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feat: Add utility tools

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I'm hoping to have these be a separate package that are also used in the
website.
This commit is contained in:
NunoSempere 2022-06-15 23:00:54 -04:00
parent 193b86a212
commit bb0108fb60
12 changed files with 1451 additions and 3 deletions
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.gitignore vendored
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# personal notes # personal notes
Notes.md Notes.md
# personal outputs
packages/utility-tools/input/input-links-*
# vim files # vim files
.swp .swp

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.vscode/settings.json vendored
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{
"cSpell.words": ["Stdev"]
}

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packages/utility-tools/README.md Normal file
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## Utility function processor
This package contains a series of utilities to work with the utility functions produced by [this utility function extractor](https://utility-function-extractor.quantifieduncertainty.org/openphil-2018-ai-risk)
### Merge sort
Given a list of elements and a list of utilitity comparisons, sort the list.
Gotcha: The list of elements has to be the same list, and in the same order, as that produced when initially doing the comparisons. This is because the merge-sort algorithm depends on the initial order of the list.

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[
{
"source": "Stanford University — Machine Learning Security Research Led by Dan Boneh and Florian Tramer",
"target": "Wilson Center — AI Policy Seminar Series",
"distance": 4.039836724233664,
"reasoning": "Jaime's estimates.\nThe Wilson Center seems to not be running the AI Policy Seminar Series anymore, so I am led to believe it was not a great success (?). There could be someone key influenced that will facilitate things later but seems unlikely\nThe ML Security program does not seem to have resulted on anything substantial",
"squiggleString": "1 to 10"
},
{
"source": "Stanford University — Machine Learning Security Research Led by Dan Boneh and Florian Tramer",
"target": "Open Phil AI Fellowship — 2018 Class",
"distance": 657.4661082204123,
"reasoning": "The AI fellows have produced work on interpretability and out of distribution learning.\nSeems to have been better for purchasing influence too, though that's a secondary consideration IMO",
"squiggleString": "400 to 1000"
},
{
"source": "Wilson Center — AI Policy Seminar Series",
"target": "Open Phil AI Fellowship — 2018 Class",
"distance": 403.9836724233662,
"reasoning": "The research seems more directly relevant from the AI fellows, the policy seminar has no legible output",
"squiggleString": "100 to 1000"
},
{
"source": "UC Berkeley — AI Safety Research (2018)",
"target": "Machine Intelligence Research Institute — AI Safety Retraining Program",
"distance": 40.39836724233665,
"reasoning": "Seems to support directly people working on the topic, and more counterfactual",
"squiggleString": "10 to 100"
},
{
"source": "Stanford University — Machine Learning Security Research Led by Dan Boneh and Florian Tramer",
"target": "UC Berkeley — AI Safety Research (2018)",
"distance": 7.229755173700019,
"reasoning": "AI Safety Research Affects more people, someone might end up doing something cool",
"squiggleString": "5 to 10"
},
{
"source": "Wilson Center — AI Policy Seminar Series",
"target": "UC Berkeley — AI Safety Research (2018)",
"distance": 2.663515640351876,
"reasoning": "Similar value from the outside",
"squiggleString": "0.1 to 10"
},
{
"source": "UC Berkeley — AI Safety Research (2018)",
"target": "Open Phil AI Fellowship — 2018 Class",
"distance": 247.53475654135346,
"reasoning": "AI fellows produced directly relevant research, are more successful",
"squiggleString": "(1/(0.001 to 0.01))"
},
{
"source": "Machine Intelligence Research Institute — AI Safety Retraining Program",
"target": "Open Phil AI Fellowship — 2018 Class",
"distance": 49.50695130827075,
"reasoning": "aI fellows seem to have produced more relevant research, though grant is less counterfactual",
"squiggleString": "(1/(0.005 to 0.05))"
},
{
"source": "Ought — General Support (2018)",
"target": "Oxford University — Research on the Global Politics of AI",
"distance": 403.9836724233662,
"reasoning": "GovAI is doing cool stuff, Ought not so much",
