brian/d3-spring-model
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Pitchaya Boonsarngsuk
2018-01-31 16:02:37 +00:00
parent 3f21a875df
commit 7bb1cd755b
2 changed files with 36 additions and 4 deletions
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15
src/interpolation/interpBruteForce.js
View File

@@ -1,9 +1,20 @@
import {pointOnCircle, takeSampleFrom} from "./helpers";
import {placeNearToNearestNeighbour} from "./interpCommon";
/**
* Perform interpolation where the nearest neighbour is found by brute-force.
* For each point to be interpolated:
* - Phase 1: find a nearest beighbour by comparing high-d distance against
each point already in the graph.
* - 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) {
// var distance = calculateEuclideanDistance;
// console.log("Brute-force");
let sampleSubset = takeSampleFrom(sampleSet, Math.sqrt(sampleSet.length)).sample;
for (let node of remainderSet) {

25
src/interpolation/interpolationPivots.js
View File

@@ -1,6 +1,27 @@
import {pointOnCircle, takeSampleFrom} from "./helpers";
import {placeNearToNearestNeighbour} from "./interpCommon";
/**
* Perform interpolation where the near neighbour is estimated by pivot-based searching.
* - Pre-processing: assign random samples as pivots,
* put the others in each pivot's bucket.
* ie. non-pivot sample X may be in
* - bucket 3 of pivot A,
* - bucket 1 of pivot B,
* - bucket 5 of pivot C,
* all at the same time
* For each point to be interpolated:
* - Phase 1: for each pivot: compare distance against the pivot
* compare against other points in the same bucket of that pivot
* note down the nearest neighbour found
* - 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, numPivots, distanceFn) {
// Pivot based parent finding
let numBuckets = Math.floor(Math.sqrt(sampleSet.length));
@@ -18,7 +39,7 @@ export default function(sampleSet, remainderSet, numPivots, distanceFn) {
// Pre-calculate distance between each non-pivot sample to each pivot
// At the same time, determine the bucket width for each pivot based on furthest non-pivot sample
let distCache = []; // [ For each non-pivot Sample:[For each Pivot: distance] ]
let distCache = []; // [ For each non-pivot sample:[For each Pivot: distance] ]
let bucketWidths = []; // [ For each Pivot: width of each bucket ]
for (let i = 0; i < nonPivotSamples.length; i++)
@@ -37,7 +58,6 @@ export default function(sampleSet, remainderSet, numPivots, distanceFn) {
bucketWidths.push(maxDist / numBuckets);
}
// ---------------------------------------------------------------------
// Put samples (pivot not included) into buckets
for (let j = 0; j < numPivots; j++) {
@@ -53,6 +73,7 @@ export default function(sampleSet, remainderSet, numPivots, distanceFn) {
pivotsBuckets[j][bucketNumber].push(sample);
}
}
// ---------------------------------------------------------------------
let sampleSubset = takeSampleFrom(sampleSet, Math.sqrt(sampleSet.length)).sample;