From SW's laptop

batch_process.py

@@ -38,16 +38,8 @@ for input_file in input_files:
     for i in range(20, 100, 10):
 
         # 침하 예측을 수행하고 반환값 저장
-        return_values = settle_prediction_steps_main.\
+        return_values = settle_prediction_steps_main. \
-            run_settle_prediction(input_file=input_file, output_dir=output_dir,
+                            run_settle_prediction(,
-                                  final_step_predict_percent=i,
-                                  additional_predict_percent=100,
-                                  plot_show=False,
-                                  print_values=False,
-                                  run_original_hyperbolic=True,
-                                  run_nonlinear_hyperbolic=True,
-                                  run_step_prediction=True,
-                                  settle_unit=settle_unit)
 
         # 데이터프레임에 일단 및 다단 성토를 포함한 예측의 에러를 저장
         df_overall.loc[len(df_overall.index)] = [input_file, i, return_values[0], return_values[1],

controller.py

@@ -25,7 +25,8 @@ nod: number of date
 def settlement_prediction(point_name):
 
     # connect the database
-    connection = pg2.connect("host=localhost dbname=postgres user=postgres password=lab36981 port=5432")
+    #connection = pg2.connect("host=localhost dbname=postgres user=postgres password=lab36981 port=5432") # local
+    connection = pg2.connect("host=192.168.0.13 dbname=sgis user=sgis password=sgis port=5432") # ICTWay internal
 
     # set cursor
     cursor = connection.cursor()
@@ -43,9 +44,9 @@ def settlement_prediction(point_name):
 
     # fill lists
     for row in monitoring_record:
-        settlement.append(float(row[6]))
+        settlement.append(float(row[5]))
-        surcharge.append(float(row[8]))
+        surcharge.append(float(row[7]))
-        time.append(float(row[12]))
+        time.append(float(row[1]))
 
     # convert lists to np arrays
     settlement = np.array(settlement)
@@ -53,19 +54,14 @@ def settlement_prediction(point_name):
     time = np.array(time)
 
     # run the settlement prediction and get results
-    results = settle_prediction_steps_main.run_settle_prediction(point_name=point_name,
+    results = settle_prediction_steps_main.run_settle_prediction(point_name=point_name, np_time=time,
-                                                                 np_time=time,
+                                                                 np_surcharge=surcharge, np_settlement=settlement,
-                                                                 np_surcharge=surcharge,
-                                                                 np_settlement=settlement,
                                                                  final_step_predict_percent=90,
-                                                                 additional_predict_percent=300,
+                                                                 additional_predict_percent=300, plot_show=False,
-                                                                 plot_show=False,
+                                                                 print_values=False, run_original_hyperbolic=True,
-                                                                 print_values=False,
-                                                                 run_original_hyperbolic=True,
                                                                  run_nonlinear_hyperbolic=True,
                                                                  run_weighted_nonlinear_hyperbolic=True,
-                                                                 run_asaoka=True,
+                                                                 run_asaoka=True, run_step_prediction=True,
-                                                                 run_step_prediction=True,
                                                                  asaoka_interval=3)
 
     # if there are prediction data for the given data point, delete it first
@@ -73,6 +69,14 @@ def settlement_prediction(point_name):
     cursor.execute(postgres_delete_query)
     connection.commit()
 
+    # prediction method code
+    # 0: original hyperbolic method
+    # 1: nonlinear hyperbolic method
+    # 2: weighted nonlinear hyperbolic method
+    # 3: Asaoka method
+    # 4: Step loading
+    # 5: temp
+
     # insert predicted settlement into database
     for i in range(5):
 
@@ -85,7 +89,8 @@ def settlement_prediction(point_name):
 
             # construct insert query
             postgres_insert_query \
-                = """INSERT INTO apptb_pred02 (cons_code, prediction_progress_days, predicted_settlement, prediction_method) """\
+                = """INSERT INTO apptb_pred02 """ \
+                  + """(cons_code, prediction_progress_days, predicted_settlement, prediction_method) """ \
                   + """VALUES (%s, %s, %s, %s)"""
 
