espnet2.train.preprocessor.any_allzero

source

espnet2.train.preprocessor.any_allzero(signal)

Check if any of the elements in the input signal are all zeros.

This function evaluates whether any given element in a signal (which can be a single array or a list/tuple of arrays) consists entirely of zeros. It uses NumPy’s allclose function to check for numerical closeness to zero, which is particularly useful for floating-point comparisons.

• Parameters:
  • signal (Union *[*np.ndarray , list , tuple ]) – The input signal, which can be
  • array (a NumPy)
  • list (a)
  • tuple (or a tuple. Each element of the list or)
  • zeros. (should be an array that is to be checked for being all)
• Returns: Returns True if any element in the input signal is all zeros; otherwise returns False.
• Return type: bool

Examples

>>> any_allzero(np.array([0.0, 0.0, 0.0]))
True

>>> any_allzero(np.array([1.0, 0.0, 0.0]))
False

>>> any_allzero([np.array([0.0, 0.0]), np.array([1.0, 2.0])])
True

>>> any_allzero([np.array([1.0, 2.0]), np.array([3.0, 4.0])])
False

>>> any_allzero((np.array([0.0, 0.0]), np.array([1.0, 2.0])))
True

NOTE

This function uses NumPy’s allclose which allows for a numerical tolerance when checking if values are close to zero.