First you need to ensure that the result you are getting is correctly converted to a float/double. I’m not sure how the short[] version works, but the byte[] version only returns the raw byte version. This byte array then needs to be properly converted to a floating point number. The code for the conversion should … Read more
The aubio libraries have been wrapped with SWIG and can thus be used by Python. Among their many features include several methods for pitch detection/estimation including the YIN algorithm and some harmonic comb algorithms. However, if you want something simpler, I wrote some code for pitch estimation some time ago and you can take it … Read more
Your best bet is KissFFT – as its name implies it’s simple, but it’s still quite respectably fast, and a lot more lightweight than FFTW. It’s also free, wheras FFTW requires a hefty licence fee if you want to include it in a commercial product.
Assuming that I is your input image and F is its Fourier Transform (i.e. F = fft2(I)) You can use this code: F = fftshift(F); % Center FFT F = abs(F); % Get the magnitude F = log(F+1); % Use log, for perceptual scaling, and +1 since log(0) is undefined F = mat2gray(F); % Use … Read more
Python provides several api to do this fairly quickly. I download the sheep-bleats wav file from this link. You can save it on the desktop and cd there within terminal. These lines in the python prompt should be enough: (omit >>>) import matplotlib.pyplot as plt from scipy.fftpack import fft from scipy.io import wavfile # get … Read more
You should neither look for the real or imaginative part of a complex number (that what’s your real and imaginary array is). Instead you want to look for the magnitude of the frequency which is defined as sqrt (real * real + imag * imag). This number will always be positive. Now all you have … Read more
1) Why does the x-axis (frequency) end at 500? How do I know that there aren’t more frequencies or are they just ignored? It ends at 500Hz because that is the Nyquist frequency of the signal when sampled at 1000Hz. Look at this line in the Mathworks example: f = Fs/2*linspace(0,1,NFFT/2+1); The frequency axis of … Read more
Here is my Python code, simplified for this answer: import scipy, pylab def stft(x, fs, framesz, hop): framesamp = int(framesz*fs) hopsamp = int(hop*fs) w = scipy.hanning(framesamp) X = scipy.array([scipy.fft(w*x[i:i+framesamp]) for i in range(0, len(x)-framesamp, hopsamp)]) return X def istft(X, fs, T, hop): x = scipy.zeros(T*fs) framesamp = X.shape[1] hopsamp = int(hop*fs) for n,i in enumerate(range(0, … Read more
np.fft.fftfreq tells you the frequencies associated with the coefficients: import numpy as np x = np.array([1,2,1,0,1,2,1,0]) w = np.fft.fft(x) freqs = np.fft.fftfreq(len(x)) for coef,freq in zip(w,freqs): if coef: print(‘{c:>6} * exp(2 pi i t * {f})’.format(c=coef,f=freq)) # (8+0j) * exp(2 pi i t * 0.0) # -4j * exp(2 pi i t * 0.25) # … Read more
FFTW is the ‘fastest fourier transform in the west’, and has some Java wrappers: http://www.fftw.org/download.html Hope that helps!