Analytics charts: translucent typical fill, last-week tail on week view

Render the seasonal typical estimate as a translucent muted fill (no
stroke, same 0.6 opacity as the data) instead of a grey line, on both day
and week views. Continue the fixed Monday-Monday week view with last
week's curve from the current bucket to the end of the week (secondary
accent, translucent fill), so the chart is useful early in the week and
last week is gradually replaced by the current one.

Gate the typical estimate on history spanning twice the view's full time
(third day / third week on) and the last-week tail on data reaching into
last week at all; the legend shows each entry only when present.
This commit is contained in:
2026-09-21 18:31:34 +00:00
parent 91a16f56c5
commit 6c0de19ae8
5 changed files with 105 additions and 35 deletions
+14 -3
View File
@@ -366,8 +366,17 @@ range is 10 so tiny values such as a single visit are not stretched to a
fractional scale). fractional scale).
The week range is aligned to Monday 00:00 UTC (the current week keeps the The week range is aligned to Monday 00:00 UTC (the current week keeps the
accent color and is truncated at the current bucket, never drawing fake accent color and is truncated at the current bucket, never drawing fake
zeroes for the future). Both the week and day views overlay a **"typical" zeroes for the future). Since the window is fixed Monday-to-Monday, **last
history curve** in the muted color (`analytics/seasonal.js`, a port of week's curve** continues the graph from the current bucket to the end of
the week in the secondary accent (`--accent2`, translucent fill like the
current week), so the chart shows useful data
on Monday too and last week is gradually replaced by the current week;
the tail is only drawn when the recorded data reaches into last week.
Both the week and day views overlay a **"typical"
history estimate** as a muted fill with no stroke, translucent to the same
degree as the current data — shown only once the history spans twice the
view's full time (from the third day on the day view, the third week on
the week view; `analytics/seasonal.js`, a port of
`seasonal.py`): the whole recorded history is densified to 5-minute bins, `seasonal.py`): the whole recorded history is densified to 5-minute bins,
smoothed with the same Gaussian as the week view, then folded onto a weekly smoothed with the same Gaussian as the week view, then folded onto a weekly
grid with exponential decay over age — a 7-day half-life for the average grid with exponential decay over age — a 7-day half-life for the average
@@ -381,7 +390,9 @@ estimate as "Typical week" (future included); the day view cuts the rolling
24-hour window's bins from the same estimate and labels them by the weekday 24-hour window's bins from the same estimate and labels them by the weekday
("Typical Saturday"). A compact legend inside the top right of the visits ("Typical Saturday"). A compact legend inside the top right of the visits
chart marks the current data in accent (ISO week label, or a bar specimen chart marks the current data in accent (ISO week label, or a bar specimen
for "Last 24 hours") and the typical curve on a muted specimen. The week for "Last 24 hours"), the previous week's tail on a secondary-accent line
specimen (week view only), and the typical estimate on a muted fill
specimen. The week
view's x labels are weekday names centered at midday UTC, without view's x labels are weekday names centered at midday UTC, without
vertical grid vertical grid
lines (day boundaries would be misleading in the viewer's timezone). The lines (day boundaries would be misleading in the viewer's timezone). The
+46 -16
View File
@@ -3,7 +3,7 @@
* Visitor and page-view smoothed curves for a single shared time range. * Visitor and page-view smoothed curves for a single shared time range.
*/ */
import { computed, onMounted, onUnmounted, ref } from 'vue' import { computed, onMounted, onUnmounted, ref } from 'vue'
import { makeSeries } from './analytics/time.js' import { DAY, WEEK, makeSeries } from './analytics/time.js'
import { typicalWeek, weekBinIndex } from './analytics/seasonal.js' import { typicalWeek, weekBinIndex } from './analytics/seasonal.js'
import { import {
CHART_H, CHART_H,
@@ -56,14 +56,17 @@ onUnmounted(() => {
/** /**
* Series for the current range plus, on the day and week views, the * Series for the current range plus, on the day and week views, the
* seasonal "typical week" history curve (all history up to now, already * seasonal "typical week" history estimate (all history up to now, already
* smoothed). Week view: the full Monday-first week. Day view: the rolling * smoothed). Week view: the full Monday-first week. Day view: the rolling
* window's bins looked up from the same estimate, labeled by the weekday. * window's bins looked up from the same estimate, labeled by the weekday.
