Sample: working with audio data¶
Sample: a class representing audio data (wraps a numpy float array).
A Sample contains the audio (read from a soundfile or synthesized) as a numpy float array.
It aware of its sr, original format and encoding, etc. It can also perform many operations
on the sample data (fade-in/out, cut, insert, reverse, normalize, etc) and implements most
math operations valid for audio data (+, -, *, /).
Note
Some operations are performed in place while others return a copy. In general, whenever the number of samples or the number of channels is modified (e.g. `mixdown` or `stripLeft`), a copy is returned. Otherwise the operation is performed in-place
Copy: all others (
appendSilence,prependSilence,mixdown,stripLeft, …)
Demo Notebooks¶
A Sample implements multiple feature extraction algorithms, like
onset detection, fundamental tracking, etc.
maelzel.snd.audiosample Module¶
audiosample¶
This module is based on the Sample class,
which contains the audio of a soundfile as a numpy array and it aware of its sr,
original format and encoding, etc. It can also perform simple actions
(fade-in/out, cut, insert, reverse, normalize, etc) on its own audio
destructively or return a new Sample. It implements most math operations
valid for audio data (+, -, *, /)
Note
All operations are samplerate-aware: any operation involving
multiple Sample instances will broadcast these to the highest samplerate used
Examples
# load a Sample, fade it, play and write
from maelzel.snd.audiosample import *
s = Sample("snd/Numbers_EnglishFemale.flac")
s.fade(0.5)
s.play(speed=0.5, block=True)
# Plot a 6 second fragment startine at time=1
s[1:7].plotSpectrogram(fftsize=4096, overlap=8, mindb=-100, maxfreq=8000)
samples = [Sample("soundA.wav"),
Sample("soundB.aif"),
Sample("soundC.flac")]
a, b, c = broadcastSamplerate(samples)
# mix them down
out = a.prependSilence(2) + b + c
out.write("mixed.wav")
Classes¶
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A class representing audio data |