root mean square in numpy and complications of matrix and arrays of numpy

Question

Can anyone direct me to the section of numpy manual where i can get functions to accomplish root mean square calculations ... (i know this can be accomplished using np.mean and

Answer 1

For rms, the fastest expression I have found for small x.size (~ 1024) and real x is:

def rms(x):
    return np.sqrt(x.dot(x)/x.size)

This seems to be around twice as fast as the linalg.norm version (ipython %timeit on a really old laptop).

If you want complex arrays handled more appropriately then this also would work:

def rms(x):
    return np.sqrt(np.vdot(x, x)/x.size)

However, this version is nearly as slow as the norm version and only works for flat arrays.