more black formatting

Author: petercorke

roboticstoolbox/mobile/Animations.py

@@ -5,6 +5,7 @@
 from abc import ABC
 from math import pi, atan2
 import numpy as np
+
 # from scipy import integrate, linalg, interpolate
 from pathlib import Path
 import matplotlib.pyplot as plt
@@ -14,6 +15,7 @@
 from spatialmath import SE2, base
 from roboticstoolbox import rtb_load_data
 
+
 class VehicleAnimationBase(ABC):
     """
     Abstract base class to support animation of a vehicle on Matplotlib plot
@@ -114,6 +116,7 @@ def __del__(self):
         if self._object is not None:
             self._object.remove()
 
+
 # ========================================================================= #
 class VehicleMarker(VehicleAnimationBase):
     def __init__(self, **kwargs):
@@ -161,6 +164,7 @@ def _add(self, x=None, **kwargs):
 
 # ========================================================================= #
 
+
 class VehiclePolygon(VehicleAnimationBase):
     def __init__(self, shape="car", scale=1, **kwargs):
         """
@@ -272,7 +276,7 @@ def __init__(self, filename, origin=None, scale=1, rotation=0):
 
         Creates an object that can be passed to a ``Vehicle`` subclass to
         depict the moving robot as an image icon during simulation.  The image
-        is translated and rotated to represent the vehicle configuration. 
+        is translated and rotated to represent the vehicle configuration.
 
         The car is scaled to an image with a horizontal length (width) of
         ``scale`` in the units of the plot. By default the image is assumed to
@@ -416,7 +420,7 @@ def _update(self, x):
 
     V = np.diag(np.r_[0.02, 0.5 * pi / 180] ** 2)
 
-    v = VehiclePolygon(facecolor='None', edgecolor='k')
+    v = VehiclePolygon(facecolor="None", edgecolor="k")
     # v = VehicleIcon('greycar2', scale=2, rotation=90)
 
     veh = Bicycle(covar=V, animation=v, control=RandomPath(10), verbose=False)

roboticstoolbox/mobile/DistanceTransformPlanner.py

@@ -40,7 +40,7 @@ class DistanceTransformPlanner(PlannerBase):
 
     The map is described by a 2D occupancy ``occgrid`` whose elements are zero
     if traversable of nonzero if untraversable, ie. an obstacle.
-    
+
     The cells are assumed to be unit squares. Crossing the cell horizontally or
     vertically is a travel distance of 1, and for the Euclidean distance
     measure, the crossing the cell diagonally is a distance of :math:`\sqrt{2}`.
@@ -148,7 +148,7 @@ def next(self, position):
         :raises RuntimeError: no plan has been computed
         :return: next robot position
         :rtype: ndarray(2)
-        
+
         Return the robot position that is one step closer to the goal. Called
         by :meth:`query` to find a path from start to goal.