Phase 5.2 구현 완료: GraphAnalytics (중심성 + 커뮤니티)
[GraphAnalytics] - calculate_centrality(type): degree, pagerank, betweenness, closeness - detect_communities(algorithm): Louvain, label propagation - get_graph_statistics(): density, diameter, connectivity - find_influential_entities(): 복합 점수 기반 중요도 분석 - Community 데이터 클래스 [특징] - 정규화된 점수 (0-1 범위) - 순위 지정 (1, 2, 3, ...) - GDS 라이브러리 지원 (폴백 포함) - 성능 최적화된 Cypher 쿼리 [테스트] - test_phase5_graph_analytics.py (8 테스트 통과) - 모든 통합 테스트 통과 Phase 5.0-5.2 완성! 다음: API 엔드포인트 통합 Co-Authored-By: Claude Haiku 4.5 <noreply@anthropic.com>
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test_phase5_graph_analytics.py
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test_phase5_graph_analytics.py
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#!/usr/bin/env python3
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"""Phase 5.2 Graph Analytics tests."""
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import asyncio
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import sys
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from pathlib import Path
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sys.path.insert(0, str(Path(__file__).parent / "ontology_platform"))
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from ont_platform.core.graph.graph_analytics import GraphAnalytics, Community
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class MockAdapter:
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"""Mock Neo4j adapter for testing."""
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async def execute_cypher(self, cypher: str, params=None):
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"""Mock Cypher execution."""
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params = params or {}
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# Degree centrality
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if "size((" in cypher and "out_degree" not in cypher:
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return [
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{"result": {"entity_id": 1, "label": "Hub", "centrality_score": 10, "type": "degree"}},
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{"result": {"entity_id": 2, "label": "Node_2", "centrality_score": 5, "type": "degree"}},
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{"result": {"entity_id": 3, "label": "Node_3", "centrality_score": 3, "type": "degree"}},
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]
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# Pagerank centrality
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if "out_degree" in cypher or "in_degree" in cypher:
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return [
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{
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"result": {
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"entity_id": 1,
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"label": "Hub",
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"centrality_score": 0.45,
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"in_degree": 8,
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"out_degree": 2,
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"type": "pagerank",
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}
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},
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{
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"result": {
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"entity_id": 2,
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"label": "Node_2",
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"centrality_score": 0.30,
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"in_degree": 5,
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"out_degree": 3,
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"type": "pagerank",
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}
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},
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]
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# Communities (Louvain)
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if "communityId" in cypher or "algo.louvain" in cypher:
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return [
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{
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"result": {
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"community_id": 0,
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"entities": [1, 2, 3, 4],
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"labels": ["Entity_1", "Entity_2", "Entity_3", "Entity_4"],
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"size": 4,
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}
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},
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{
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"result": {
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"community_id": 1,
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"entities": [5, 6, 7],
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"labels": ["Entity_5", "Entity_6", "Entity_7"],
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"size": 3,
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}
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},
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]
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# Graph statistics
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if "node_count" in cypher or "edge_count" in cypher:
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return [
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{
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"stats": {
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"total_nodes": 20,
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"total_edges": 45,
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"avg_degree": 4.5,
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"density": 0.118,
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"max_possible_edges": 190,
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}
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}
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]
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# Diameter
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if "diameter" in cypher:
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return [{"diameter": 5}]
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# Components
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if "componentId" in cypher or "algo.unionFind" in cypher:
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return [{"num_components": 1}]
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return []
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async def test_calculate_centrality_degree():
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"""Test degree centrality calculation."""
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print("\n[TEST 1] Degree Centrality")
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adapter = MockAdapter()
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analytics = GraphAnalytics(adapter)
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entities = await analytics.calculate_centrality(centrality_type="degree", top_n=10)
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assert len(entities) > 0, "Should find entities"
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assert all("entity_id" in e and "centrality_score" in e for e in entities), "Should have required fields"
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assert all(e["centrality_score"] > 0 for e in entities), "Centrality scores should be positive"
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print(f" [OK] Found {len(entities)} entities by degree")
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top_entity = entities[0]
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print(f" [OK] Top entity: {top_entity['label']} (degree={top_entity['centrality_score']})")
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print(" [PASS]")
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async def test_calculate_centrality_pagerank():
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"""Test PageRank centrality calculation."""
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print("\n[TEST 2] PageRank Centrality")
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adapter = MockAdapter()
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analytics = GraphAnalytics(adapter)
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entities = await analytics.calculate_centrality(centrality_type="pagerank", top_n=10)
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assert len(entities) > 0, "Should find entities"
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assert all(0 < e["centrality_score"] <= 1 for e in entities), "PageRank should be 0-1"
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print(f" [OK] Found {len(entities)} entities by PageRank")
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top_entity = entities[0]
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print(f" [OK] Top entity: {top_entity['label']} (score={top_entity['centrality_score']:.3f})")
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print(" [PASS]")
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async def test_invalid_centrality_type():
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"""Test invalid centrality type."""
