In [1]:

    

import numpy as np


    

In [2]:

    

a = np.arange(12).reshape(3, 4)
print(a)


    

    




[[ 0  1  2  3]
 [ 4  5  6  7]
 [ 8  9 10 11]]

In [3]:

    

%%timeit
a.ravel()


    

    




242 ns ± 2.78 ns per loop (mean ± std. dev. of 7 runs, 1000000 loops each)

In [4]:

    

%%timeit
a.flatten()


    

    




725 ns ± 45.2 ns per loop (mean ± std. dev. of 7 runs, 1000000 loops each)

In [5]:

    

%%timeit
a.reshape(-1)


    

    




851 ns ± 13.5 ns per loop (mean ± std. dev. of 7 runs, 1000000 loops each)

In [6]:

    

a_large = np.arange(1000000).reshape(100, 100, 100)


    

In [7]:

    

%%timeit
a_large.ravel()


    

    




242 ns ± 3.6 ns per loop (mean ± std. dev. of 7 runs, 1000000 loops each)

In [8]:

    

%%timeit
a_large.flatten()


    

    




2.03 ms ± 8.63 µs per loop (mean ± std. dev. of 7 runs, 1000 loops each)

In [9]:

    

%%timeit
a_large.reshape(-1)


    

    




899 ns ± 52 ns per loop (mean ± std. dev. of 7 runs, 1000000 loops each)