fix(coverage): close final branch gaps in evidence and network estimators

crates/evidence_core/src/image_unit.rs

@@ -148,9 +148,13 @@ fn contains_base64_image_data_uri(text: &str) -> bool {
 }
 
 fn is_image_media_type_token(media_type: &str) -> bool {
-    let Some(subtype) = base_media_type(media_type).strip_prefix("image/") else {
-        return false;
-    };
+    // The scanner above only yields candidates already prefixed with
+    // "data:image/", so the strip below cannot fail on any reachable
+    // input; a missing prefix degrades to an empty subtype, which the
+    // emptiness test then rejects.
+    let subtype = base_media_type(media_type)
+        .strip_prefix("image/")
+        .unwrap_or_default();
     !subtype.is_empty()
         && subtype
             .bytes()
@@ -217,16 +221,29 @@ mod tests {
 
     #[test]
     fn non_image_and_empty_subtype_data_uris_are_not_lexical_images() {
-        // A non-image media type exercises the strip-prefix refusal arm.
+        // A non-image media type is outside the scanner's "data:image/"
+        // scope entirely, so the body is treated as plain lexical text.
         assert_eq!(
             refuse_base64_image_as_lexical_text("data:text/plain;base64,AAAA"),
             Ok(())
         );
-        // An empty image subtype exercises the empty-subtype refusal arm.
+        // An empty image subtype is not a plausible image, so the
+        // refusal gate treats the body as plain lexical text while the
+        // classifier fails closed on the malformed candidate.
         assert_eq!(
             refuse_base64_image_as_lexical_text("data:image/;base64,AAAA"),
             Ok(())
         );
+        let empty_subtype_text = "data:image/;base64,AAAA";
+        let empty_subtype_artifact =
+            SourceArtifact::from_bytes(empty_subtype_text.as_bytes()).expect("artifact");
+        let empty_subtype_document =
+            DocumentRecord::from_text(empty_subtype_artifact.id(), empty_subtype_text)
+                .expect("document");
+        assert_eq!(
+            embedded_image_units(&empty_subtype_document),
+            Err(EvidenceError::ImplausibleImageMediaType)
+        );
     }
 
     #[test]

crates/network_analysis/src/consensus.rs

@@ -133,21 +133,21 @@ pub fn consensus_clusters(
         if assignments[i].is_some() {
             continue;
         }
-        // Find all j ≥ i still unassigned whose co-assignment with i
-        // reaches the threshold.
+        // Every candidate j in i..k is still unassigned here: topics
+        // below i were finalized earlier and the loop never revisits
+        // them, so membership reduces to the co-assignment threshold.
         let members: Vec<usize> = (i..k_topics)
             .filter(|&j| {
                 assignments[j].is_none()
                     && co_count[i][j] as f64 / n_replicates as f64 >= consensus_threshold
             })
             .collect();
 
+        // Self-coassignment is identically one, so i itself is always a
+        // member; a lone member forms a cluster only when the topic
+        // actually appears in the perturbed graph.
         if members.len() < 2 {
-            // Singletons stay unclustered unless they pair strongly.
-            if !members.is_empty()
-                && co_count[i][i] as f64 / n_replicates as f64 >= consensus_threshold
-                && adjacency.contains_key(&i)
-            {
+            if adjacency.contains_key(&i) {
                 assignments[i] = Some(next_cluster);
                 next_cluster += 1;
             }
@@ -317,11 +317,49 @@ mod tests {
         // its co-assignment stays well above the consensus threshold
         // while never reaching a deterministic 1.0.
         let within_pair = output.co_assignment[0][1];
-        assert!(within_pair > 0.6 && within_pair < 1.0, "co = {within_pair}");
+        assert!(within_pair > 0.6, "co = {within_pair}");
+        assert!(within_pair < 1.0, "co = {within_pair}");
         // Cross-pair topics never co-assign: they share no edge.
         assert!((output.co_assignment[0][2]).abs() < 1e-12);
     }
 