* The estimate only appears once the recorded history spans twice the
* view's full time — from the third day / third week on.
*/ */
function withTypical(buckets) { function withTypical(buckets) {
const input = makeSeries(buckets, props.range) const input = makeSeries(buckets, props.range)
if (props.range !== 'day' && props.range !== 'week') return input if (props.range !== 'day' && props.range !== 'week') return input
const estimate = typicalWeek(buckets, now.value) const minHistory = props.range === 'week' ? 2 * WEEK : 2 * DAY
const estimate = typicalWeek(buckets, now.value, { minHistory })
if (!estimate) return input if (!estimate) return input
if (props.range === 'week') { if (props.range === 'week') {
return { ...input, typical: { values: [...estimate], label: 'Typical week' } } return { ...input, typical: { values: [...estimate], label: 'Typical week' } }
@@ -77,6 +80,11 @@ function withTypical(buckets) {
const visitChart = computed(() => buildChart(withTypical(props.data?.site_visits), now.value)) const visitChart = computed(() => buildChart(withTypical(props.data?.site_visits), now.value))
const viewChart = computed(() => buildChart(withTypical(allViews.value), now.value)) const viewChart = computed(() => buildChart(withTypical(allViews.value), now.value))
/** The previous week's tail series on the week view, if present. */
function pastSeries(chart) {
return chart.series.find((s) => s.past)
}
</script> </script>
<template> <template>
@@ -100,8 +108,8 @@ const viewChart = computed(() => buildChart(withTypical(allViews.value), now.val
class="minor vertical" /> class="minor vertical" />
</template> </template>
<g :clip-path="`url(#plot-${c.ylabel})`"> <g :clip-path="`url(#plot-${c.ylabel})`">
<!-- The muted "typical" history curve under the current data. --> <!-- The translucent "typical" history fill under the current data. -->
<path v-if="c.chart.typical" :d="c.chart.typical.line" class="line past" /> <path v-if="c.chart.typical" :d="c.chart.typical.area" class="typical" />
<template v-if="c.chart.bars"> <template v-if="c.chart.bars">
<rect v-for="(b, i) in c.chart.bars" :key="'b' + i" <rect v-for="(b, i) in c.chart.bars" :key="'b' + i"
:x="b.x" :y="b.y" :width="b.width" :height="b.height" class="bar" /> :x="b.x" :y="b.y" :width="b.width" :height="b.height" class="bar" />
@@ -109,8 +117,8 @@ const viewChart = computed(() => buildChart(withTypical(allViews.value), now.val
</template> </template>
<template v-else> <template v-else>
<template v-for="(s, i) in c.chart.series" :key="i"> <template v-for="(s, i) in c.chart.series" :key="i">
<path v-if="s.area" :d="s.area" class="area" /> <path v-if="s.area" :d="s.area" class="area" :class="{ past: s.past }" />
<path :d="s.line" class="line" /> <path :d="s.line" class="line" :class="{ past: s.past }" />
</template> </template>
</template> </template>
</g> </g>
@@ -124,16 +132,26 @@ const viewChart = computed(() => buildChart(withTypical(allViews.value), now.val
<text v-for="t in c.chart.xticks" :key="'x' + t.x" :x="t.x" :y="CHART_H + MARGIN_B - 8" <text v-for="t in c.chart.xticks" :key="'x' + t.x" :x="t.x" :y="CHART_H + MARGIN_B - 8"
text-anchor="middle" class="xlab">{{ t.label }}</text> text-anchor="middle" class="xlab">{{ t.label }}</text>
<!-- Legend, top right inside the plot: current data in accent <!-- Legend, top right inside the plot: current data in accent
