Sequency methods

Basic methods

Sequency.walsh_matrix(scale)	Generate sequency order Walsh functions and return in a matrix.
Sequency.denoise(input_values[, method, …])	Perform a denoise operation on the input_values using either Walsh or Fourier method.

Transform methods

Sequency.fwt(input_values[, basis_span, …])	Perform a Fast Discrete Walsh Transform on the input data.
Sequency.ifwt(fwt_data[, scale, return_length])	Perform an inverse Fast Discrete Walsh Transform on the input data.
Sequency.fft(data[, sampling_frequency])	A basic implementation of the Fast Fourier Transform as implemented in Numpy.fft.fft.
Sequency.ifft(data)	A basic implementation of the inverse Fast Fourier Transform as implemented in Numpy.fft.ifft.

Analysis methods

Sequency.sequency_spectrum(input_values[, …])	A convenient Sequency power spectrum representation of the input_values data, this will be normalised by the sum of squares of all amplitude values, thus representing a proportional power spectrum.
Sequency.frequency_spectrum(data[, …])	A basic implementation of the Fast Fourier Transform power spectrum as implemented in Numpy.fft.fft.