What I want to do is to rotate a 2D numpy array over a given angle. The approach I'm taking is using a rotation matrix. The rotation matrix I defined as:
angle = 65.
theta = (angle/180.) * numpy.pi
rotMatrix = numpy.array([[numpy.cos(theta), -numpy.sin(theta)],
[numpy.sin(theta), numpy.cos(theta)]])
The matrix I want to rotate is shaped (1002,1004). However, just for testing purposes I created a 2D array with shape (7,6)
c = numpy.array([[0,0,6,0,6,0], [0,0,0,8,7,0], [0,0,0,0,5,0], [0,0,0,3,4,0], [0,0,2,0,1,0], [0,8,0,0,9,0], [0,0,0,0,15,0]])
Now, when I apply the rotation matrix on my 2D array I get the following error:
c = numpy.dot(rotMatrix, c)
print c
c = numpy.dot(rotMatrix, c)
ValueError: matrices are not aligned
Exception in thread Thread-1 (most likely raised during interpreter shutdown):
What am I doing wrong?
Matrix dimensions will need to be compatible in order to obtain a matrix product. You are trying to multiply a 7x6 matrix with a 2x2 matrix. This is not mathematically coherent. It only really makes sense to apply a 2D rotation to a 2D vector to obtain the transformed coordinates.
The result of a matrix product is defined only when the left hand matrix has column count equal to right hand matrix row count.