"squiggleString": "100 to 1000"
},
{
"source": "AI Impacts — General Support (2018)",
"target": "Michael Cohen and Dmitrii Krasheninnikov — Scholarship Support (2018)",
"distance": 2.5202870466776885,
"reasoning": "Direct work seems more important, but Ai impacts work is pretty cool",
"squiggleString": "1 to 5"
},
{
"source": "Ought — General Support (2018)",
"target": "AI Impacts — General Support (2018)",
"distance": 109.28343925564944,
"reasoning": "AI impacts work has been more successful \\ useful for my research",
"squiggleString": "50 to 200"
},
{
"source": "AI Impacts — General Support (2018)",
"target": "Oxford University — Research on the Global Politics of AI",
"distance": 39.678020061969825,
"reasoning": "GovAI is doing more work and on a more neglected topic. Both are doing good work, but GOvAI output is bigger",
"squiggleString": "(1/(0.01 to 0.05))"
},
{
"source": "Oxford University — Research on the Global Politics of AI",
"target": "Michael Cohen and Dmitrii Krasheninnikov — Scholarship Support (2018)",
"distance": 2.865987655844147,
"reasoning": "Cohens work seems harder to replace.\nGovAI is doing more work though",
"squiggleString": "0.01 to 10"
},
{
"source": "Stanford University — Machine Learning Security Research Led by Dan Boneh and Florian Tramer",
"target": "Ought — General Support (2018)",
"distance": 14.338510859889407,
"reasoning": "At least Ought is trying ",
"squiggleString": "1 to 50"
},
{
"source": "Wilson Center — AI Policy Seminar Series",
"target": "Ought — General Support (2018)",
"distance": 2.663515640351876,
"reasoning": "Unclear",
"squiggleString": "0.1 to 10"
},
{
"source": "UC Berkeley — AI Safety Research (2018)",
"target": "Ought — General Support (2018)",
"distance": 4.039836724233664,
"reasoning": "At least ought is trying",
"squiggleString": "1 to 10"
},
{
"source": "Machine Intelligence Research Institute — AI Safety Retraining Program",
"target": "Ought — General Support (2018)",
"distance": 1.4338510859889406,
"reasoning": "Value more the potential new hire than oughts research",
"squiggleString": "0.1 to 5"
},
{
"source": "Ought — General Support (2018)",
"target": "Open Phil AI Fellowship — 2018 Class",
"distance": 247.53475654135346,
"reasoning": "Fellows seem to have produced more relevant research",
"squiggleString": "(1/(0.001 to 0.01))"
},
{
"source": "AI Impacts — General Support (2018)",
"target": "Open Phil AI Fellowship — 2018 Class",
"distance": 13.831727022205978,
"reasoning": "Fellows produced more relevant research, AI impacts work is cool though",
"squiggleString": "(1/(0.05 to 0.1))"
},
{
"source": "Open Phil AI Fellowship — 2018 Class",
"target": "Oxford University — Research on the Global Politics of AI",
"distance": 32.87330541102063,
"reasoning": "GovAI's grant seems moe counterfactual, their work more directly relevant\n",
"squiggleString": "20 to 50"
}
]

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packages/utility-tools/input/input-list.json Normal file
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[
{
"name": "Michael Cohen and Dmitrii Krasheninnikov — Scholarship Support (2018)",
"url": "https://docs.google.com/document/d/1VlN6I4Jauarx-0Fp7AC1ggeQ02AITsN7S56ffAO9NTU/edit#heading=h.jnlrsr63yliq",
"amount": "$159k"
},
{
"name": "AI Impacts — General Support (2018)",
"url": "https://docs.google.com/document/d/1VlN6I4Jauarx-0Fp7AC1ggeQ02AITsN7S56ffAO9NTU/edit#heading=h.6m6tebpouzt1",
"amount": "$100k"
},
{
"name": "Oxford University — Research on the Global Politics of AI",
"url": "https://docs.google.com/document/d/1VlN6I4Jauarx-0Fp7AC1ggeQ02AITsN7S56ffAO9NTU/edit#heading=h.c6r2m7i749ay",
"amount": "$429k"
},
{
"name": "Ought — General Support (2018)",
"url": "https://docs.google.com/document/d/1VlN6I4Jauarx-0Fp7AC1ggeQ02AITsN7S56ffAO9NTU/edit#heading=h.xnzaj48k3fdb",
"amount": "$525k"
},
{
"name": "Machine Intelligence Research Institute — AI Safety Retraining Program",
"url": "https://docs.google.com/document/d/1VlN6I4Jauarx-0Fp7AC1ggeQ02AITsN7S56ffAO9NTU/edit#heading=h.h922w7eh5rq6",
"amount": "$150k"
},
{
"name": "UC Berkeley — AI Safety Research (2018)",
"url": "https://docs.google.com/document/d/1VlN6I4Jauarx-0Fp7AC1ggeQ02AITsN7S56ffAO9NTU/edit#heading=h.rrsbecbboed8",
"amount": "$1.145M"
},
{
"name": "Open Phil AI Fellowship — 2018 Class",
"url": "https://docs.google.com/document/d/1VlN6I4Jauarx-0Fp7AC1ggeQ02AITsN7S56ffAO9NTU/edit#heading=h.p8xd58asz6a2",
"amount": "$1.135M"
},
{
