I have a 2x2 rotation matrix and several vectors stored in a Nx2 array. Is there a way to rotate them all (ie multiply them all by the rotation matrix) at once?
I'm sure there is a numpy method for that, it's just not obvious.
import numpy as np
vectors = np.array( ( (1,1), (1,2), (2,2), (4,2) ) ) # 4 2D vectors
ang = np.radians(30)
m = np.array( ( (np.cos(ang), -np.sin(ang)),
(np.sin(ang), np.cos(ang)) )) # 2x2 rotation matrix
# rotate 1 vector:
m.dot(vectors[0,:])
# rotate all vectors at once??
Because m
has shape (2,2)
and vectors
has shape (4,2)
, you can simply do
dots = vectors @ m.T
Then each row i
contains the matrix-vector product m @ vectors[i, :]
.
Another option is to use the powerful einsum
function and do:
dots = np.einsum("ij,kj->ik", vectors, m)
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