Add comments for style

main.py

@@ -2,7 +2,7 @@
 #   Cal Wing, Sem 2 2023
 
 # Import System / Common Libs 
-import os, pickle, time
+import os, pickle
 import numpy as np
 import pandas as pd
 from tqdm import tqdm
@@ -168,11 +168,13 @@ TRANS_DATA_HEADER = TIME_HEADER + IMU_WBE_HEADERS + NED_ACCELERATION_HEADER + NE
 def calculateVelocityPosition(missionData, initial_values, gpsData=None) -> pd.DataFrame:
     print("Translating Motion & Calculating Resulting Forces")
 
+    # By default this is a reference to an object, as we update it it needs to be a copy to not modify the original.
     offset = initial_values.copy()
 
     translatedData = pd.DataFrame(columns=TRANS_DATA_HEADER, dtype=float)
     for i in tqdm(range(len(missionData))):
-        mData = lambda header, j=i: missionData.loc[j, header].values 
+        mData = lambda header, j=i: missionData.loc[j, header].values # Easy value extraction
+        # dt = t[i] - t[i-1] BUT for t == 0; dt = t[i+1] - t[i]
         dt = mData(TIME_HEADER, i)[0] - mData(TIME_HEADER, i-1)[0] if i > 0 else mData(TIME_HEADER, i+1)[0] - mData(TIME_HEADER, i)[0]
 
         # Get the time point data
@@ -185,14 +187,18 @@ def calculateVelocityPosition(missionData, initial_values, gpsData=None) -> pd.D
         NED_velocity = NED_acceleration * dt + offset["velocity"]
         NED_position = NED_velocity * dt + offset["position"]
 
+        # If we have GPS data prefer that.
+        # TL;DR If GPS Data at time point use that else use above calculated position 
         if gpsData is not None and gpsData[TIME_HEADER].isin([mData(TIME_HEADER, i)[0]]).any().any():
             timeIdx = gpsData[TIME_HEADER].isin([mData(TIME_HEADER, i)[0]]).idxmax()
             NED_position = gpsData.loc[timeIdx, GPS_NED_POS_HEADER[0:]].values[0]
 
+        # Update the offsets
         offset["attitude"] = NED_attitude
         offset["velocity"] = NED_velocity
         offset["position"] = NED_position
 
+        # Add the data to the translated frame
         translatedData.loc[i, TIME_HEADER] = mData(TIME_HEADER)
         translatedData.loc[i, IMU_WBE_HEADERS] = NED_attitude_rate
         translatedData.loc[i, NED_ACCELERATION_HEADER] = NED_acceleration
@@ -203,6 +209,7 @@ def calculateVelocityPosition(missionData, initial_values, gpsData=None) -> pd.D
   
 def generateGraphs(missionData, mission, gpsData=None):
     pBar = tqdm(total=7)
+    # Graph just the R-P-Y
     graphData = {
         "figTitle":  f"Mission {mission} Flight Characteristics",
         "figTitleFontSize": 16,
@@ -240,6 +247,7 @@ def generateGraphs(missionData, mission, gpsData=None):
     makeGraph(graphData, False, False, figSavePath=f"./images/m{mission}_rpy.png")
     pBar.update(1)
 
+    # Graph the position of the UAV (Without 3D Plots)
     graphData = {
         "figTitle":  f"Mission {mission} Flight Position",
         "figTitleFontSize": 16,
@@ -284,6 +292,7 @@ def generateGraphs(missionData, mission, gpsData=None):
     makeGraph(graphData, False, False, figSavePath=f"./images/m{mission}_flight_pos.png")
     pBar.update(1)
 
+    # Graph the position of the UAV (With 3D Plots) 
     graphData = {
         "figTitle":  f"Mission {mission} Flight Position",
         "figTitleFontSize": 16,
@@ -360,6 +369,7 @@ def generateGraphs(missionData, mission, gpsData=None):
     makeGraph(graphData, False, False, figSavePath=f"./images/m{mission}_flight_pos_3d.png")
     pBar.update(1)
 
+    # Graph Just the velocity
     graphData = {
         "figTitle":  f"Mission {mission} Flight Velocity",
         "figTitleFontSize": 16,
@@ -397,6 +407,7 @@ def generateGraphs(missionData, mission, gpsData=None):
     makeGraph(graphData, False, False, figSavePath=f"./images/m{mission}_flight_velocity.png")
     pBar.update(1)
 