"name": "Wilson Center — AI Policy Seminar Series",
"url": "https://docs.google.com/document/d/1VlN6I4Jauarx-0Fp7AC1ggeQ02AITsN7S56ffAO9NTU/edit#heading=h.qiurhycylgi3",
"amount": "$400k"
},
{
"name": "Stanford University — Machine Learning Security Research Led by Dan Boneh and Florian Tramer",
"url": "https://docs.google.com/document/d/1VlN6I4Jauarx-0Fp7AC1ggeQ02AITsN7S56ffAO9NTU/edit#heading=h.ox8adhpgba86",
"amount": "$100k"
}
]

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Sorted output:
[
'Stanford University — Machine Learning Security Research Led by Dan Boneh and Florian Tramer',
'Wilson Center — AI Policy Seminar Series',
'UC Berkeley — AI Safety Research (2018)',
'Machine Intelligence Research Institute — AI Safety Retraining Program',
'Ought — General Support (2018)',
'AI Impacts — General Support (2018)',
'Open Phil AI Fellowship — 2018 Class',
'Oxford University — Research on the Global Politics of AI',
'Michael Cohen and Dmitrii Krasheninnikov — Scholarship Support (2018)'
]
Stanford University — Machine Learning Security Research Led by Dan Boneh and Florian Tramer
Number of paths: 102
Mean: 0.04340463625937361
90% confidence interval: [
3.102187977841675e-7,
0.10636313508232977
]
3.902 seconds needed for processing
Wilson Center — AI Policy Seminar Series
Number of paths: 52
Mean: 0.23923636834715892
90% confidence interval: [
0.0000012797707857581555,
0.7647175734237982
]
0.855 seconds needed for processing
UC Berkeley — AI Safety Research (2018)
Number of paths: 37
Mean: 0.6148765126821536
90% confidence interval: [
0.0000012857319777641759,
2.4285898907477064
]
0.484 seconds needed for processing
Machine Intelligence Research Institute — AI Safety Retraining Program
Number of paths: 21
Mean: 46.33576477417035
90% confidence interval: [
0.000022241280559831212,
201.37264605399085
]
0.173 seconds needed for processing
Ought — General Support (2018)
Number of paths: 36
Mean: 63.37826067838051
90% confidence interval: [
0.00004411196776834627,
145.5050535108514
]
0.412 seconds needed for processing
AI Impacts — General Support (2018)
Number of paths: 47
Mean: 9862.157135402398
90% confidence interval: [
0.018650934888088284,
22307.090052203544
]
0.635 seconds needed for processing
Open Phil AI Fellowship — 2018 Class
Number of paths: 372
Mean: 86301.01328794319
90% confidence interval: [
26.02179139839112,
115734.18190287006
]
35.203 seconds needed for processing
Oxford University — Research on the Global Politics of AI
Number of paths: 2261
Mean: 785779.6653748289
90% confidence interval: [
114.32195138741375,
960250.7929788446
]
1048.955 seconds needed for processing
Michael Cohen and Dmitrii Krasheninnikov — Scholarship Support (2018)
Number of paths: 5243
Mean: 1482642.2273006735
90% confidence interval: [
8.379381400123396,
330071.1150485886
]
5550.563 seconds needed for processing

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{
"name": "utility-tools",
"version": "0.0.1",
"description": "Process the json produced by utility-function-extractor.quantifieduncertainty.org",
"scripts": {
"start": "node --max-old-space-size=8192 src/index.js"
},
"type": "module",
"main": "src/index.js",
"author": "Nuño Sempere",
"license": "MIT",
"dependencies": {
"@quri/squiggle-lang": "^0.2.11"
}
}

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// EXPORTS
import { run } from "@quri/squiggle-lang";
export function aggregatePaths(pathsArray, nodes) {
pathsArray.map((paths, i) => {
console.log(nodes[i].name);
let multipliedDistributions = paths.map(
(path) => path.multipliedDistributionsInPath
);
console.group();
console.log("Number of paths: ", multipliedDistributions.length);
// console.log(multipliedDistributions.slice(0, 10));
let squiggleCode = `aggregatePath = mx(${multipliedDistributions
.filter((distributions) => distributions != undefined)
// .slice(0, 600)
.join(", ")})`;
// Start measuring time
let start = Date.now();
// Get the mean
let squiggleCodeForMean = squiggleCode + "\n" + "mean(aggregatePath)";
let meanAnswer = run(squiggleCodeForMean);
let mean = meanAnswer.value.value;
console.log(`Mean: ${mean}`);
// Get the 90% CI
let squiggleCodeFor90CI =
squiggleCode +
"\n" +
"[inv(aggregatePath, 0.05), inv(aggregatePath, 0.95)]";
let ci90percentAnswer = run(squiggleCodeFor90CI);
// Display output
let processCI90 = (answer) => {
let value = answer.value.value;
let lower = value[0].value;
let upper = value[1].value;
return [lower, upper];
};
console.log(
