@bunchmark/presentation - npm Package Compare versions

Comparing version 1.0.0-pre-11 to 1.0.0-pre-12

package.json

 {
     "name": "@bunchmark/presentation",
-    "version": "1.0.0-pre-11",
+    "version": "1.0.0-pre-12",
     "description": "The Bunchmark data presentation utilities",
@@ -5,0 +5,0 @@ "type": "module",

src/bins.js

@@ -5,60 +5,60 @@ export {getBins, getBounds, QNDMedian}
 const QNDMedian = ary => {
-  ary.sort((a,b)=>{a-b})
-  if (ary.length % 2) return ary[(ary.length - 1)/2]
-  else return (ary[(ary.length)/2-1] + ary[(ary.length)/2])/2
+	ary.sort((a,b)=>{a-b})
+	if (ary.length % 2) return ary[(ary.length - 1)/2]
+	else return (ary[(ary.length)/2-1] + ary[(ary.length)/2])/2
 }
 const {
-  exp: mexp,
-  floor: mfloor, 
-  log: mlog, 
-  max: mmax,
-  min: mmin, 
-  round: mround,
+	exp: mexp,
+	floor: mfloor,
+	log: mlog,
+	max: mmax,
+	min: mmin,
+	round: mround,
 } = Math
 
 function getBounds(entries) {
-  const min = mmin(...entries.map(e => mmin(...e.workspace)))
-  const max = mmax(...entries.map(e => mmax(...e.workspace)))
-  return {min, max}
+	const min = mmin(...entries.map(e => mmin(...e.workspace)))
+	const max = mmax(...entries.map(e => mmax(...e.workspace)))
+	return {min, max}
 }
 
 function getBins(entries, quantiles, maxN) {
-  const {max, min} = getBounds(entries)
-  let minHamBound = 1/0
-  let maxHamBound = -1/0
-  let largestIQR = -1/0
-  quantiles.forEach(q => {
-    // find the non-outlier bounds using the IQR
-    // method. Given the data distribution,
-    // we work in log space as we do for the rest.
-    const lq1 = mlog(q.q1)
-    const lq3 = mlog(q.q3)
-    const logIQR = lq3 - lq1
-    
-    largestIQR = mmax(logIQR, largestIQR)
-    const scaleFactor = 1.75
-    minHamBound = mmin(minHamBound, mexp(lq1 - scaleFactor * logIQR))
-    maxHamBound = mmax(maxHamBound, mexp(lq3 + scaleFactor * logIQR))
-  })
-  const N = entries[0].workspace.length
-  // one bin per 10 points in the IQR
-  // (half of N are, per the IQR definition)
-  const binWidth = largestIQR / mmax(N / 2 / 10, 1)
-  const span = mlog(maxHamBound)-mlog(minHamBound)
-  const numBins = mmin(span / binWidth, maxN)
+	const {max, min} = getBounds(entries)
+	let minHamBound = 1/0
+	let maxHamBound = -1/0
+	let largestIQR = -1/0
+	quantiles.forEach(q => {
+		// find the non-outlier bounds using the IQR
+		// method. Given the data distribution,
+		// we work in log space as we do for the rest.
+		const lq1 = mlog(q.q1)
+		const lq3 = mlog(q.q3)
+		const logIQR = lq3 - lq1
 
-  return addBins(
-    entries,
-    mround(numBins),
-    // gradually shift from the whole data set
-    // to only the non-spam data points.
-    interpolate(min, minHamBound, N, 30),
-    interpolate(max, maxHamBound, N, 30),
-  )
+		largestIQR = mmax(logIQR, largestIQR)
+		const scaleFactor = 1.75
+		minHamBound = mmin(minHamBound, mexp(lq1 - scaleFactor * logIQR))
+		maxHamBound = mmax(maxHamBound, mexp(lq3 + scaleFactor * logIQR))
+	})
+	const N = entries[0].workspace.length
+	// one bin per 10 points in the IQR
+	// (half of N are, per the IQR definition)
+	const binWidth = largestIQR / mmax(N / 2 / 10, 1)
+	const span = mlog(maxHamBound)-mlog(minHamBound)
+	const numBins = mmin(span / binWidth, maxN)
+
+	return addBins(
+		entries,
+		mround(numBins),
+		// gradually shift from the whole data set
+		// to only the non-spam data points.
+		interpolate(min, minHamBound, N, 30),
+		interpolate(max, maxHamBound, N, 30),
+	)
 }
 
 function interpolate(exact, ham, n, max) {
-  n = mmin(n, max)
-  p = n/max
-  return (1 - p) * exact + p * ham
+	n = mmin(n, max)
+	p = n/max
+	return (1 - p) * exact + p * ham
 }
@@ -68,30 +68,30 @@
 function addBins(entries, N, min, max) {
-  const bounds = Array.from({length: N})
-  const mul = (max/min)**(1/N)
-  const amplitude = min - max
-  let from = min
-  for (let i = 0; i < N; i++) {
-    bounds[i] = {from, to : (from *= mul)}
-  }
+	const bounds = Array.from({length: N})
+	const mul = (max/min)**(1/N)
+	const amplitude = min - max
+	let from = min
+	for (let i = 0; i < N; i++) {
+		bounds[i] = {from, to : (from *= mul)}
+	}
 
-  const result = {
-    min, max, N, bounds,
-    bins: Array.from(
-      entries, 
-      e => bounds.map(
-        ({from, to}, i) => {
+	const result = {
+		min, max, N, bounds,
+		bins: Array.from(
+			entries,
+			e => bounds.map(
+				({from, to}, i) => {
 
-          return e.workspace.reduce((acc, res) => acc + (from < res && res <= to), 0)
-        }
-      )
-    ),
-    bins2: Array.from(entries, ()=>Array.from(bounds, ()=>0))
-  }
+					return e.workspace.reduce((acc, res) => acc + (from < res && res <= to), 0)
+				}
+			)
+		),
+		bins2: Array.from(entries, ()=>Array.from(bounds, ()=>0))
+	}
 
-  entries.forEach((e, i) => {
-    e.workspace.forEach(res => {
-      result.bins2[i][mfloor((res - min)/amplitude)]++
-    })
-  })
-  return result
+	entries.forEach((e, i) => {
+		e.workspace.forEach(res => {
+			result.bins2[i][mfloor((res - min)/amplitude)]++
+		})
+	})
+	return result
 }

src/timeline.js

@@ -43,3 +43,3 @@ export {makeTimelines}
     if (dotWidth > 1) {
-      p("B")
+      console.log("TODO: support low res data")
     } else {
@@ -46,0 +46,0 @@ const threshold = 1/dotWidth

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Worsened metrics

Total package byte prevSize

14289

decreased by-0.58%

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