Audio ClassesΒΆ
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
andFrequencyData
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.