feat(clustering): link identities by keystroke-rhythm proximity

Campaign clusterer gains a keystroke edge: when two identities'
kd_digraph_simhash centroids are within KD_HAMMING_MAX bits, a graded
weight (1.0 at identical, fading to 0 at the cutoff) feeds the campaign
graph. Supporting tier (0.6) — a typing match plus temporal overlap
reaches threshold, but typing alone never merges (FP guard against
coarse, noisy terminal timing).

Projects the column through IdentityFeatures + from_identity_row.

tests/clustering/test_campaign_keystroke.py

@@ -0,0 +1,75 @@
+# SPDX-License-Identifier: AGPL-3.0-or-later
+"""Campaign-level keystroke-rhythm edge.
+
+The digraph-SimHash centroid is a *supporting* signal: a typing match
+alone must not merge two identities (FP guard), but it tips an otherwise
+sub-threshold pair (e.g. co-temporal identities) into one campaign.
+"""
+from __future__ import annotations
+
+from decnet.clustering.campaign.impl.connected_components import from_identity_row
+from decnet.clustering.campaign.impl.similarity import (
+    CAMPAIGN_EDGE_THRESHOLD,
+    KD_HAMMING_MAX,
+    IdentityFeatures,
+    combined_campaign_weight,
+    keystroke_weight,
+)
+from decnet.util.simhash import to_bytes8
+
+_H = 0xABCD1234ABCD1234
+
+
+def _flip_low_bits(value: int, n: int) -> int:
+    """XOR the n low bits → a hash exactly n bits away from ``value``."""
+    return value ^ ((1 << n) - 1)
+
+
+def test_identical_rhythm_is_full_weight() -> None:
+    a = IdentityFeatures("a", kd_digraph_simhash=_H)
+    b = IdentityFeatures("b", kd_digraph_simhash=_H)
+    assert keystroke_weight(a, b) == 1.0
+
+
+def test_missing_centroid_is_zero() -> None:
+    a = IdentityFeatures("a", kd_digraph_simhash=_H)
+    b = IdentityFeatures("b")  # no biometric yet
+    assert keystroke_weight(a, b) == 0.0
+
+
+def test_weight_grades_by_hamming() -> None:
+    half = KD_HAMMING_MAX // 2
+    a = IdentityFeatures("a", kd_digraph_simhash=_H)
+    b = IdentityFeatures("b", kd_digraph_simhash=_flip_low_bits(_H, half))
+    assert keystroke_weight(a, b) == 1.0 - half / KD_HAMMING_MAX
+
+
+def test_far_apart_contributes_nothing() -> None:
+    a = IdentityFeatures("a", kd_digraph_simhash=_H)
+    b = IdentityFeatures("b", kd_digraph_simhash=_flip_low_bits(_H, KD_HAMMING_MAX))
+    assert keystroke_weight(a, b) == 0.0
+
+
+def test_typing_alone_does_not_merge() -> None:
+    # FP guard: identical rhythm, no other signal → below threshold.
+    a = IdentityFeatures("a", kd_digraph_simhash=_H)
+    b = IdentityFeatures("b", kd_digraph_simhash=_H)
+    assert combined_campaign_weight(a, b) < CAMPAIGN_EDGE_THRESHOLD
+
+
+def test_typing_plus_temporal_overlap_crosses_threshold() -> None:
+    window = ((0.0, 100.0),)
+    a = IdentityFeatures("a", kd_digraph_simhash=_H, session_windows=window)
+    b = IdentityFeatures("b", kd_digraph_simhash=_H, session_windows=window)
+    # temporal overlap (0.4) + keystroke (0.6) reaches the 1.0 threshold.
+    assert combined_campaign_weight(a, b) >= CAMPAIGN_EDGE_THRESHOLD
+    # Strip the biometric and the same co-temporal pair falls back under.
+    a2 = IdentityFeatures("a", session_windows=window)
+    b2 = IdentityFeatures("b", session_windows=window)
+    assert combined_campaign_weight(a2, b2) < CAMPAIGN_EDGE_THRESHOLD
+
+
+def test_from_identity_row_projects_bytes_and_none() -> None:
+    feat = from_identity_row({"uuid": "x", "kd_digraph_simhash": to_bytes8(_H)})
+    assert feat.kd_digraph_simhash == _H
+    assert from_identity_row({"uuid": "y"}).kd_digraph_simhash is None