+    # Graph just the acceleration
     graphData = {
         "figTitle":  f"Mission {mission} Flight Acceleration",
         "figTitleFontSize": 16,
@@ -434,6 +445,7 @@ def generateGraphs(missionData, mission, gpsData=None):
     makeGraph(graphData, False, False, figSavePath=f"./images/m{mission}_flight_accell.png")
     pBar.update(1)
 
+    # Graph the position, velocity & acceleration on one big graph
     graphData = {
         "figTitle":  f"Mission {mission} Flight Characteristics",
         "figTitleFontSize": 16,
@@ -525,6 +537,7 @@ def generateGraphs(missionData, mission, gpsData=None):
     makeGraph(graphData, False, False, figSavePath=f"./images/m{mission}_flight_chars.png")
     pBar.update(1)
 
+    # Graph the R-P-Y, velocity & acceleration on one big graph
     graphData = {
         "figTitle":  f"Mission {mission} Flight Characteristics",
         "figTitleFontSize": 16,
@@ -613,21 +626,22 @@ def generateGraphs(missionData, mission, gpsData=None):
 TRUTH_NPOS_DELTA_HEADER = ["Calculated vs True Position Delta [m]", "Calculated vs True Position Error [%]"]
 def doTruthComparison(missionData, truthData):
     for i, mData in enumerate(missionData):
+        # Add & calculate the error of each position to the dataframe
         mData[TRUTH_N_POS_HEADER[1]] = truthData[i][TRUTH_N_POS_HEADER[1]]
 
         mData[TRUTH_NPOS_DELTA_HEADER[0]] = mData[NED_POSITION_HEADER[0]] - mData[TRUTH_N_POS_HEADER[1]]
         mData[TRUTH_NPOS_DELTA_HEADER[1]] = np.abs(mData[TRUTH_NPOS_DELTA_HEADER[0]]) / mData[TRUTH_N_POS_HEADER[1]] * 100
 
+        # Correct the DataType in the injected column
         mData[mData.columns] = mData[mData.columns].astype(float)
 
     return missionData
 
 def generateTruthErrorGraphs(missionData):
-    
+    # Use polyfit to generate the 2nd order polynomial to best fit the error data
-    #print(missionData[0][[IMU_TIME_HEADER[0]] + [NED_POSITION_HEADER[0]] + [TRUTH_N_POS_HEADER[1]] + [TRUTH_NPOS_DELTA_HEADER[0]]])
-
     poly_low  = np.polyfit(missionData[0][TIME_HEADER[0]], missionData[0][TRUTH_NPOS_DELTA_HEADER[0]], 2)
     poly_high = np.polyfit(missionData[1][TIME_HEADER[0]], missionData[1][TRUTH_NPOS_DELTA_HEADER[0]], 2)
+
     graphData = {
         "grid": True,
         "xLabel": "Time [s]",
@@ -641,11 +655,8 @@ def generateTruthErrorGraphs(missionData):
 
         ]
     }
-    
     makeGraph(graphData, False, False, figSavePath="./images/m1_error_delta.png")
 
-    #poly_low_perc  = np.polyfit(missionData[0][TIME_HEADER[0]], missionData[0][TRUTH_NPOS_DELTA_HEADER[1]], 2)
-    #poly_high_perc = np.polyfit(missionData[1][TIME_HEADER[0]], missionData[1][TRUTH_NPOS_DELTA_HEADER[1]], 2)
     graphData = {
         "grid": True,
         "xLabel": "Time [s]",
@@ -654,9 +665,6 @@ def generateTruthErrorGraphs(missionData):
         "plots": [
             {"x":missionData[0][TIME_HEADER[0]], "y": np.abs(missionData[0][TRUTH_NPOS_DELTA_HEADER[1]]), "label": "Low Grade IMU Error"},
             {"x":missionData[1][TIME_HEADER[0]], "y": np.abs(missionData[1][TRUTH_NPOS_DELTA_HEADER[1]]), "label": "High Grade IMU Error"},
-            #{"x":missionData[0][IMU_TIME_HEADER[0]], "y": np.polyval(poly_low_perc, missionData[0][IMU_TIME_HEADER[0]]), "label": "Low Grade Best Fit Curve"},
-            #{"x":missionData[1][IMU_TIME_HEADER[0]], "y": np.polyval(poly_high_perc, missionData[1][IMU_TIME_HEADER[0]]), "label": "High Grade Best Fit Curve"},
-
         ]
     }
     makeGraph(graphData, False, False, figSavePath="./images/m1_error_percent.png")