@jbrowse/core/esm/data_adapters/BaseAdapter/stats.js

JBrowse 2 core libraries used by plugins

import { firstValueFrom } from 'rxjs';
import { toArray } from 'rxjs/operators';
import { max, min, sum } from "../../util/index.js";
import { rectifyStats } from "../../util/stats.js";
const DENSITY_SAMPLE_INITIAL_INTERVAL = 1000;
const DENSITY_SAMPLE_MIN_FEATURES = 70;
const DENSITY_SAMPLE_TIMEOUT_MS = 5000;
export function aggregateQuantitativeStats(stats) {
    const meanMins = stats.map(s => s.scoreMeanMin).filter(s => s !== undefined);
    const meanMaxs = stats.map(s => s.scoreMeanMax).filter(s => s !== undefined);
    return rectifyStats({
        scoreMax: max(stats.map(s => s.scoreMax)),
        scoreMin: min(stats.map(s => s.scoreMin)),
        scoreSum: sum(stats.map(s => s.scoreSum)),
        scoreSumSquares: sum(stats.map(s => s.scoreSumSquares)),
        featureCount: sum(stats.map(s => s.featureCount)),
        basesCovered: sum(stats.map(s => s.basesCovered)),
        ...(meanMins.length > 0 ? { scoreMeanMin: min(meanMins) } : {}),
        ...(meanMaxs.length > 0 ? { scoreMeanMax: max(meanMaxs) } : {}),
    });
}
export function sampleFeaturesForInterval(region, interval, getFeatures, opts) {
    const { start, end } = region;
    const sampleCenter = start * 0.75 + end * 0.25;
    return firstValueFrom(getFeatures({
        ...region,
        start: Math.max(0, Math.round(sampleCenter - interval / 2)),
        end: Math.min(Math.round(sampleCenter + interval / 2), end),
    }, opts).pipe(toArray()));
}
export async function calculateFeatureDensityStats(region, getFeatures, opts) {
    const refLen = region.end - region.start;
    let interval = DENSITY_SAMPLE_INITIAL_INTERVAL;
    let expansionTime = 0;
    let lastTime = performance.now();
    while (true) {
        const features = await sampleFeaturesForInterval(region, interval, getFeatures, opts);
        const featureCount = features.length;
        if (featureCount >= DENSITY_SAMPLE_MIN_FEATURES || interval * 2 > refLen) {
            return { featureDensity: featureCount / interval };
        }
        if (expansionTime > DENSITY_SAMPLE_TIMEOUT_MS) {
            console.warn("Stats estimation reached timeout, or didn't get enough features");
            return { featureDensity: Number.POSITIVE_INFINITY };
        }
        const currTime = performance.now();
        expansionTime += currTime - lastTime;
        lastTime = currTime;
        interval *= 2;
    }
}
export { blankStats } from "../../util/stats.js";