139 lines
4.5 KiB
Python
139 lines
4.5 KiB
Python
#!/usr/bin/env python
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"""
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测试新数据集的训练功能
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"""
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import sys
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import os
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sys.path.append('server')
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def test_data_size():
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"""测试数据量是否足够"""
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print("=== 检查数据量 ===")
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# 检查CSV文件
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csv_file = 'pharmacy_sales_multi_store.csv'
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if not os.path.exists(csv_file):
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print(f"FAIL: 数据文件不存在: {csv_file}")
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return False
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# 计算行数
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with open(csv_file, 'r', encoding='utf-8') as f:
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lines = f.readlines()
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total_lines = len(lines) - 1 # 减去表头
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print(f"OK: 数据文件存在: {csv_file}")
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print(f"INFO: 总记录数: {total_lines}")
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# 检查是否有足够的数据
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min_required = 8 # LOOK_BACK(5) + FORECAST_HORIZON(3)
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if total_lines >= min_required:
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print(f"OK: 数据量充足: {total_lines} >= {min_required}")
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return True
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else:
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print(f"FAIL: 数据量不足: {total_lines} < {min_required}")
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return False
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def test_quick_training():
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"""测试快速训练（低轮次）"""
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print("\n=== 测试快速训练 ===")
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try:
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from core.predictor import PharmacyPredictor
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# 创建预测器
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predictor = PharmacyPredictor()
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print("OK: PharmacyPredictor 初始化成功")
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# 测试训练（使用很少的轮次进行快速测试）
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print("INFO: 开始训练测试（TCN模型，2轮次）...")
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try:
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metrics = predictor.train_model(
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product_id='P001',
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model_type='tcn',
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epochs=2, # 很少的轮次用于快速测试
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training_mode='product'
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)
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if metrics:
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print("OK: 训练成功完成！")
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print(f"训练指标: {metrics}")
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return True
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else:
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print("FAIL: 训练失败，返回None")
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return False
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except Exception as e:
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print(f"FAIL: 训练过程中出错: {e}")
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# 检查是否是数据不足错误
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if "数据不足" in str(e) or "num_samples" in str(e):
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print("INFO: 这是预期的数据不足错误，说明错误检测正常工作")
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return True # 错误检测工作正常也算成功
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else:
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return False
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except Exception as e:
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print(f"FAIL: PharmacyPredictor 初始化失败: {e}")
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return False
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def test_data_standardization():
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"""测试数据标准化功能"""
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print("\n=== 测试数据标准化 ===")
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try:
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from utils.multi_store_data_utils import load_multi_store_data
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# 加载并标准化数据
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df = load_multi_store_data('pharmacy_sales_multi_store.csv', product_id='P001')
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required_columns = ['sales', 'price', 'weekday', 'month', 'is_holiday', 'is_weekend', 'is_promotion', 'temperature']
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missing_columns = [col for col in required_columns if col not in df.columns]
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if missing_columns:
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print(f"FAIL: 数据标准化失败，缺少列: {missing_columns}")
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return False
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else:
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print("OK: 数据标准化成功，所有必需列都存在")
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print(f"INFO: P001产品数据量: {len(df)} 条记录")
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return True
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except Exception as e:
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print(f"FAIL: 数据标准化测试失败: {e}")
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return False
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def main():
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"""主测试函数"""
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print("开始训练功能测试")
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tests_passed = 0
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total_tests = 3
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# 测试数据量
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if test_data_size():
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tests_passed += 1
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# 测试数据标准化
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if test_data_standardization():
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tests_passed += 1
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# 测试训练
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if test_quick_training():
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tests_passed += 1
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print(f"\n测试结果: {tests_passed}/{total_tests} 项测试通过")
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if tests_passed == total_tests:
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print("SUCCESS: 所有测试通过！训练系统已准备就绪")
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print("\n建议：")
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print("1. 现在可以通过Web界面进行正常训练")
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print("2. 如果遇到问题，检查是否需要更多数据")
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print("3. 可以尝试不同的训练模式（产品/店铺/全局）")
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else:
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print("WARNING: 部分测试失败，请检查问题")
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if tests_passed == 0:
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print("建议先运行: uv run generate_multi_store_data.py")
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if __name__ == "__main__":
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main() |