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| Ligne 26 : | Ligne 26 : | ||
<syntaxhighlight lang="java">  | <syntaxhighlight lang="java">  | ||
| − | + | ||
  * This sketch shows how to use the FFT class to analyze a stream  |   * This sketch shows how to use the FFT class to analyze a stream  | ||
  * of sound. Change the number of bands to get more spectral bands  |   * of sound. Change the number of bands to get more spectral bands  | ||
| Ligne 76 : | Ligne 76 : | ||
public void draw() {  | public void draw() {  | ||
| − | + | ||
| − | |||
| − | |||
| − | |||
   // Perform the analysis  |    // Perform the analysis  | ||
   fft.analyze();  |    fft.analyze();  | ||
| − | + |   int currentBand = 0;  | |
| + |   float maxVal = 0;  | ||
| + | |||
   for (int i = 0; i < bands; i++) {  |    for (int i = 0; i < bands; i++) {  | ||
| − | + | ||
| − | + |      if(fft.spectrum[i] > maxVal){  | |
| − | + |       currentBand = i;  | |
| − | + |       maxVal = fft.spectrum[i];  | |
| − | + |     }  | |
| + | |||
| + | |||
| + |   }  | ||
| + | |||
| + |   if(currentBand > 10){  | ||
| + |      background(0);  | ||
| + |   }else{  | ||
| + |      background(255);  | ||
   }  |    }  | ||
| + | |||
| + | |||
}  | }  | ||
</syntaxhighlight>  | </syntaxhighlight>  | ||
Version du 22 octobre 2018 à 09:28
projet : Assigner un programme différent à chaque octave de la voix. Donc avec un système de détection des notes et des hauteurs. Chacune des notes seraient assignée à un effet de type stéréo, réverbe, granulator...
Utilisation de processing.
- Réaliser du code qui récupère les données enregistrées par un Micro externe, analyser ces données.
Exo 1 : traduire par une couleur des paliers sur la hauteur du son enregistré.
Code utilisé : Modifications réalisées sur le code : -FFT à partir d'un enregistrement micro input -Retour Micro
ATTENTION UTILISER CASQUE AUDIO SINON LARSEN
 * This sketch shows how to use the FFT class to analyze a stream
 * of sound. Change the number of bands to get more spectral bands
 * (at the expense of more coarse-grained time resolution of the spectrum).
 */
import processing.sound.*;
// Declare the sound source and FFT analyzer variables
FFT fft;
AudioIn in;
// Define how many FFT bands to use (this needs to be a power of two)
int bands = 128;
// Define a smoothing factor which determines how much the spectrums of consecutive
// points in time should be combined to create a smoother visualisation of the spectrum.
// A smoothing factor of 1.0 means no smoothing (only the data from the newest analysis
// is rendered), decrease the factor down towards 0.0 to have the visualisation update
// more slowly, which is easier on the eye.
float smoothingFactor = 0.2;
// Create a vector to store the smoothed spectrum data in
float[] sum = new float[bands];
// Variables for drawing the spectrum:
// Declare a scaling factor for adjusting the height of the rectangles
int scale = 5;
// Declare a drawing variable for calculating the width of the 
float barWidth;
public void setup() {
  size(640, 360);
  background(255);
  // Calculate the width of the rects depending on how many bands we have
  barWidth = width/float(bands);
  // Load and play a soundfile and loop it.
  fft = new FFT(this, bands);
  in = new AudioIn(this, 0);
  
  // Create the FFT analyzer and connect the playing soundfile to it.
  in.start();
  fft.input(in);
  //retour micro
  in.play();
}
public void draw() {
 
  // Perform the analysis
  fft.analyze();
  int currentBand = 0;
  float maxVal = 0;
  
  for (int i = 0; i < bands; i++) {
    
    if(fft.spectrum[i] > maxVal){
      currentBand = i;
      maxVal = fft.spectrum[i];
    }
   
    
  }
  
  if(currentBand > 10){
    background(0);
  }else{
    background(255);
  }
  
  
}

