Mercurial > hg > js-dsp-test
view fft/test.html @ 1:1c027151f7ec
Beginnings of a test script
author | Chris Cannam |
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date | Thu, 01 Oct 2015 16:56:01 +0100 |
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children | 44f670784d5f |
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<html> <body> <p>If 2150 iterations of real-to-complex FFT of size 2048 takes less than 10 seconds, then we may be able to make a high quality real-time phase vocoder (just).</p> <p>A phase-vocoder of course must use overlapped windowed FFT (although you can choose the size, within limits), IFFT, and cartesian-polar conversion to calculate the phase for the instantaneous frequency.</p> <p>A reasonable estimate of CPU cost for the whole thing is somewhere around 10x the cost of simple non-overlapping short-time forward Fourier transforms across the signal. </p> <p>2150 iterations corresponds to 100 seconds of audio non-overlapped at 44.1kHz, so if that takes less than 10 second, then in theory we might be OK.</p> <pre> <script src="nayuki/fft.js"></script> <script> /* for a phase vocoder, we probably want 2048-point real-to-complex * FFTs (if available) */ function inputReals(size) { var result = new Array(size); for (var i = 0; i < result.length; i++) result[i] = (i % 20) / 10.0 - 1.0; return result; } function zeroReals(size) { var result = new Array(size); for (var i = 0; i < result.length; i++) result[i] = 0.0; return result; } function inputReal64s(size) { var result = new Float64Array(size); for (var i = 0; i < result.length; i++) result[i] = (i % 20) / 10.0 - 1.0; return result; } var iterations = 2150; var size = 2048; var start = performance.now(); var total = 0.0; for (var i = 0; i < iterations; ++i) { var real = inputReals(size); var imag = zeroReals(size); transform(real, imag); for (var j = 0; j < size; ++j) { total += real[j] + imag[j]; } } document.write("total = " + total + "<br>"); var end = performance.now(); document.write("nayuki fft.js: " + iterations + " iterations at size " + size + " took " + (end - start) + "ms (" + (1000.0 / ((end - start) / iterations)) + " iterations/sec)<br>"); </script> <script src="fft.js/lib/complex.js"></script> <script> var fft = new FFT.complex(size, false); start = performance.now(); total = 0.0; for (var i = 0; i < iterations; ++i) { var ri = inputReal64s(size); var co = new Float64Array(2 * size); fft.simple(co, ri, 'real'); for (var j = 0; j < 2 * size; ++j) { total += co[j]; } } document.write("total = " + total + "<br>"); var end = performance.now(); document.write("nockert fft.js: " + iterations + " iterations at size " + size + " took " + (end - start) + "ms (" + (1000.0 / ((end - start) / iterations)) + " iterations/sec)<br>"); </script> </pre> </body>