Testing numpy and scipy setups

test_numpy.py

#!/usr/bin/env python                                                           
import numpy
import sys
import timeit

try:
    import numpy.core._dotblas
    print 'FAST BLAS'
except ImportError:
    print 'slow blas'

print "version:", numpy.__version__
print "maxint:", sys.maxint
print

x = numpy.random.random((1000,1000))

setup = "import numpy; x = numpy.random.random((1000,1000))"
count = 5

t = timeit.Timer("numpy.dot(x, x.T)", setup=setup)
print "dot:", t.timeit(count)/count, "sec"

test_scipy.py

#!/usr/bin/env python                                                           
import timeit


setup = "import numpy;\
        import scipy.linalg as linalg;\
        x = numpy.random.random((1000,1000));\
        z = numpy.dot(x, x.T)"
count = 5

t = timeit.Timer("linalg.cholesky(z, lower=True)", setup=setup)
print "cholesky:", t.timeit(count)/count, "sec"

t = timeit.Timer("linalg.svd(z)", setup=setup)
print "svd:", t.timeit(count)/count, "sec"

Note that in recent numpy versions (>1.10) it will always report SLOW BLAS due to the missing numpy.core._dotblas.

Here's a more updated way of checking if it's linked properly:
http://stackoverflow.com/questions/21671040/link-atlas-mkl-to-an-installed-numpy/21673585#21673585