2020-06-23 00:09:42 +05:30
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import { uniqWith, isEqual } from 'lodash';
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/*
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The following functions are the main engine in transforming the data as
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received from the endpoint into the format the d3 graph expects.
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Input is of the form:
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2020-10-24 23:57:45 +05:30
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[nodes]
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nodes: [{category, name, jobs, size}]
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category is the stage name
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name is a group name; in the case that the group has one job, it is
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also the job name
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size is the number of parallel jobs
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jobs: [{ name, needs}]
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job name is either the same as the group name or group x/y
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needs: [job-names]
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needs is an array of job-name strings
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2020-06-23 00:09:42 +05:30
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Output is of the form:
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{ nodes: [node], links: [link] }
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node: { name, category }, + unused info passed through
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link: { source, target, value }, with source & target being node names
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and value being a constant
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2020-10-24 23:57:45 +05:30
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We create nodes in the GraphQL update function, and then here we create the node dictionary,
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then create links, and then dedupe the links, so that in the case where
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2020-06-23 00:09:42 +05:30
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job 4 depends on job 1 and job 2, and job 2 depends on job 1, we show only a single link
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from job 1 to job 2 then another from job 2 to job 4.
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CREATE LINKS
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2020-10-24 23:57:45 +05:30
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nodes.name -> target
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nodes.name.needs.each -> source (source is the name of the group, not the parallel job)
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2020-06-23 00:09:42 +05:30
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10 -> value (constant)
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*/
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export const createNodeDict = nodes => {
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return nodes.reduce((acc, node) => {
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const newNode = {
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...node,
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needs: node.jobs.map(job => job.needs || []).flat(),
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};
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if (node.size > 1) {
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node.jobs.forEach(job => {
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acc[job.name] = newNode;
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});
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}
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acc[node.name] = newNode;
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return acc;
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}, {});
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};
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export const makeLinksFromNodes = (nodes, nodeDict) => {
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const constantLinkValue = 10; // all links are the same weight
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return nodes
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.map(group => {
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return group.jobs.map(job => {
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if (!job.needs) {
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return [];
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}
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return job.needs.map(needed => {
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return {
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source: nodeDict[needed]?.name,
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target: group.name,
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value: constantLinkValue,
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};
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});
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});
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})
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.flat(2);
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};
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export const getAllAncestors = (nodes, nodeDict) => {
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const needs = nodes
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.map(node => {
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return nodeDict[node].needs || '';
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})
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.flat()
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.filter(Boolean);
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if (needs.length) {
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return [...needs, ...getAllAncestors(needs, nodeDict)];
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}
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return [];
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};
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export const filterByAncestors = (links, nodeDict) =>
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links.filter(({ target, source }) => {
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/*
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for every link, check out it's target
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for every target, get the target node's needs
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then drop the current link source from that list
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call a function to get all ancestors, recursively
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is the current link's source in the list of all parents?
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then we drop this link
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*/
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const targetNode = target;
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const targetNodeNeeds = nodeDict[targetNode].needs;
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const targetNodeNeedsMinusSource = targetNodeNeeds.filter(need => need !== source);
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const allAncestors = getAllAncestors(targetNodeNeedsMinusSource, nodeDict);
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return !allAncestors.includes(source);
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});
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2020-10-24 23:57:45 +05:30
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export const parseData = nodes => {
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const nodeDict = createNodeDict(nodes);
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2020-06-23 00:09:42 +05:30
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const allLinks = makeLinksFromNodes(nodes, nodeDict);
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const filteredLinks = filterByAncestors(allLinks, nodeDict);
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const links = uniqWith(filteredLinks, isEqual);
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return { nodes, links };
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};
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/*
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The number of nodes in the most populous generation drives the height of the graph.
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*/
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export const getMaxNodes = nodes => {
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const counts = nodes.reduce((acc, { layer }) => {
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if (!acc[layer]) {
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acc[layer] = 0;
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}
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acc[layer] += 1;
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return acc;
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}, []);
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return Math.max(...counts);
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};
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/*
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Because we cannot know if a node is part of a relationship until after we
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generate the links with createSankey, this function is used after the first call
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to find nodes that have no relations.
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*/
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export const removeOrphanNodes = sankeyfiedNodes => {
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return sankeyfiedNodes.filter(node => node.sourceLinks.length || node.targetLinks.length);
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};
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