On Sep 30, 2009, at 6:43 AM, Chris Colbert wrote:

Lets say I have function that applies a homogeneous transformation matrix to an Nx3 array of points using np.dot.

since the matrix is 4x4 I have to add a 4 column of ones to the array so the function looks something like this:

def foo(): <--snip--> pts = np.column_stack((Xquad, Yquad, Zquad, np.ones(Zquad.shape)))

transpts = np.dot(transmat, pts.T).T

return transpts[:,:3]

Since i'm returning just the view of the array, I imagine python doesnt garbage collect transpts once the function returns and falls out of scope (because numpy has increfed it in the view operation?).

So in essence, I still have that whole column of ones hanging around wasting memory, is that about right?

Yes. You will have the entire underlying array sitting there until the last view on it is deleted. You can make return a copy explicitly using: return transpts[:,:3].copy() Then, the transpts array will be removed when the function returns. -Travis