`90% confidence interval: ${JSON.stringify(
processCI90(ci90percentAnswer),
null,
4
)}`
);
// Stop measuring time
let end = Date.now();
console.log(`${(end - start) / 1000} seconds needed for processing`);
console.groupEnd();
console.log("");
});
}

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/* Functions */
const pathPlusLink = (pathSoFar, link) => {
return [...pathSoFar, link];
// previously: pathSoFar.concat(link).flat()
// Note that concat is not destructive
// https://developer.mozilla.org/en-US/docs/Web/JavaScript/Reference/Global_Objects/Array/concat
};
const findElementPosition = (name, nodes) => {
let node = nodes.find((node) => node.name == name);
return node.position;
};
async function findPathsWithoutPrunning({
sourceElementName,
targetElementName,
maxLengthOfPath,
pathSoFar,
links,
nodes,
}) {
// This is an un-used function which might make findPaths more understandable
// It uses the same recursive functionality
// but has no path prunning
let paths = [];
/* Path traversing */
if (maxLengthOfPath > 0) {
for (let link of links) {
// vs let link of linksNow in findPaths
if (
(link.source == sourceElementName &&
link.target == targetElementName) ||
(link.source == targetElementName && link.target == sourceElementName)
) {
// direct Path
let newPath = pathPlusLink(pathSoFar, link);
paths.push(newPath);
} else if (link.source == sourceElementName) {
let newPaths = await findPaths({
pathSoFar: pathPlusLink(pathSoFar, link),
maxLengthOfPath: maxLengthOfPath - 1,
sourceElementName: link.target,
targetElementName,
links: links, // vs let link of linksInner in findPaths
nodes,
});
if (newPaths.length != 0) {
paths.push(...newPaths);
}
} else if (link.target == sourceElementName) {
let newPaths = await findPaths({
pathSoFar: pathPlusLink(pathSoFar, link),
maxLengthOfPath: maxLengthOfPath - 1,
sourceElementName: link.source,
targetElementName,
links: links, // vs let link of linksInner in findPaths
nodes,
});
if (newPaths.length != 0) {
paths.push(...newPaths);
}
}
}
}
return paths;
}
async function findPaths({
sourceElementName,
sourceElementPosition,
targetElementName,
targetElementPosition,
maxLengthOfPath,
pathSoFar,
links,
nodes,
}) {
// This is the key path finding function
// It finds the path from one element to another, recursively
// It used to be very computationally expensive until I added
// the path prunning step: Instead of traversing all links,
// traverse only those which are between the origin and target links
// this requires us to have a notion of "between"
let paths = [];
/* Path prunning*/
let minPos = Math.min(sourceElementPosition, targetElementPosition);
let maxPos = Math.max(sourceElementPosition, targetElementPosition);
let linksInner = links.filter(
(link) =>
minPos <= link.sourceElementPosition &&
link.sourceElementPosition <= maxPos &&
minPos <= link.targetElementPosition &&
link.targetElementPosition <= maxPos
);
let linksNow = linksInner.filter(
(link) =>
link.source == sourceElementName || link.target == sourceElementName
);
/* Path traversing */
if (maxLengthOfPath > 0) {
for (let link of linksNow) {
if (
(link.source == sourceElementName &&
link.target == targetElementName) ||
(link.source == targetElementName && link.target == sourceElementName)
) {
// direct Path
let newPath = pathPlusLink(pathSoFar, link);
paths.push(newPath);
} else if (link.source == sourceElementName) {
let newPaths = await findPaths({
pathSoFar: pathPlusLink(pathSoFar, link),
maxLengthOfPath: maxLengthOfPath - 1,
sourceElementPosition: link.sourceElementPosition,
sourceElementName: link.target,
targetElementName,
targetElementPosition,
links: linksInner,
nodes,
});
if (newPaths.length != 0) {
paths.push(...newPaths);
}
} else if (link.target == sourceElementName) {
let newPaths = await findPaths({
pathSoFar: pathPlusLink(pathSoFar, link),
maxLengthOfPath: maxLengthOfPath - 1,
sourceElementPosition: link.sourceElementPosition,
sourceElementName: link.source,
targetElementPosition,
targetElementName,
links: linksInner,
nodes,
});
if (newPaths.length != 0) {
paths.push(...newPaths);
}
}
}
}
return paths;
}
async function findExpectedValuesAndDistributionsForElement({
sourceElementName,
sourceElementPosition,
targetElementName,
targetElementPosition,
nodes,
links,
}) {
// This function gets all possible paths using findPaths
// then orders them correctly in the for loop
// (by flipping the distance to 1/distance when necessary)
// and then gets the array of weights for the different paths.