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print("\n[TEST 3] Invalid Centrality Type")
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adapter = MockAdapter()
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analytics = GraphAnalytics(adapter)
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result = await analytics.calculate_centrality(centrality_type="invalid", top_n=10)
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assert isinstance(result, dict) and "error" in result, "Should return error"
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print(f" [OK] Correctly rejects invalid type: {result['error']}")
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print(" [PASS]")
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async def test_detect_communities():
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"""Test community detection."""
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print("\n[TEST 4] Community Detection")
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adapter = MockAdapter()
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analytics = GraphAnalytics(adapter)
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communities = await analytics.detect_communities(algorithm="louvain")
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assert isinstance(communities, list), "Should return list"
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if communities:
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assert all("community_id" in c and "entities" in c for c in communities), "Should have required fields"
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assert all(isinstance(c["size"], int) for c in communities), "Should have size"
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print(f" [OK] Detected {len(communities)} communities")
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for comm in communities:
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print(f" Community {comm['community_id']}: {comm['size']} entities")
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print(" [PASS]")
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async def test_get_graph_statistics():
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"""Test graph statistics."""
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print("\n[TEST 5] Graph Statistics")
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adapter = MockAdapter()
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analytics = GraphAnalytics(adapter)
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stats = await analytics.get_graph_statistics()
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if stats:
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assert "total_nodes" in stats, "Should have total_nodes"
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assert "total_edges" in stats, "Should have total_edges"
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assert "avg_degree" in stats, "Should have avg_degree"
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assert "density" in stats, "Should have density"
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print(f" [OK] Total nodes: {stats['total_nodes']}")
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print(f" [OK] Total edges: {stats['total_edges']}")
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print(f" [OK] Average degree: {stats['avg_degree']:.2f}")
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print(f" [OK] Density: {stats['density']:.4f}")
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print(f" [OK] Is connected: {stats.get('is_connected', False)}")
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print(" [PASS]")
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async def test_find_influential_entities():
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"""Test influential entity detection."""
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print("\n[TEST 6] Influential Entities")
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adapter = MockAdapter()
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analytics = GraphAnalytics(adapter)
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influential = await analytics.find_influential_entities(top_n=10)
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assert isinstance(influential, list), "Should return list"
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if influential:
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assert all("entity_id" in e and "composite_score" in e for e in influential), "Should have required fields"
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assert all(0 <= e["composite_score"] <= 1 for e in influential), "Scores should be 0-1"
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print(f" [OK] Found {len(influential)} influential entities")
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for idx, entity in enumerate(influential[:3], 1):
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print(
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f" {idx}. {entity['label']} (score={entity['composite_score']:.3f})"
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)
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print(" [PASS]")
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async def test_community_object():
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"""Test Community data class."""
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print("\n[TEST 7] Community Object")
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community = Community(
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community_id=1,
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entities=[1, 2, 3, 4, 5],
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size=5,
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density=0.75,
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modularity=0.42,
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)
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assert community.community_id == 1, "ID should be preserved"
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assert len(community.entities) == 5, "Should have 5 entities"
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assert community.size == 5, "Size should be 5"
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community_dict = community.to_dict()
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assert "community_id" in community_dict, "Dict should have community_id"
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assert community_dict["size"] == 5, "Dict should have size"
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print(" [OK] Community object creation and conversion")
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print(" [PASS]")
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async def test_centrality_ranking():
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"""Test that centrality results are ranked."""
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print("\n[TEST 8] Centrality Ranking")
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adapter = MockAdapter()
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analytics = GraphAnalytics(adapter)
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entities = await analytics.calculate_centrality(centrality_type="degree", top_n=10)
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if len(entities) > 1:
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assert all("rank" in e for e in entities), "Should have rank field"
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assert entities[0]["rank"] == 1, "Top entity should have rank 1"
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assert entities[1]["rank"] == 2, "Second entity should have rank 2"
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print(f" [OK] Entities ranked correctly")
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for entity in entities[:3]:
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print(f" Rank {entity['rank']}: {entity['label']}")
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print(" [PASS]")
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async def main():
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"""Run all tests."""
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print("=" * 70)
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print("Phase 5.2 Graph Analytics Tests")
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print("=" * 70)
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try:
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await test_calculate_centrality_degree()
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await test_calculate_centrality_pagerank()
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await test_invalid_centrality_type()
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await test_detect_communities()
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await test_get_graph_statistics()
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await test_find_influential_entities()
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await test_community_object()
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await test_centrality_ranking()
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print("\n" + "=" * 70)
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print("All tests passed!")
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print("=" * 70)
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print("\nPhase 5.2 Graph Analytics capabilities:")
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print(" [OK] Degree centrality calculation")
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print(" [OK] PageRank centrality calculation")
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print(" [OK] Community detection (Louvain)")
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print(" [OK] Graph statistics (density, diameter, components)")
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print(" [OK] Influential entity detection")
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print(" [OK] Input validation")
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return True
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except AssertionError as e:
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print(f"\nTest failed: {e}")
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import traceback
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traceback.print_exc()
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return False
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except Exception as e:
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print(f"\nUnexpected error: {e}")
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import traceback
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traceback.print_exc()
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return False
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if __name__ == "__main__":
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success = asyncio.run(main())
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sys.exit(0 if success else 1)
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