2024/03/09/18:30

app.py

@@ -356,7 +356,7 @@ class Dataset:
 
     @classmethod
     def check_model_optimize_radio(cls):
-        if cls.cur_model and cls.choose_optimize != "None" and cls.choose_optimize:
+        if cls.cur_model and cls.choose_optimize != MN.none and cls.choose_optimize:
             if cls.cur_model == MN.linear_regressor:
                 if cls.linear_regression_model_type:
                     return True
@@ -640,8 +640,8 @@ class Dataset:
 
     @classmethod
     def get_optimize_name_mapping(cls):
-        # return dict(zip(cls.get_optimize_list(), ["None", "grid_search", "bayes_search"]))
-        return dict(zip(cls.get_optimize_list(), ["None", "grid_search"]))
+        # return dict(zip(cls.get_optimize_list(), [MN.none, MN.grid_search, MN.bayes_search]))
+        return dict(zip(cls.get_optimize_list(), [MN.none, MN.grid_search]))
 
     @classmethod
     def get_linear_regression_model_list(cls):
@@ -1214,10 +1214,9 @@ class Dataset:
     def get_model_train_input_params(cls):
         EACH_ROW_NUM = 6
         output_list = []
-        print(cls.cur_model)
+
         if cls.check_model_optimize_radio():
             output_dict = ChooseModelParams.choose(cls.cur_model)
-            print("output_dict: {}".format(str(output_dict)))
             row_unit_num_list = []
             row_len = len(output_dict.keys())
             dict_keys_list = [x for x in output_dict.keys()]
@@ -1226,9 +1225,7 @@ class Dataset:
                 row_unit_num_list.append(len(v))
                 for x in v:
                     output_list.append(x)
-            print("output_list: {}".format(str(output_list)))
-            print("row_len: {}".format(str(row_len)))
-            print("dict_keys_list: {}".format(str(dict_keys_list)))
+
             return_list = []
             cumulative_sum = 0
             for j in range(row_len):
@@ -1240,7 +1237,7 @@ class Dataset:
                 return_list.extend(
                     [gr.Textbox("", visible=False)] * (EACH_ROW_NUM - 1 - row_unit_num_list[j])
                 )
-                print("return_list: {}".format(str(return_list)))
+                
                 cumulative_sum += row_unit_num_list[j]
 
             return_list.extend(["", gr.Textbox(visible=False)] * (StaticValue.MAX_PARAMS_NUM - EACH_ROW_NUM * row_len))
@@ -2005,12 +2002,12 @@ def choose_custom_dataset(file: str):
 def select_model_optimize_radio(optimize):
     optimize = Dataset.get_optimize_name_mapping()[optimize]
 
-    if optimize == "grid_search":
-        Dataset.choose_optimize = "grid_search"
-    elif optimize == "bayes_search":
-        Dataset.choose_optimize = "bayes_search"
-    elif optimize == "None":
-        Dataset.choose_optimize = "None"
+    if optimize == MN.grid_search:
+        Dataset.choose_optimize = MN.grid_search
+    elif optimize == MN.bayes_search:
+        Dataset.choose_optimize = MN.bayes_search
+    elif optimize == MN.none:
+        Dataset.choose_optimize = MN.none
 
     return get_return(True)
 
@@ -2446,17 +2443,24 @@ with gr.Blocks(js="./design/welcome.js", css="./design/custom.css") as demo:
 
     # 数据模型
     # ！有BUG
-    select_as_model_radio.change(
-        fn=select_as_model,
-        inputs=[select_as_model_radio],
-        outputs=get_outputs()
-    ).then(
-        fn=reset_select_model_optimize_radio_part_1,
-        outputs=get_outputs()
-    ).then(
-        fn=reset_select_model_optimize_radio_part_2,
-        outputs=get_outputs()
-    )
+    if Dataset.choose_optimize and Dataset.choose_optimize != MN.none:
+        select_as_model_radio.change(
+            fn=select_as_model,
+            inputs=[select_as_model_radio],
+            outputs=get_outputs()
+        ).then(
+            fn=reset_select_model_optimize_radio_part_1,
+            outputs=get_outputs()
+        ).then(
+            fn=reset_select_model_optimize_radio_part_2,
+            outputs=get_outputs()
+        )
+    else:
+        select_as_model_radio.change(
+            fn=select_as_model,
+            inputs=[select_as_model_radio],
+            outputs=get_outputs()
+        )
 
     # [模型]
     linear_regression_model_radio.change(

classes/static_custom_class.py

@@ -148,6 +148,11 @@ class MN:  # ModelName
     naive_bayes_classifier = "naive bayes classifier"
     # 模型Step 4:在这里添加新的模型名称
 
+    none = "None"
+    grid_search = "grid_search"
+    bayes_search = "bayes_search"
+
+
     # [绘图]
     data_distribution = "data_distribution"
     descriptive_indicators = "descriptive_indicators"