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import type {PlotOptions, ProcessOptions, TermEntry} from './analysisMenu'
import {useContext, useEffect, useState} from 'react'
import {getProcessedTerm} from './processTerms'
import type {FixedTerm, NetworkLookup} from './term'
import {ResourceContext} from './resources'
import {BuildContext, type NumberObject} from './building'
import {timers} from './addedTerms'
import type {DictEntry} from './storage'
import dynamic from 'next/dynamic'
const Graph = dynamic(() => import('./graph'))
export function getIntersects(a: string, b: NetworkLookup) {
return {
lemma: +(a in b.lemma),
lemma_related: +(a in b.lemma_related),
lemma_synset: +(a in b.lemma_synset),
related: +(a in b.related),
related_lemma: +(a in b.related_lemma),
related_related: +(a in b.related_related),
related_synset: +(a in b.related_synset),
synset: +(a in b.synset),
synset_lemma: +(a in b.synset_lemma),
synset_related: +(a in b.synset_related),
synset_synset: +(a in b.synset_synset),
}
}
function getSimilarity(a: TermEntry, b: TermEntry, dense: boolean) {
Iif (!b.processed) return 0
const sim = getIntersects(a.term, b.processed.lookup)
return dense
? 0.35 * sim.lemma +
0.1 * sim.lemma_related +
0.001 * sim.lemma_synset +
0.25 * sim.related +
0.1 * sim.related_lemma +
0.001 * sim.related_related +
0.001 * sim.related_synset +
0.001 * sim.synset +
0.001 * sim.synset_lemma +
0.001 * sim.synset_related +
0.001 * sim.synset_synset
: 0.35 * sim.lemma + 0.25 * sim.related + 0.001 * sim.synset
}
export type Edge = {
source: string
target: string
value: number
lineStyle: {width: number; opacity: number}
}
export type Node = {
x: number
y: number
category: string | string[]
host: string
name: string
value: number
prop: number
symbolSize: number
itemStyle: {
opacity: number
}
label: {
show: boolean
}
}
async function processComparisons(
i: number,
terms: {[index: string]: TermEntry},
edges: Edge[],
record: {[index: string]: boolean},
catCounts: NumberObject,
progress: (progress: number[]) => void,
finish: (data: {edges: Edge[]; nodes: Node[]}) => void,
options: ProcessOptions
) {
clearTimeout(timers.comparisons)
const termKeys = Object.keys(terms)
const n = termKeys.length
for (let step = 0; i < n && step < 100; step++, i++) {
const term = terms[termKeys[i]]
term.processed.lookup.map.forEach((_, child) => {
const key = term.term + '.' + child
const rkey = child + '.' + term.term
if (term.term !== child && !(key in record) && !(rkey in record) && child in terms) {
record[key] = record[rkey] = true
const value = getSimilarity(term, terms[child], options.dense)
if (value > options.min_sim)
edges.push({
source: term.term,
target: child,
value: value,
lineStyle: {width: 0.3 + value * 2, opacity: 0.35},
})
}
})
}
progress([i, n])
if (i < n) {
timers.comparisons = setTimeout(
() => processComparisons(i, terms, edges, record, catCounts, progress, finish, options),
0
)
} else {
setTimeout(() => {
const nodeIndices: {[index: string]: number} = {}
const nodes: Node[] = Object.values(terms).map((term, index) => {
nodeIndices[term.term] = index
return {
x: Math.random() * window.innerWidth,
y: Math.random() * window.innerHeight,
host: term.host || '',
category: Object.keys(term.categories).sort((a, b) => catCounts[a] - catCounts[b]),
name: term.term,
prop: 1,
value: 0,
symbolSize: 10,
itemStyle: {
opacity: 1,
},
label: {
show: true,
},
}
})
edges.forEach(edge => {
nodes[nodeIndices[edge.source]].value += edge.value
nodes[nodeIndices[edge.target]].value += edge.value
})
let max = 0
nodes.forEach(({value}) => {
if (value > max) max = value
})
finish({
edges,
nodes: nodes.map(node => {
node.prop = node.value / max
node.itemStyle = {opacity: 0.6 + node.prop * 0.4}
return node
}),
})
}, 0)
}
}
export default function Results({
allTerms,
catCounts,
selectedCategories,
options,
plotOptions,
}: {
allTerms: Map<string, DictEntry>
catCounts: NumberObject
selectedCategories: string[]
options: ProcessOptions
plotOptions: PlotOptions
}) {
const data = useContext(ResourceContext)
const dict = useContext(BuildContext)
const [network, setNetwork] = useState<{edges: Edge[]; nodes: Node[]}>({edges: [], nodes: []})
const [progress, setProgress] = useState([0, 0])
useEffect(() => {
const selectedMap = new Map(selectedCategories.map((cat, index) => [index, cat]))
const terms: {[index: string]: TermEntry} = {}
allTerms.forEach((entry, term) => {
let keep = false
const cats: {[index: string]: number} = {}
selectedMap.forEach(cat => {
if (cat in entry.categories || (cat === 'no categories' && !Object.keys(entry.categories).length)) {
keep = true
cats[cat] = entry.categories[cat]
}
})
if (keep) {
const processed = getProcessedTerm(term, data, dict, true)
Iif (processed.type === 'fixed') {
if (!(term in terms)) {
terms[term] = {term, categories: cats, processed}
}
} else if (options.include_fuzzy) {
processed.matches.forEach(match => {
Eif (!(match in dict) && !(match in terms)) {
terms[match] = {
host: term,
term: match,
categories: cats,
processed: getProcessedTerm(match, data, {}, true) as FixedTerm,
}
}
})
}
}
})
const record: {[index: string]: boolean} = {}
const edges: Edge[] = []
processComparisons(0, terms, edges, record, catCounts, setProgress, setNetwork, options)
}, [dict, data, options, selectedCategories, allTerms, catCounts])
return progress[0] < progress[1] ? (
<Box sx={{position: 'relative', width: '100%', height: '100%'}}>
<Box
sx={{
display: 'flex',
position: 'absolute',
top: 0,
right: 0,
bottom: 0,
left: 0,
alignItems: 'center',
justifyContent: 'center',
textAlign: 'center',
}}
>
<Stack>
<Typography variant="h5">Calculating Pairwise Similarities</Typography>
<LinearProgress variant="determinate" value={(progress[0] / progress[1]) * 100} />
<Typography variant="caption">{progress[0] + ' / ' + progress[1]}</Typography>
</Stack>
</Box>
</Box>
) : (
<Box sx={{position: 'relative', width: '100%', height: '100%'}}>
<Graph allNodes={network.nodes} edges={network.edges} options={plotOptions} />
</Box>
)
}
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