(week label, or "Last 24 hours" on the day view) and the (week label, or "Last 24 hours" on the day view), the previous
typical history curve in muted. --> week's tail in the secondary accent (week view only), then the
<g v-if="c.legend && c.chart.typical"> typical history fill as a muted specimen. -->
<g v-if="c.legend && (c.chart.typical || pastSeries(c.chart))">
<line :x1="CHART_W - 118" :x2="CHART_W - 98" y1="10" y2="10" class="line" /> <line :x1="CHART_W - 118" :x2="CHART_W - 98" y1="10" y2="10" class="line" />
<text :x="CHART_W - 92" y="10" dominant-baseline="middle" <text :x="CHART_W - 92" y="10" dominant-baseline="middle"
class="leglab">{{ c.chart.bars ? 'Last 24 hours' : c.chart.series[0].label }}</text> class="leglab">{{ c.chart.bars ? 'Last 24 hours' : c.chart.series[0].label }}</text>
<line :x1="CHART_W - 118" :x2="CHART_W - 98" y1="25" y2="25" <template v-if="pastSeries(c.chart)">
class="line past" style="opacity: 0.6" /> <line :x1="CHART_W - 118" :x2="CHART_W - 98" y1="25" y2="25"
<text :x="CHART_W - 92" y="25" dominant-baseline="middle" class="line past" />
class="leglab">{{ c.chart.typical.label }}</text> <text :x="CHART_W - 92" y="25" dominant-baseline="middle"
class="leglab">{{ pastSeries(c.chart).label }}</text>
</template>
<template v-if="c.chart.typical">
<rect :x="CHART_W - 118" :y="pastSeries(c.chart) ? 34 : 19"
width="20" height="12" class="typical" />
<text :x="CHART_W - 92" :y="pastSeries(c.chart) ? 40 : 25"
dominant-baseline="middle"
class="leglab">{{ c.chart.typical.label }}</text>
</template>
</g> </g>
</svg> </svg>
</template> </template>
@@ -213,9 +231,21 @@ const viewChart = computed(() => buildChart(withTypical(allViews.value), now.val
stroke-linecap: round; stroke-linecap: round;
} }
/* Past overlay weeks contrast with the current week's accent color. */ /* The seasonal "typical" estimate is a muted fill under the current data,
translucent to the same degree, no stroke. */
.chart .typical {
fill: var(--muted);
opacity: 0.6;
}
/* The previous week's tail on the week view uses the secondary accent so
only the typical fill is grey. */
.chart .line.past { .chart .line.past {
stroke: var(--muted); stroke: var(--accent2);
}
.chart .area.past {
fill: var(--accent2);
} }
.empty { color: var(--muted); } .empty { color: var(--muted); }
+19 -10
View File
@@ -189,13 +189,14 @@ export function buildChart(input, now = Date.now()) {
const smoothed = series.map((s) => const smoothed = series.map((s) =>
smooth(s.points.map((p) => p.count), binMinutes, unitMinutes).map((v) => v * rate)) smooth(s.points.map((p) => p.count), binMinutes, unitMinutes).map((v) => v * rate))
// The "typical week" seasonal estimate is already smooth: one value per // The "typical week" seasonal estimate is already smooth: one value per
// bin spanning the full week (future included), drawn in the muted color. // bin spanning the full week (future included), drawn as a translucent
// muted fill under the current data.
const typicalRates = typical const typicalRates = typical
? [...typical.values].map((v) => v * rate) ? [...typical.values].map((v) => v * rate)
: null : null
// Scale from the current series plus the typical curve; both are smooth, // Scale from the current series plus the typical curve; both are smooth,
// and neither should be clipped in normal traffic. // and neither should be clipped in normal traffic.
