Increase neighbors to 9 in all directions, but this severely limits m…

…ax free params

datafit/src/CurveFit.ts

@@ -5,7 +5,7 @@ export abstract class CurveFit {
     /**
      * Anything beyond this takes several minutes of computation time.
      */
-    private static readonly MAX_PARAMS: number = 18;
+    private static readonly MAX_PARAMS: number = 8;
     /**
      * 
      * @param f The model function for curve fitting.
@@ -23,7 +23,7 @@ export abstract class CurveFit {
      * @param iterations Define the number of iterations for this algorithm.
      * @returns The set of parameters for the best fit and sum of squared errors.
      */
-    public static fit(f: fx, data: Array<Point>, a_initial: Array<number> = [], searchDistance: number = 10, iterations: number = 1e3): Fit {
+    public static fit(f: fx, data: Array<Point>, a_initial: Array<number> = [], distance: number = 10, iterations: number = 1e3): Fit {
         const N_params: number = f.length - 1;
         if (a_initial.length === 0) {
             a_initial.length = N_params;
@@ -35,12 +35,12 @@ export abstract class CurveFit {
         if (N_params > this.MAX_PARAMS) {
             throw new Error('Your function includes too many unknown parameters.');
         }
-        if (searchDistance < 0 || iterations < 0) {
+        if (distance < 0 || iterations < 0) {
             throw new Error('Invalid search distance or iteration count.');
         }
-        let bestFit: Fit = this.fitStep(f, a_initial, data, searchDistance);
+        let bestFit: Fit = this.fitStep(f, a_initial, data, distance);
         for (let i = 0; i < iterations; i++) {
-            bestFit = this.fitStep(f, bestFit.a, data, SMath.translate(i, 0, iterations, searchDistance, 0));
+            bestFit = this.fitStep(f, bestFit.a, data, SMath.translate(i, 0, iterations, distance, 0));
         }
         return bestFit;
     }
@@ -55,7 +55,7 @@ export abstract class CurveFit {
      * @returns The best fit for the model up to the distance specified.
      */
     private static fitStep(f: fx, a: Array<number>, data: Array<Point>, distance: number): Fit {
-        const d: number = 5,
+        const d: number = 9,
             n: number = a.length;
         let err_min: number = this.sumSquares(f, a, data),
             a_min: Array<number> = a.slice();