Autocomplete: period-based dish scoring

Replace flat recency penalty with cycle detection. For each dish with
≥2 appearances in history, compute the median interval between uses and
score by how well weeksSinceLast aligns with that period:
  ratio < 0.5  → 0.10 (too soon)
  ratio ~1.0   → 3.00 (right on schedule, boost)
  ratio > 2.5  → 1.00 (pattern may have changed, neutral)

Expand history window from 4 to 12 weeks so monthly cycles (period=4)
have enough data points to be detected reliably.

Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>

MealMood/Services/AutocompleteEngine.swift

@@ -15,7 +15,7 @@ struct AutocompleteEngine {
         let dishName: String
     }
 
-    // recentPlans: up to 4 previous weeks (sorted newest-first) for historical scoring.
+    // recentPlans: up to 12 previous weeks for period detection (weekly/bi-weekly/monthly cycles).
     static func autocomplete(
         emptySlots: [MealSlot],
         currentPlan: WeekPlan,
@@ -25,7 +25,7 @@ struct AutocompleteEngine {
     ) -> AutocompleteResult {
         let tagMap = Dictionary(uniqueKeysWithValues: allTags.map { ($0.id, $0) })
         let dishMap = Dictionary(uniqueKeysWithValues: allDishes.map { ($0.id, $0) })
-        let historyScores = historicalScores(dishes: allDishes, recentPlans: recentPlans)
+        let historyScores = periodScores(dishes: allDishes, recentPlans: recentPlans, currentWeekStart: currentPlan.weekStartDate)
 
         var filledSlots: [(slotId: UUID, dishId: UUID)] = []
         var unfilledCount = 0
@@ -181,31 +181,73 @@ struct AutocompleteEngine {
         return result
     }
 
-    // MARK: - Historical scoring
+    // MARK: - Period-based scoring
 
-    // Returns a recency-penalty multiplier [0.0, 1.0] per dish.
+    // Weight multiplier per dish based on its detected recurrence cycle.
-    // Dishes used more recently get a lower multiplier (deprioritised).
+    // Values > 1.0 boost a dish that is "due"; < 1.0 suppress one used too recently.
-    private static func historicalScores(dishes: [Dish], recentPlans: [WeekPlan]) -> [UUID: Double] {
+    // Requires recentPlans covering ≥ 8–12 weeks to reliably detect monthly cycles.
+    private static func periodScores(
+        dishes: [Dish],
+        recentPlans: [WeekPlan],
+        currentWeekStart: Date
+    ) -> [UUID: Double] {
         guard !recentPlans.isEmpty else { return [:] }
-        let sorted = recentPlans.sorted { $0.weekStartDate > $1.weekStartDate }
+        let calendar = Calendar.current
         var scores: [UUID: Double] = [:]
+
         for dish in dishes {
-            for (weekIndex, plan) in sorted.enumerated() {
+            // Week offsets: how many weeks ago did this dish appear?
+            var offsets: [Int] = []
+            for plan in recentPlans {
                 guard plan.slots.contains(where: { $0.dishId == dish.id }) else { continue }
-                let multiplier: Double
+                let diff = calendar.dateComponents([.weekOfYear], from: plan.weekStartDate, to: currentWeekStart).weekOfYear ?? 0
-                switch weekIndex {
+                if diff > 0 { offsets.append(diff) }
-                case 0: multiplier = 0.20   // used last week — strongly deprioritise
-                case 1: multiplier = 0.50   // 2 weeks ago
-                case 2: multiplier = 0.75   // 3 weeks ago
-                default: multiplier = 0.90
-                }
-                scores[dish.id] = multiplier
-                break // only the most recent appearance matters
             }
+            guard !offsets.isEmpty else { continue }
+
+            let weeksSinceLast = offsets.min()!
+
+            guard offsets.count >= 2 else {
+                // Single sighting: simple recency penalty, no cycle to detect
+                switch weeksSinceLast {
+                case 1:  scores[dish.id] = 0.20
+                case 2:  scores[dish.id] = 0.50
+                case 3:  scores[dish.id] = 0.75
+                default: break  // ≥4 weeks ago → neutral (1.0)
+                }
+                continue
+            }
+
+            // Estimate recurrence period via median of consecutive intervals
+            let sorted = offsets.sorted()
+            var intervals: [Int] = []
+            for i in 0..<sorted.count - 1 {
+                intervals.append(sorted[i + 1] - sorted[i])
+            }
+            let period = medianDouble(intervals)
+
+            // Score by how well weeksSinceLast aligns with the detected period
+            let ratio = Double(weeksSinceLast) / period
+            let score: Double
+            switch ratio {
+            case ..<0.50:     score = 0.10  // too soon — strongly suppress
+            case 0.50..<0.75: score = 0.30  // a bit early
+            case 0.75..<1.25: score = 3.00  // right on schedule — boost
+            case 1.25..<1.75: score = 2.00  // slightly overdue
+            case 1.75..<2.50: score = 1.50  // overdue
+            default:          score = 1.00  // very overdue or pattern changed
+            }
+            scores[dish.id] = score
         }
         return scores
     }
 
+    private static func medianDouble(_ values: [Int]) -> Double {
+        let s = values.sorted()
+        let n = s.count
+        return n % 2 == 1 ? Double(s[n / 2]) : Double(s[n / 2 - 1] + s[n / 2]) / 2.0
+    }
+
     // MARK: - Weighted pick
 
     private static func weightedRandomPick(

MealMood/ViewModels/HomeViewModel.swift

@@ -120,7 +120,7 @@ final class HomeViewModel: ObservableObject {
         let recentPlans = allPlans
             .filter { $0.weekStartDate < plan.weekStartDate }
             .sorted { $0.weekStartDate > $1.weekStartDate }
-            .prefix(4)
+            .prefix(12)
 
         let emptySlots = plan.slots.filter { $0.dishId == nil && !$0.isEatingOut }
         let result = AutocompleteEngine.autocomplete(