package oldfiles;/*
Previously implemented programs which we need to redo using classes
  case 2 :           // Starts clear program
    clearScreen();
break;
  case 3 :           // Uses reduced screen raster
//      rectangularStim(64, 5);
//      proto488flashraster(screenWidth - 1500, 400, screenWidth - 6*menu.width, screenHeight - 400);
//      heatup();
//      squareCorridor();
//      LEDtest();
//      colorScreen();
//      clearScreen();
//      circleArrayStim(screenWidth - 1500, 800, 5, 5, 20, 5);
//      angleMove(screenWidth - (displayWidth-750*cos(45*PI/360)-x-menu.width), centerY, 45, 750, 0.01);
//      window(20, 20);
//      separate(0.1);
//      merge(0.1);
//      shrinkingWindow(0.01, 0, 0, 255, 10);
//      translateCircle(0.1);
//      gradientWindow(0,0,0,0,0,15,500);
//      randomLED();
//      lineRotate(50, 0.01);
    break;
  case 4 :           // Create LED sequences or paint backgrounds to be loaded later
    angleGather(screenWidth - 1400, centerY, 45, 750);
//      protoGather(screenWidth - 800, 300, screenWidth - 8*menu.width, screenHeight - 500);
    break;
*/

class ClearScreen {

    int timeElapsed, timeCurrent, timeInitial, euglenaCountInitial, euglenaCount,
            roiCornerX, roiCornerY, roiWidth, roiHeight;
    float euglenaReduction, targetReduction;

//    opencv = new OpenCV(this, roiWidth, roiHeight);
//    opencv.startBackgroundSubtraction(7, 3, .35);
//    roiFrame = new PImage(roiWidth, roiHeight);
//    break;
//
//    /* Identify Euglena in a certain portion of the camera feed */
//    void countEuglena() {
//        roiFrame = get(roiCornerX, roiCornerY, roiWidth, roiHeight); // Get pixels of interest and saves as image for valid image path
//        opencv.loadImage(roiFrame);   // Input proper pixels into cv processing
//        opencv.updateBackground();    //Necessary for background subtraction
//        opencv.useGray();             //Create grayscale image
//        opencv.dilate();              //Clean up image
//        opencv.erode();
//        opencv.blur(3);
//        dst = opencv.getOutput();     //Save computer vision as separate image path
//        contours = opencv.findContours();  //Find outline of moving objects - euglena
//        euglenaCount = contours.size();           // Count number of outlines
//    }
//
//    void reset() {
//        timeInitial = millis();
//        timeElapsed = 0;
//        identifyEuglena();
//        euglenaCountInitial = euglenaCount;
//    }
//
//    ClearScreen(targetReduction){
//        this.reset();
//    }
//
//    void mouseClicked(float x, float y){
//        if (!point1complete){
//            lineinprogress.x1 = x;
//            lineinprogress.y1 = y;
//            point1complete = true;
//        } else {
//            lineinprogress.x2 = x;
//            lineinprogress.y2 = y;
//            lineinprogress.visible = true;
//            lines.add(lineinprogress);
//
//            lineinprogress.draw();
//            this.reset();
//        }
//    }
//}