details

systemtests/plotter_class.py

@@ -26,13 +26,11 @@ def __init__(self, sim_backend = False):
         self.EPSILON = 0.1 # euclidian distance in [m] between ideal and recorded trajectory under which the drone has to stay to pass the test (NB : epsilon is doubled for multi_trajectory test)
         self.ALLOWED_DEV_POINTS = 0.05  #allowed percentage of datapoints whose deviation > EPSILON while still passing test (currently % for fig8 and 10% for mt)
         self.DELAY_CONST_FIG8 = 4.75 #this is the delay constant which I found by adding up all the time.sleep() etc in the figure8.py file. 
-        self.DELAY_CONST_MT = 0
         if self.SIM :                #It allows to temporally adjust the ideal and real trajectories on the graph. Could this be implemented in a better (not hardcoded) way ?
             self.DELAY_CONST_FIG8 = -0.18  #for an unknown reason, the delay constant with the sim_backend is different
-            self.DELAY_CONST_MT = 0
         self.ALTITUDE_CONST_FIG8 = 1 #this is the altitude given for the takeoff in figure8.py. I should find a better solution than a symbolic constant ?
-        self.ALTITUDE_CONST_MULTITRAJ = 0 #takeoff altitude for traj0 in multi_trajectory.py
-        self.X_OFFSET_CONST_MULTITRAJ = 0 #offest on the x axis between ideal and real trajectory. Reason: ideal trajectory (traj0.csv) starts with offset of 0.3m and CrazyflieServer.startTrajectory() is relative to start position
+        # self.ALTITUDE_CONST_MULTITRAJ = 0 #takeoff altitude for traj0 in multi_trajectory.py
+        # self.X_OFFSET_CONST_MULTITRAJ = 0 #offest on the x axis between ideal and real trajectory. Reason: ideal trajectory (traj0.csv) starts with offset of 0.3m and CrazyflieServer.startTrajectory() is relative to start position
 
     def file_guard(self, pdf_path):
         msg = None
@@ -103,13 +101,13 @@ def read_csv_and_set_arrays(self, ideal_csvfile, rosbag_csvfile):
 
             self.ideal_traj_x[i], self.ideal_traj_y[i], self.ideal_traj_z[i]= pos[0], pos[1], pos[2]
 
-            #special cases 
-            if self.test_name == "fig8":                                                                                                         
-                # self.ideal_traj_z[i] = self.ALTITUDE_CONST_FIG8                     #special case: in fig8 no altitude is given in the trajectory polynomials  (idealcsv) but is fixed as the takeoff altitude in figure8.py  
-                pass
-            elif self.test_name == "m_t":                                                                   
-                self.ideal_traj_z[i] = pos[2] + self.ALTITUDE_CONST_MULTITRAJ       #for multi_trajectory the altitude given in the trajectory polynomials is added to the fixed takeoff altitude specified in multi_trajectory.py
-                self.ideal_traj_x[i] = pos[0] + self.X_OFFSET_CONST_MULTITRAJ       #the x-axis is offset by 0.3 m because ideal start position not being (0,0,0)
+            # #special cases 
+            # if self.test_name == "fig8":                                                                                                         
+            #     # self.ideal_traj_z[i] = self.ALTITUDE_CONST_FIG8                     #special case: in fig8 no altitude is given in the trajectory polynomials  (idealcsv) but is fixed as the takeoff altitude in figure8.py  
+            #     pass
+            # elif self.test_name == "m_t":                                                                   
+            #     self.ideal_traj_z[i] = pos[2] + self.ALTITUDE_CONST_MULTITRAJ      #for multi_trajectory the altitude given in the trajectory polynomials is added to the fixed takeoff altitude specified in multi_trajectory.py
+            #     self.ideal_traj_x[i] = pos[0] + self.X_OFFSET_CONST_MULTITRAJ       #the x-axis is offset by 0.3 m because ideal start position not being (0,0,0)
 
 
             self.euclidian_dist[i] = np.linalg.norm([self.ideal_traj_x[i]-self.bag_x[i], 
@@ -207,7 +205,7 @@ def create_figures(self, ideal_csvfile:str, rosbag_csvfile:str, pdfname:str, ove
             self.test_name = "mt"
             self.params["trajectory"] = "multi_trajectory"
             self.EPSILON *= 2  #multi_trajectory test has way more difficulties
-            self.ALLOWED_DEV_POINTS *= 10
+            self.ALLOWED_DEV_POINTS *= 2
             print("Plotting multi_trajectory test data")
         else:
             self.test_name = "undefined"
@@ -355,7 +353,7 @@ def test_passed(self) -> bool :
         percentage = (len(self.deviation) / len(self.bag_times)) * 100 
 
         if nb_dev_points < threshold:
-            print(f"Test {self.test_name} passed : {percentage:8.4f}% of datapoints had deviation larger than {self.EPSILON}m ({self.ALLOWED_DEV_POINTS * 100}% needed for pass)")
+            print(f"Test {self.test_name} passed : {percentage:8.4f}% of datapoints had deviation larger than {self.EPSILON}m ({self.ALLOWED_DEV_POINTS * 100}% max for pass)")
             return True
         else:
             print(f"Test {self.test_name} failed : The deviation between ideal and recorded trajectories is greater than {self.EPSILON}m for {percentage:8.4f}% of  datapoints")