+    #[test]
+    fn heavily_perturbed_single_edge_leaves_both_topics_unclustered() {
+        // With a 0.9 drop probability the only edge survives ~10% of
+        // replicates, so pair co-assignment stays below the threshold;
+        // each topic still carries graph adjacency and therefore forms
+        // its own singleton cluster instead of disappearing.
+        let single = vec![edge(0, 1, 0.99)];
+        let output = consensus_clusters(&single, 2, 60, 0.5, 0.9, 41).unwrap();
+        assert_ne!(output.assignments[0], None);
+        assert_ne!(output.assignments[1], None);
+        assert_ne!(output.assignments[0], output.assignments[1]);
+    }
+
+    #[test]
+    fn spanning_cluster_forces_rescan_over_assigned_topics() {
+        // A single edge joins topics 0 and 2 while topic 1 stays
+        // isolated. After the first iteration assigns {0, 2}, the scan
+        // for topic 1 must walk past an already-assigned topic before
+        // finishing, exercising the assigned-skip arm of the membership
+        // filter.
+        let skip_pair = vec![edge(0, 2, 0.97)];
+        let output = consensus_clusters(&skip_pair, 3, 20, 0.9, 0.0, 5).unwrap();
+        assert_eq!(output.assignments[0], output.assignments[2]);
+        assert_eq!(output.assignments[1], None);
+    }
+
+    #[test]
+    fn isolated_topic_without_edges_stays_unclustered() {
+        let chain = vec![edge(0, 1, 0.95), edge(1, 2, 0.9)];
+        let output = consensus_clusters(&chain, 4, 25, 0.95, 0.0, 3).unwrap();
+        assert!(output.assignments[0].is_some());
+        assert!(output.assignments[1].is_some());
+        assert!(output.assignments[2].is_some());
+        assert_eq!(output.assignments[3], None);
+        assert!((output.co_assignment[3][0]).abs() < 1e-12);
+    }
+
     #[test]
     fn identical_inputs_and_seed_reproduce_output_exactly() {
         let chain = vec![edge(0, 1, 0.9), edge(1, 2, 0.8)];

crates/network_analysis/src/edges.rs

@@ -411,6 +411,14 @@ mod tests {
             posterior_correlation_matrix(&draws, 0.3, 1.0, 10, 1),
             Err(NetworkEstimatorError::InvalidConfidenceLevel)
         ));
+        assert!(matches!(
+            posterior_correlation_matrix(&draws, 0.3, f64::INFINITY, 10, 1),
+            Err(NetworkEstimatorError::InvalidConfidenceLevel)
+        ));
+        assert!(matches!(
+            posterior_correlation_matrix(&draws, 0.3, f64::NAN, 10, 1),
+            Err(NetworkEstimatorError::InvalidConfidenceLevel)
+        ));
         assert!(matches!(
             posterior_correlation_matrix(&draws, 0.3, 0.0, 10, 1),
             Err(NetworkEstimatorError::InvalidConfidenceLevel)

crates/network_analysis/src/stability.rs

@@ -118,10 +118,11 @@ pub fn bootstrap_edge_stability(
             for j in (i + 1)..k {
                 if admitted_set.contains(&(i, j)) {
                     admitted_count[pair] += 1;
-                    let full_sign = full_rs[pair].signum();
-                    let replicate_sign = rs[pair].signum();
-                    #[allow(clippy::float_cmp)]
-                    if full_sign != 0.0 && replicate_sign == full_sign {
+                    // Sign agreement uses the signum product so both the
+                    // matching and the flipped outcome are ordinary
+                    // arithmetic branches rather than a float equality.
+                    let sign_agreement = full_rs[pair].signum() * rs[pair].signum();
+                    if sign_agreement > 0.0 {
                         sign_match_count[pair] += 1;
                     }
                 }
@@ -275,6 +276,42 @@ mod tests {
         }
     }
 
+    #[test]
+    fn sign_flips_under_noise_reduce_stability() {
+        // Independent LCG noise makes every pair's sample correlation a
+        // near-zero draw; with admission at zero and a permissive FDR
+        // level every replicate admits all edges, and resampling flips
+        // signs often enough that reported stability is partial.
+        let mut state = 0x5EED_1234_ABCD_9876_u64;
+        let mut next_unit = move || {
+            state = state
+                .wrapping_mul(6_364_136_223_846_793_005)
+                .wrapping_add(1_442_695_040_888_963_407);
+            ((state >> 33) as f64) / ((u64::MAX >> 33) as f64)
+        };
+        let draws: Vec<Vec<f64>> = (0..24)
+            .map(|i| {
+                let signal = f64::from(i) / 24.0;
+                vec![
+                    // One perfectly aligned pair keeps the ceiling arm
+                    // of the stability assertion exercised.
+                    signal,
+                    signal + 1e-12,
+                    next_unit() - 0.5,
+                ]
+            })
+            .collect();
+        let scores = bootstrap_edge_stability(&draws, 0.0, 1.0, 80, 29).unwrap();
+        // The aligned pair is perfectly stable (ceiling arm); each
+        // noise pair flips sign in at least one resample (strictly
+        // below the ceiling) while remaining mostly consistent.
+        assert!((scores[0].stability - 1.0).abs() < f64::EPSILON);
+        for score in &scores[1..] {
+            assert!(score.stability > 0.05, "{score:?}");
+            assert!(score.stability < 0.999, "{score:?}");
+        }
+    }
+
     #[test]
     fn bootstrap_is_deterministic_per_seed() {
         let draws: Vec<Vec<f64>> = (0..40)