/*
console.log(
`findDistance@findPaths.js from ${sourceElementPosition} to ${targetElementPosition}`
);
*/
let maxLengthOfPath = Math.abs(sourceElementPosition - targetElementPosition);
let paths = await findPaths({
sourceElementName,
sourceElementPosition,
targetElementName,
targetElementPosition,
links,
nodes,
maxLengthOfPath,
pathSoFar: [],
});
let processedPaths = [];
for (let path of paths) {
let currentSource = sourceElementName;
let expectedRelativeValue = 1;
let multipliedDistributionsInPath = 1;
let distances = [];
for (let element of path) {
let distance = 0;
let anotherDistributionInPath = 1;
if (element.source == currentSource) {
distance = element.distance;
anotherDistributionInPath = element.squiggleString;
currentSource = element.target;
} else if (element.target == currentSource) {
distance = 1 / Number(element.distance);
anotherDistributionInPath = `1 / (${element.squiggleString})`;
currentSource = element.source;
}
expectedRelativeValue = expectedRelativeValue * distance;
distances.push(distance);
multipliedDistributionsInPath = `${multipliedDistributionsInPath} * (${anotherDistributionInPath})`;
}
processedPaths.push({
distances,
expectedRelativeValue,
multipliedDistributionsInPath,
// path,
});
}
return processedPaths;
/*
let expectedValues = [];
for (let path of paths) {
let currentSource = sourceElementName;
let weight = 1;
for (let element of path) {
let distance = 0;
if (element.source == currentSource) {
distance = element.distance;
currentSource = element.target;
} else if (element.target == currentSource) {
distance = 1 / Number(element.distance);
currentSource = element.source;
}
weight = weight * distance;
}
expectedValues.push(weight);
}
let distributionalForm = [];
for (let path of paths) {
let currentSource = sourceElementName;
let multipliedDistributionsInPath = 1;
for (let element of path) {
let anotherDistributionInPath;
if (element.source == currentSource) {
distributionInPath = element.squiggleString;
currentSource = element.target;
} else if (element.target == currentSource) {
distance = `1 / (${element.squiggleString})`;
currentSource = element.source;
}
multipliedDistributionsInPath = `${multipliedDistributionsInPath} * (${anotherDistributionInPath})`;
}
distributionalForm.push(multipliedDistributionsInPath);
}
return {
expectedValues,
distributionalForm,
// paths,
};
*/
}
async function findDistancesFromAllElementsToReferencePoint({
nodes,
links,
referenceElement,
}) {
// Simple wrapper function around findDistance
// Needs to find the reference point first
// console.log("findDistancesForAllElements@findPaths.js");
/* Get or build reference element */
let midpoint = Math.round(nodes.length / 2);
referenceElement = referenceElement || nodes[midpoint];
// console.log(`referenceElement.position: ${referenceElement.position}`);
/* Get distances. */
let distancesArray = nodes.map((node) => {
if (node.name == referenceElement.name) {
return [1];
} else {
// console.log("node");
// console.log(node);
let expectedValuesAndDistributionsForElement =
findExpectedValuesAndDistributionsForElement({
sourceElementName: referenceElement.name,
sourceElementPosition: referenceElement.position,
targetElementName: node.name,
targetElementPosition: node.position,
nodes: nodes,
links: links,
});
return expectedValuesAndDistributionsForElement;
}
});
distancesArray = await Promise.all(distancesArray);
return distancesArray;
}
export async function findDistancesFromAllElementsToAllReferencePoints({
nodes,
links,
}) {
let nodes2 = nodes.map((node) => ({ ...node, isReferenceValue: false }));
let distancesForAllElements = Array(nodes.length);
for (let i = 0; i < nodes.length; i++) {
distancesForAllElements[i] = [];
}
for (let node of nodes2) {
let distancesFromNode = await findDistancesFromAllElementsToReferencePoint({
nodes: nodes2,
links,
referenceElement: node,
});
// alert(`distancesFromNode.length: ${distancesFromNode.length}`);
