From 6c997e4e2c1093981986c6c0cfe713860ce52ec8 Mon Sep 17 00:00:00 2001 From: NunoSempere Date: Wed, 30 Nov 2022 17:11:33 +0000 Subject: [PATCH] feat: add js section --- .gitignore | 1 + js/package.json | 10 ++ js/samples.js | 66 ++++++++ js/yarn.lock | 399 ++++++++++++++++++++++++++++++++++++++++++++++++ 4 files changed, 476 insertions(+) create mode 100644 .gitignore create mode 100644 js/package.json create mode 100644 js/samples.js create mode 100644 js/yarn.lock diff --git a/.gitignore b/.gitignore new file mode 100644 index 00000000..cf709889 --- /dev/null +++ b/.gitignore @@ -0,0 +1 @@ +**/node_modules diff --git a/js/package.json b/js/package.json new file mode 100644 index 00000000..a3b3aec2 --- /dev/null +++ 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 new file mode 100644 index 00000000..62976f8e --- /dev/null +++ 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 new file mode 100644 index 00000000..71289225 --- /dev/null +++ b/js/yarn.lock @@ -0,0 +1,399 @@ +# THIS IS AN AUTOGENERATED FILE. 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