fix: weekly chart prediction and data pipeline extraction

app/components/Package/TrendsChart.vue

@@ -18,7 +18,11 @@ import type {
   YearlyDataPoint,
 } from '~/types/chart'
 import { DATE_INPUT_MAX } from '~/utils/input'
-import { applyDataCorrection } from '~/utils/chart-data-correction'
+import {
+  applyDataPipeline,
+  endDateOnlyToUtcMs,
+  DEFAULT_PREDICTION_POINTS,
+} from '~/utils/chart-data-prediction'
 import { applyBlocklistCorrection, getAnomaliesForPackages } from '~/utils/download-anomalies'
 import { copyAltTextForTrendLineChart, sanitise, loadFile, applyEllipsis } from '~/utils/charts'
 
@@ -368,14 +372,25 @@ const displayedGranularity = shallowRef<ChartTimeGranularity>(DEFAULT_GRANULARIT
 
 const isEndDateOnPeriodEnd = computed(() => {
   const g = selectedGranularity.value
-  if (g !== 'monthly' && g !== 'yearly') return false
 
   const iso = String(endDate.value ?? '').slice(0, 10)
   if (!/^\d{4}-\d{2}-\d{2}$/.test(iso)) return false
 
   const [year, month, day] = iso.split('-').map(Number)
   if (!year || !month || !day) return false
 
+  if (g === 'daily') return true // every day is a complete period
+
+  if (g === 'weekly') {
+    // The last week bucket is complete when the range length is divisible by 7
+    const startIso = String(startDate.value ?? '').slice(0, 10)
+    if (!/^\d{4}-\d{2}-\d{2}$/.test(startIso)) return false
+    const startMs = Date.UTC(...(startIso.split('-').map(Number) as [number, number, number]))
+    const endMs = Date.UTC(year, month - 1, day)
+    const totalDays = Math.floor((endMs - startMs) / 86400000) + 1
+    return totalDays % 7 === 0
+  }
+
   // Monthly: endDate is the last day of its month (UTC)
   if (g === 'monthly') {
     const lastDayOfMonth = new Date(Date.UTC(year, month, 0)).getUTCDate()
@@ -386,11 +401,8 @@ const isEndDateOnPeriodEnd = computed(() => {
   return month === 12 && day === 31
 })
 
-const isEstimationGranularity = computed(
-  () => displayedGranularity.value === 'monthly' || displayedGranularity.value === 'yearly',
-)
 const supportsEstimation = computed(
-  () => isEstimationGranularity.value && selectedMetric.value !== 'contributors',
+  () => displayedGranularity.value !== 'daily' && selectedMetric.value !== 'contributors',
 )
 
 const hasDownloadAnomalies = computed(() =>
@@ -972,11 +984,6 @@ const effectiveDataSingle = computed<EvolutionData>(() => {
         granularity: displayedGranularity.value,
       })
     }
-
-    return applyDataCorrection(
-      data as Array<{ value: number }>,
-      settings.value.chartFilter,
-    ) as EvolutionData
   }
 
   return data
@@ -1021,10 +1028,6 @@ const chartData = computed<{
       if (settings.value.chartFilter.anomaliesFixed) {
         data = applyBlocklistCorrection({ data, packageName: pkg, granularity })
       }
-      data = applyDataCorrection(
-        data as Array<{ value: number }>,
-        settings.value.chartFilter,
-      ) as EvolutionData
     }
     const points = extractSeriesPoints(granularity, data)
 
@@ -1066,16 +1069,26 @@ const chartData = computed<{
 })
 
 const normalisedDataset = computed(() => {
-  return chartData.value.dataset?.map(d => {
-    const lastValue = d.series.at(-1) ?? 0
+  const granularity = displayedGranularity.value
+  const endDateMs = endDate.value ? endDateOnlyToUtcMs(endDate.value) : null
+  const referenceMs = endDateMs ?? Date.now()
+  const lastDateMs = chartData.value.dates.at(-1) ?? 0
+  const isAbsoluteMetric = selectedMetric.value === 'contributors'
 
-    // Contributors is an absolute metric: keep the partial period value as-is.
-    const projectedLastValue =
-      selectedMetric.value === 'contributors' ? lastValue : extrapolateLastValue(lastValue)
+  return chartData.value.dataset?.map(d => {
+    const series = applyDataPipeline(
+      d.series.map(v => v ?? 0),
+      {
+        averageWindow: settings.value.chartFilter.averageWindow,
+        smoothingTau: settings.value.chartFilter.smoothingTau,
+        predictionPoints: settings.value.chartFilter.predictionPoints ?? DEFAULT_PREDICTION_POINTS,
+      },
+      { granularity, lastDateMs, referenceMs, isAbsoluteMetric },
+    )
 
     return {
       ...d,
-      series: [...d.series.slice(0, -1), projectedLastValue],
+      series,
       dashIndices: d.dashIndices ?? [],
     }
   })
@@ -1137,144 +1150,6 @@ const granularityItems = computed(() =>
   })),
 )
 
