补充动态因子缺失回归测试

crates/fidc-core/src/platform_expr_strategy.rs

@@ -8298,6 +8298,141 @@ mod tests {
         assert!(!strategy.stock_extra_factor_identifiers.contains("prev_close"));
     }
 
+    #[test]
+    fn platform_expr_missing_requested_factor_does_not_default_to_zero() {
+        let date = d(2025, 5, 19);
+        let missing_symbol = "000001.SZ";
+        let present_symbol = "000002.SZ";
+        let symbols = [missing_symbol, present_symbol];
+        let data = DataSet::from_components(
+            symbols
+                .iter()
+                .map(|symbol| Instrument {
+                    symbol: (*symbol).to_string(),
+                    name: (*symbol).to_string(),
+                    board: "SZ".to_string(),
+                    round_lot: 100,
+                    listed_at: Some(d(2020, 1, 1)),
+                    delisted_at: None,
+                    status: "active".to_string(),
+                })
+                .collect(),
+            symbols
+                .iter()
+                .map(|symbol| DailyMarketSnapshot {
+                    date,
+                    symbol: (*symbol).to_string(),
+                    timestamp: Some("2025-05-19 10:18:00".to_string()),
+                    day_open: 10.0,
+                    open: 10.0,
+                    high: 10.5,
+                    low: 9.8,
+                    close: 10.0,
+                    last_price: 10.0,
+                    bid1: 9.99,
+                    ask1: 10.01,
+                    prev_close: 9.9,
+                    volume: 1_000_000,
+                    minute_volume: 10_000,
+                    bid1_volume: 2_000,
+                    ask1_volume: 2_000,
+                    trading_phase: Some("continuous".to_string()),
+                    paused: false,
+                    upper_limit: 11.0,
+                    lower_limit: 9.0,
+                    price_tick: 0.01,
+                })
+                .collect(),
+            vec![
+                DailyFactorSnapshot {
+                    date,
+                    symbol: missing_symbol.to_string(),
+                    market_cap_bn: 12.0,
+                    free_float_cap_bn: 10.0,
+                    pe_ttm: 8.0,
+                    turnover_ratio: Some(1.0),
+                    effective_turnover_ratio: Some(1.0),
+                    extra_factors: BTreeMap::new(),
+                },
+                DailyFactorSnapshot {
+                    date,
+                    symbol: present_symbol.to_string(),
+                    market_cap_bn: 12.0,
+                    free_float_cap_bn: 10.0,
+                    pe_ttm: 8.0,
+                    turnover_ratio: Some(1.0),
+                    effective_turnover_ratio: Some(1.0),
+                    extra_factors: BTreeMap::from([("model_score".to_string(), 2.0)]),
+                },
+            ],
+            symbols
+                .iter()
+                .map(|symbol| CandidateEligibility {
+                    date,
+                    symbol: (*symbol).to_string(),
+                    is_st: false,
+                    is_new_listing: false,
+                    is_paused: false,
+                    allow_buy: true,
+                    allow_sell: true,
+                    is_kcb: false,
+                    is_one_yuan: false,
+                    risk_level_code: None,
+                })
+                .collect(),
+            vec![BenchmarkSnapshot {
+                date,
+                benchmark: "000852.SH".to_string(),
+                open: 1000.0,
+                close: 1002.0,
+                prev_close: 998.0,
+                volume: 1_000_000,
+            }],
+        )
+        .expect("dataset");
+        let portfolio = PortfolioState::new(1_000_000.0);
+        let subscriptions = BTreeSet::new();
+        let ctx = StrategyContext {
+            execution_date: date,
+            decision_date: date,
+            decision_index: 100,
+            data: &data,
+            portfolio: &portfolio,
+            futures_account: None,
+            open_orders: &[],
+            dynamic_universe: None,
+            subscriptions: &subscriptions,
+            process_events: &[],
+            active_process_event: None,
+            active_datetime: None,
+            order_events: &[],
+            fills: &[],
+        };
+        let mut cfg = PlatformExprStrategyConfig::microcap_rotation();
+        cfg.signal_symbol = missing_symbol.to_string();
+        cfg.stock_filter_expr = "model_score < 1.0".to_string();
+        let strategy = PlatformExprStrategy::new(cfg);
+        let day = strategy.day_state(&ctx, date).expect("day state");
+        let missing_stock = strategy
+            .stock_state_with_factor_date(&ctx, date, date, missing_symbol)
+            .expect("missing stock state");
+        let present_stock = strategy
+            .stock_state_with_factor_date(&ctx, date, date, present_symbol)
+            .expect("present stock state");
+
+        assert!(day.available_factor_names.contains("model_score"));
+        assert!(
+            !strategy
+                .stock_passes_expr(&ctx, &day, &missing_stock)
+                .expect("missing stock filter")
+        );
+        assert!(
+            !strategy
+                .stock_passes_expr(&ctx, &day, &present_stock)
+                .expect("present stock filter")
+        );
+    }
+
     #[test]
     fn platform_expr_rewrites_prelude_assignment_ternary() {
         let prelude = "let cap_low = sig_close <= 0 ? 7 : max(5, min(cap_low_raw, 70));";