Added method for manual testing of hyperparameters

main.py

@@ -13,7 +13,7 @@ from pipeline import (
     prepare_user_data,
     train_models,
     evaluate_models,
-    prepare_data_for_model, model_type_gru, model_type_lstm, model_type_bilstm, train_models_v2
+    prepare_data_for_model, model_type_gru, model_type_lstm, model_type_bilstm, train_models_v2, train_one_model
 )
 
 year_str = 'Year'
@@ -321,11 +321,53 @@ def test(model_type):
                             ignore_index=True)
     print(results)
 
+def manual_tuning(model_type):
+    # load dataset
+    sequence_length = 20
+    data_filename = 'ALL32USERS15MIN_WITHTHRESHOLD.xlsx'
+    timespan_id = min_timespan_str
+    threshold_id = with_threshold_str
+
+    file_path = os.path.join(dataset_path, data_filename)
+    df = load_dataset(file_path)
+    df = remove_covid_data(df)
+
+    tr, val, te = split_data_by_userdata_percentage(df, percentages=(80, 10, 10), sample=20)
+    tr = reduce_columns(tr, data_filename)
+    val = reduce_columns(val, data_filename)
+    te = reduce_columns(te, data_filename)
+
+    user_data_train = prepare_user_data(tr)
+    user_data_val = prepare_user_data(val)
+
+    # fit and evaluate model
+    # config
+    repeats = 5
+    n_batch = 4
+    n_epochs = 500
+    n_neurons = 1
+
+    history_list = list()
+    # run diagnostic tests
+    for i in range(repeats):
+        history = train_one_model(user_data_train, user_data_val, n_batch, n_epochs, n_neurons,
+                                     sequence_length=sequence_length,
+                                     model_type=model_type)
+        history_list.append(history)
+    for metric in ['p', 'r', 'f1']:
+        for history in history_list:
+            plt.plot(history['train_'+metric], color='blue')
+            plt.plot(history['test_'+metric], color='orange')
+        plt.savefig(figure_path+metric+'_epochs_diagnostic.png')
+        plt.clf()
+    print('Done')
+
 
 if __name__ == "__main__":
     # main_two_v1()
     # visualise_results_v1()
-    test(model_type=model_type_gru)
+    #test(model_type=model_type_gru)
    # main_two_v2(model_type=model_type_gru)
     #visualise_results_v2()
+    manual_tuning(model_type=model_type_lstm)
     print('Done')