code clean up for LGTM

AerialNavigation/drone_3d_trajectory_following/drone_3d_trajectory_following.py

@@ -73,8 +73,8 @@ def quad_sim(x_c, y_c, z_c):
             # des_x_pos = calculate_position(x_c[i], t)
             # des_y_pos = calculate_position(y_c[i], t)
             des_z_pos = calculate_position(z_c[i], t)
-            des_x_vel = calculate_velocity(x_c[i], t)
+            # des_x_vel = calculate_velocity(x_c[i], t)
-            des_y_vel = calculate_velocity(y_c[i], t)
+            # des_y_vel = calculate_velocity(y_c[i], t)
             des_z_vel = calculate_velocity(z_c[i], t)
             des_x_acc = calculate_acceleration(x_c[i], t)
             des_y_acc = calculate_acceleration(y_c[i], t)

AerialNavigation/rocket_powered_landing/rocket_powered_landing.py

@@ -576,7 +576,7 @@ def plot_animation(X, U):  # pragma: no cover
         axis3d_equal(X[2, :], X[3, :], X[1, :], ax)
 
         rx, ry, rz = X[1:4, k]
-        vx, vy, vz = X[4:7, k]
+        # vx, vy, vz = X[4:7, k]
         qw, qx, qy, qz = X[7:11, k]
 
         CBI = np.array([
@@ -618,8 +618,6 @@ def main():
     integrator = Integrator(m, K)
     problem = SCProblem(m, K)
 
-    last_linear_cost = None
-
     converged = False
     w_delta = W_DELTA
     for it in range(iterations):
@@ -633,7 +631,7 @@ def main():
                                X_last=X, U_last=U, sigma_last=sigma,
                                weight_sigma=W_SIGMA, weight_nu=W_NU,
                                weight_delta=w_delta, weight_delta_sigma=W_DELTA_SIGMA)
-        info = problem.solve()
+        problem.solve()
 
         X = problem.get_variable('X')
         U = problem.get_variable('U')

ArmNavigation/arm_obstacle_navigation/arm_obstacle_navigation_2.py

@@ -53,7 +53,7 @@ def animate(grid, arm, route):
         theta2 = 2 * pi * node[1] / M - pi
         arm.update_joints([theta1, theta2])
         plt.subplot(1, 2, 2)
-        arm.plot(plt, obstacles=obstacles)
+        arm.plot_arm(plt, obstacles=obstacles)
         plt.xlim(-2.0, 2.0)
         plt.ylim(-3.0, 3.0)
         plt.show()
@@ -272,7 +272,7 @@ class NLinkArm(object):
 
         self.end_effector = np.array(self.points[self.n_links]).T
 
-    def plot(self, myplt, obstacles=[]):  # pragma: no cover
+    def plot_arm(self, myplt, obstacles=[]):  # pragma: no cover
         myplt.cla()
 
         for obstacle in obstacles:

PathPlanning/ClosedLoopRRTStar/pure_pursuit.py

@@ -222,7 +222,6 @@ def extend_path(cx, cy, cyaw):
 
 def main():
     #  target course
-    import numpy as np
     cx = np.arange(0, 50, 0.1)
     cy = [math.sin(ix / 5.0) * ix / 2.0 for ix in cx]
 

PathPlanning/LQRPlanner/LQRplanner.py

@@ -73,7 +73,6 @@ def solve_DARE(A, B, Q, R):
         Xn = A.T * X * A - A.T * X * B * \
             la.inv(R + B.T * X * B) * B.T * X * A + Q
         if (abs(Xn - X)).max() < eps:
-            X = Xn
             break
         X = Xn
 

PathPlanning/PotentialFieldPlanning/potential_field_planning.py

@@ -157,7 +157,7 @@ def main():
         plt.axis("equal")
 
     # path generation
-    rx, ry = potential_field_planning(
+    _, _ = potential_field_planning(
         sx, sy, gx, gy, ox, oy, grid_size, robot_radius)
 
     if show_animation:

PathTracking/lqr_steer_control/lqr_steer_control.py

@@ -5,15 +5,18 @@ Path tracking simulation with LQR steering control and PID speed control.
 author Atsushi Sakai (@Atsushi_twi)
 
 """
-
+import scipy.linalg as la
+import matplotlib.pyplot as plt
+import math
+import numpy as np
 import sys
 sys.path.append("../../PathPlanning/CubicSpline/")
 
-import numpy as np
+try:
-import math
-import matplotlib.pyplot as plt
-import scipy.linalg as la
     import cubic_spline_planner
+except:
+    raise
+
 
 Kp = 1.0  # speed proportional gain
 
@@ -76,7 +79,6 @@ def solve_DARE(A, B, Q, R):
         Xn = A.T @ X @ A - A.T @ X @ B @ \
             la.inv(R + B.T @ X @ B) @ B.T @ X @ A + Q
         if (abs(Xn - X)).max() < eps:
-            X = Xn
             break
         X = Xn
 
@@ -206,8 +208,8 @@ def closed_loop_prediction(cx, cy, cyaw, ck, speed_profile, goal):
             plt.plot(cx[target_ind], cy[target_ind], "xg", label="target")
             plt.axis("equal")
             plt.grid(True)
-            plt.title("speed[km/h]:" + str(round(state.v * 3.6, 2)) +
+            plt.title("speed[km/h]:" + str(round(state.v * 3.6, 2))
-                      ",target index:" + str(target_ind))
+                      + ",target index:" + str(target_ind))
             plt.pause(0.0001)
 
     return t, x, y, yaw, v

PathTracking/pure_pursuit/pure_pursuit.py

@@ -140,6 +140,7 @@ def main():
     assert lastIndex >= target_ind, "Cannot goal"
 
     if show_animation:
+        plt.cla()
         plt.plot(cx, cy, ".r", label="course")
         plt.plot(x, y, "-b", label="trajectory")
         plt.legend()
@@ -148,7 +149,7 @@ def main():
         plt.axis("equal")
         plt.grid(True)
 
-        flg, ax = plt.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]")