It's not. The operators are overlpoaded differently. For matrix * means dot
product, for arrays element wise operations. There's another hand full of
features which make it different.


On Tue, Jan 15, 2013 at 2:54 PM, Christian Brodbeck <
notifications@github.com> wrote:

> In mne/transforms/transforms.py:
>
> > +        pts = trans * pts
> > +        pts = np.array(pts[:3].T)
> > +    return pts
> > +
> > +
> > +def rotation(x=0, y=0, z=0):
> > +    "Create a rotation matrix"
> > +    r = np.matrix([[cos(y) * cos(z),
> > +                    - cos(x) * sin(z) + sin(x) * sin(y) * cos(z),
> > +                    sin(x) * sin(z) + cos(x) * sin(y) * cos(z), 0],
> > +                   [cos(y) * sin(z),
> > +                    cos(x) * cos(z) + sin(x) * sin(y) * sin(z),
> > +                    - sin(x) * cos(z) + cos(x) * sin(y) * sin(z), 0],
> > +                   [-sin(y), sin(x) * cos(y), cos(x) * cos(y), 0],
> > +                   [0, 0, 0, 1]], dtype=float)
> > +    return r
>
> We could. I'm curious as to your reason, is it because np.matrix's
> behavior is inconsistent with arrays?
>
> —
> Reply to this email directly or view it on GitHub<https://github.com/mne-tools/mne-python/pull/379/files#r2649137>.
>
>