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    <p>The complex data is interleaved, with real components at even indices and imaginary components at odd indices, i.e. the real components are at index <code>2*i</code>, the imaginary components are at index <code>2*i+1</code>.</p> <p>To get the magnitude of the spectrum at index i, you want:</p> <pre><code>re = fft[2*i]; im = fft[2*i+1]; magnitude[i] = sqrt(re*re+im*im); </code></pre> <p>Then you can plot magnitude[i] for i = 0 to N / 2 to get the power spectrum. Depending on the nature of your audio input you should see one or more peaks in the spectrum.</p> <p>To get the approximate frequency of any given peak you can convert the index of the peak as follows:</p> <pre><code>freq = i * Fs / N; </code></pre> <p>where:</p> <pre><code>freq = frequency in Hz i = index of peak Fs = sample rate (e.g. 44100 Hz or whatever you are using) N = size of FFT (e.g. 1024 in your case) </code></pre> <p>Note: if you have not previously applied a suitable <a href="http://en.wikipedia.org/wiki/Window_function" rel="noreferrer">window function</a> to the time-domain input data then you will get a certain amount of <a href="http://en.wikipedia.org/wiki/Spectral_leakage" rel="noreferrer">spectral leakage</a> and the power spectrum will look rather "smeared".</p> <hr> <p>To expand on this further, here is pseudo-code for a complete example where we take audio data and identify the frequency of the largest peak:</p> <pre><code>N = 1024 // size of FFT and sample window Fs = 44100 // sample rate = 44.1 kHz data[N] // input PCM data buffer fft[N * 2] // FFT complex buffer (interleaved real/imag) magnitude[N / 2] // power spectrum capture audio in data[] buffer apply window function to data[] // copy real input data to complex FFT buffer for i = 0 to N - 1 fft[2*i] = data[i] fft[2*i+1] = 0 perform in-place complex-to-complex FFT on fft[] buffer // calculate power spectrum (magnitude) values from fft[] for i = 0 to N / 2 - 1 re = fft[2*i] im = fft[2*i+1] magnitude[i] = sqrt(re*re+im*im) // find largest peak in power spectrum max_magnitude = -INF max_index = -1 for i = 0 to N / 2 - 1 if magnitude[i] &gt; max_magnitude max_magnitude = magnitude[i] max_index = i // convert index of largest peak to frequency freq = max_index * Fs / N </code></pre>
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    1. POHow to get frequency from fft result?
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    1. USPaul R
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    1. POHow to get frequency from fft result?
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    1. COThanks so much Paul, I see where that was in previous answers now, I got to run some tests now! thanks
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    2. COby index of peak, do you mean the index of the output array, where the peak in the graph lies?
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    3. COFor the code above the index will be the index of the `magnitude` array.
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