jsPsych/docs/demos/js/webgazer/ridgeWorker.mjs

"use strict";

console.log("thread starting");

// Add src/util.mjs and src/mat.mjs to the same directory as your html file
importScripts("./worker_scripts/util.js", "./worker_scripts/mat.js"); // [20200708] Figure out how to make all of this wrap up neatly
var ridgeParameter = Math.pow(10, -5);
var resizeWidth = 10;
var resizeHeight = 6;
var dataWindow = 700;
var trailDataWindow = 10;
var trainInterval = 500;

var screenXClicksArray = new self.webgazer.util.DataWindow(dataWindow);
var screenYClicksArray = new self.webgazer.util.DataWindow(dataWindow);
var eyeFeaturesClicks = new self.webgazer.util.DataWindow(dataWindow);
var dataClicks = new self.webgazer.util.DataWindow(dataWindow);

var screenXTrailArray = new self.webgazer.util.DataWindow(trailDataWindow);
var screenYTrailArray = new self.webgazer.util.DataWindow(trailDataWindow);
var eyeFeaturesTrail = new self.webgazer.util.DataWindow(trailDataWindow);
var dataTrail = new self.webgazer.util.DataWindow(trailDataWindow);

/**
 * Performs ridge regression, according to the Weka code.
 * @param {Array} y - corresponds to screen coordinates (either x or y) for each of n click events
 * @param {Array.<Array.<Number>>} X - corresponds to gray pixel features (120 pixels for both eyes) for each of n clicks
 * @param {Array} k - ridge parameter
 * @return{Array} regression coefficients
 */
function ridge(y, X, k) {
  var nc = X[0].length;
  var m_Coefficients = new Array(nc);
  var xt = self.webgazer.mat.transpose(X);
  var solution = new Array();
  var success = true;
  do {
    var ss = self.webgazer.mat.mult(xt, X);
    // Set ridge regression adjustment
    for (var i = 0; i < nc; i++) {
      ss[i][i] = ss[i][i] + k;
    }

    // Carry out the regression
    var bb = self.webgazer.mat.mult(xt, y);
    for (var i = 0; i < nc; i++) {
      m_Coefficients[i] = bb[i][0];
    }
    try {
      var n = m_Coefficients.length !== 0 ? m_Coefficients.length / m_Coefficients.length : 0;
      if (m_Coefficients.length * n !== m_Coefficients.length) {
        console.log("Array length must be a multiple of m");
      }
      solution =
        ss.length === ss[0].length
          ? self.webgazer.mat.LUDecomposition(ss, bb)
          : self.webgazer.mat.QRDecomposition(ss, bb);

      for (var i = 0; i < nc; i++) {
        m_Coefficients[i] = solution[i][0];
      }
      success = true;
    } catch (ex) {
      k *= 10;
      console.log(ex);
      success = false;
    }
  } while (!success);
  return m_Coefficients;
}

//TODO: still usefull ???
/**
 *
 * @returns {Number}
 */
function getCurrentFixationIndex() {
  var index = 0;
  var recentX = this.screenXTrailArray.get(0);
  var recentY = this.screenYTrailArray.get(0);
  for (var i = this.screenXTrailArray.length - 1; i >= 0; i--) {
    var currX = this.screenXTrailArray.get(i);
    var currY = this.screenYTrailArray.get(i);
    var euclideanDistance = Math.sqrt(Math.pow(currX - recentX, 2) + Math.pow(currY - recentY, 2));
    if (euclideanDistance > 72) {
      return i + 1;
    }
  }
  return i;
}

/**
 * Event handler, it store screen position to allow training
 * @param {Event} event - the receive event
 */
self.onmessage = function (event) {
  var data = event.data;
  var screenPos = data["screenPos"];
  var eyes = data["eyes"];
  var type = data["type"];
  if (type === "click") {
    self.screenXClicksArray.push([screenPos[0]]);
    self.screenYClicksArray.push([screenPos[1]]);

    self.eyeFeaturesClicks.push(eyes);
  } else if (type === "move") {
    self.screenXTrailArray.push([screenPos[0]]);
    self.screenYTrailArray.push([screenPos[1]]);

    self.eyeFeaturesTrail.push(eyes);
    self.dataTrail.push({ eyes: eyes, screenPos: screenPos, type: type });
  }
  self.needsTraining = true;
};

/**
 * Compute coefficient from training data
 */
function retrain() {
  if (self.screenXClicksArray.length === 0) {
    return;
  }
  if (!self.needsTraining) {
    return;
  }
  var screenXArray = self.screenXClicksArray.data.concat(self.screenXTrailArray.data);
  var screenYArray = self.screenYClicksArray.data.concat(self.screenYTrailArray.data);
  var eyeFeatures = self.eyeFeaturesClicks.data.concat(self.eyeFeaturesTrail.data);

  var coefficientsX = ridge(screenXArray, eyeFeatures, ridgeParameter);
  var coefficientsY = ridge(screenYArray, eyeFeatures, ridgeParameter);
  self.postMessage({ X: coefficientsX, Y: coefficientsY });
  self.needsTraining = false;
}

setInterval(retrain, trainInterval);