estimated spectrograms. You can also specify projection_back explicitly. Default: True.

  • record_loss (bool, optional) – Record the loss at each iteration of the update algorithm if record_loss=True. Default: None.

  • reference_id (int) – Reference channel for projection back. Default: 0.

class ssspy.bss.hva.HVA(mu1=1, mu2=1, alpha=None, relaxation=1, attenuation=None, mask_iter=1, flooring_fn=functools.partial(<function max_flooring>, eps=1e-10), callbacks=None, scale_restoration=True, record_loss=None, reference_id=0)

Alias of MaskingPDSHVA.