FAQ

• Convert pose object to NumPy array
• Plotting with Jupyter notebook
• Convert between SE3 and SO3

Convert pose object to NumPy array

All pose objects have a .A property which is the underlying NumPy array

>>> T = SE3.Tx(2)
>>> T.A
Out[16]: array([[ 1, 0, 0, 2],
[ 0, 1, 0, 0],
[ 0, 0, 1, 0],
[ 0, 0, 0, 1]])

If the object has multiple values the result will be a list of NumPy arrays

>>> T=SE3.Tx([2,3,4])
>>> T.A
[array([[ 1, 0, 0, 2],
[ 0, 1, 0, 0],
[ 0, 0, 1, 0],
[ 0, 0, 0, 1]]),
array([[ 1, 0, 0, 3],
[ 0, 1, 0, 0],
[ 0, 0, 1, 0],
[ 0, 0, 0, 1]]),
array([[ 1, 0, 0, 4],
[ 0, 1, 0, 0],
[ 0, 0, 1, 0],
[ 0, 0, 0, 1]])]

Plotting with Jupyter notebook

Plots will appear within the notebook if use the

%matplotlib notebook

magic command. However this is incapable of showing animations, for that to work you need the graphics window to "pop out" so choose a different backend.

Convert between SE3 and SO3

It is frequently necessary to convert between these types. The constructors handle a variety of types so the easiest way to do this is

>>> R = SO3.Rx(0.3)
>>> T = SE3(R)
>>> T
1 0 0 0 0 0.9553 -0.2955 0 0 0.2955 0.9553 0 0 0 0 1 

The opposite operation is

>>> SO3(T)
1 0 0 0 0.9553 -0.2955 0 0.2955 0.9553 

Note that the .R property gives an SO(3) NumPy array not an SO3 object

>>> T.R
array([[ 1, 0, 0],
[ 0, 0.9553, -0.2955],
[ 0, 0.2955, 0.9553]])