How to calculate a Fourier series in Numpy?

In the end, the most simple thing (calculating the coefficient with a riemann sum) was the most portable/efficient/robust way to solve my problem: import numpy as np def cn(n): c = y*np.exp(-1j*2*n*np.pi*time/period) return c.sum()/c.size def f(x, Nh): f = np.array([2*cn(i)*np.exp(1j*2*i*np.pi*x/period) for i in range(1,Nh+1)]) return f.sum() y2 = np.array([f(t,50).real for t in time]) plot(time, y) … Read more

Improving FFT performance in Python

You could certainly wrap whatever FFT implementation that you wanted to test using Cython or other like-minded tools that allow you to access external libraries. GPU-based If you’re going to test FFT implementations, you might also take a look at GPU-based codes (if you have access to the proper hardware). There are several: reikna.fft, scikits.cuda. … Read more

What does the FFT data in the Web Audio API correspond to?

yes,getByteFrequencyData results in a normalized array of values between 0 and 255. (it copies the data to the array it gets passed-in). the frequency bands are split equally, so each element N of your array corresponds to: N * samplerate/fftSize so, the first bin is 0. and, assuming a samplerate of 44100 and a <analyzerNode>.fftSize … Read more

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