void openDatabase(){
  pixelData.clear();

  for (int i = 0; i < total-1; i++){
    lines = loadStrings("database/"+(i)+".txt");
    lineCount = i;
   // println("there are " + lines.length + " lines");
    // println(i);


    float[] vectorArray = new float[lines.length];
    for (int j=0; j < lines.length; j++) {

      String[] splitLines = splitTokens(lines[j]);

      String f = splitLines[1];

      float k = Float.valueOf(f).floatValue();

      lineString[j] = k;

      binaryPixels[j] = k;
      vectorArray[j] = k; 
      //pixelData.add(binaryPixels[i]);
      //println(binaryPixels[i]);
     // println(vectorArray[j]);
    }

    pixelData.add(vectorArray);

  }
}
void welcome() {
  textFont(f);
  textAlign(CENTER);
  fill(0);
  text("This is a gesture recognation demo. \n" + 
    "You can record gestures or. \n" + 
    "you can make a gesture and see its name.",width/2,height/2);
  recordButton.render();
  recordButton.rollover(mouseX,mouseY);
  guessButton.render();
  guessButton.rollover(mouseX,mouseY);
}

// Train the network
void train() {
  openDatabase();

  // Adjust this number to make training appear to be faster / slower
  int cyclesPerFrame = 50;

  for (int i = 0; i < cyclesPerFrame; i++) {
    // Pick a number 
    int num = (int) random(total);
    // Look at the pixels for that number


    ////////////////////////////////////////////////////////////////////////////////////////////////
    //// this needs to change with "look in to vector document"
    //println(lineCount);
    float[] pixies = binaryPixels;  
    // Train the network according to those pixels
    nn.train(pixies, (float)num/total);
    // Increase the training iteration count
    trainingCount++;
    //println(trainingCount);
  }

}



// Display info about the training
void showTraining() {
  pushMatrix();
  translate(20,150);
  textFont(f);
  textAlign(LEFT);

  // How much training is complete
  float percentage = (float) trainingCount / maxTrainingIterations;
  // Draw status bar
  float statusBar = percentage*width/2;
  stroke(0);
  noFill();
  rect(5,5,width/2,10);
  fill(0);
  rect(5,5,statusBar,10);
  text("Training. . .",5,30);

  // Now we'll show what the network is currently guessing for each input image
  fill(0);
  float mse = 0;

  for (int i = 0; i < pixelData.size(); i++) {
    // println((Float) pixelData.get(14));


    float[] inp = (float[]) pixelData.get(i); 
    float known = (float) i/total;
    float result = nn.feedForward(inp);                                          

    text("My guess for image # " + i + " is " + nf((float)result * total,1,2),5,100+i*20);
    mse += (result - known)*(result - known);
  }
  // How many interations
  text("Total iterations: " + trainingCount,5,60);
  // Root mean squarted error
 // println(pixelData.size());
  float rmse = sqrt(mse/pixelData.size());
  text("Root mean squared error: " + nf(rmse,1,4), 5,80);
  // If we've finished training
  if (percentage >= 1.0) {
    trainingComplete = true;
    text("I'm done training!  Press the space bar\nto draw a shape for me to guess.",5,-50);
  }
  popMatrix();
}




// What to do with the user's input image
void guess() {
  // If it's not time to guess yet just give the user some instructions
  // and show submit button

  if (!guessing) {

    textFont(f);
    fill(50);
    textAlign(CENTER);
    text("Draw something and submit!",width/2,20);

    //   submit.rollover(mouseX,mouseY);
    // submit.render();
    // Otherwise, show the result of the guess!
  } 
  else {

    //noStroke();
    //fill(255);
    // rect(0,400,width,height);
    //fill(0);
    //textAlign(CENTER);
    //textSize(14);
  //  println((int)(round(guess)));
     text("My output is " + nf(guess,1,2) + " so I guess " + (int)(round(guess)) + 
     "\n Please type the correct # to help train me.",460,420);
    //println(  (int)(round(guess)));
  }
}

// Get an array of floats 0 to 1 from an input image

////////////////////////////////////////////////////////////////////////////////////////////////
//////// this should be change for vector file




///////// guessing is accordin to file number. but it is working now, 
// next: make training work, interface, get more then one input, get input name, match the guessing number(file name) with the input