In IPython, we can profile small snippets of code using timeit. We can also profile a larger script. We will show both approaches.
First, we will time a small snippet.
Start IPython in pylab mode:
ipython -pylab
Create an array containing 1000 integer values between 0 and 1000:
In [1]: a = arange(1000)
Measure the time taken for searching "the answer to everything"—42, in the array. Yes, the answer to everything is 42. If you don't believe me please read http://en.wikipedia.org/wiki/42_%28number%29.
In [2]: %timeit searchsorted(a, 42) 100000 loops, best of 3: 7.58 us per loop
Profile a script.
We will profile this small script that inverts a matrix of varying size containing random values. The
.Iattribute (that's uppercase I) of a NumPy array represents the inverse of a matrix:import numpy def invert(n): a = numpy.matrix(numpy.random.rand(n, n)) return a.I sizes = 2 ** numpy.arange(0, 12) for n in sizes: invert(n)
We can time this as...