Fixes a bug in grid where the cartesian coordinate array is not set properly

CHANGELOG.rst

@@ -18,6 +18,9 @@ Bugfix
   directivity to ``Room.add_microphone_array``, the directivity was dropped
   from the object.
 
+- Fixes issue #380: Caused by the attribute ``cartesian`` of ``GridSphere`` not
+  being set properly when the grid is only initialized with a number of points.
+
 `0.8.2`_ - 2024-11-06
 ---------------------
 

pyroomacoustics/doa/grid.py

@@ -209,12 +209,11 @@ def __init__(
             # If no list was provided, samples points on the sphere
             # as uniformly as possible
 
-            self.x, self.y, self.z = fibonacci_spherical_sampling(n_points)
+            self.x[:], self.y[:], self.z[:] = fibonacci_spherical_sampling(n_points)
 
             # Create convenient arrays
             # to access both in cartesian and spherical coordinates
-            self.azimuth[:] = np.arctan2(self.y, self.x)
-            self.colatitude[:] = np.arctan2(np.sqrt(self.x**2 + self.y**2), self.z)
+            self.azimuth[:], self.colatitude[:], _ = cart2spher(self.cartesian)
 
         self._neighbors = None
         if precompute_neighbors:

pyroomacoustics/doa/tests/test_grid.py

@@ -2,7 +2,7 @@
 import pytest
 from scipy.spatial import SphericalVoronoi
 
-from pyroomacoustics.doa import fibonacci_spherical_sampling
+import pyroomacoustics as pra
 
 
 @pytest.mark.parametrize("n", [20, 100, 200, 500, 1000, 2000, 5000, 10000])
@@ -18,7 +18,7 @@ def test_voronoi_area(n, tol):
     We observed empirically that the relative max error is
     around 6% so we set that as the threshold for the test
     """
-    points = fibonacci_spherical_sampling(n_points=n)
+    points = pra.doa.fibonacci_spherical_sampling(n_points=n)
     sphere_area = 4.0 * np.pi
     area_one_pt = sphere_area / n
 
@@ -34,6 +34,43 @@ def test_voronoi_area(n, tol):
     assert max_err < tol
 
 
+def _check_grid_consistency(grid):
+
+    cart = pra.doa.spher2cart(grid.azimuth, grid.colatitude)
+    assert np.allclose(grid.cartesian, np.array([grid.x, grid.y, grid.z]))
+    assert np.allclose(grid.cartesian, cart)
+
+    az, co, _ = pra.doa.cart2spher(grid.cartesian)
+    assert np.allclose(grid.spherical, np.array([grid.azimuth, grid.colatitude]))
+    assert np.allclose(grid.spherical, np.array([az, co]))
+
+
+@pytest.mark.parametrize("n_points", [20, 100, 200, 500, 1000])
+def test_grid_sphere_from_spherical(n_points):
+
+    x, y, z = pra.doa.fibonacci_spherical_sampling(n_points)
+    az, co, _ = pra.doa.cart2spher(np.array([x, y, z]))
+
+    grid = pra.doa.GridSphere(spherical_points=np.array([az, co]))
+    _check_grid_consistency(grid)
+
+
+@pytest.mark.parametrize("n_points", [20, 100, 200, 500, 1000])
+def test_grid_sphere_from_cartesian(n_points):
+
+    x, y, z = pra.doa.fibonacci_spherical_sampling(n_points)
+
+    grid = pra.doa.GridSphere(cartesian_points=np.array([x, y, z]))
+    _check_grid_consistency(grid)
+
+
+@pytest.mark.parametrize("n_points", [20, 100, 200, 500, 1000])
+def test_grid_sphere_from_fibonacci(n_points):
+
+    grid = pra.doa.GridSphere(n_points=n_points)
+    _check_grid_consistency(grid)
+
+
 if __name__ == "__main__":
     test_voronoi_area(20, 0.01)
     test_voronoi_area(100, 0.01)