nsolvejs/lib/deltax.js

Solve equations using numerical methods

const sortInterval = require('./sortInterval');

module.exports = function (npoints, interval, pointsDistribution) {
  let a; let b; let N; let n; const x_n_array = [];
  let alpha; let
    beta;
    // The default distribution is the linear.
  pointsDistribution = pointsDistribution || 'linear';
  sortInterval(interval);
  N = npoints;
  a = interval[0];
  b = interval[1];
  const Distribution = {
    linear() {
      alpha = (b - a) / (N - 1);
      beta = a - alpha;
      for (n = 1; n <= N; n++) x_n_array[n] = alpha * n + beta;
    },
    exponential() {
      beta = Math.log(b / a) / (N - 1);
      alpha = Math.exp(Math.log(a) - beta);
      for (n = 1; n <= N; n++) x_n_array[n] = alpha * Math.exp(beta * n);
    },
    logarithmic() {
      beta = (b - a) / Math.log(N);
      alpha = a;
      for (n = 1; n <= N; n++) x_n_array[n] = alpha + beta * Math.log(n);
    },
    law() {
      beta = Math.log(b / a) / Math.log(N);
      alpha = a;
      for (n = 1; n <= N; n++) x_n_array[n] = alpha * Math.pow(n, beta);
    },
    cuadratic() {
      alpha = (b - a + 1 - N * N) / (N - 1);
      beta = a - 1 - alpha;
      for (n = 1; n <= N; n++) x_n_array[n] = n * n + alpha * n + beta;
    },
    inverse() {
      alpha = (1 / b - 1 / a) / (N - 1);
      beta = a - alpha;
      for (n = 1; n <= N; n++) x_n_array[n] = alpha * n + beta;
    },
  };
  Distribution[pointsDistribution]();
  return {
    x_n_array,
    pointsdistribution: pointsDistribution,
  };
};