distancesForAllElements = distancesForAllElements.map((arr, i) => {
return !!arr && arr.length > 0
? [...arr, ...distancesFromNode[i]]
: distancesFromNode[i];
});
}
return distancesForAllElements;
}

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// IMPORTS
import * as fs from "fs";
import { mergeSort } from "./mergeSort.js";
import { findDistancesFromAllElementsToAllReferencePoints } from "./findPaths.js";
import { aggregatePaths } from "./aggregatePaths.js";
// DEFS
const inputLinksFilePath = "./input/input-links.json";
const inputListFilePath = "./input/input-list.json";
const outputFilePath = "./output/output.json";
// HELPERS
const findElementPosition = (name, orderedList) => {
let node = orderedList.find((node) => node.name == name);
return node.position;
};
// MAIN
async function main() {
// read file
const inputLinksAsString = fs.readFileSync(inputLinksFilePath);
const inputListAsString = fs.readFileSync(inputListFilePath);
const links = JSON.parse(inputLinksAsString);
const list = JSON.parse(inputListAsString);
// process file
// const sources = links.map((link) => link.source);
// const targets = links.map((link) => link.target);
// const list = [...new Set([...sources, ...targets])];
// Merge sort
let mergeSortOutput = mergeSort({ list, links });
// console.log("Output: ");
console.log("Sorted output: ");
console.group();
console.log(mergeSortOutput.map((x) => x.name));
console.groupEnd();
console.log("");
// find Paths
let nodes = mergeSortOutput.map((element, i) => ({
...element,
position: i,
}));
const linksWithPosition = links.map((link) => ({
...link,
sourceElementPosition: findElementPosition(link.source, nodes),
targetElementPosition: findElementPosition(link.target, nodes),
}));
let paths = await findDistancesFromAllElementsToAllReferencePoints({
nodes,
links: linksWithPosition,
});
// console.log(JSON.stringify(paths, null, 4));
// Aggregate paths.
let aggregatedPaths = aggregatePaths(paths, nodes);
}
main();

115
packages/utility-tools/src/mergeSort.js Normal file
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@ -0,0 +1,115 @@
const errorMsg = "No link found; unable to proceed";
function isFirstElementGreater(links, element1, element2) {
const relevantComparisons = links.filter(
(link) =>
(link.source == element1.name && link.target == element2.name) ||
(link.source == element2.name && link.target == element1.name)
);
if (relevantComparisons.length == 0) {
// console.log(element1, "vs", element2);
return errorMsg;
} else {
const firstLink = relevantComparisons[0];
// console.log(firstLink);
const firstElementFirst =
firstLink.source == element1.name && firstLink.target == element2.name
? true
: false;
const distanceIsGreaterThanOne = Number(firstLink.distance) > 1;
const answer =
(firstElementFirst && !distanceIsGreaterThanOne) ||
(!firstElementFirst && distanceIsGreaterThanOne);
return !answer;
}
}
function merge(links, left, right) {
let sortedArr = []; // the sorted elements will go here
while (left.length && right.length) {
// insert the biggest element to the sortedArr
let link = isFirstElementGreater(links, left[0], right[0]);
if (link == errorMsg) {
// console.log("Error@:");
// console.group();
// console.log({ left, right });
// console.groupEnd();
return errorMsg;
} else if (link) {
// left[0] > right[0]
sortedArr.push(left.shift());
} else {
sortedArr.push(right.shift());
}
}
// use spread operator and create a new array, combining the three arrays
return [...sortedArr, ...left, ...right]; // if they don't have the same size, the remaining ones will be greater than the ones before
}
export function mergeSortInner({ list, links }) {
// console.log({ l: list.length });
if (list == errorMsg) {
return errorMsg;
}
const half = list.length / 2;
// the base case is list length <=1
if (list.length <= 1) {
return list;
}
const left = list.slice(0, half); // the first half of the list
const right = list.slice(half, list.length); // Note that splice is destructive.
