convolution:

import convolution, numpy
a = numpy.ones((1000, 1000))
%timeit convolution.convolution(a)

fbcorr:

from random import random
imgs = [[[[random() for i in xrange(8)] for j in xrange(32)] for j in xrange(32)] for k in xrange(32)]
filters = [[[[random() for i in xrange(8)] for j in xrange(5)] for j in xrange(5)] for k in xrange(6)]
import numpy
imgs = numpy.array(imgs)
filters = numpy.array(filters)
import fbcorr
%timeit fbcorr.fbcorr(imgs, filters)

pi_buffon:

import pi_buffon
%timeit pi_buffon.pi_estimate(40000000)

mandel:

import mandel
%timeit mandel.mandel(800, 0, 0, 800)

matmul:

import matmul
import numpy
a = numpy.array([[float(i) for i in xrange(600)] for j in xrange(600)])
%timeit matmul.matrix_multiply(a, a)

pairwise:

import random, numpy, pairwise
X = numpy.array([[random.random() for i in xrange(10000) ] for j in xrange(30) ])
%timeit pairwise.pairwise(X)
