137 lines
No EOL
3.9 KiB
JavaScript
137 lines
No EOL
3.9 KiB
JavaScript
import { GPU, input, Input } from "gpu.js";
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// derived from https://git.dervland.net/biglyderv/new-bigly-chat/src/branch/master/docs/stats.php
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function rankCalc(result, iterations = 10, main = [], domain_mode = false) {
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let fng = {};
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let fnc = {};
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let frs = {};
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let msum_old = 0.001;
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let pr = {};
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let rl = Object.keys(result).length;
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let matrixe = new Float32Array(rl ** 2);
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for (let i = 0; i < rl ** 2; i += (rl + 1)) {
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matrixe[i] = 1;
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}
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let keys = Object.keys(result);
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for (let unn in result) {
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let v = true;
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if (domain_mode) {
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v = false;
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try {
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let test = new URL(unn);
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v = true;
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} catch (err) {
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v = false;
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}
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}
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if (!v) {
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continue;
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}
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frs[unn] = result[unn].followers || [];
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fng[unn] = result[unn].following || [];
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let lf = Object.keys(fng[unn]).length;
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if (domain_mode) {
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let domains = [];
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for (let x of fng[unn]) {
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try {
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let a = new URL(x);
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domains.push(a.host);
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} catch (err) {
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}
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}
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domains = [...new Set(domains)];
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fnc[unn] = lf / (1 + domains.length);
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} else {
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fnc[unn] = lf;
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}
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pr[unn] = 0.1 / rl;
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}
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for (let unn in result) {
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let fnu = frs[unn];
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if (!pr[unn]) pr[unn] = 0;
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for (let follow of fnu) {
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if (follow == unn) continue;
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let dst = fnc[fnu] || 0;
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let n = (keys.indexOf(unn) || 0) * (rl) + (keys.indexOf(follow) || 0) * 1;
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matrixe[n] = 1 + 5 / (dst + 3);
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msum_old += matrixe[n];
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}
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}
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let mm = (process.env.matrixIterations || iterations);
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let gpu = new GPU();
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const multiplyMatrix = gpu.createKernel(function (a, b, c) {
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let sum = 0;
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for (let i = 0; i < c; i++) {
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sum += a[this.thread.x / c][i] * b[i][this.thread.x % c];
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}
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return sum;
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}).setOutput([keys.length ** 2,1]);
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for (let i = 0; i < mm; i++) {
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let prold = pr;
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pr = [];
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let msum = 1;
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let intv = Math.pow(0.01 / rl, Math.pow(0.09, i / mm));
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console.log(`Completed ${i} iterations with ${intv} threshold`)
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matrixe = multiplyMatrix(matrixe, matrixe, keys.length)[0];
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for (let h in matrixe) {
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msum += matrixe[h];
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}
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for (let h in matrixe) {
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matrixe[h] /= msum / rl;
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}
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for (let una in keys) {
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let una2 = keys[una];
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pr[una2] = 0.1 / rl;
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if ((frs[una2]).length == 0) continue;
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for (let unb in keys) {
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if (isNaN(prold[una2])) continue;
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pr[una2] += prold[una2] * matrixe[una * rl + unb * 1];
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}
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}
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let ov = Object.keys(pr);
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let new_sum = ov.filter(i => !isNaN(pr[i]) && main.indexOf(i) != -1).map(n => pr[n]).reduce((a, b) => a + b, 1e-9);
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let new_sum2 = ov.filter(i => !isNaN(pr[i]) && main.indexOf(i) == -1 && (domain_mode && new URL(i).host == new URL(main[0]).host)).map(n => pr[n]).reduce((a, b) => a + b, 1e-9);
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let new_sum3 = ov.filter(i => !isNaN(pr[i]) && main.indexOf(i) == -1 && !(domain_mode && new URL(i).host == new URL(main[0]).host)).map(n => pr[n]).reduce((a, b) => a + b, 1e-9);
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for (let unn of ov) {
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if (!result[unn]) {
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pr[unn] = 0;
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} else if ((domain_mode && new URL(unn).host == new URL(main[0]).host) && main.indexOf(unn) == -1) {
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pr[unn] /= new_sum2 * 3;
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} else if (main.indexOf(unn) == -1) {
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pr[unn] /= new_sum3 * (domain_mode ? 3 : 2);
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} else {
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pr[unn] /= new_sum * (domain_mode ? 3 : 2);
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}
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}
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}
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return pr;
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}
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export {
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rankCalc
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} |