Skip to content
New issue

Have a question about this project? Sign up for a free GitHub account to open an issue and contact its maintainers and the community.

Sign up for GitHub

By clicking “Sign up for GitHub”, you agree to our terms of service and privacy statement. We’ll occasionally send you account related emails.

Already on GitHub? Sign in to your account

Jump to bottom

Switch to data-driven percentiles #2962

Closed
wants to merge 2 commits into from
Closed

Switch to data-driven percentiles #2962

Show file tree
Hide file tree
Changes from all commits
Commits
Show all changes
2 commits
Select commit Hold shift + click to select a range
091e304
Switch to data-driven percentiles
francois-rozet Jul 21, 2023
2cc3e54
Sub-linear score search
francois-rozet Dec 6, 2023
File filter

Filter by extension

Filter by extension
Conversations
Failed to load comments.
Loading
Jump to
Jump to file
Failed to load files.
Loading
Diff view
Diff view
168 changes: 129 additions & 39 deletions src/calculateRank.js
View file
Open in desktop
Original file line number Diff line number Diff line change
@@ -1,12 +1,114 @@
function exponential_cdf(x) {
return 1 - 2 ** -x;
function searchSorted(arr, x) {
if (x < arr[0]) {
Copy link

Choose a reason for hiding this comment

The reason will be displayed to describe this comment to others. Learn more.

As the size of the list is small and constant, it may be interesting to use a dictionary instead of a list and a "complex" find algorithm ?

Copy link
Collaborator Author

Choose a reason for hiding this comment

The reason will be displayed to describe this comment to others. Learn more.

I am not sure how you would use a dictionary to find the index i for which arr[i - 1] <= x < arr[i].

return 0;
}

// arr[l] <= x < arr[r]
let l = 0;
let r = arr.length;
let m;

while (r - l > 1) {
m = Math.floor((l + r) / 2);

if (x < arr[m]) {
r = m;
} else {
l = m;
}
}

return r;
}

function log_normal_cdf(x) {
// approximation
return x / (1 + x);
function score(x, quantiles) {
const i = searchSorted(quantiles, x);

if (i == 0) {
return 0.0;
} else if (i == quantiles.length) {
return 1.0;
}

const a = quantiles[i - 1];
const b = quantiles[i];

