Function renderModelPredictions

polynomial-regression/index.js:192–223

(
    canvas, order, model, xPowerMeans, xPowerStddevs, yMean, yStddev)

// Render the predictions made by the model.
function renderModelPredictions(
    canvas, order, model, xPowerMeans, xPowerStddevs, yMean, yStddev) {
  const ctx = canvas.getContext('2d');
  const width = canvas.width;
  let x = -0.5 * width;
  const xStep = 0.02 * width;
  const xs = [];
  const xPowers = [];
  let n = 0;
  while (x < 0.5 * width) {
    xs.push(x);
    let d = 1;
    for (let j = 0; j < order + 1; ++j) {
      xPowers.push(
          j === 0 ? d : ((d - xPowerMeans[j - 1]) / xPowerStddevs[j - 1]));
      d *= x;
    }
    x += xStep;
    n++;
  }

  const predictOut = model.predict(tf.tensor2d(xPowers, [n, order + 1]));
  const normalizedYs = predictOut.dataSync();
  ctx.beginPath();
  let canvasXY = world2canvas(canvas, xs[0], normalizedYs[0] * yStddev + yMean);
  ctx.moveTo(canvasXY[0], canvasXY[1]);
  for (let i = 1; i < n; ++i) {
    canvasXY = world2canvas(canvas, xs[i], normalizedYs[i] * yStddev + yMean);
    ctx.lineTo(canvasXY[0], canvasXY[1]);
    ctx.stroke();
  }
}

// Generate x-y data based on the size of the canvas.
function generateXYData(canvas, coeffs) {