smallmath.js

// least squares from https://medium.com/@sahirnambiar/linear-least-squares-a-javascript-implementation-and-a-definitional-question-e3fba55a6d4b
// mod to return object of m, b, values.x, values.y,
var smallmath = {
  lsq: function(values_x, values_y) {
    var x_sum = 0;
    var y_sum = 0;
    var xy_sum = 0;
    var xx_sum = 0;
    var count = 0;

    /*
     * The above is just for quick access, makes the program faster
     */
    var x = 0;
    var y = 0;
    var values_length = values_x.length;

    if (values_length != values_y.length) {
      throw new Error('The parameters values_x and values_y need to have same size!');
    }

    /*
     * Above and below cover edge cases
     */
    if (values_length === 0) {
      return [
        [],
        []
      ];
    }

    /*
     * Calculate the sum for each of the parts necessary.
     */
    for (let i = 0; i < values_length; i++) {
      x = values_x[i];
      y = values_y[i];
      x_sum += x;
      y_sum += y;
      xx_sum += x * x;
      xy_sum += x * y;
      count++;
    }

    /*
     * Calculate m and b for the line equation:
     * y = x * m + b
     */
    var m = (count * xy_sum - x_sum * y_sum) / (count * xx_sum - x_sum * x_sum);
    var b = (y_sum / count) - (m * x_sum) / count;

    /*
     * We then return the x and y data points according to our fit
     */
    var result_values_x = [];
    var result_values_y = [];

    for (let i = 0; i < values_length; i++) {
      x = values_x[i];
      y = x * m + b;
      result_values_x.push(x);
      result_values_y.push(y);
    }

    return {
      m: m,
      b: b,
      values: {
        x: result_values_x,
        y: result_values_y
      }
    }
  }
}

export default smallmath