修复find_new_center_pipe中心点代码错误的bug

app/algorithms/burst_location/similarity_calculator.py

@@ -577,7 +577,7 @@ def cal_similarity_all_multi_new_sq_improve_double_lzr(
                 similarity[each_candidate] = similarity_all.loc[
                     :, each_candidate
                 ].mean()
-        similarity = similarity.sort_values(ascending=False)
+        similarity = similarity.sort_values(ascending=False, kind="mergesort")
         detail_index = [str(pipe) for pipe in candidate_pipe]
         similarity_detail = pd.DataFrame(index=detail_index)
         similarity_detail.index.name = "pipe_id"
@@ -620,7 +620,7 @@ def cal_similarity_all_multi_new_sq_improve_double_lzr(
         similarity_detail["pressure_sensor_count"] = int(len(important_p_sensor))
         similarity_detail["flow_sensor_count"] = int(len(important_f_sensor))
         similarity_detail = similarity_detail.sort_values(
-            by="final_similarity", ascending=False
+            by="final_similarity", ascending=False, kind="mergesort"
         )
     else:
         break_flag = 1
@@ -729,7 +729,7 @@ def cal_top_sensors(monitor_p, predict_p, Top_sensor_num):
     dpressure = abs(predict_p - monitor_p)
     if type(dpressure) == pd.core.frame.DataFrame:
         dpressure = dpressure.mean()
-    dpressure_rank = dpressure.sort_values(ascending=False)
+    dpressure_rank = dpressure.sort_values(ascending=False, kind="mergesort")
     return list(dpressure_rank.index[:Top_sensor_num])
 
 
@@ -747,7 +747,7 @@ def remove_3_sigma(similarity_t):
 
 
 def update_similarity(leak_candidate_center, similarity, leak_center_dict):
-    similarity_new = pd.Series(dtype=object)
+    similarity_new = pd.Series(dtype=float)
     for each_center in leak_candidate_center:
         houxuan_center = leak_center_dict[each_center]
         if len(houxuan_center) > 1:
@@ -758,7 +758,7 @@ def update_similarity(leak_candidate_center, similarity, leak_center_dict):
                 similarity_new[each_center] = similarity[each_center].mean()
             else:
                 similarity_new[each_center] = similarity[each_center]
-    similarity_new = similarity_new.sort_values(ascending=False)
+    similarity_new = similarity_new.sort_values(ascending=False, kind="mergesort")
     return similarity_new
 
 
@@ -767,10 +767,10 @@ def extra_judge(similarity):
     record_sensor = []
     record_value = []
     for i in range(len(similarity.index)):
-        if similarity.iloc[i] >= mean_similarity:
+        if similarity.iloc[i] >= mean_similarity - 1e-10:
             record_value.append(similarity.iloc[i])
             record_sensor.append(similarity.index[i])
-    out_put_similarity = pd.Series(record_value, index=record_sensor, dtype=object)
+    out_put_similarity = pd.Series(record_value, index=record_sensor, dtype=float)
     cut_ratio = len(out_put_similarity.index) / len(similarity.index)
     return cut_ratio, out_put_similarity