88 lines
2.5 KiB
Python
88 lines
2.5 KiB
Python
"""
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直接测试阵容推荐功能，不通过HTTP请求
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"""
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from src.data_provider import DataQueryAPI
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from src.scoring.scoring_system import TeamScorer
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from src.recommendation import RecommendationEngine
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import copy
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def test_direct_recommendation():
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"""直接测试阵容推荐功能"""
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# 创建自定义配置
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config = {
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"base_weights": {
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"synergy_level_weight": 1.5,
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"synergy_count_weight": 0.8,
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"chess_cost_weight": 0.3
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},
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"synergy_weights": {
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"重装战士": 2.0,
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"斗士": 1.8
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},
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"chess_weights": {
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"盖伦": 2.0,
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"赛娜": 2.5
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},
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"synergy_level_weights": {
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"1": 1.0,
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"2": 1.2,
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"3": 1.5,
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"4": 1.8,
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"5": 2.0,
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"6": 2.3,
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"7": 2.6,
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"8": 3.0,
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"9": 3.3,
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"10": 3.5
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},
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"cost_weights": {
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"1": 1.0,
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"2": 1.2,
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"3": 1.5,
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"4": 1.8,
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"5": 2.0
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}
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}
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# 初始化组件
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data_api = DataQueryAPI()
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scorer = TeamScorer(api=data_api, config_obj=copy.deepcopy(config))
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engine = RecommendationEngine(api=data_api, scorer=scorer, config_obj=copy.deepcopy(config))
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# 定义参数
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population = 9
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required_synergies = [] # 这里可以添加必选羁绊
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required_chess = [] # 这里可以添加必选棋子
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max_results = 3
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# 生成阵容推荐
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print("正在生成阵容推荐...")
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teams = engine.recommend_team(
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population=population,
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required_synergies=required_synergies,
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required_chess=required_chess,
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max_results=max_results
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)
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# 打印结果
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print(f"生成了 {len(teams)} 个推荐阵容")
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for i, team in enumerate(teams):
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print(f"\n阵容 #{i+1} (评分: {team.score:.2f})")
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print("\n棋子列表:")
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for chess in team.chess_list:
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print(f" {chess.get('displayName')} ({chess.get('price')}费)")
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print("\n激活的职业羁绊:")
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for job in team.synergy_levels['job']:
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print(f" {job['name']} (等级 {job['level']})")
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print("\n激活的特质羁绊:")
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for race in team.synergy_levels['race']:
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print(f" {race['name']} (等级 {race['level']})")
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print("\n" + "-"*50)
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if __name__ == "__main__":
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test_direct_recommendation() |