feat(fusion_accounting_assets): asset anomaly detection service

Made-with: Cursor

fusion_accounting_assets/tests/__init__.py

@@ -1,3 +1,4 @@
 from . import test_depreciation_methods
 from . import test_prorate
 from . import test_salvage_value
+from . import test_asset_anomaly_detection

fusion_accounting_assets/tests/test_asset_anomaly_detection.py

@@ -0,0 +1,71 @@
+from odoo.tests.common import TransactionCase
+from odoo.tests import tagged
+from odoo.addons.fusion_accounting_assets.services.anomaly_detection import (
+    detect_schedule_variance, detect_low_utilization, AssetAnomaly,
+)
+
+
+@tagged('post_install', '-at_install')
+class TestAssetAnomalyDetection(TransactionCase):
+
+    def test_schedule_variance_within_threshold_returns_none(self):
+        # 5% variance < 10% threshold
+        result = detect_schedule_variance(
+            asset_id=1, asset_name='Truck', expected_accumulated=10000,
+            actual_accumulated=10500,
+        )
+        self.assertIsNone(result)
+
+    def test_schedule_variance_behind_schedule_low_severity(self):
+        # 15% behind: low severity, behind_schedule
+        result = detect_schedule_variance(
+            asset_id=1, asset_name='Truck', expected_accumulated=10000,
+            actual_accumulated=8500,
+        )
+        self.assertIsNotNone(result)
+        self.assertEqual(result.anomaly_type, 'behind_schedule')
+        self.assertEqual(result.severity, 'low')
+
+    def test_schedule_variance_ahead_high_severity(self):
+        # 60% ahead: high severity
+        result = detect_schedule_variance(
+            asset_id=2, asset_name='Server', expected_accumulated=10000,
+            actual_accumulated=16000,
+        )
+        self.assertIsNotNone(result)
+        self.assertEqual(result.anomaly_type, 'ahead_of_schedule')
+        self.assertEqual(result.severity, 'high')
+
+    def test_schedule_variance_zero_expected_returns_none(self):
+        result = detect_schedule_variance(
+            asset_id=1, asset_name='Truck', expected_accumulated=0,
+            actual_accumulated=500,
+        )
+        self.assertIsNone(result)
+
+    def test_low_utilization_flags_when_underused(self):
+        # 60% deficit -> high severity
+        result = detect_low_utilization(
+            asset_id=3, asset_name='Mill', expected_units=1000, actual_units=400,
+        )
+        self.assertIsNotNone(result)
+        self.assertEqual(result.anomaly_type, 'low_utilization')
+        self.assertEqual(result.severity, 'high')
+
+    def test_low_utilization_within_tolerance_returns_none(self):
+        # 95% used: within 10% tolerance
+        result = detect_low_utilization(
+            asset_id=3, asset_name='Mill', expected_units=1000, actual_units=950,
+        )
+        self.assertIsNone(result)
+
+    def test_anomaly_to_dict_round_trip(self):
+        anomaly = AssetAnomaly(
+            asset_id=1, asset_name='X', anomaly_type='behind_schedule',
+            severity='medium', expected=100.0, actual=70.0, variance_pct=30.0,
+            detail='example',
+        )
+        d = anomaly.to_dict()
+        self.assertEqual(d['asset_id'], 1)
+        self.assertEqual(d['anomaly_type'], 'behind_schedule')
+        self.assertEqual(d['severity'], 'medium')