erp5_wendelin_drone: update to new timestamping format

bt5/erp5_wendelin_drone/PathTemplateItem/portal_callables/DataAnalysisLine_convertDroneDataArrayToScoreArray.py

@@ -39,7 +39,16 @@ def rated_value(next_value, previous_value, rate):
 def nparray_to_dataframe(nparray):
   return pd.DataFrame(
     data=nparray.getArray(),
-    columns=["timestamp (ms)","latitude ()","longitude ()","AMSL (m)","rel altitude (m)","yaw ()","ground speed (m/s)","climb rate (m/s)"],
+    columns=[
+      'timestamp (ms)',
+      'latitude ()',
+      'longitude ()',
+      'AMSL (m)',
+      'rel altitude (m)',
+      'yaw ()',
+      'ground speed (m/s)',
+      'climb rate (m/s)',
+    ],
   )
 
 
@@ -95,70 +104,57 @@ if seen_sims is None:
 simulated_flight_list = []
 simulated_flights_value_dict_list = []
 selected_simulation_data_dict_list = []
-if len([x for x in sim_flight_names if x not in seen_sims]) == 0:
-  return
-
 
+not_seen_list = [x for x in sim_flight_names if x not in seen_sims]
+if len(not_seen_list) == 0:
+  return
 
+distance_criterion_tuple = (
+  'latitude ()',
+  'longitude ()',
+  'AMSL (m)',
+  'ground speed (m/s)',
+  'climb rate (m/s)',
+)
 
-not_seen_list = [x for x in sim_flight_names if x not in seen_sims]
-for name in not_seen_list[:]:
+for name in not_seen_list:
   if name[:14] == 'simulation_log':
     splitted_filename = name[:-4].split('_')
     distance_list_tuple = ([],[], [], [], [])
     simulated_flight = nparray_to_dataframe(sim_array.get(name))
     simulated_flight = simulated_flight.applymap(lambda value: np.format_float_scientific(float(value)) if isinstance(value, str) and 'e' in value else value)
     simulated_flight_list.append(simulated_flight)
-    max_simulator_timestamp = simulated_flight["timestamp (ms)"].max()
-    min_simulator_timestamp = simulated_flight["timestamp (ms)"].min()
-
-
-    tmp_sim = {
-    'longitude': [],
-    'latitude': [],
-    'asml': [],
-    'ground_speed': [],
-    'climb_rate': []
-    }
-    tmp_real = {
-    'longitude': [],
-    'latitude': [],
-    'asml': [],
-    'ground_speed': [],
-    'climb_rate': []
-    }
+    timestamp_diff = simulated_flight['timestamp (ms)'].min() - real_flight['timestamp (ms)'].min()
+    max_simulator_timestamp = simulated_flight['timestamp (ms)'].max() - timestamp_diff
+
+    tmp_sim = {k: [] for k in distance_criterion_tuple}
+    tmp_real = {k: [] for k in distance_criterion_tuple}
 
     for idx, row in real_flight.iterrows():
-      if max_simulator_timestamp < row["timestamp (ms)"]:
+      if max_simulator_timestamp < row['timestamp (ms)']:
         break
-      if min_simulator_timestamp > row["timestamp (ms)"]:
+
+      try:
+        under_timestamp = simulated_flight[simulated_flight['timestamp (ms)'] - timestamp_diff < row['timestamp (ms)']].tail(1)
+      except IndexError:
         continue
-      over_timestamp = simulated_flight[simulated_flight["timestamp (ms)"] >= row["timestamp (ms)"]].head(1)
-      under_timestamp = simulated_flight[simulated_flight["timestamp (ms)"] <= row["timestamp (ms)"]].tail(1)
-      rate = (float(over_timestamp["timestamp (ms)"]) - row["timestamp (ms)"])/(float(over_timestamp["timestamp (ms)"]) - float(under_timestamp["timestamp (ms)"]))
-
-      tmp_sim["latitude"].append(rated_value(float(over_timestamp["latitude ()"]), float(under_timestamp["latitude ()"]), rate))
-      tmp_sim["longitude"].append(rated_value(float(over_timestamp["longitude ()"]), float(under_timestamp["longitude ()"]), rate))
-      tmp_sim["asml"].append(rated_value(float(over_timestamp["AMSL (m)"]), float(under_timestamp["AMSL (m)"]), rate))
-      tmp_sim["ground_speed"].append(rated_value(float(over_timestamp["ground speed (m/s)"]), float(under_timestamp["ground speed (m/s)"]), rate))
-      tmp_sim["climb_rate"].append(rated_value(float(over_timestamp["climb rate (m/s)"]), float(under_timestamp["climb rate (m/s)"]), rate))
-      tmp_real["latitude"].append(row["latitude ()"])
-      tmp_real["longitude"].append(row["longitude ()"])
-      tmp_real["asml"].append(row["AMSL (m)"])
-      tmp_real["ground_speed"].append(row["ground speed (m/s)"])
-      tmp_real["climb_rate"].append(row["climb rate (m/s)"])
+      over_timestamp = simulated_flight[simulated_flight['timestamp (ms)'] - timestamp_diff >= row['timestamp (ms)']].head(1)
+      rate = (float(over_timestamp["timestamp (ms)"]) - timestamp_diff - row["timestamp (ms)"])/(float(over_timestamp["timestamp (ms)"]) - float(under_timestamp["timestamp (ms)"]))
+
+      for criterion in distance_criterion_tuple:
+        tmp_sim[criterion].append(rated_value(float(over_timestamp[criterion]), float(under_timestamp[criterion]), rate))
+        tmp_real[criterion].append(row[criterion])
 
       for index, value in enumerate((
-            row["timestamp (ms)"] / 1000,
-            distance(
-                row["latitude ()"],
-                row["longitude ()"],
-                rated_value(float(over_timestamp["latitude ()"]), float(under_timestamp["latitude ()"]), rate),
-                rated_value(float(over_timestamp["longitude ()"]), float(under_timestamp["longitude ()"]), rate),
+            row['timestamp (ms)'] / 1000,
+            distance(row['latitude ()'],
+                row['longitude ()'],
+                tmp_sim['latitude ()'][-1],
+                tmp_sim['longitude ()'][-1],
             ),
-            rated_value(float(over_timestamp["AMSL (m)"]), float(under_timestamp["AMSL (m)"]), rate) - row["AMSL (m)"],
-            rated_value(float(over_timestamp["ground speed (m/s)"]), float(under_timestamp["ground speed (m/s)"]), rate) - row["ground speed (m/s)"],
-            rated_value(float(over_timestamp["climb rate (m/s)"]), float(under_timestamp["climb rate (m/s)"]), rate) - row["climb rate (m/s)"]
+            tmp_sim['AMSL (m)'][-1],
+            tmp_sim['ground speed (m/s)'][-1],
+            tmp_real['climb rate (m/s)'][-1]
         )):
 
         distance_list_tuple[index].append(value)