biofriction-wp-theme/node_modules/webpack/lib/util/deterministicGrouping.js

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2021-10-26 14:18:09 +02:00
/*
MIT License http://www.opensource.org/licenses/mit-license.php
Author Tobias Koppers @sokra
*/
"use strict";
// Simulations show these probabilities for a single change
// 93.1% that one group is invalidated
// 4.8% that two groups are invalidated
// 1.1% that 3 groups are invalidated
// 0.1% that 4 or more groups are invalidated
//
// And these for removing/adding 10 lexically adjacent files
// 64.5% that one group is invalidated
// 24.8% that two groups are invalidated
// 7.8% that 3 groups are invalidated
// 2.7% that 4 or more groups are invalidated
//
// And these for removing/adding 3 random files
// 0% that one group is invalidated
// 3.7% that two groups are invalidated
// 80.8% that 3 groups are invalidated
// 12.3% that 4 groups are invalidated
// 3.2% that 5 or more groups are invalidated
/**
*
* @param {string} a key
* @param {string} b key
* @returns {number} the similarity as number
*/
const similarity = (a, b) => {
const l = Math.min(a.length, b.length);
let dist = 0;
for (let i = 0; i < l; i++) {
const ca = a.charCodeAt(i);
const cb = b.charCodeAt(i);
dist += Math.max(0, 10 - Math.abs(ca - cb));
}
return dist;
};
/**
* @param {string} a key
* @param {string} b key
* @param {Set<string>} usedNames set of already used names
* @returns {string} the common part and a single char for the difference
*/
const getName = (a, b, usedNames) => {
const l = Math.min(a.length, b.length);
let i = 0;
while (i < l) {
if (a.charCodeAt(i) !== b.charCodeAt(i)) {
i++;
break;
}
i++;
}
while (i < l) {
const name = a.slice(0, i);
const lowerName = name.toLowerCase();
if (!usedNames.has(lowerName)) {
usedNames.add(lowerName);
return name;
}
i++;
}
// names always contain a hash, so this is always unique
// we don't need to check usedNames nor add it
return a;
};
/**
* @param {Record<string, number>} total total size
* @param {Record<string, number>} size single size
* @returns {void}
*/
const addSizeTo = (total, size) => {
for (const key of Object.keys(size)) {
total[key] = (total[key] || 0) + size[key];
}
};
/**
* @param {Record<string, number>} total total size
* @param {Record<string, number>} size single size
* @returns {void}
*/
const subtractSizeFrom = (total, size) => {
for (const key of Object.keys(size)) {
total[key] -= size[key];
}
};
/**
* @param {Iterable<Node>} nodes some nodes
* @returns {Record<string, number>} total size
*/
const sumSize = nodes => {
const sum = Object.create(null);
for (const node of nodes) {
addSizeTo(sum, node.size);
}
return sum;
};
const isTooBig = (size, maxSize) => {
for (const key of Object.keys(size)) {
const s = size[key];
if (s === 0) continue;
const maxSizeValue = maxSize[key];
if (typeof maxSizeValue === "number") {
if (s > maxSizeValue) return true;
}
}
return false;
};
const isTooSmall = (size, minSize) => {
for (const key of Object.keys(size)) {
const s = size[key];
if (s === 0) continue;
const minSizeValue = minSize[key];
if (typeof minSizeValue === "number") {
if (s < minSizeValue) return true;
}
}
return false;
};
const getTooSmallTypes = (size, minSize) => {
const types = new Set();
for (const key of Object.keys(size)) {
const s = size[key];
if (s === 0) continue;
const minSizeValue = minSize[key];
if (typeof minSizeValue === "number") {
if (s < minSizeValue) types.add(key);
}
}
return types;
};
const getNumberOfMatchingSizeTypes = (size, types) => {
let i = 0;
for (const key of Object.keys(size)) {
if (size[key] !== 0 && types.has(key)) i++;
}
return i;
};
const selectiveSizeSum = (size, types) => {
let sum = 0;
for (const key of Object.keys(size)) {
if (size[key] !== 0 && types.has(key)) sum += size[key];
}
return sum;
};
/**
* @template T
*/
class Node {
/**
* @param {T} item item
* @param {string} key key
* @param {Record<string, number>} size size
