1

pages/2_TECT_IDXYZ.py

@@ -37,7 +37,9 @@ def GetListOf_XYZV_ToTrainClassifier(repo):
 @st.cache_data
 def GetCachedClassifier(lstDfOriginal, nHystorySteps):
     classifier_object, df_train_with_predict, time_elapsed = my_stm.GetClassifier(lstDfOriginal, nHystorySteps)
-    st.session_state.df_train_with_predict = df_train_with_predict
+    #st.session_state.df_train_with_predict = df_train_with_predict
+    columns_xyzv = [c for c in df_train_with_predict.columns if "Vis" in c] + [c for c in df_train_with_predict.columns if c[0] in "XYZ"]
+    st.session_state.df_train_with_predict = df_train_with_predict[columns_xyzv]
     print(f"GetCachedClassifier() : {time_elapsed=}")
     return classifier_object
 
@@ -140,7 +142,7 @@ if selectedFile is not None:
         classifier_object = GetCachedClassifier(lstDfOriginal, pack_size-1)
         col2.popover(type(classifier_object).__name__).write(type(classifier_object))
         # прогноз на обучающей выборке
-        columns_xyzv = [c for c in df_train_with_predict.columns if "Vis" in c] + [c for c in df_train_with_predict.columns if c[0] in "XYZ"]
+        #columns_xyzv = [c for c in df_train_with_predict.columns if "Vis" in c] + [c for c in df_train_with_predict.columns if c[0] in "XYZ"]
         #col2.dataframe(df_train_with_predict[columns_xyzv], height=650)
         # расчет пакетов
         xyz = ["X","Y","Z"]