return ((x - a) / (b - a) + i - 1) / (quantiles.length - 1);
}

const QUANTILES = {
commits: [
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 1, 1, 1, 2, 2, 3, 3,
4, 4, 5, 6, 7, 7, 8, 9, 10, 11, 12, 13, 15, 16, 17, 19, 20, 22, 23, 25, 27,
29, 31, 33, 35, 38, 40, 43, 45, 48, 51, 54, 57, 60, 64, 67, 71, 76, 80, 85,
89, 94, 99, 105, 111, 118, 125, 132, 140, 147, 155, 164, 173, 184, 195, 207,
220, 233, 249, 265, 284, 304, 326, 353, 380, 411, 451, 495, 545, 611, 691,
794, 933, 1195, 1704, 9722,
],
all_commits: [
0, 0, 0, 0, 2, 4, 8, 11, 15, 19, 23, 27, 32, 36, 41, 45, 50, 55, 60, 65, 71,
76, 82, 87, 93, 99, 105, 111, 117, 124, 131, 137, 145, 151, 159, 166, 174,
182, 190, 198, 207, 215, 225, 234, 244, 253, 264, 274, 285, 296, 306, 318,
330, 342, 355, 368, 382, 396, 409, 424, 440, 457, 475, 493, 512, 531, 551,
570, 593, 618, 643, 667, 695, 723, 752, 784, 815, 857, 893, 934, 984, 1037,
1094, 1152, 1217, 1289, 1379, 1475, 1576, 1696, 1851, 2023, 2232, 2480,
2835, 3242, 3885, 4868, 6614, 11801, 792319,
],
prs: [
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 1, 1,
1, 1, 1, 1, 1, 2, 2, 2, 2, 2, 3, 3, 3, 3, 4, 4, 4, 5, 5, 5, 6, 6, 6, 7, 7,
8, 8, 9, 10, 10, 11, 11, 12, 13, 14, 14, 15, 16, 17, 18, 19, 20, 21, 23, 24,
25, 27, 28, 30, 32, 34, 36, 38, 40, 43, 46, 50, 53, 57, 61, 65, 70, 76, 83,
90, 99, 110, 123, 139, 159, 185, 219, 273, 360, 562, 2291,
],
issues: [
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 2, 2, 2, 2, 2, 3, 3, 3, 3, 3,
4, 4, 4, 5, 5, 5, 6, 6, 6, 7, 7, 8, 8, 9, 10, 10, 11, 12, 12, 13, 14, 15,
16, 17, 19, 20, 21, 23, 24, 26, 28, 30, 32, 35, 38, 41, 45, 49, 54, 59, 66,
73, 82, 92, 106, 123, 150, 186, 255, 409, 1590,
],
reviews: [
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 1, 1, 1, 1, 1, 1, 2, 2, 3, 4, 5, 6, 8, 11, 15, 23, 36, 61,
129, 764,
],
repos: [
0, 0, 1, 2, 2, 3, 3, 4, 4, 5, 5, 6, 6, 6, 7, 7, 8, 8, 8, 9, 9, 10, 10, 11,
11, 12, 12, 12, 13, 13, 14, 14, 15, 15, 16, 16, 17, 17, 18, 18, 19, 19, 20,
20, 21, 21, 22, 22, 23, 24, 24, 25, 25, 26, 27, 28, 28, 29, 30, 30, 31, 32,
33, 34, 35, 36, 37, 38, 39, 40, 41, 42, 43, 45, 46, 47, 49, 50, 52, 54, 56,
58, 60, 62, 65, 68, 70, 74, 77, 82, 86, 92, 98, 105, 115, 127, 144, 170,
211, 316, 2002,
],
stars: [
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 1, 1, 1,
1, 1, 1, 1, 1, 2, 2, 2, 2, 2, 2, 2, 3, 3, 3, 3, 4, 4, 4, 4, 5, 5, 5, 6, 6,
7, 7, 8, 8, 9, 9, 10, 11, 11, 12, 13, 14, 15, 16, 17, 18, 19, 21, 22, 24,
26, 28, 30, 31, 33, 35, 38, 41, 44, 48, 52, 56, 61, 67, 74, 83, 93, 104,
117, 134, 154, 181, 215, 257, 321, 417, 565, 818, 1298, 2599, 18304,
],
followers: [
0, 0, 0, 0, 0, 0, 0, 1, 1, 1, 1, 1, 2, 2, 2, 2, 2, 3, 3, 3, 3, 4, 4, 4, 4,
5, 5, 5, 5, 6, 6, 6, 7, 7, 7, 8, 8, 8, 9, 9, 9, 10, 10, 10, 11, 11, 12, 12,
13, 13, 14, 14, 15, 15, 16, 16, 17, 18, 18, 19, 20, 20, 21, 22, 23, 24, 25,
26, 27, 28, 29, 30, 32, 33, 35, 36, 38, 40, 42, 44, 46, 49, 51, 54, 57, 61,
65, 70, 75, 81, 88, 97, 108, 121, 139, 161, 193, 240, 334, 569, 3583,
],
};

const WEIGHT = {
commits: 2.0,
prs: 3.0,
issues: 1.0,
reviews: 0.5,
repos: 0.0,
stars: 4.0,
followers: 1.0,
};

/**
* Calculates the users rank.
*
Expand All @@ -27,48 +129,36 @@ function calculateRank({
prs,
issues,
reviews,
// eslint-disable-next-line no-unused-vars
repos, // unused
repos,
stars,
followers,
}) {
const COMMITS_MEDIAN = all_commits ? 1000 : 250,
COMMITS_WEIGHT = 2;
const PRS_MEDIAN = 50,
PRS_WEIGHT = 3;
const ISSUES_MEDIAN = 25,
ISSUES_WEIGHT = 1;
const REVIEWS_MEDIAN = 2,
REVIEWS_WEIGHT = 1;
const STARS_MEDIAN = 50,
STARS_WEIGHT = 4;
const FOLLOWERS_MEDIAN = 10,
FOLLOWERS_WEIGHT = 1;

const TOTAL_WEIGHT =
COMMITS_WEIGHT +
PRS_WEIGHT +
ISSUES_WEIGHT +
REVIEWS_WEIGHT +
STARS_WEIGHT +
FOLLOWERS_WEIGHT;

const THRESHOLDS = [1, 12.5, 25, 37.5, 50, 62.5, 75, 87.5, 100];
const LEVELS = ["S", "A+", "A", "A-", "B+", "B", "B-", "C+", "C"];

const rank =
1 -
(COMMITS_WEIGHT * exponential_cdf(commits / COMMITS_MEDIAN) +
PRS_WEIGHT * exponential_cdf(prs / PRS_MEDIAN) +
ISSUES_WEIGHT * exponential_cdf(issues / ISSUES_MEDIAN) +
REVIEWS_WEIGHT * exponential_cdf(reviews / REVIEWS_MEDIAN) +
STARS_WEIGHT * log_normal_cdf(stars / STARS_MEDIAN) +
FOLLOWERS_WEIGHT * log_normal_cdf(followers / FOLLOWERS_MEDIAN)) /
TOTAL_WEIGHT;
const total_weight =
WEIGHT.commits +
WEIGHT.prs +
WEIGHT.issues +
WEIGHT.reviews +
WEIGHT.repos +
WEIGHT.stars +
WEIGHT.followers;

