LagrangePolynomialApproximation.js 2.4 KB

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  1. import defined from './defined.js';
  2. /**
  3. * An {@link InterpolationAlgorithm} for performing Lagrange interpolation.
  4. *
  5. * @exports LagrangePolynomialApproximation
  6. */
  7. var LagrangePolynomialApproximation = {
  8. type : 'Lagrange'
  9. };
  10. /**
  11. * Given the desired degree, returns the number of data points required for interpolation.
  12. *
  13. * @param {Number} degree The desired degree of interpolation.
  14. * @returns {Number} The number of required data points needed for the desired degree of interpolation.
  15. */
  16. LagrangePolynomialApproximation.getRequiredDataPoints = function(degree) {
  17. return Math.max(degree + 1.0, 2);
  18. };
  19. /**
  20. * Interpolates values using Lagrange Polynomial Approximation.
  21. *
  22. * @param {Number} x The independent variable for which the dependent variables will be interpolated.
  23. * @param {Number[]} xTable The array of independent variables to use to interpolate. The values
  24. * in this array must be in increasing order and the same value must not occur twice in the array.
  25. * @param {Number[]} yTable The array of dependent variables to use to interpolate. For a set of three
  26. * dependent values (p,q,w) at time 1 and time 2 this should be as follows: {p1, q1, w1, p2, q2, w2}.
  27. * @param {Number} yStride The number of dependent variable values in yTable corresponding to
  28. * each independent variable value in xTable.
  29. * @param {Number[]} [result] An existing array into which to store the result.
  30. * @returns {Number[]} The array of interpolated values, or the result parameter if one was provided.
  31. */
  32. LagrangePolynomialApproximation.interpolateOrderZero = function(x, xTable, yTable, yStride, result) {
  33. if (!defined(result)) {
  34. result = new Array(yStride);
  35. }
  36. var i;
  37. var j;
  38. var length = xTable.length;
  39. for (i = 0; i < yStride; i++) {
  40. result[i] = 0;
  41. }
  42. for (i = 0; i < length; i++) {
  43. var coefficient = 1;
  44. for (j = 0; j < length; j++) {
  45. if (j !== i) {
  46. var diffX = xTable[i] - xTable[j];
  47. coefficient *= (x - xTable[j]) / diffX;
  48. }
  49. }
  50. for (j = 0; j < yStride; j++) {
  51. result[j] += coefficient * yTable[i * yStride + j];
  52. }
  53. }
  54. return result;
  55. };
  56. export default LagrangePolynomialApproximation;