Update 'src/interpolation/interpBruteForce.js'

2018-03-16 10:19:13 +07:00
parent 5b75f5b588
commit 6335389c7c
1 changed files with 48 additions and 48 deletions
--- a/src/interpolation/interpBruteForce.js
+++ b/src/interpolation/interpBruteForce.js
@@ -1,48 +1,48 @@
-import {pointOnCircle, takeSampleFrom} from "./helpers";
-import {placeNearToNearestNeighbour} from "./interpCommon";
-
-/**
- * Perform interpolation where the "parent" node is found by brute-force.
- * A "parent" of a node to be interpolated is a node whose position in 2D space
- * is already known and have the least high-dimensional distance to the node in
- * question.
- * For each point to be interpolated:
- * - Phase 1: find the "parent" by comparing high-d distance against every
-              points already plotted on the graph.
-              this is essentially a nearest neighbour finding problem.
- * - Phase 2 and 3 are passed onto placeNearToNearestNeighbour
- * @param  {list} sampleSet      - nodes already plotted on the 2D graph
- * @param  {list} remainderSet   - nodes to be interpolated onto the graph
- * @param  {function} distanceFn - f(nodex, nodey) that calculate high-dimensional
- *                                 distance between 2 nodes
- * @param  {number} endingIts    - for phase 3, how many iterations to refine the
- *                                 placement of each interpolated point
- */
-export default function(sampleSet, remainderSet, distanceFn, endingIts) {
-  let
-    sampleSubset = takeSampleFrom(sampleSet, Math.sqrt(sampleSet.length)).sample,
-    sampleSubsetDistanceCache = [];
-
-  // For each datapoint "node" to be interpolated
-  for (let i = remainderSet.length-1; i>=0; i--) {
-    let
-      node = remainderSet[i],
-      nearestSample, minDist, sample, dist, index;
-
-    // For each datapoint "sample" in the sample set
-    for (let j = sampleSet.length-1; j>=0; j--) {
-      sample = sampleSet[j];
-      dist = distanceFn(node, sample);
-      if (nearestSample === undefined || dist < minDist) {
-        minDist = dist;
-        nearestSample = sample;
-      }
-
-      index = sampleSubset.indexOf(sample);
-      if (index !== -1)
-        sampleSubsetDistanceCache[index] = dist;
-    }
-
-    placeNearToNearestNeighbour(node, nearestSample, minDist, sampleSubset, sampleSubsetDistanceCache, endingIts);
-  }
-}
+import {takeSampleFrom} from "./helpers";
+import {placeNearToNearestNeighbour} from "./interpCommon";
+
+/**
+ * Perform interpolation where the "parent" node is found by brute-force.
+ * A "parent" of a node to be interpolated is a node whose position in 2D space
+ * is already known and have the least high-dimensional distance to the node in
+ * question.
+ * For each point to be interpolated:
+ * - Phase 1: find the "parent" by comparing high-d distance against every
+              points already plotted on the graph.
+              this is essentially a nearest neighbour finding problem.
+ * - Phase 2 and 3 are passed onto placeNearToNearestNeighbour
+ * @param  {list} sampleSet      - nodes already plotted on the 2D graph
+ * @param  {list} remainderSet   - nodes to be interpolated onto the graph
+ * @param  {function} distanceFn - f(nodex, nodey) that calculate high-dimensional
+ *                                 distance between 2 nodes
+ * @param  {number} endingIts    - for phase 3, how many iterations to refine the
+ *                                 placement of each interpolated point
+ */
+export default function(sampleSet, remainderSet, distanceFn, endingIts) {
+  let
+    sampleSubset = takeSampleFrom(sampleSet, Math.sqrt(sampleSet.length)).sample,
+    sampleSubsetDistanceCache = [];
+
+  // For each datapoint "node" to be interpolated
+  for (let i = remainderSet.length-1; i>=0; i--) {
+    let
+      node = remainderSet[i],
+      nearestSample, minDist, sample, dist, index;
+
+    // For each datapoint "sample" in the sample set
+    for (let j = sampleSet.length-1; j>=0; j--) {
+      sample = sampleSet[j];
+      dist = distanceFn(node, sample);
+      if (nearestSample === undefined || dist < minDist) {
+        minDist = dist;
+        nearestSample = sample;
+      }
+
+      index = sampleSubset.indexOf(sample);
+      if (index !== -1)
+        sampleSubsetDistanceCache[index] = dist;
+    }
+
+    placeNearToNearestNeighbour(node, nearestSample, minDist, sampleSubset, sampleSubsetDistanceCache, endingIts);
+  }
+}