             # set data to insert
@@ -128,8 +133,18 @@ def read_database_and_plot(point_name):
     surcharge_monitored = np.array(surcharge_monitored)
     time_monitored = np.array(time_monitored)
 
+    # prediction method code
+    # 0: original hyperbolic method
+    # 1: nonlinear hyperbolic method
+    # 2: weighted nonlinear hyperbolic method
+    # 3: Asaoka method
+    # 4: Step loading
+    # 5: temp
+
+    # temporarily set the prediction method as 0
     prediction_method = 0
-    # select monitoring data for the monitoring point
+
+    # select predicted data for the monitoring point
     postgres_select_query = """SELECT prediction_progress_days, predicted_settlement """ \
                             + """FROM apptb_pred02 WHERE cons_code= '""" + point_name \
                             + """' and prediction_method = """ + str(prediction_method) \
@@ -169,12 +184,10 @@ def read_database_and_plot(point_name):
                  linestyle='--', color='red', label='Original Hyperbolic')
 
 
-
+# script to call: python3 controller.py [business_code] [cons_code]
-# python3 controller.py 1_SP-5
+# for example:
 if __name__ == '__main__':
     args = sys.argv[1:]
     point_name = args[0]
-    #settlement_prediction(point_name=point_name)
+    settlement_prediction(point_name=point_name)
-    read_database_and_plot(point_name=point_name)
+#    read_database_and_plot(point_name=point_name) #DB 입력 결과 확인 시에 활성화 / 평소에는 비활성화
-
-

settle_prediction_steps_main.py

@@ -79,19 +79,12 @@ def run_settle_prediction_from_file(input_file, output_dir,
     settle = data['Settlement'].to_numpy()
     surcharge = data['Surcharge'].to_numpy()
 
-    run_settle_prediction(point_name=input_file,
+    run_settle_prediction(point_name=input_file, np_time=time, np_surcharge=surcharge, np_settlement=settle,
-                          np_time=time,
-                          np_surcharge=surcharge,
-                          np_settlement=settle,
                           final_step_predict_percent=final_step_predict_percent,
-                          additional_predict_percent=additional_predict_percent,
+                          additional_predict_percent=additional_predict_percent, plot_show=plot_show,
-                          plot_show=plot_show,
+                          print_values=print_values, run_original_hyperbolic=run_original_hyperbolic,
-                          print_values=print_values,
+                          run_nonlinear_hyperbolic=run_nonlinear_hyperbolic, run_weighted_nonlinear_hyperbolic='False',
-                          run_original_hyperbolic=run_original_hyperbolic,
+                          run_asaoka=run_asaoka, run_step_prediction=run_step_prediction,
-                          run_nonlinear_hyperbolic=run_nonlinear_hyperbolic,
-                          run_weighted_nonlinear_hyperbolic='False',
-                          run_asaoka=run_asaoka,
-                          run_step_prediction=run_step_prediction,
                           asaoka_interval=asaoka_interval)
 
 def run_settle_prediction(point_name,
@@ -101,10 +94,10 @@ def run_settle_prediction(point_name,
                           print_values,
                           run_original_hyperbolic='True',
                           run_nonlinear_hyperbolic='True',
-                          run_weighted_nonlinear_hyperbolic='False',
+                          run_weighted_nonlinear_hyperbolic='True',
                           run_asaoka = 'True',
                           run_step_prediction='True',
-                          asaoka_interval = 3):
+                          asaoka_interval = 5):
 
     # ====================
     # 파일 읽기, 데이터 설정
@@ -757,6 +750,11 @@ def run_settle_prediction(point_name,
             final_error_hyper_original, final_error_hyper_nonlinear, final_error_hyper_weight_nonlinear,
             final_error_asaoka, final_error_step]
 
+#def run_postprocessing_error(point_name, np_time, np_surcharge, np_settlement):
+#    a = a + 1
+
+#def run_postprocessing_graph(point_name, np_time, np_surcharge, np_)
+#
 '''
 run_settle_prediction(input_file='data/2-5_No.39.csv',
                       output_dir='output',