add test

PathPlanning/FrenetOptimalTrajectory/frenet_optimal_trajectory.py

@@ -333,9 +333,10 @@ def main():
             plt.pause(0.0001)
 
     print("Finish")
-    plt.grid(True)
-    plt.pause(0.0001)
-    plt.show()
+    if show_animation:
+        plt.grid(True)
+        plt.pause(0.0001)
+        plt.show()
 
 
 if __name__ == '__main__':

README.md

@@ -350,15 +350,16 @@ Ref:
 - [ghliu/pyReedsShepp: Implementation of Reeds Shepp curve\.](https://github.com/ghliu/pyReedsShepp)
 
 
-## Frenet Optimal Trajectory
+## Optimal Trajectory in a Frenet Frame 
 
 ![3](https://github.com/AtsushiSakai/PythonRobotics/blob/master/PathPlanning/FrenetOptimalTrajectory/animation.gif)
 
-It is a optimal trajectory generation on Frenet Frame.
+It is a optimal trajectory generation in a Frenet Frame.
 
-The cyan line is target course and black crosses are obstacles.
+The cyan line is the target course and black crosses are obstacles.
 
 The red line is predicted path.
+
 　
 Ref:
 
@@ -367,6 +368,7 @@ Ref:
 - [Optimal trajectory generation for dynamic street scenarios in a Frenet Frame](https://www.youtube.com/watch?v=Cj6tAQe7UCY)
 
 
+
 ## Mix Integer Optimization based model predictive planning and control
 
 ![2](https://github.com/AtsushiSakai/PythonRobotics/blob/master/PathPlanning/MixIntegerPathPlanning/animation.gif)

tests/test_frenet_optimal_trajectory.py

@@ -0,0 +1,15 @@
+from unittest import TestCase
+
+import sys
+sys.path.append("./PathPlanning/FrenetOptimalTrajectory/")
+
+from PathPlanning.FrenetOptimalTrajectory import frenet_optimal_trajectory as m
+
+print(__file__)
+
+
+class Test(TestCase):
+
+    def test1(self):
+        m.show_animation = False
+        m.main()