Audio Classes

Audio data are at the core or pyfar and three classes can be used for storing, processing, and visualizing such data

• The Signal class can be used to store equidistant and complete signals that can be converted between the time and frequency domain.

• The TimeData and FrequencyData classes are intended for incomplete or non-equidistant audio data in the time and frequency domain that can not be converted between the time and frequency domain.

All three classes provide methods for accessing the data and useful meta data such as the sampling rate or number of channels, and almost all functions in pyfar take audio classes as their main input. See audio classes for a complete documentation.

Signal Types

The Signal class distinguishes between two kinds of signals

• energy signals are of finite length and energy, such as impulse responses.

• power signals are finite samples of signals with infinite length and and energy, such as noise signals or sound textures.

The difference is important for

• plotting the frequency response of signals because different signal types require different FFT normalizations.

• performing arithmetic operatoins because not all signals types can be combined with each other.