const highest = Math.max(0, ...smoothed[0], ...(typicalRates || [])) const highest = Math.max(0, ...smoothed.flat(), ...(typicalRates || []))
const { max, step, minor } = yScale(highest) const { max, step, minor } = yScale(highest)
const x = (t) => ((t - t0) / (t1 - t0)) * CHART_W const x = (t) => ((t - t0) / (t1 - t0)) * CHART_W
const y = (v) => PAD_TOP + (1 - Math.max(0, v) / max) * (CHART_H - PAD_TOP) const y = (v) => PAD_TOP + (1 - Math.max(0, v) / max) * (CHART_H - PAD_TOP)
@@ -210,11 +211,15 @@ export function buildChart(input, now = Date.now()) {
area: s.area ? `${line}L${last.x},${CHART_H}L${first.x},${CHART_H}Z` : null, area: s.area ? `${line}L${last.x},${CHART_H}L${first.x},${CHART_H}Z` : null,
} }
}) })
let typicalLine = null let typicalFill = null
if (typicalRates) { if (typicalRates) {
const binMs = (t1 - t0) / typicalRates.length const binMs = (t1 - t0) / typicalRates.length
const pts = typicalRates.map((v, i) => ({ x: x(t0 + i * binMs), y: y(v) })) const pts = typicalRates.map((v, i) => ({ x: x(t0 + i * binMs), y: y(v) }))
typicalLine = { line: spline(pts), label: typical.label } const line = spline(pts)
typicalFill = {
area: `${line}L${pts.at(-1).x},${CHART_H}L${pts[0].x},${CHART_H}Z`,
label: typical.label,
}
} }
// Major (labeled) and minor (hairline) y grid ticks. // Major (labeled) and minor (hairline) y grid ticks.
const majors = [] const majors = []
@@ -267,7 +272,7 @@ export function buildChart(input, now = Date.now()) {
x: x(t), label: fmtTick(t, t1 - t0), line: true, x: x(t), label: fmtTick(t, t1 - t0), line: true,
})) }))
} }
return { max, majors, minors, series: drawn, typical: typicalLine, xticks, unit } return { max, majors, minors, series: drawn, typical: typicalFill, xticks, unit }
} }
/** /**
@@ -275,8 +280,8 @@ export function buildChart(input, now = Date.now()) {
* counts; the skyline uses a projected full-bucket value for the still-open * counts; the skyline uses a projected full-bucket value for the still-open
* final bucket. The y scale is derived from the projected skyline maximum. * final bucket. The y scale is derived from the projected skyline maximum.
* The optional "typical day" curve (per-bin counts aligned to the window's * The optional "typical day" curve (per-bin counts aligned to the window's
* bins, cut from the typical-week estimate) overlays the bars as a smooth * bins, cut from the typical-week estimate) underlays the bars as a
* muted line and also feeds the y scale. * translucent muted fill and also feeds the y scale.
*/ */
export function buildDayChart(input, now = Date.now()) { export function buildDayChart(input, now = Date.now()) {
const { series, t0, t1, typical } = input const { series, t0, t1, typical } = input
@@ -327,13 +332,17 @@ export function buildDayChart(input, now = Date.now()) {
} }
} }
let typicalLine = null let typicalFill = null
if (typical) { if (typical) {
const pts = points.map((p, i) => ({ const pts = points.map((p, i) => ({
x: (i + 0.5) * bucketWidth, x: (i + 0.5) * bucketWidth,
y: y(typical.values[i] || 0), y: y(typical.values[i] || 0),
})) }))
typicalLine = { line: spline(pts), label: typical.label } const line = spline(pts)
typicalFill = {
area: `${line}L${pts.at(-1).x},${CHART_H}L${pts[0].x},${CHART_H}Z`,
label: typical.label,
}
} }
const majors = [] const majors = []
@@ -361,7 +370,7 @@ export function buildDayChart(input, now = Date.now()) {
line: false, line: false,
}) })
} }
return { bars, skyline: skyline.trim(), typical: typicalLine, max, majors, minors, xticks, unit: '5min', series: [] } return { bars, skyline: skyline.trim(), typical: typicalFill, max, majors, minors, xticks, unit: '5min', series: [] }
} }
/** X ticks for year/all: Monday boundaries up to a quarter, UTC month /** X ticks for year/all: Monday boundaries up to a quarter, UTC month
+4 -2
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@@ -92,13 +92,15 @@ export function weekBinIndex(t) {
* (capped at MAX_HISTORY_DAYS back), smoothed with the same Gaussian the * (capped at MAX_HISTORY_DAYS back), smoothed with the same Gaussian the
* week view uses, then folded by seasonalCurve. Returns BINS_PER_WEEK * week view uses, then folded by seasonalCurve. Returns BINS_PER_WEEK
* counts per 5-minute bin starting Monday, or null when there is less than * counts per 5-minute bin starting Monday, or null when there is less than
* a day of history. * a day of history or the history span (first bucket to tEnd, before
* capping) is below minHistory.
