yodel.analysis module

This module provides classes for audio signal analysis such as spectral analysis.

class yodel.analysis.DFT(size)

Bases: builtins.object

The Discrete Fourier Transform allows to convert a time-domain signal into a frequency-domain spectrum.

Warning:

It should not be used in practice for computational reasons, and should only be used for testing purposes. Instead, prefer using the FFT.

Reference:

“Digital Signal Processing, a practical guide for engineers and scientists”, Steven W. Smith

__init__(size)

Initialize the Discrete Fourier Transform.

Parameters:size – length of the DFT (should only be a power of 2)

forward(real_signal, real_spec, imag_spec)

Compute the complex spectrum of a given real time-domain signal

Parameters:

• real_signal – real time-domain input signal
• real_spec – real-part of the output complex spectrum
• imag_spec – imaginary-part of the output complex spectrum

inverse(real_spec, imag_spec, real_signal)

Compute the real time-domain signal of a given complex spectrum

Parameters:

• real_spec – real-part of the complex spectrum
• imag_spec – imaginary-part of the complex spectrum
• real_signal – real time-domain output signal

class yodel.analysis.FFT(size)

Bases: builtins.object

The Fast Fourier Transform is a faster algorithm for performing the DFT. It allows converting a time-domain signal into a frequency-domain spectrum.

Reference:

“Digital Signal Processing, a practical guide for engineers and scientists”, Steven W. Smith

__init__(size)

Initialize the Fast Fourier Transform.

Parameters:size – length of the FFT (should only be a power of 2)

forward(real_signal, real_spec, imag_spec)

Compute the complex spectrum of a given real time-domain signal

Parameters:

• real_signal – real time-domain input signal
• real_spec – real-part of the output complex spectrum
• imag_spec – imaginary-part of the output complex spectrum

inverse(real_spec, imag_spec, real_signal)

Compute the real time-domain signal of a given complex spectrum

Parameters:

• real_spec – real-part of the complex spectrum
• imag_spec – imaginary-part of the complex spectrum
• real_signal – real time-domain output signal

class yodel.analysis.Window(size)

Bases: builtins.object

An analysis window function allows to reduce unwanted frequencies when performing spectrum analysis.

__init__(size)

Initialize the analysis window. By default, a flat window is applied. Use one of the provided methods to make it Hanning or Hamming.

Parameters:size – length of the analysis window

blackman(size)

Make a Blackman analysis window.

Parameters:size – length of the analysis window

hamming(size)

Make a Hamming analysis window.

Parameters:size – length of the analysis window

hanning(size)

Make a Hanning analysis window.

Parameters:size – length of the analysis window

process(input_signal, output_signal)

Perform windowing on an input signal.

Parameters:

• input_signal – input signal to be windowed
• output_signal – resulting windowed signal

rectangular(size)

Make a rectangular (flat) window. This type of window does not have any affect when applied on an input signal.

Parameters:size – length of the analysis window