*/
constructor(item, key, size) {
this.item = item;
this.key = key;
this.size = size;
}
}
/**
* @template T
*/
class Group {
/**
* @param {Node<T>[]} nodes nodes
* @param {number[]} similarities similarities between the nodes (length = nodes.length - 1)
* @param {Record<string, number>=} size size of the group
*/
constructor(nodes, similarities, size) {
this.nodes = nodes;
this.similarities = similarities;
this.size = size || sumSize(nodes);
/** @type {string} */
this.key = undefined;
}
/**
* @param {function(Node): boolean} filter filter function
* @returns {Node[]} removed nodes
*/
popNodes(filter) {
const newNodes = [];
const newSimilarities = [];
const resultNodes = [];
let lastNode;
for (let i = 0; i < this.nodes.length; i++) {
const node = this.nodes[i];
if (filter(node)) {
resultNodes.push(node);
} else {
if (newNodes.length > 0) {
newSimilarities.push(
lastNode === this.nodes[i - 1]
? this.similarities[i - 1]
: similarity(lastNode.key, node.key)
);
}
newNodes.push(node);
lastNode = node;
}
}
this.nodes = newNodes;
this.similarities = newSimilarities;
this.size = sumSize(newNodes);
return resultNodes;
}
}
/**
* @param {Iterable<Node>} nodes nodes
* @returns {number[]} similarities
*/
const getSimilarities = nodes => {
// calculate similarities between lexically adjacent nodes
/** @type {number[]} */
const similarities = [];
let last = undefined;
for (const node of nodes) {
if (last !== undefined) {
similarities.push(similarity(last.key, node.key));
}
last = node;
}
return similarities;
};
/**
* @template T
* @typedef {Object} GroupedItems<T>
* @property {string} key
* @property {T[]} items
* @property {Record<string, number>} size
*/
/**
* @template T
* @typedef {Object} Options
* @property {Record<string, number>} maxSize maximum size of a group
* @property {Record<string, number>} minSize minimum size of a group (preferred over maximum size)
* @property {Iterable<T>} items a list of items
* @property {function(T): Record<string, number>} getSize function to get size of an item
* @property {function(T): string} getKey function to get the key of an item
*/
/**
* @template T
* @param {Options<T>} options options object
* @returns {GroupedItems<T>[]} grouped items
*/
module.exports = ({ maxSize, minSize, items, getSize, getKey }) => {
/** @type {Group<T>[]} */
const result = [];
const nodes = Array.from(
items,
item => new Node(item, getKey(item), getSize(item))
);
/** @type {Node<T>[]} */
const initialNodes = [];
// lexically ordering of keys
nodes.sort((a, b) => {
if (a.key < b.key) return -1;
if (a.key > b.key) return 1;
return 0;
});
// return nodes bigger than maxSize directly as group
// But make sure that minSize is not violated
for (const node of nodes) {
if (isTooBig(node.size, maxSize) && !isTooSmall(node.size, minSize)) {
result.push(new Group([node], []));
} else {
initialNodes.push(node);
}
}
if (initialNodes.length > 0) {
const initialGroup = new Group(initialNodes, getSimilarities(initialNodes));
const removeProblematicNodes = group => {
const problemTypes = getTooSmallTypes(group.size, minSize);
if (problemTypes.size > 0) {
// We hit an edge case where the working set is already smaller than minSize
// We merge problematic nodes with the smallest result node to keep minSize intact
const problemNodes = group.popNodes(
n => getNumberOfMatchingSizeTypes(n.size, problemTypes) > 0
);
// Only merge it with result nodes that have the problematic size type
const possibleResultGroups = result.filter(
n => getNumberOfMatchingSizeTypes(n.size, problemTypes) > 0
);
if (possibleResultGroups.length > 0) {
const bestGroup = possibleResultGroups.reduce((min, group) => {
const minMatches = getNumberOfMatchingSizeTypes(min, problemTypes);
const groupMatches = getNumberOfMatchingSizeTypes(
group,
problemTypes
);
if (minMatches !== groupMatches)
return minMatches < groupMatches ? group : min;
if (
selectiveSizeSum(min.size, problemTypes) >
