Dear all,
Can someone point me to a doc on dot product vectorisation ?
Here is what I try to do :
I've got a rotation function which looks like :
def rotat_scal(phi, V):
s = math.sin(phi)
c = math.cos(phi)
M = np.zeros((3, 3))
M[2, 2] = M[1, 1] = c
M[1, 2] = -s
M[2, 1] = s
M[0, 0] = 1
return np.dot(M, V)
(where phi is a scalar, and V and array of size (3,1))
Now, I want to apply it to a time series of phi and V, in a vectorised way.
So, I tried to simply add a first dimension :
Phi is now of size(n) and V (n, 3).
(I really whish to have this shape, for direct correspondance to file).
The corresponding function looks like :
def rotat_vect(phi, V):
s = np.sin(phi)
c = np.cos(phi)
M = np.zeros((len(phi), 3, 3))
M[:, 2, 2] = M[:, 1, 1] = c
M[:, 1, 2] = -s
M[:, 2, 1] = s
M[:, 0, 0] = np.ones (len(phi))
return np.dot(M, V)
It was not really a surprise to see that it didn't work :
> [...]
> return np.dot(M, V)
> ValueError: objects are not aligned
Any hint ?
Bruno.
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