diff --git a/api_ex/pipeline_health_analyzer.py b/api_ex/pipeline_health_analyzer.py
index 7cdb699..0edb27a 100644
--- a/api_ex/pipeline_health_analyzer.py
+++ b/api_ex/pipeline_health_analyzer.py
@@ -1,8 +1,6 @@
 import os
 import joblib
 import pandas as pd
-import numpy as np
-from sksurv.ensemble import RandomSurvivalForest
 import matplotlib.pyplot as plt
 
 
@@ -16,7 +14,7 @@ class PipelineHealthAnalyzer:
     使用前需确保安装依赖：joblib, pandas, numpy, scikit-survival, matplotlib。
     """
 
-    def __init__(self, model_path: str = 'model/my_survival_forest_model_quxi.joblib'):
+    def __init__(self, model_path: str = "model/my_survival_forest_model_quxi.joblib"):
         """
         初始化分析器，加载预训练的随机生存森林模型。
 
@@ -35,8 +33,10 @@ class PipelineHealthAnalyzer:
         try:
             self.rsf = joblib.load(model_path)
             self.features = [
-                'Material', 'Diameter', 'Flow Velocity',
-                'Pressure', # 'Temperature', 'Precipitation',
+                "Material",
+                "Diameter",
+                "Flow Velocity",
+                "Pressure",  # 'Temperature', 'Precipitation',
                 # 'Location', 'Structural Defects', 'Functional Defects'
             ]
         except Exception as e:
@@ -65,7 +65,9 @@ class PipelineHealthAnalyzer:
         survival_functions = self.rsf.predict_survival_function(x_test)
         return list(survival_functions)
 
-    def plot_survival(self, survival_functions: list, save_path: str = None, show_plot: bool = True):
+    def plot_survival(
+        self, survival_functions: list, save_path: str = None, show_plot: bool = True
+    ):
         """
         可视化生存函数，生成生存概率图表。
 
@@ -75,7 +77,7 @@ class PipelineHealthAnalyzer:
         """
         plt.figure(figsize=(10, 6))
         for i, sf in enumerate(survival_functions):
-            plt.step(sf.x, sf.y, where='post', label=f'样本 {i + 1}')
+            plt.step(sf.x, sf.y, where="post", label=f"样本 {i + 1}")
         plt.xlabel("时间（年）")
         plt.ylabel("生存概率")
         plt.title("管道生存概率预测")
@@ -83,7 +85,7 @@ class PipelineHealthAnalyzer:
         plt.grid(True, alpha=0.3)
 
         if save_path:
-            plt.savefig(save_path, dpi=300, bbox_inches='tight')
+            plt.savefig(save_path, dpi=300, bbox_inches="tight")
             print(f"图表已保存到: {save_path}")
 
         if show_plot:
@@ -137,4 +139,4 @@ class PipelineHealthAnalyzer:
 - 数据格式必须匹配特征列表，特征值为数值型。
 - 模型文件需从原项目复制或重新训练。
 - 如果需要自定义特征或模型参数，可修改类中的features列表或继承此类。
-"""
\ No newline at end of file
+"""