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Step3 插值算法 OOM 修复 + 多进程加速 + 全链路累积改动（14 文件）

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DXC
2026-06-15 16:49:17 +08:00
parent 82e0b92af6
commit 60a9d7d922
14 changed files with 855 additions and 152 deletions
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6
src/core/modeling/regression.py
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@ -315,7 +315,7 @@ def main():
# 示例1: 使用所有回归方法分析光谱指数
print("\n1. 光谱指数与叶绿素a的回归分析:")
sample_data = pd.read_csv(r"E:\code\WQ\pipeline_result\work_dir\5_training_spectra\water_quality_results.csv")
sample_data = pd.read_csv(r"E:\code\WQ\pipeline_result\work_dir\6_Spectral_Feature_Extraction\water_quality_results.csv")
spectral_indices = ['Al10SABI','Am092Bsub']
results1 = analyzer.batch_single_variable_regression(
@ -323,7 +323,7 @@ def main():
x_columns=spectral_indices,
y_column='Chlorophyll',
methods='all',
output_file=r'E:\code\WQ\pipeline_result\work_dir\5_training_spectra\spectral_indices_regression.csv'
output_file=r'E:\code\WQ\pipeline_result\work_dir\6_Spectral_Feature_Extraction\spectral_indices_regression.csv'
)
# # 示例2: 使用特定方法分析反射率波段
@ -343,7 +343,7 @@ def main():
best_models = analyzer.get_best_models_summary()
if not best_models.empty:
print(best_models[['x_variable', 'regression_method', 'r_squared', 'equation']].to_string(index=False))
best_models.to_csv(r'E:\code\WQ\pipeline_result\work_dir\5_training_spectra\best_models_summary.csv', index=False)
best_models.to_csv(r'E:\code\WQ\pipeline_result\work_dir\6_Spectral_Feature_Extraction\best_models_summary.csv', index=False)
print("\n最佳模型汇总已保存到 'best_models_summary.csv'")
#
# def advanced_usage_example():