-function clampRatio(value: number): number {
-  if (value < 0) return 0
-  if (value > 1) return 1
-  return value
-}
-
-/**
- * Convert a `YYYY-MM-DD` date to UTC timestamp representing the end of that day.
- * The returned timestamp corresponds to `23:59:59.999` in UTC
- *
- * @param endDateOnly - ISO-like date string (`YYYY-MM-DD`)
- * @returns The UTC timestamp in milliseconds for the end of the given day,
- * or `null` if the input is invalid.
- */
-function endDateOnlyToUtcMs(endDateOnly: string): number | null {
-  if (!/^\d{4}-\d{2}-\d{2}$/.test(endDateOnly)) return null
-  const [y, m, d] = endDateOnly.split('-').map(Number)
-  if (!y || !m || !d) return null
-  return Date.UTC(y, m - 1, d, 23, 59, 59, 999)
-}
-
-/**
- * Computes the UTC timestamp corresponding to the start of the time bucket
- * that contains the given timestamp.
- *
- * This function is used to derive period boundaries when computing completion
- * ratios or extrapolating values for partially completed periods.
- *
- * Bucket boundaries are defined in UTC:
- * - **monthly** : first day of the month at `00:00:00.000` UTC
- * - **yearly** : January 1st of the year at `00:00:00.000` UTC
- *
- * @param timestampMs - Reference timestamp in milliseconds
- * @param granularity - Bucket granularity (`monthly` or `yearly`)
- * @returns The UTC timestamp representing the start of the corresponding
- * time bucket.
- */
-function getBucketStartUtc(timestampMs: number, granularity: 'monthly' | 'yearly'): number {
-  const date = new Date(timestampMs)
-  if (granularity === 'yearly') return Date.UTC(date.getUTCFullYear(), 0, 1, 0, 0, 0, 0)
-  return Date.UTC(date.getUTCFullYear(), date.getUTCMonth(), 1, 0, 0, 0, 0)
-}
-
-/**
- * Computes the UTC timestamp corresponding to the end of the time
- * bucket that contains the given timestamp. This end timestamp is paired with `getBucketStartUtc` to define
- * a half-open interval `[start, end)` when computing elapsed time or completion
- * ratios within a period.
- *
- * Bucket boundaries are defined in UTC and are **exclusive**:
- * - **monthly** : first day of the following month at `00:00:00.000` UTC
- * - **yearly** : January 1st of the following year at `00:00:00.000` UTC
- *
- * @param timestampMs - Reference timestamp in milliseconds
- * @param granularity - Bucket granularity (`monthly` or `yearly`)
- * @returns The UTC timestamp (in milliseconds) representing the exclusive end
- * of the corresponding time bucket.
- */
-function getBucketEndUtc(timestampMs: number, granularity: 'monthly' | 'yearly'): number {
-  const date = new Date(timestampMs)
-  if (granularity === 'yearly') return Date.UTC(date.getUTCFullYear() + 1, 0, 1, 0, 0, 0, 0)
-  return Date.UTC(date.getUTCFullYear(), date.getUTCMonth() + 1, 1, 0, 0, 0, 0)
-}
-
-/**
- * Computes the completion ratio of a time bucket relative to a reference time.
- *
- * The ratio represents how much of the bucket’s duration has elapsed at
- * `referenceMs`, expressed as a normalized value in the range `[0, 1]`.
- *
- * The bucket is defined by the calendar period (monthly or yearly) that
- * contains `bucketTimestampMs`, using UTC boundaries:
- * - start: `getBucketStartUtc(...)`
- * - end: `getBucketEndUtc(...)`
- *
- * The returned value is clamped to `[0, 1]`:
- * - `0`: reference time is at or before the start of the bucket
- * - `1`: reference time is at or after the end of the bucket
- *
- * This function is used to detect partially completed periods and to
- * extrapolate full period values from partial data.
- *
- * @param params.bucketTimestampMs - Timestamp belonging to the bucket
- * @param params.granularity - Bucket granularity (`monthly` or `yearly`)
- * @param params.referenceMs - Reference timestamp used to measure progress
- * @returns A normalized completion ratio in the range `[0, 1]`.
- */
-function getCompletionRatioForBucket(params: {
-  bucketTimestampMs: number
-  granularity: 'monthly' | 'yearly'
-  referenceMs: number
-}): number {
-  const start = getBucketStartUtc(params.bucketTimestampMs, params.granularity)
-  const end = getBucketEndUtc(params.bucketTimestampMs, params.granularity)
-  const total = end - start
-  if (total <= 0) return 1
-  return clampRatio((params.referenceMs - start) / total)
-}
-
-/**
- * Extrapolate the last observed value of a time series when the last bucket
- * (month or year) is only partially complete.
- *
- * This is used to replace the final value in each `VueUiXy` series
- * before rendering, so the chart can display an estimated full-period value
- * for the current month or year.
- *
- * Notes:
- * - This function assumes `lastValue` is the value corresponding to the last
- *   date in `chartData.value.dates`
- *
- * @param lastValue - The last observed numeric value for a series.
- * @returns The extrapolated value for partially completed monthly or yearly granularities,
- * or the original `lastValue` when no extrapolation should be applied.
- */
-function extrapolateLastValue(lastValue: number) {
-  if (selectedMetric.value === 'contributors') return lastValue
-
-  if (displayedGranularity.value !== 'monthly' && displayedGranularity.value !== 'yearly')
-    return lastValue
-
-  const endDateMs = endDate.value ? endDateOnlyToUtcMs(endDate.value) : null
-  const referenceMs = endDateMs ?? Date.now()
-
-  const completionRatio = getCompletionRatioForBucket({
-    bucketTimestampMs: chartData.value.dates.at(-1) ?? 0,
-    granularity: displayedGranularity.value,
-    referenceMs,
-  })
-
-  if (!(completionRatio > 0 && completionRatio < 1)) return lastValue
-
-  const extrapolatedValue = lastValue / completionRatio
-  if (!Number.isFinite(extrapolatedValue)) return lastValue
-
-  return extrapolatedValue
-}
-
 /**
  * Build and return svg markup for estimation overlays on the chart.
  *
@@ -1709,14 +1584,15 @@ watch(selectedMetric, value => {
     :aria-busy="activeMetricState.pending ? 'true' : 'false'"
   >
     <div class="w-full mb-4 flex flex-col gap-3">
-      <div class="flex flex-col sm:flex-row gap-3 sm:gap-2 sm:items-end">
+      <div class="grid grid-cols-2 sm:flex sm:flex-row gap-3 sm:gap-2 sm:items-end">
         <SelectField
           v-if="showFacetSelector"
           id="trends-metric-select"
           v-model="selectedMetric"
           :disabled="activeMetricState.pending"
           :items="METRICS.map(m => ({ label: m.label, value: m.id }))"
           :label="$t('package.trends.facet')"
+          block
         />
 
