!hostname

compute1-us

$\int_0^\infty x\; \mathrm{d}x$

import numpy as np; np; np.__version__

'1.10.2'

import pandas as pd

import numba
print(numba)
numba.__version__

<module 'numba' from '/projects/anaconda3/lib/python3.5/site-packages/numba/__init__.py'>

'0.23.1'

def faster(x, y):
    a = 0.0
    for i in range(x):
        for j in range(i, x):
            b = a
            a += y * .2
            a -= y * .1
            a = (a + b) / 2.
    return a

%timeit faster(2222, 1.111)

1 loop, best of 3: 375 ms per loop

import numba
faster2 = numba.autojit(faster)

%timeit faster2(2222, 1.111)

The slowest run took 7.94 times longer than the fastest. This could mean that an intermediate result is being cached.
100 loops, best of 3: 10.4 ms per loop

def f2(x, y):
    k = 0
    for i in range(x):
        for j in range(y):
            k += i / x + j / y
    return k

%timeit f2(200, 300)

@numba.jit(nopython=True, nogil=True)
def f(x, y):
    k = 0
    for i in range(x):
        for j in range(y):
            k += i / x + j / y
    return k

%timeit f(200, 300)

%matplotlib inline
import matplotlib.pyplot as plt

plt.plot([f(x, 2.2) for x in range(1000)])

np.test()

np.__version__