From 5b2a03d416a7bd709680a1adf52013e3eadc199a Mon Sep 17 00:00:00 2001
From: boris <shuaibo.zhang@hotmail.com>
Date: Sat, 5 Sep 2026 01:00:33 +0800
Subject: [PATCH] revert: remove unproven duplicate rolling reuse

---
 crates/fidc-core/src/data.rs | 140 +----------------------------------
 1 file changed, 1 insertion(+), 139 deletions(-)

diff --git a/crates/fidc-core/src/data.rs b/crates/fidc-core/src/data.rs
index 52a0c0d..a699e37 100644
--- a/crates/fidc-core/src/data.rs
+++ b/crates/fidc-core/src/data.rs
@@ -688,17 +688,7 @@ impl AdjustedCloseSeries {
         end: usize,
         lookbacks: &[usize; N],
     ) -> [Option<f64>; N] {
-        let mut values = [None; N];
-        for index in 0..N {
-            if let Some(previous) =
-                (0..index).find(|previous| lookbacks[*previous] == lookbacks[index])
-            {
-                values[index] = values[previous];
-            } else {
-                values[index] = self.moving_average_at_end(end, lookbacks[index]);
-            }
-        }
-        values
+        std::array::from_fn(|index| self.moving_average_at_end(end, lookbacks[index]))
     }
 
     fn moving_average_at_end(&self, end: usize, lookback: usize) -> Option<f64> {
@@ -5409,82 +5399,6 @@ mod tests {
         );
     }
 
-    #[test]
-    #[ignore = "manual release-mode duplicate rolling lookback benchmark"]
-    fn benchmark_adjusted_close_reuses_duplicate_lookbacks() {
-        use std::hint::black_box;
-        use std::time::Instant;
-
-        let data = adjusted_close_benchmark_data();
-        let symbol_id = data.symbol_id("000001.SZ").expect("symbol id");
-        let series = data
-            .adjusted_close_series_by_symbol_id(symbol_id)
-            .expect("adjusted close series");
-        let lookbacks = [1usize, 2, 3, 1, 2, 3, 1];
-        let end = 3usize;
-        let iterations = 3_000_000usize;
-        let mut repeated_nanos = 0u128;
-        let mut reused_nanos = 0u128;
-        let mut repeated_checksum = 0.0;
-        let mut reused_checksum = 0.0;
-
-        for sample in 0..6 {
-            let measure_repeated = || {
-                let started = Instant::now();
-                let mut checksum = 0.0;
-                for _ in 0..iterations {
-                    let values = std::array::from_fn::<_, 7, _>(|index| {
-                        series.moving_average_at_end(black_box(end), black_box(lookbacks[index]))
-                    });
-                    checksum += black_box(values).into_iter().flatten().sum::<f64>();
-                }
-                (started.elapsed().as_nanos(), checksum)
-            };
-            let measure_reused = || {
-                let started = Instant::now();
-                let mut checksum = 0.0;
-                for _ in 0..iterations {
-                    checksum += black_box(
-                        series.moving_averages_at_end(black_box(end), black_box(&lookbacks)),
-                    )
-                    .into_iter()
-                    .flatten()
-                    .sum::<f64>();
-                }
-                (started.elapsed().as_nanos(), checksum)
-            };
-            let (baseline, candidate) = if sample % 2 == 0 {
-                (measure_repeated(), measure_reused())
-            } else {
-                let candidate = measure_reused();
-                let baseline = measure_repeated();
-                (baseline, candidate)
-            };
-            repeated_nanos += baseline.0;
-            repeated_checksum += baseline.1;
-            reused_nanos += candidate.0;
-            reused_checksum += candidate.1;
-        }
-
-        assert_eq!(repeated_checksum, reused_checksum);
-        assert!(repeated_checksum > 0.0);
-        let repeated_seconds = repeated_nanos as f64 / 1_000_000_000.0;
-        let reused_seconds = reused_nanos as f64 / 1_000_000_000.0;
-        eprintln!(
-            "{}",
-            serde_json::json!({
-                "schemaVersion": "fidc-adjusted-close-duplicate-lookback-benchmark/v1",
-                "samples": 6,
-                "iterationsPerSample": iterations,
-                "lookbacks": lookbacks,
-                "repeatedSeconds": repeated_seconds,
-                "reusedSeconds": reused_seconds,
-                "speedup": repeated_seconds / reused_seconds,
-                "checksum": repeated_checksum,
-            })
-        );
-    }
-
     #[test]
     #[ignore = "manual component benchmark"]
     fn benchmark_daily_snapshot_view_lookup() {
@@ -5876,58 +5790,6 @@ mod tests {
         );
     }
 
-    fn adjusted_close_benchmark_data() -> DataSet {
-        let dates = [
-            NaiveDate::from_ymd_opt(2025, 1, 2).unwrap(),
-            NaiveDate::from_ymd_opt(2025, 1, 3).unwrap(),
-            NaiveDate::from_ymd_opt(2025, 1, 6).unwrap(),
-        ];
-        DataSet::from_components(
-            vec![Instrument {
-                symbol: "000001.SZ".to_string(),
-                name: "000001.SZ".to_string(),
-                board: "SZ".to_string(),
-                round_lot: 100,
-                listed_at: None,
-                delisted_at: None,
-                status: "active".to_string(),
-            }],
-            dates
-                .iter()
-                .enumerate()
-                .map(|(index, date)| {
-                    market_row(
-                        &date.format("%Y-%m-%d").to_string(),
-                        10.0 + index as f64,
-                        100_000,
-                    )
-                })
-                .collect(),
-            dates
-                .iter()
-                .map(|date| DailyFactorSnapshot {
-                    date: *date,
-                    symbol: "000001.SZ".to_string(),
-                    market_cap_bn: 10.0,
-                    free_float_cap_bn: 8.0,
-                    pe_ttm: 10.0,
-                    turnover_ratio: None,
-                    effective_turnover_ratio: None,
-                    extra_factors: NumericFactorMap::from([(
-                        Cow::Borrowed(BACKWARD_ADJUSTMENT_FACTOR_FIELD),
-                        1.0,
-                    )]),
-                })
-                .collect(),
-            Vec::new(),
-            dates
-                .iter()
-                .map(|date| benchmark_row(&date.format("%Y-%m-%d").to_string(), 1_000.0))
-                .collect(),
-        )
-        .expect("adjusted close benchmark dataset")
-    }
-
     fn volume_contract_data(availability: Option<[f64; 3]>) -> DataSet {
         let dates = [
             NaiveDate::parse_from_str("2025-01-02", "%Y-%m-%d").unwrap(),