ThinkDSP

This notebook contains an example related to Chapter 5: Autocorrelation

Copyright 2015 Allen Downey

License: Creative Commons Attribution 4.0 International

In [1]:
from __future__ import print_function, division

import thinkdsp
import thinkplot
import thinkstats2

import numpy as np

import warnings
warnings.filterwarnings('ignore')

from IPython.html.widgets import interact, fixed
from IPython.html import widgets

PI2 = np.pi * 2

%matplotlib inline

The case of the missing fundamental

This notebook investigates autocorrelation, pitch perception and a phenomenon called the "missing fundamental".

I'll start with a recording of a saxophone.

In [2]:
wave = thinkdsp.read_wave('100475__iluppai__saxophone-weep.wav')
wave.normalize()
wave.make_audio()
Out[2]: