scipy.spatial.transform.Rotation.

# as_matrix#

Rotation.as_matrix(self)#

Represent as rotation matrix.

3D rotations can be represented using rotation matrices, which are 3 x 3 real orthogonal matrices with determinant equal to +1 [1].

Returns:
matrixndarray, shape (3, 3) or (N, 3, 3)

Shape depends on shape of inputs used for initialization.

Notes

This function was called as_dcm before.

References

Examples

```>>> from scipy.spatial.transform import Rotation as R
>>> import numpy as np
```

Represent a single rotation:

```>>> r = R.from_rotvec([0, 0, np.pi/2])
>>> r.as_matrix()
array([[ 2.22044605e-16, -1.00000000e+00,  0.00000000e+00],
[ 1.00000000e+00,  2.22044605e-16,  0.00000000e+00],
[ 0.00000000e+00,  0.00000000e+00,  1.00000000e+00]])
>>> r.as_matrix().shape
(3, 3)
```

Represent a stack with a single rotation:

```>>> r = R.from_quat([[1, 1, 0, 0]])
>>> r.as_matrix()
array([[[ 0.,  1.,  0.],
[ 1.,  0.,  0.],
[ 0.,  0., -1.]]])
>>> r.as_matrix().shape
(1, 3, 3)
```

Represent multiple rotations:

```>>> r = R.from_rotvec([[np.pi/2, 0, 0], [0, 0, np.pi/2]])
>>> r.as_matrix()
array([[[ 1.00000000e+00,  0.00000000e+00,  0.00000000e+00],
[ 0.00000000e+00,  2.22044605e-16, -1.00000000e+00],
[ 0.00000000e+00,  1.00000000e+00,  2.22044605e-16]],
[[ 2.22044605e-16, -1.00000000e+00,  0.00000000e+00],
[ 1.00000000e+00,  2.22044605e-16,  0.00000000e+00],
[ 0.00000000e+00,  0.00000000e+00,  1.00000000e+00]]])
>>> r.as_matrix().shape
(2, 3, 3)
```