selectiveSizeSum(group.size, problemTypes)
)
return group;
return min;
});
for (const node of problemNodes) bestGroup.nodes.push(node);
bestGroup.nodes.sort((a, b) => {
if (a.key < b.key) return -1;
if (a.key > b.key) return 1;
return 0;
});
} else {
// There are no other nodes with the same size types
// We create a new group and have to accept that it's smaller than minSize
result.push(new Group(problemNodes, null));
}
return true;
} else {
return false;
}
};
if (initialGroup.nodes.length > 0) {
const queue = [initialGroup];
while (queue.length) {
const group = queue.pop();
// only groups bigger than maxSize need to be splitted
if (!isTooBig(group.size, maxSize)) {
result.push(group);
continue;
}
// If the group is already too small
// we try to work only with the unproblematic nodes
if (removeProblematicNodes(group)) {
// This changed something, so we try this group again
queue.push(group);
continue;
}
// find unsplittable area from left and right
// going minSize from left and right
// at least one node need to be included otherwise we get stuck
let left = 1;
let leftSize = Object.create(null);
addSizeTo(leftSize, group.nodes[0].size);
while (left < group.nodes.length && isTooSmall(leftSize, minSize)) {
addSizeTo(leftSize, group.nodes[left].size);
left++;
}
let right = group.nodes.length - 2;
let rightSize = Object.create(null);
addSizeTo(rightSize, group.nodes[group.nodes.length - 1].size);
while (right >= 0 && isTooSmall(rightSize, minSize)) {
addSizeTo(rightSize, group.nodes[right].size);
right--;
}
if (left - 1 > right) {
// can't split group while holding minSize
// because minSize is preferred of maxSize we return
// the problematic nodes as result here even while it's too big
// To avoid this make sure maxSize > minSize * 3
result.push(group);
continue;
}
if (left <= right) {
// when there is a area between left and right
// we look for best split point
// we split at the minimum similarity
// here key space is separated the most
// But we also need to make sure to not create too small groups
let best = -1;
let bestSimilarity = Infinity;
let pos = left;
let rightSize = sumSize(group.nodes.slice(pos));
while (pos <= right) {
const similarity = group.similarities[pos - 1];
if (
similarity < bestSimilarity &&
!isTooSmall(leftSize, minSize) &&
!isTooSmall(rightSize, minSize)
) {
best = pos;
bestSimilarity = similarity;
}
addSizeTo(leftSize, group.nodes[pos].size);
subtractSizeFrom(rightSize, group.nodes[pos].size);
pos++;
}
if (best < 0) {
// can't split group while holding minSize
result.push(group);
continue;
}
left = best;
right = best - 1;
}
// create two new groups for left and right area
// and queue them up
const rightNodes = [group.nodes[right + 1]];
/** @type {number[]} */
const rightSimilarities = [];
for (let i = right + 2; i < group.nodes.length; i++) {
rightSimilarities.push(group.similarities[i - 1]);
rightNodes.push(group.nodes[i]);
}
queue.push(new Group(rightNodes, rightSimilarities));
const leftNodes = [group.nodes[0]];
/** @type {number[]} */
const leftSimilarities = [];
for (let i = 1; i < left; i++) {
leftSimilarities.push(group.similarities[i - 1]);
leftNodes.push(group.nodes[i]);
}
queue.push(new Group(leftNodes, leftSimilarities));
}
}
}
// lexically ordering
result.sort((a, b) => {
if (a.nodes[0].key < b.nodes[0].key) return -1;
if (a.nodes[0].key > b.nodes[0].key) return 1;
return 0;
});
// give every group a name
const usedNames = new Set();
for (let i = 0; i < result.length; i++) {
const group = result[i];
if (group.nodes.length === 1) {
group.key = group.nodes[0].key;
} else {
const first = group.nodes[0];
const last = group.nodes[group.nodes.length - 1];
const name = getName(first.key, last.key, usedNames);
group.key = name;
}
}
// return the results
return result.map(group => {
/** @type {GroupedItems} */
return {
key: group.key,
items: group.nodes.map(node => node.item),
size: group.size
};
});
};