const total_score =
WEIGHT.commits *
score(commits, all_commits ? QUANTILES.all_commits : QUANTILES.commits) +
WEIGHT.prs * score(prs, QUANTILES.prs) +
WEIGHT.issues * score(issues, QUANTILES.issues) +
WEIGHT.reviews * score(reviews, QUANTILES.reviews) +
WEIGHT.repos * score(repos, QUANTILES.repos) +
WEIGHT.stars * score(stars, QUANTILES.stars) +
WEIGHT.followers * score(followers, QUANTILES.followers);

const level = LEVELS[THRESHOLDS.findIndex((t) => rank * 100 <= t)];
const percentile = 100 * (1 - total_score / total_weight);
const level = LEVELS[THRESHOLDS.findIndex((t) => percentile <= t)];

return { level, percentile: rank * 100 };
return { level, percentile };
}

export { calculateRank };
Expand Down
77 changes: 31 additions & 46 deletions tests/calculateRank.test.js
View file
Open in desktop
Original file line number Diff line number Diff line change
Expand Up @@ -3,7 +3,7 @@ import { calculateRank } from "../src/calculateRank.js";
import { expect, it, describe } from "@jest/globals";

describe("Test calculateRank", () => {
it("new user gets C rank", () => {
it("new user gets C+ rank", () => {
expect(
calculateRank({
all_commits: false,
Expand All @@ -15,82 +15,67 @@ describe("Test calculateRank", () => {
stars: 0,
followers: 0,
}),
).toStrictEqual({ level: "C", percentile: 100 });
).toStrictEqual({ level: "C+", percentile: 78.26086956521738 });
});

it("beginner user gets B- rank", () => {
it("beginner user gets B rank", () => {
expect(
calculateRank({
all_commits: false,
commits: 125,
prs: 25,
issues: 10,
reviews: 5,
repos: 0,
stars: 25,
commits: 50,
prs: 5,
issues: 5,
reviews: 0,
repos: 5,
stars: 5,
followers: 5,
}),
).toStrictEqual({ level: "B-", percentile: 65.02918514848255 });
).toStrictEqual({ level: "B", percentile: 51.97101449275363 });
});

it("median user gets B+ rank", () => {
it("advanced user gets A- rank", () => {
expect(
calculateRank({
all_commits: false,
commits: 250,
prs: 50,
prs: 25,
issues: 25,
reviews: 10,
repos: 0,
stars: 50,
followers: 10,
reviews: 0,
repos: 25,
stars: 25,
followers: 25,
}),
).toStrictEqual({ level: "B+", percentile: 46.09375 });
).toStrictEqual({ level: "A-", percentile: 27.07608695652174 });
});

it("average user gets B+ rank (include_all_commits)", () => {
it("advanced user gets A- rank (include_all_commits)", () => {
expect(
calculateRank({
all_commits: true,
commits: 1000,
prs: 50,
prs: 25,
issues: 25,
reviews: 10,
repos: 0,
stars: 50,
followers: 10,
reviews: 0,
repos: 25,
stars: 25,
followers: 25,
}),
).toStrictEqual({ level: "B+", percentile: 46.09375 });
).toStrictEqual({ level: "A-", percentile: 27.55619360131255 });
});

it("advanced user gets A rank", () => {
it("expert user gets A+ rank", () => {
expect(
calculateRank({
all_commits: false,
commits: 500,
prs: 100,
issues: 50,
reviews: 20,
repos: 0,
stars: 200,
followers: 40,
}),
).toStrictEqual({ level: "A", percentile: 20.841471354166664 });
});

it("expert user gets A+ rank", () => {
expect(
calculateRank({
all_commits: false,
commits: 1000,
prs: 200,
issues: 100,
reviews: 40,
repos: 0,
stars: 800,
followers: 160,
reviews: 0,
repos: 100,
stars: 100,
followers: 100,
}),
).toStrictEqual({ level: "A+", percentile: 5.575988339442828 });
).toStrictEqual({ level: "A+", percentile: 10.794579333709752 });
});

it("sindresorhus gets S rank", () => {
Expand All @@ -105,6 +90,6 @@ describe("Test calculateRank", () => {
stars: 600000,
followers: 50000,
}),
).toStrictEqual({ level: "S", percentile: 0.4578556547153667 });
).toStrictEqual({ level: "S", percentile: 0.4312953010223719 });
});
});
Loading