Think DSP by Allen B. Downey
Author:Allen B. Downey
Language: eng
Format: epub
Publisher: O'Reilly Media
Published: 2016-07-26T16:00:00+00:00
# class Dct def make_wave(self): n = len(self.hs) ys = scipy.fftpack.idct(self.hs, type=2) / 2 / n return Wave(ys, framerate=self.framerate)
By default, the inverse DCT doesn’t normalize the result, so we have to divide through by 2N.
Exercises
For the following exercises, I provide some starter code in chap06starter.ipynb. Solutions are in chap06soln.ipynb.
Exercise 6-1.
In this chapter I claim that analyze1 takes time proportional to n3 and analyze2 takes time proportional to n2. To see if that’s true, run them on a range of input sizes and time them. In Jupyter, you can use the “magic command” %timeit.
If you plot run time versus input size on a log-log scale, you should get a straight line with slope 3 for analyze1 and slope 2 for analyze2.
You also might want to test dct_iv and scipy.fftpack.dct.
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