imporve covergage ratio

PathPlanning/ClosedLoopRRTStar/pure_pursuit.py

@@ -131,15 +131,15 @@ def closed_loop_prediction(cx, cy, cyaw, speed_profile, goal):
         a.append(ai)
         d.append(di)
 
-        if target_ind % 1 == 0 and animation:
+        if target_ind % 1 == 0 and animation:  # pragma: no cover
             plt.cla()
             plt.plot(cx, cy, "-r", label="course")
             plt.plot(x, y, "ob", label="trajectory")
             plt.plot(cx[target_ind], cy[target_ind], "xg", label="target")
             plt.axis("equal")
             plt.grid(True)
-            plt.title("speed:" + str(round(state.v, 2)) +
-                      "tind:" + str(target_ind))
+            plt.title("speed:" + str(round(state.v, 2))
+                      + "tind:" + str(target_ind))
             plt.pause(0.0001)
 
     else:
@@ -196,7 +196,7 @@ def calc_speed_profile(cx, cy, cyaw, target_speed):
 
     speed_profile, d = set_stop_point(target_speed, cx, cy, cyaw)
 
-    if animation:
+    if animation:  # pragma: no cover
         plt.plot(speed_profile, "xb")
 
     return speed_profile
@@ -220,7 +220,7 @@ def extend_path(cx, cy, cyaw):
     return cx, cy, cyaw
 
 
-def main():
+def main():  # pragma: no cover
     #  target course
     cx = np.arange(0, 50, 0.1)
     cy = [math.sin(ix / 5.0) * ix / 2.0 for ix in cx]
@@ -277,7 +277,7 @@ def main():
     plt.axis("equal")
     plt.grid(True)
 
-    subplots(1)
+    plt.subplots(1)
     plt.plot(t, [iv * 3.6 for iv in v], "-r")
     plt.xlabel("Time[s]")
     plt.ylabel("Speed[km/h]")
@@ -285,7 +285,7 @@ def main():
     plt.show()
 
 
-def main2():
+def main2():  # pragma: no cover
     import pandas as pd
     data = pd.read_csv("rrt_course.csv")
     cx = np.array(data["x"])
@@ -321,7 +321,7 @@ def main2():
     plt.show()
 
 
-if __name__ == '__main__':
+if __name__ == '__main__':  # pragma: no cover
     print("Pure pursuit path tracking simulation start")
     #  main()
     main2()