Changin back sampling size

- sampling size should always be at least 2, as start and end point always have to be part of the samples
- some classes like test_endeffector use the sampling size wrong, but without changing there test methods, this bug can not be fixed

src/pybullet_industrial/g_code_processor.py

@@ -338,7 +338,7 @@ def __build_precise_path(self, g_com: int):
                     previous_postion = position
 
                 interpolation_steps = total_distance/self.interpolation_precision
-                interpolation_steps = int(np.ceil(interpolation_steps))
+                interpolation_steps = int(np.ceil(interpolation_steps)) + 2
 
         return path
 

src/pybullet_industrial/interpolation.py

@@ -38,7 +38,7 @@ def build_circular_path(center: np.array, radius: float,
         radius (float): the radius of the circle
         min_angle (float): minimum angle of the circle path
         max_angle (float): maximum angle of the circle path
-        step_num (int): the number of steps between min_angle and max_angle
+        step_num (int): the number of steps including min_angle and max_angle
         clockwise (bool): boolean value indicating if the interpolation is performed clockwise
                           or anticlockwise
 
@@ -69,14 +69,13 @@ def linear_interpolation(start_point: np.array, end_point: np.array, samples: in
     Args:
         start_point (np.array): The start point of the interpolation
         end_point (np.array): The end point of the interpolation
-        samples (int): The number of samples between start and end
+        samples (int): The number of samples including start and end
         start_orientation (np.array): Start orientation as quaternion
         end_orientation (np.array): End orientation as quaternion
 
     Returns:
         ToolPath: A ToolPath object of the interpolated path
     """
-    samples = samples + 2
     positions = np.linspace(start_point, end_point, num=samples)
     final_path = ToolPath(positions=positions.transpose())
 
@@ -103,7 +102,7 @@ def planar_circular_interpolation(start_point: np.array, end_point: np.array,
         start_point (np.array): The start point of the interpolation
         end_point (np.array): The end point of the interpolation
         radius (float): The radius of the circle
-        samples (int): The number of samples between start and end
+        samples (int): The number of including start and end
         clockwise (bool): boolean value indicating if the interpolation is performed clockwise
                             or anticlockwise
 
@@ -148,7 +147,7 @@ def circular_interpolation(start_point: np.array, end_point: np.array,
         start_point (np.array): The start point of the interpolation
         end_point (np.array): The end point of the interpolation
         radius (float): The radius of the circle used for the interpolation
-        samples (int): The number of samples between start and end
+        samples (int): The number of samples including start and end
         axis (int, optional): The axis around which the circle is interpolated.
                               Defaults to 2 which corresponds to the z-axis (0=x, 1=y).
         clockwise (bool, optional): The direction of circular travel. Defaults to True.
@@ -158,7 +157,6 @@ def circular_interpolation(start_point: np.array, end_point: np.array,
     Returns:
         ToolPath: A ToolPath object of the interpolated path
     """
-    samples = samples + 2
     all_axis = [0, 1, 2]
     all_axis.remove(axis)
 

tests/test_interpolation.py

@@ -14,7 +14,7 @@ def test_linear_interpolation(self):
         # Case 1: Test with both start and end orientations
         start_point = np.array([0.0, 0.0, 0.0])
         end_point = np.array([10.0, 10.0, 10.0])
-        samples = 3
+        samples = 5
         start_orientation = p.getQuaternionFromEuler(
             [0, 0, 0])  # Neutral orientation
         end_orientation = p.getQuaternionFromEuler(
@@ -35,7 +35,7 @@ def test_linear_interpolation(self):
         start_rot = R.from_quat(start_orientation)
         end_rot = R.from_quat(end_orientation)
         rotations = R.from_quat([start_rot.as_quat(), end_rot.as_quat()])
-        t_vals = np.linspace(0, 1, samples+2)
+        t_vals = np.linspace(0, 1, samples)
         slerp_spline = RotationSpline([0, 1], rotations)
         expected_orientations_both = slerp_spline(t_vals).as_quat()
 
@@ -58,7 +58,7 @@ def test_linear_interpolation(self):
 
         # Expected orientations for only start orientation case
         expected_orientations_start_only = np.tile(
-            start_orientation, (samples+2, 1)).transpose()
+            start_orientation, (samples, 1)).transpose()
 
         expected_toolpath_with_start_only = ToolPath(
             positions=expected_positions,
@@ -79,7 +79,7 @@ def test_circular_interpolation(self):
         start_point = np.array([1.0, 0.0, 0.0])
         end_point = np.array([0.0, 1.0, 0.0])
         radius = 1.0
-        samples = 3
+        samples = 5
         axis = 2  # Z-axis
         clockwise = True
         start_orientation = p.getQuaternionFromEuler(
@@ -102,7 +102,7 @@ def test_circular_interpolation(self):
         start_rot = R.from_quat(start_orientation)
         end_rot = R.from_quat(end_orientation)
         rotations = R.from_quat([start_rot.as_quat(), end_rot.as_quat()])
-        t_vals = np.linspace(0, 1, samples+2)
+        t_vals = np.linspace(0, 1, samples)
         slerp_spline = RotationSpline([0, 1], rotations)
         expected_orientations_both = slerp_spline(t_vals).as_quat()
 
@@ -125,7 +125,7 @@ def test_circular_interpolation(self):
 
         # Expected orientations for only start orientation case
         expected_orientations_start_only = np.tile(
-            start_orientation, (samples+2, 1)).transpose()
+            start_orientation, (samples, 1)).transpose()
 
         expected_toolpath_with_start_only = ToolPath(
             positions=expected_positions,
@@ -139,11 +139,11 @@ def test_circular_interpolation(self):
             result_with_only_start_orientation.orientations,
             expected_toolpath_with_start_only.orientations, decimal=6)
 
-    def test_sample_size(self):
+    def test_zero_sample_size(self):
         start_point = np.array([1.0, 0.0, 0.0])
         end_point = np.array([0.0, 1.0, 0.0])
         radius = 1.0
-        samples = 0
+        samples = 2
         axis = 2  # Z-axis
         clockwise = True
         start_orientation = p.getQuaternionFromEuler(