feat: seeded transcription-error injection + Recall@k

src/eval.rs

@@ -1 +1,39 @@
-// implemented in a later task
+use rand::rngs::StdRng;
+use rand::{Rng, SeedableRng};
+
+/// Inject realistic transcription errors deterministically (seeded):
+/// char drop, adjacent swap, umlaut flattening, digit transposition.
+pub fn inject_errors(text: &str, rate: f64, seed: u64) -> String {
+    let mut rng = StdRng::seed_from_u64(seed);
+    let mut chars: Vec<char> = text.chars().collect();
+    let n = chars.len();
+    let mut i = 0;
+    while i < chars.len() {
+        if rng.gen::<f64>() < rate {
+            match rng.gen_range(0..4) {
+                0 => { chars.remove(i); continue; }                 // drop
+                1 => { if i + 1 < chars.len() { chars.swap(i, i + 1); } } // swap
+                2 => {                                               // flatten umlaut
+                    chars[i] = match chars[i] {
+                        'ä' => 'a', 'ö' => 'o', 'ü' => 'u', 'ß' => 's',
+                        other => other,
+                    };
+                }
+                _ => {                                               // digit transpose
+                    if chars[i].is_ascii_digit() && i + 1 < chars.len()
+                        && chars[i + 1].is_ascii_digit() {
+                        chars.swap(i, i + 1);
+                    }
+                }
+            }
+        }
+        i += 1;
+    }
+    let _ = n;
+    chars.into_iter().collect()
+}
+
+/// 1.0 if `expected` appears in the first k predictions, else 0.0.
+pub fn recall_at_k(predicted: &[String], expected: &str, k: usize) -> f64 {
+    if predicted.iter().take(k).any(|p| p == expected) { 1.0 } else { 0.0 }
+}

tests/eval_tests.rs

@@ -0,0 +1,17 @@
+use alpha_id::eval::{inject_errors, recall_at_k};
+
+#[test]
+fn injection_is_deterministic_for_seed() {
+    let a = inject_errors("Diabetes mellitus Typ 2", 0.3, 42);
+    let b = inject_errors("Diabetes mellitus Typ 2", 0.3, 42);
+    assert_eq!(a, b);
+    assert_ne!(a, "Diabetes mellitus Typ 2"); // some corruption at rate 0.3
+}
+
+#[test]
+fn recall_counts_hit_within_k() {
+    let predicted = vec!["E11.9".to_string(), "I10.90".to_string(), "J45.0".to_string()];
+    assert_eq!(recall_at_k(&predicted, "I10.90", 5), 1.0);
+    assert_eq!(recall_at_k(&predicted, "I10.90", 1), 0.0);
+    assert_eq!(recall_at_k(&predicted, "Z99.9", 5), 0.0);
+}