gistfile1.py

import numpy as np
import timeit
def random_data(N):
    return np.random.uniform(0., 10., N)
array1 = np.array([random_data(4) for _ in range(1000)])
array2 = np.array([random_data(4) for _ in range(2000)])
def func():
    lst = []
    for elem in array1:
        # Define factors.
        a_01, a_11 = max(elem[1], 1e-10), max(elem[3], 1e-10)
        a_02, a_12 = array2[:,1], array2[:,3]
        # Combine the factors defined above.
        a_0 = a_01**2 + a_02**2
        a_1 = a_11**2 + a_12**2
        Bs, Cs = -0.5/a_0, -0.5/a_1
        # Perform operations.
        A = 1./(np.sqrt(a_0*a_1))
        B = Bs*(elem[0]-array2[:,0])**2
        C = Cs*(elem[2]-array2[:,2])**2
        ABC = A*np.exp(B+C)
        lst.append(max(ABC.sum(), 1e-10))
    return lst
def func2():
    lst = []
    # Define factors.
    a_02, a_12 = array2[:,1], array2[:,3]
    a_022 = a_02 ** 2
    a_122 = a_12 ** 2
    e10 = np.array([1e-10 for _ in xrange(len(array1))])
    a_01 = np.maximum(array1[:,1], e10)
    a_11 = np.maximum(array1[:,3], e10)
    for i, elem in enumerate(array1):
        # Combine the factors defined above.
        a_0 = a_01[i]**2 + a_022
        a_1 = a_11[i]**2 + a_122
        Bs, Cs = -0.5/a_0, -0.5/a_1
        # Perform operations.
        A = 1./(np.sqrt(a_0*a_1))
        B = Cs*(elem[0]-array2[:,0])**2
        C = Cs*(elem[2]-array2[:,2])**2
        ABC = A*np.exp(B+C)
        lst.append(max(ABC.sum(), 1e-10))
    return lst
N = 100
func_time = timeit.timeit(func, number=N)
print "Original\t", func_time / N
print "-" * 50
func2_time = timeit.timeit(func2, number=N)
print "Revision 1\t", func2_time / N
print "Improvement\t", str(int((func_time - func2_time) / func_time * 100)) + "%"
print "-" * 50