commit 6c997e4e2c1093981986c6c0cfe713860ce52ec8
parent 88f7736590e6bf8eb1eb12d007578d21eaba0881
Author: NunoSempere <nuno.sempere@protonmail.com>
Date: Wed, 30 Nov 2022 17:11:33 +0000
feat: add js section
Diffstat:
4 files changed, 476 insertions(+), 0 deletions(-)
diff --git a/.gitignore b/.gitignore
@@ -0,0 +1 @@
+**/node_modules
diff --git a/js/package.json b/js/package.json
@@ -0,0 +1,10 @@
+{
+ "name": "time-to-botec",
+ "version": "1.0.0",
+ "main": "index.js",
+ "license": "MIT",
+ "dependencies": {
+ "@stdlib/random": "^0.0.12"
+ },
+ "type": "module"
+}
diff --git a/js/samples.js b/js/samples.js
@@ -0,0 +1,66 @@
+// Imports
+
+import stdlib_normal from '@stdlib/random/base/normal/lib/main.js';
+import stdlib_lognormal from '@stdlib/random/base/lognormal/lib/main.js';
+
+// Functions
+const DEFAULT_N = 10**5
+function generator(f) {
+ let g = (a, b, n = DEFAULT_N) => {
+ let result = new Array(n)
+ for (let i = 0; i < n; i++) {
+ result[i] = f(a, b, n)
+ }
+ return result
+ }
+ return g
+}
+const sum = xs => xs.reduce((acc, x) => acc + x, 0)
+
+const normal = generator(stdlib_normal)
+const lognormal = generator(stdlib_lognormal)
+const to = (low, high, n = DEFAULT_N) => {
+ let normal95confidencePoint = 1.6448536269514722
+ let logLow = Math.log(low)
+ let logHigh = Math.log(high)
+ let meanlog = (logLow + logHigh) / 2
+ let sdlog = (logHigh - logLow) / (2.0 * normal95confidencePoint)
+ return lognormal(meanlog, sdlog, n)
+}
+
+const mixture = (dists_array, weights_array, n = DEFAULT_N) => {
+ let normalized_weights = weights_array.map(w => w / sum(weights_array))
+ let cummulative_sums = Array(normalized_weights.length)
+ normalized_weights.reduce((acc, x, i) => {
+ cummulative_sums[i] = acc + x
+ return cummulative_sums[i]
+ }, 0)
+ const helper_probs = [...new Array(n)].map(_ => Math.random())
+ const results = helper_probs.map(p => {
+ let match_index = cummulative_sums.findIndex(x => x > p)
+ let target_loc = match_index == -1 ? 0 : match_index
+ let target_samples = dists_array[target_loc]
+ return target_samples[Math.floor(Math.random() * target_samples.length)];
+ })
+ return(results)
+
+}
+
+// Example
+let p_a = 0.8
+let p_b = 0.5
+let p_c = p_a * p_b
+
+let dists = [
+ [0], [1], to(1, 3),
+ to(2, 10)
+]
+let weights = [
+ (1 - p_c),
+ p_c / 2,
+ p_c / 4,
+ p_c / 4
+]
+let result = mixture(dists, weights)
+let mean_result = sum(result)/result.length
+console.log(mean_result)
diff --git a/js/yarn.lock b/js/yarn.lock
@@ -0,0 +1,399 @@
+# THIS IS AN AUTOGENERATED FILE. DO NOT EDIT THIS FILE DIRECTLY.
+# yarn lockfile v1
+
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