Modeling source signals

API references

class doatools.model.signals.SignalGenerator

Bases: abc.ABC

Abstrace base class for all signal generators.

Extend this class to create your own signal generators.

dim

Retrieves the dimension of the signal generator.

emit(n)

Emits the signal matrix.

Generates a k x n matrix where k is the dimension of the signal and each column represents a sample.

class doatools.model.signals.ComplexStochasticSignal(dim, C=1.0)

Bases: doatools.model.signals.SignalGenerator

Creates a signal generator that generates zero-mean complex circularly-symmetric Gaussian signals.

Parameters:

• dim (int) – Dimension of the complex Gaussian distribution. Must match the size of C if C is not a scalar.
• C –

  Covariance matrix of the complex Gaussian distribution. Can be specified by

  1. A full covariance matrix.
  2. An real vector denoting the diagonals of the covariance matrix if the covariance matrix is diagonal.
  3. A scalar if the covariance matrix is diagonal and all diagonal elements share the same value. In this case, parameter n must be specified.

  Default value is 1.0.

dim

Retrieves the dimension of the signal generator.

emit(n)

Emits the signal matrix.

Generates a k x n matrix where k is the dimension of the signal and each column represents a sample.

class doatools.model.signals.RandomPhaseSignal(dim, amplitudes=1.0)

Bases: doatools.model.signals.SignalGenerator

Creates a random phase signal generator.

The phases are uniformly and independently sampled from \([-\pi, \pi]\).

Parameters:

• dim (int) – Dimension of the signal (usually equal to the number of sources).
• amplitudes –

  Amplitudes of the signal. Can be specified by

  1. A scalar if all sources have the same amplitude.
  2. A vector if the sources have different amplitudes.

dim

Retrieves the dimension of the signal generator.

emit(n)

Emits the signal matrix.

Generates a k x n matrix where k is the dimension of the signal and each column represents a sample.