         <SelectField
@@ -1725,9 +1601,10 @@ watch(selectedMetric, value => {
           v-model="selectedGranularity"
           :disabled="activeMetricState.pending"
           :items="granularityItems"
+          block
         />
 
-        <div class="grid grid-cols-2 gap-2 flex-1">
+        <div class="col-span-2 sm:col-span-1 grid grid-cols-2 gap-2 flex-1">
           <div class="flex flex-col gap-1">
             <label
               for="startDate"
@@ -1797,7 +1674,7 @@ watch(selectedMetric, value => {
           />
           {{ $t('package.trends.data_correction') }}
         </button>
-        <div v-if="showCorrectionControls" class="flex items-end gap-3">
+        <div v-if="showCorrectionControls" class="grid grid-cols-2 sm:flex items-end gap-3">
           <label class="flex flex-col gap-1 flex-1">
             <span class="text-2xs font-mono text-fg-subtle tracking-wide uppercase">
               {{ $t('package.trends.average_window') }}
@@ -1826,6 +1703,20 @@ watch(selectedMetric, value => {
               class="accent-[var(--accent-color,var(--fg-subtle))]"
             />
           </label>
+          <label class="flex flex-col gap-1 flex-1">
+            <span class="text-2xs font-mono text-fg-subtle tracking-wide uppercase">
+              {{ $t('package.trends.prediction') }}
+              <span class="text-fg-muted">({{ settings.chartFilter.predictionPoints }})</span>
+            </span>
+            <input
+              v-model.number="settings.chartFilter.predictionPoints"
+              type="range"
+              min="0"
+              max="30"
+              step="1"
+              class="accent-[var(--accent-color,var(--fg-subtle))]"
+            />
+          </label>
           <div class="flex flex-col gap-1 shrink-0">
             <span
               class="text-2xs font-mono text-fg-subtle tracking-wide uppercase flex items-center justify-between"
@@ -1879,7 +1770,7 @@ watch(selectedMetric, value => {
               </TooltipApp>
             </span>
             <label
-              class="flex items-center gap-1.5 text-2xs font-mono text-fg-subtle cursor-pointer"
+              class="flex items-center gap-1.5 text-2xs font-mono text-fg-subtle cursor-pointer h-4"
               :class="{ 'opacity-50 pointer-events-none': !hasAnomalies }"
             >
               <input

app/composables/useSettings.ts

@@ -45,6 +45,7 @@ export interface AppSettings {
     averageWindow: number
     smoothingTau: number
     anomaliesFixed: boolean
+    predictionPoints: number
   }
 }
 
@@ -68,6 +69,7 @@ const DEFAULT_SETTINGS: AppSettings = {
     averageWindow: 0,
     smoothingTau: 1,
     anomaliesFixed: true,
+    predictionPoints: 4,
   },
 }