update

app.py

@@ -261,45 +261,6 @@ def submit_model(name):
         return "ERROR: Unexpected error. Please try again later."
 
 
-all_data = {}
-time_list = []
-for folder in get_folders_matching_format('data'):
-    folder_name = os.path.basename(folder)
-    time_list.append(folder_name)
-    if all_data.get(folder) is None:
-        all_data[folder_name] = {}
-    for file_name in file_name_list:
-        if all_data.get(file_name) is None:
-            all_data[folder_name][file_name] = {}
-        for sheet_name in sheet_name_list:
-            final_file_name = os.path.join(folder, file_name)
-            all_data[folder_name][file_name][sheet_name] = rename_columns(
-                pd.read_excel(final_file_name + '.xlsx', sheet_name=sheet_name))
-
-
-# def create_scaling_plot(all_data, period):
-#     selected_columns = ['Name', 'Parameters Count (B)', 'Average (The lower the better)']
-#     target_data = all_data[period]
-#     new_df = pd.DataFrame()
-#
-#     for size in target_data.keys():
-#         new_df = pd.concat([new_df, target_data[size]['cr'].loc[:, selected_columns]], axis=0)
-#
-#     new_df.rename(columns={
-#         'Parameters Count (B)': 'Params(B)',
-#         'Average (The lower the better)': 'Compression Rate (%)'
-#     }, inplace=True)
-#
-#     fig = px.scatter(new_df,
-#                      x='Params(B)',
-#                      y='Compression Rate (%)',
-#                      title='Compression Rate Scaling Law',
-#                      hover_name='Name'
-#                      )
-#     fig.update_traces(marker=dict(size=12))
-#     return fig
-
-
 def create_scaling_plot(all_data, period):
     selected_columns = ['Name', 'Parameters Count (B)', 'Average (The lower the better)']
     target_data = all_data[period]
@@ -385,6 +346,21 @@ def create_scaling_plot(all_data, period):
     return fig
 
 
+all_data = {}
+time_list = []
+for folder in get_folders_matching_format('data'):
+    folder_name = os.path.basename(folder)
+    time_list.append(folder_name)
+    if all_data.get(folder) is None:
+        all_data[folder_name] = {}
+    for file_name in file_name_list:
+        if all_data.get(file_name) is None:
+            all_data[folder_name][file_name] = {}
+        for sheet_name in sheet_name_list:
+            final_file_name = os.path.join(folder, file_name)
+            all_data[folder_name][file_name][sheet_name] = rename_columns(
+                pd.read_excel(final_file_name + '.xlsx', sheet_name=sheet_name))
+
 initial_fig = create_scaling_plot(all_data, time_list[-1])
 
 initial_period = time_list[-1]