let orderedFirstHalf = mergeSortInner({ list: left, links });
let orderedSecondHalf = mergeSortInner({ list: right, links });
if (orderedFirstHalf != errorMsg && orderedSecondHalf != errorMsg) {
let result = merge(links, orderedFirstHalf, orderedSecondHalf);
return result;
} else {
return errorMsg;
}
}
export function mergeSort({ list, links }) {
// Try normally
let answer = mergeSortInner({ list, links });
if (answer != errorMsg) return answer;
// otherwise
let permutation = list.slice();
var length = list.length;
// let result = [list.slice()];
let c = new Array(length).fill(0);
let i = 1;
let k;
let p;
let counter = 0;
while (i < length) {
counter++;
if (counter > 10) console.log(counter);
if (c[i] < i) {
k = i % 2 && c[i];
p = permutation[i];
permutation[i] = permutation[k];
permutation[k] = p;
// ++c[i];
c[i] = c[i] + 1;
i = 1;
let answer = mergeSortInner({ list: permutation, links });
if (answer != errorMsg) {
console.log(answer);
return answer;
}
// result.push(permutation.slice());
} else {
c[i] = 0;
i = i + 1;
// ++i;
}
}
console.log("Error");
return "Error: The original list was wrongly ordered, and trying permutations didn't work";
}

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packages/utility-tools/yarn.lock Normal file
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complex.js@^2.1.1:
version "2.1.1"
resolved "https://registry.yarnpkg.com/complex.js/-/complex.js-2.1.1.tgz#0675dac8e464ec431fb2ab7d30f41d889fb25c31"
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core-util-is@~1.0.0:
version "1.0.3"
resolved "https://registry.yarnpkg.com/core-util-is/-/core-util-is-1.0.3.tgz#a6042d3634c2b27e9328f837b965fac83808db85"
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debug@^2.6.9:
version "2.6.9"
resolved "https://registry.yarnpkg.com/debug/-/debug-2.6.9.tgz#5d128515df134ff327e90a4c93f4e077a536341f"
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dependencies:
ms "2.0.0"
decimal.js@^10.3.1:
version "10.3.1"
resolved "https://registry.yarnpkg.com/decimal.js/-/decimal.js-10.3.1.tgz#d8c3a444a9c6774ba60ca6ad7261c3a94fd5e783"
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escape-latex@^1.2.0:
version "1.2.0"
resolved "https://registry.yarnpkg.com/escape-latex/-/escape-latex-1.2.0.tgz#07c03818cf7dac250cce517f4fda1b001ef2bca1"
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fraction.js@^4.2.0:
version "4.2.0"
resolved "https://registry.yarnpkg.com/fraction.js/-/fraction.js-4.2.0.tgz#448e5109a313a3527f5a3ab2119ec4cf0e0e2950"
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inherits@~2.0.3:
version "2.0.4"
resolved "https://registry.yarnpkg.com/inherits/-/inherits-2.0.4.tgz#0fa2c64f932917c3433a0ded55363aae37416b7c"
integrity sha512-k/vGaX4/Yla3WzyMCvTQOXYeIHvqOKtnqBduzTHpzpQZzAskKMhZ2K+EnBiSM9zGSoIFeMpXKxa4dYeZIQqewQ==
isarray@~1.0.0:
version "1.0.0"
resolved "https://registry.yarnpkg.com/isarray/-/isarray-1.0.0.tgz#bb935d48582cba168c06834957a54a3e07124f11"
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javascript-natural-sort@^0.7.1:
version "0.7.1"
resolved "https://registry.yarnpkg.com/javascript-natural-sort/-/javascript-natural-sort-0.7.1.tgz#f9e2303d4507f6d74355a73664d1440fb5a0ef59"
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jstat@^1.9.5:
version "1.9.5"
resolved "https://registry.yarnpkg.com/jstat/-/jstat-1.9.5.tgz#9941741566f683624ddeb56f5ba60ed8c29b374e"
integrity sha512-cWnp4vObF5GmB2XsIEzxI/1ZTcYlcfNqxQ/9Fp5KFUa0Jf/4tO0ZkGVnqoEHDisJvYgvn5n3eWZbd2xTVJJPUQ==
lodash@^4.17.21:
version "4.17.21"
resolved "https://registry.yarnpkg.com/lodash/-/lodash-4.17.21.tgz#679591c564c3bffaae8454cf0b3df370c3d6911c"