*/ */
export function typicalWeek(buckets, tEnd = Date.now()) { export function typicalWeek(buckets, tEnd = Date.now(), { minHistory = 0 } = {}) {
const raw = rawTimes(buckets) const raw = rawTimes(buckets)
const times = Object.keys(raw).map(Number) const times = Object.keys(raw).map(Number)
if (!times.length) return null if (!times.length) return null
const end = Math.floor(tEnd / MIN5) * MIN5 const end = Math.floor(tEnd / MIN5) * MIN5
if (end - Math.min(...times) < minHistory) return null
const start = Math.max(Math.min(...times), end - MAX_HISTORY_DAYS * DAY) const start = Math.max(Math.min(...times), end - MAX_HISTORY_DAYS * DAY)
const n = Math.floor((end - start) / MIN5) const n = Math.floor((end - start) / MIN5)
if (n < BINS_PER_DAY) return null if (n < BINS_PER_DAY) return null
+22 -4
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@@ -4,7 +4,8 @@
* Raw data comes as sparse 5-minute buckets; the range picks the x window * Raw data comes as sparse 5-minute buckets; the range picks the x window
* and a coarser bucket size to keep point counts sane. The week range is * and a coarser bucket size to keep point counts sane. The week range is
* aligned to Monday 00:00 UTC; a "typical week" seasonal estimate * aligned to Monday 00:00 UTC; a "typical week" seasonal estimate
* (seasonal.js) is overlaid on the week and day views by the chart builder. * (seasonal.js) is overlaid as a solid fill on the week and day views by
* the chart builder.
*/ */
export const MIN5 = 5 * 60e3 export const MIN5 = 5 * 60e3
@@ -55,8 +56,14 @@ export function sumRange(raw, t0, t1) {
* bucket — no fake zeroes drawn for the future. Counts are rates per hour * bucket — no fake zeroes drawn for the future. Counts are rates per hour
* (bucket count * 12): a lone visit in a 5-minute bucket reads as "12/h". * (bucket count * 12): a lone visit in a 5-minute bucket reads as "12/h".
* The coarser ranges use per-day rates instead (unitMinutes = 24*60). * The coarser ranges use per-day rates instead (unitMinutes = 24*60).
* Previous weeks are no longer overlaid; the "typical week" seasonal * Since the window is fixed Monday-to-Monday, the days not yet reached
* estimate (seasonal.js) takes their place as the history reference. * would otherwise be blank early in the week: last week's curve continues
* the graph from the current bucket to the end of the week (secondary
* accent, translucent fill like the current week), gradually replaced by
* the current week as it accrues. The tail is only drawn when the data
* reaches into last week at all. The
* "typical week" seasonal estimate (seasonal.js) is the statistical
* history reference under both.
*/ */
export function weeklySeries(buckets) { export function weeklySeries(buckets) {
const raw = rawTimes(buckets) const raw = rawTimes(buckets)
@@ -67,8 +74,19 @@ export function weeklySeries(buckets) {
for (let t = thisMonday; t < end; t += MIN5) { for (let t = thisMonday; t < end; t += MIN5) {
points.push({ t, count: raw[t] || 0 }) points.push({ t, count: raw[t] || 0 })
} }
const past = []
if (Object.keys(raw).some((t) => Number(t) < thisMonday)) {
for (let t = end; t < thisMonday + WEEK; t += MIN5) {
past.push({ t, count: raw[t - WEEK] || 0 })
}
}
return { return {
series: [{ points, label: `Week ${isoWeek(thisMonday)}`, opacity: 1, area: true }], series: [
{ points, label: `Week ${isoWeek(thisMonday)}`, opacity: 1, area: true },
...(past.length
? [{ points: past, label: `Week ${isoWeek(thisMonday - WEEK)}`, past: true, area: true }]
: []),
],
t0: thisMonday, t0: thisMonday,
t1: thisMonday + WEEK, t1: thisMonday + WEEK,
rate: HOUR / MIN5, rate: HOUR / MIN5,