Merge branch 'GH-306' into 'main'

Bugfix for 3D volume initialization (load_from_numpy)

Closes GH-306

See merge request omniverse/warp!716

warp/tests/test_volume.py

@@ -843,6 +843,33 @@ def test_volume_from_numpy(test, device):
     test.assertIsNone(sphere_vdb_array.deleter)
 
 
+def test_volume_from_numpy_3d(test, device):
+    # Volume.allocate_from_tiles() is only available with CUDA
+    mins = np.array([-3.0, -3.0, -3.0])
+    voxel_size = 0.2
+    maxs = np.array([3.0, 3.0, 3.0])
+    nums = np.ceil((maxs - mins) / (voxel_size)).astype(dtype=int)
+    centers = np.array([[-1.0, -1.0, -1.0], [0.0, 0.0, 0.0], [1.0, 1.0, 1.0]])
+    rad = 2.5
+    sphere_sdf_np = np.zeros(tuple(nums) + (3,))
+    for x in range(nums[0]):
+        for y in range(nums[1]):
+            for z in range(nums[2]):
+                for k in range(3):
+                    pos = mins + voxel_size * np.array([x, y, z])
+                    dis = np.linalg.norm(pos - centers[k])
+                    sphere_sdf_np[x, y, z, k] = dis - rad
+    sphere_vdb = wp.Volume.load_from_numpy(
+        sphere_sdf_np, mins, voxel_size, (rad + 3.0 * voxel_size,) * 3, device=device
+    )
+
+    test.assertNotEqual(sphere_vdb.id, 0)
+
+    sphere_vdb_array = sphere_vdb.array()
+    test.assertEqual(sphere_vdb_array.dtype, wp.uint8)
+    test.assertIsNone(sphere_vdb_array.deleter)
+
+
 def test_volume_aniso_transform(test, device):
     # XY-rotation + z scale
     transform = [
@@ -894,6 +921,9 @@ def test_volume_new_del(self):
 add_function_test(
     TestVolume, "test_volume_from_numpy", test_volume_from_numpy, devices=get_selected_cuda_test_devices()
 )
+add_function_test(
+    TestVolume, "test_volume_from_numpy_3d", test_volume_from_numpy_3d, devices=get_selected_cuda_test_devices()
+)
 add_function_test(
     TestVolume, "test_volume_aniso_transform", test_volume_aniso_transform, devices=get_selected_cuda_test_devices()
 )

warp/types.py

@@ -3541,8 +3541,9 @@ def load_from_numpy(
         )
         if hasattr(bg_value, "__len__"):
             # vec3, assuming the numpy array is 4D
-            padded_array = np.array((target_shape[0], target_shape[1], target_shape[2], 3), dtype=np.single)
-            padded_array[:, :, :, :] = np.array(bg_value)
+            padded_array = np.full(
+                shape=(target_shape[0], target_shape[1], target_shape[2], 3), fill_value=bg_value, dtype=np.single
+            )
             padded_array[0 : ndarray.shape[0], 0 : ndarray.shape[1], 0 : ndarray.shape[2], :] = ndarray
         else:
             padded_amount = (