Q:

Rotation of a 2D array over an angle using rotation matrix

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?

A:

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.

A:

You seem to be looking for scipy.ndimage.interpolation.rotate, or similar. If you specifically want 90, 180, or 270 degree rotations, which do not require interpolation, then numpy.rot90 is better.

