Fixed order in function cartesian_to_spherical (#2168)

* Fixed spherical coords order in cartesian_to_spherical

* Fixed space_ops tests

* [pre-commit.ci] auto fixes from pre-commit.com hooks

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Co-authored-by: pre-commit-ci[bot] <66853113+pre-commit-ci[bot]@users.noreply.github.com>
Co-authored-by: Oliver <44864613+PhotonSpheres@users.noreply.github.com>
Co-authored-by: Benjamin Hackl <devel@benjamin-hackl.at>
Co-authored-by: Darylgolden <darylgolden@gmail.com>

manim/mobject/geometry.py

@@ -179,16 +179,16 @@ class TipableVMobject(VMobject, metaclass=ConvertToOpenGL):
             anchor = self.get_end()
         angles = cartesian_to_spherical(handle - anchor)
         tip.rotate(
-            angles[2] - PI - tip.tip_angle,
+            angles[1] - PI - tip.tip_angle,
         )  # Rotates the tip along the azimuthal
         if not hasattr(self, "_init_positioning_axis"):
             axis = [
-                np.sin(angles[2]),
-                -np.cos(angles[2]),
+                np.sin(angles[1]),
+                -np.cos(angles[1]),
                 0,
             ]  # Obtains the perpendicular of the tip
             tip.rotate(
-                -angles[1] + PI / 2,
+                -angles[2] + PI / 2,
                 axis=axis,
             )  # Rotates the tip along the vertical wrt the axis
             self._init_positioning_axis = axis

manim/utils/space_ops.py

@@ -769,7 +769,7 @@ def cartesian_to_spherical(vec: Sequence[float]) -> np.ndarray:
     r = norm
     phi = np.arccos(vec[2] / r)
     theta = np.arctan2(vec[1], vec[0])
-    return np.array([r, phi, theta])
+    return np.array([r, theta, phi])
 
 
 def spherical_to_cartesian(spherical: Sequence[float]) -> np.ndarray:

tests/test_space_ops.py

@@ -8,6 +8,6 @@ def test_polar_coords():
     b = (2, np.pi / 2, np.pi / 2)
     assert all(
         np.round(cartesian_to_spherical(a), 4)
-        == np.round([2 ** 0.5, np.pi / 2, np.pi / 4], 4),
+        == np.round([2 ** 0.5, np.pi / 4, np.pi / 2], 4),
     )
     assert all(np.round(spherical_to_cartesian(b), 4) == np.array([0, 2, 0]))