Update app.py

app.py

@@ -204,7 +204,10 @@ val_data = features.loc[train_split:]
 start = past + future
 end = start + train_split
 
-x_train = train_data[[i for i in range(7)]].values
+if ("0" == "mycustom"):
+	x_train = train_data[[i for i in range(7)]].values
+if ("0" != "mycustom"):
+	x_train = train_data[[i for i in range(myfields.len())]].values
 y_train = features.iloc[start:end][[1]]
 
 sequence_length = int(past / step)
@@ -212,7 +215,10 @@ x_end = len(val_data) - past - future
 
 label_start = train_split + past + future
 
-x_val = val_data.iloc[:x_end][[i for i in range(7)]].values
+if ("0" == "mycustom"):
+	x_val = val_data.iloc[:x_end][[i for i in range(7)]].values
+if ("0" != "mycustom"):
+	x_val = val_data.iloc[:x_end][[i for i in range(myfields.len())]].values
 y_val = features.iloc[label_start:][[1]]
 
 dataset_val = keras.preprocessing.timeseries_dataset_from_array(
@@ -263,4 +269,3 @@ fig = plot()
 st.pyplot(fig)
 
 # %%
-