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mathjs@^10.6.0:
version "10.6.1"
resolved "https://registry.yarnpkg.com/mathjs/-/mathjs-10.6.1.tgz#95b34178eed65cbf7a63d35c468ad3ac912f7ddf"
integrity sha512-8iZp6uUKKBoCFoUHze9ydsrSji9/IOEzMhwURyoQXaLL1+ILEZnraw4KzZnUBt/XN6lPJPV+7JO94oil3AmosQ==
dependencies:
"@babel/runtime" "^7.18.3"
complex.js "^2.1.1"
decimal.js "^10.3.1"
escape-latex "^1.2.0"
fraction.js "^4.2.0"
javascript-natural-sort "^0.7.1"
seedrandom "^3.0.5"
tiny-emitter "^2.1.0"
typed-function "^2.1.0"
minimist@^1.2.0:
version "1.2.6"
resolved "https://registry.yarnpkg.com/minimist/-/minimist-1.2.6.tgz#8637a5b759ea0d6e98702cfb3a9283323c93af44"
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ms@2.0.0:
version "2.0.0"
resolved "https://registry.yarnpkg.com/ms/-/ms-2.0.0.tgz#5608aeadfc00be6c2901df5f9861788de0d597c8"
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pdfast@^0.2.0:
version "0.2.0"
resolved "https://registry.yarnpkg.com/pdfast/-/pdfast-0.2.0.tgz#8cbc556e1bf2522177787c0de2e0d4373ba885c9"
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process-nextick-args@~2.0.0:
version "2.0.1"
resolved "https://registry.yarnpkg.com/process-nextick-args/-/process-nextick-args-2.0.1.tgz#7820d9b16120cc55ca9ae7792680ae7dba6d7fe2"
integrity sha512-3ouUOpQhtgrbOa17J7+uxOTpITYWaGP7/AhoR3+A+/1e9skrzelGi/dXzEYyvbxubEF6Wn2ypscTKiKJFFn1ag==
readable-stream@^2.1.4:
version "2.3.7"
resolved "https://registry.yarnpkg.com/readable-stream/-/readable-stream-2.3.7.tgz#1eca1cf711aef814c04f62252a36a62f6cb23b57"
integrity sha512-Ebho8K4jIbHAxnuxi7o42OrZgF/ZTNcsZj6nRKyUmkhLFq8CHItp/fy6hQZuZmP/n3yZ9VBUbp4zz/mX8hmYPw==
dependencies:
core-util-is "~1.0.0"
inherits "~2.0.3"
isarray "~1.0.0"
process-nextick-args "~2.0.0"
safe-buffer "~5.1.1"
string_decoder "~1.1.1"
util-deprecate "~1.0.1"
regenerator-runtime@^0.13.4:
version "0.13.9"
resolved "https://registry.yarnpkg.com/regenerator-runtime/-/regenerator-runtime-0.13.9.tgz#8925742a98ffd90814988d7566ad30ca3b263b52"
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rescript@^9.1.4:
version "9.1.4"
resolved "https://registry.yarnpkg.com/rescript/-/rescript-9.1.4.tgz#1eb126f98d6c16942c0bf0df67c050198e580515"
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safe-buffer@~5.1.0, safe-buffer@~5.1.1:
version "5.1.2"
resolved "https://registry.yarnpkg.com/safe-buffer/-/safe-buffer-5.1.2.tgz#991ec69d296e0313747d59bdfd2b745c35f8828d"
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seedrandom@^3.0.5:
version "3.0.5"
resolved "https://registry.yarnpkg.com/seedrandom/-/seedrandom-3.0.5.tgz#54edc85c95222525b0c7a6f6b3543d8e0b3aa0a7"
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string_decoder@~1.1.1:
version "1.1.1"
resolved "https://registry.yarnpkg.com/string_decoder/-/string_decoder-1.1.1.tgz#9cf1611ba62685d7030ae9e4ba34149c3af03fc8"
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dependencies:
safe-buffer "~5.1.0"
tiny-emitter@^2.1.0:
version "2.1.0"
resolved "https://registry.yarnpkg.com/tiny-emitter/-/tiny-emitter-2.1.0.tgz#1d1a56edfc51c43e863cbb5382a72330e3555423"
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typed-function@^2.1.0:
version "2.1.0"
resolved "https://registry.yarnpkg.com/typed-function/-/typed-function-2.1.0.tgz#ded6f8a442ba8749ff3fe75bc41419c8d46ccc3f"
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util-deprecate@~1.0.1:
version "1.0.2"
resolved "https://registry.yarnpkg.com/util-deprecate/-/util-deprecate-1.0.2.tgz#450d4dc9fa70de732762fbd2d4a28981419a0ccf"
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