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feat(rectification): drive questions from candidate contrast

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Jesse_Chen
2026-07-31 13:17:00 +08:00
parent fdf791953e
commit a7a11a1a7a
21 changed files with 703 additions and 42 deletions
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tests/test_rectification_diagnostics_clusters.py
+50
View File
@@ -48,6 +48,56 @@ class RectificationDiagnosticsClustersTest(unittest.TestCase):
"end": "05:16",
})
def test_candidate_split_reports_actual_candidate_deltas_not_global_activation(self):
stable_event = "00000000-0000-4000-8000-000000000001"
separating_event = "00000000-0000-4000-8000-000000000002"
rows = [
{
"time": "05:13", "score": 100, "missing_layers": [],
"evidence": [
{"event_id": stable_event, "domain": "relationship", "candidate_time": "05:13", "rule_ids": ["D9:a"], "points": 50},
{"event_id": separating_event, "domain": "education", "candidate_time": "05:13", "rule_ids": ["D24:a"], "points": 50},
],
},
{
"time": "05:14", "score": 90, "missing_layers": [],
"evidence": [
{"event_id": stable_event, "domain": "relationship", "candidate_time": "05:14", "rule_ids": ["D9:b"], "points": 50},
{"event_id": separating_event, "domain": "education", "candidate_time": "05:14", "rule_ids": ["D24:b"], "points": 40},
],
},
]
built = {
"date_sensitivity": [],
"static_contexts": [
{"feature": {
"time": "05:13",
"varga_ascendants": {"D9": 1, "D24": 2},
"arudha_signs": {},
"fingerprints": {"ashtakavarga": "same", "shadbala": "same"},
}},
{"feature": {
"time": "05:14",
"varga_ascendants": {"D9": 1, "D24": 3},
"arudha_signs": {},
"fingerprints": {"ashtakavarga": "same", "shadbala": "same"},
}},
],
"matrix": {
stable_event: {
"05:13": {"points": 50, "technique_layers": ["D9", "D24"]},
"05:14": {"points": 50, "technique_layers": ["D9", "D24"]},
},
separating_event: {
"05:13": {"points": 50, "technique_layers": ["D9", "D24"]},
"05:14": {"points": 40, "technique_layers": ["D9", "D24"]},
},
},
}
result = run_diagnostics({"events": [{"id": stable_event, "domain": "relationship"}, {"id": separating_event, "domain": "education"}]}, rows, built)
self.assertEqual(result["candidate_splits"][0]["technique_layers"], ["D24"])
self.assertEqual(result["candidate_splits"][0]["event_ids"], [separating_event])
if __name__ == "__main__":
unittest.main()
tests/test_rectification_v5_services.py
+66 -1
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@@ -113,6 +113,71 @@ class RectificationV5ServicesTest(unittest.TestCase):
normalized = normalize_rectification_request(request(domain="health_pressure", event_kind="self_health_event"), today=date(2026, 7, 28))
self.assertEqual(normalized["events"][0]["event_kind"], "self_health_event")
def test_relationship_end_is_not_scoreable(self):
with self.assertRaisesRegex(ValueError, "event_kind does not match domain"):
normalize_rectification_request(
request(domain="relationship", event_kind="relationship_end"),
today=date(2026, 7, 28),
)
def test_relationship_start_and_change_use_distinct_rule_conditioned_profiles(self):
def relationship_rows(_value):
return [
{
"time": "05:13", "score": 10,
"evidence": [{
"event_id": EVENT_ID, "domain": "relationship", "candidate_time": "05:13",
"rule_ids": ["vim_md_domain_house", "vim_ad_functional_benefic_auxiliary"],
"points": 10,
}],
"missing_layers": [],
},
{
"time": "05:14", "score": 9,
"evidence": [{
"event_id": EVENT_ID, "domain": "relationship", "candidate_time": "05:14",
"rule_ids": ["controlled_transit_saturn_domain_house", "vim_ad_functional_malefic_auxiliary"],
"points": 9,
}],
"missing_layers": [],
},
]
start = normalize_rectification_request(
request(domain="relationship", event_kind="relationship_start"), today=date(2026, 7, 28)
)
change = normalize_rectification_request(
request(domain="relationship", event_kind="relationship_change"), today=date(2026, 7, 28)
)
start_matrix = build_event_contribution_matrix(start, row_provider=relationship_rows)
change_matrix = build_event_contribution_matrix(change, row_provider=relationship_rows)
self.assertGreater(start_matrix["matrix"][EVENT_ID]["05:13"]["points"], start_matrix["matrix"][EVENT_ID]["05:14"]["points"] )
self.assertGreater(change_matrix["matrix"][EVENT_ID]["05:14"]["points"], change_matrix["matrix"][EVENT_ID]["05:13"]["points"] )
self.assertEqual(change_matrix["date_sensitivity"][0]["sample_winners"], ["05:14", "05:14", "05:14"])
self.assertNotIn("event_kind_profile", change_matrix["matrix"][EVENT_ID]["05:14"]["technique_layers"])
def test_relationship_kind_profile_does_not_create_points_without_activation(self):
normalized = normalize_rectification_request(
request(domain="relationship", event_kind="relationship_change", precision="day"),
today=date(2026, 7, 28),
)
def rows(_value):
return [{
"time": "05:13", "score": 0,
"evidence": [{
"event_id": EVENT_ID, "domain": "relationship", "candidate_time": "05:13",
"rule_ids": ["no_domain_activation", "event_kind:relationship_change"],
"points": 0,
}],
"missing_layers": [],
}]
built = build_event_contribution_matrix(normalized, row_provider=rows)
self.assertEqual(built["matrix"][EVENT_ID]["05:13"]["points"], 0)
def test_date_sampling_preserves_declared_range_and_uses_bounded_samples(self):
base = request()["events"][0]
self.assertEqual(sample_event_dates({**base, "precision": "month"}), ["2016-09-01", "2016-09-15", "2016-09-30"])
@@ -167,7 +232,7 @@ class RectificationV5ServicesTest(unittest.TestCase):
}
feature = {
"calculation_spec_hash": "0" * 64,
"algorithm_version": "rectification-v5-matrix-scoring-1",
"algorithm_version": "rectification-v5-matrix-scoring-2",
"candidate_count": 2,
"feature_hash": "1" * 64,
"features": [{"time": "05:13"}, {"time": "05:14"}],