export function classifyCircleData()

in src/dataset.ts [156:188]

• 27 lines of code
• 3 McCabe index (conditional complexity)

export function classifyCircleData(numSamples: number, noise: number):
    Example2D[] {
  let points: Example2D[] = [];
  let radius = 5;
  function getCircleLabel(p: Point, center: Point) {
    return (dist(p, center) < (radius * 0.5)) ? 1 : -1;
  }

  // Generate positive points inside the circle.
  for (let i = 0; i < numSamples / 2; i++) {
    let r = randUniform(0, radius * 0.5);
    let angle = randUniform(0, 2 * Math.PI);
    let x = r * Math.sin(angle);
    let y = r * Math.cos(angle);
    let noiseX = randUniform(-radius, radius) * noise;
    let noiseY = randUniform(-radius, radius) * noise;
    let label = getCircleLabel({x: x + noiseX, y: y + noiseY}, {x: 0, y: 0});
    points.push({x, y, label});
  }

  // Generate negative points outside the circle.
  for (let i = 0; i < numSamples / 2; i++) {
    let r = randUniform(radius * 0.7, radius);
    let angle = randUniform(0, 2 * Math.PI);
    let x = r * Math.sin(angle);
    let y = r * Math.cos(angle);
    let noiseX = randUniform(-radius, radius) * noise;
    let noiseY = randUniform(-radius, radius) * noise;
    let label = getCircleLabel({x: x + noiseX, y: y + noiseY}, {x: 0, y: 0});
    points.push({x, y, label});
  }
  return points;
}