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Minim |
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specSize |
Description Returns the size of the spectrum created by this transform. In other words, the number of frequency bands produced by this transform. This is typically equal totimeSize()/2 + 1, see above for an explanation.
Signature int specSize() Returns int: the size of the spectrum Related FFTExample /**
* This sketch demonstrates how to use an FFT to analyze
* the audio being generated by an AudioPlayer.
* <p>
* FFT stands for Fast Fourier Transform, which is a
* method of analyzing audio that allows you to visualize
* the frequency content of a signal. You've seen
* visualizations like this before in music players
* and car stereos.
* <p>
* For more information about Minim and additional features,
* visit http://code.compartmental.net/minim/
*/
import ddf.minim.analysis.*;
import ddf.minim.*;
Minim minim;
AudioPlayer jingle;
FFT fft;
void setup()
{
size(512, 200, P3D);
minim = new Minim(this);
// specify that we want the audio buffers of the AudioPlayer
// to be 1024 samples long because our FFT needs to have
// a power-of-two buffer size and this is a good size.
jingle = minim.loadFile("jingle.mp3", 1024);
// loop the file indefinitely
jingle.loop();
// create an FFT object that has a time-domain buffer
// the same size as jingle's sample buffer
// note that this needs to be a power of two
// and that it means the size of the spectrum will be half as large.
fft = new FFT( jingle.bufferSize(), jingle.sampleRate() );
}
void draw()
{
background(0);
stroke(255);
// perform a forward FFT on the samples in jingle's mix buffer,
// which contains the mix of both the left and right channels of the file
fft.forward( jingle.mix );
for(int i = 0; i < fft.specSize(); i++)
{
// draw the line for frequency band i, scaling it up a bit so we can see it
line( i, height, i, height - fft.getBand(i)*8 );
}
}
Usage Web & Application |