Other functions

Single-level n-dimensional Discrete Wavelet Transform.

pywt.dwtn(data, wavelet[, mode='sym'])

Performs single-level n-dimensional Discrete Wavelet Transform.

Parameters:

• data – n-dimensional array
• wavelet – wavelet to use (Wavelet object or name string)
• mode – signal extension mode, see MODES

Results are arranged in a dictionary, where key specifies the transform type on each dimension and value is a n-dimensional coefficients array.

For example, for a 2D case the result will look something like this:

{
    'aa': <coeffs>  # A(LL) - approx. on 1st dim, approx. on 2nd dim
    'ad': <coeffs>  # H(LH) - approx. on 1st dim, det. on 2nd dim
    'da': <coeffs>  # V(HL) - det. on 1st dim, approx. on 2nd dim
    'dd': <coeffs>  # D(HH) - det. on 1st dim, det. on 2nd dim
}

Integrating wavelet functions - intwave()

pywt.intwave(wavelet[, precision=8])

Integration of wavelet function approximations as well as any other signals can be performed using the pywt.intwave() function.

The result of the call depends on the wavelet argument:

• for orthogonal wavelets - an integral of the wavelet function specified on an x-grid:

  [int_psi, x] = intwave(wavelet, precision)
  

• for other wavelets - integrals of decomposition and reconstruction wavelet functions and a corresponding x-grid:

  [int_psi_d, int_psi_r, x] = intwave(wavelet, precision)
  

• for a tuple of coefficients data and a x-grid - an integral of function and the given x-grid is returned (the x-grid is used for computations).:

  [int_function, x] = intwave((data, x), precision)
  

Example:

>>> import pywt
>>> wavelet1 = pywt.Wavelet('db2')
>>> [int_psi, x] = pywt.intwave(wavelet1, precision=5)
>>> wavelet2 = pywt.Wavelet('bior1.3')
>>> [int_psi_d, int_psi_r, x] = pywt.intwave(wavelet2, precision=5)

Central frequency of psi wavelet function

pywt.centfrq(wavelet[, precision=8])

pywt.centfrq((function_aprox, x))

Parameters:

• wavelet – Wavelet, wavelet name string or (wavelet function approx., x grid) pair
• precision – Precision that will be used for wavelet function approximation computed with the Wavelet.wavefun() method.