benchmark_array_creation.py

"""Benchmarking of numpy array creation through loops, indexing, list 
comprehension and generator expressions.

Requires:

- pip install numpy pytest pytest-benchmark

Run with:

    pytest benchmark_array_creation.py

Output of benchmarking:

-------------------------------------------- benchmark: 4 tests ---------------
Name (time in us)         Min                 Max               Mean           
-------------------------------------------------------------------------------
test_generator         4.9000 (1.0)      101.4000 (1.0)       5.3245 (1.0)     
test_loop             77.3000 (15.78)    275.3000 (2.71)     81.2008 (15.25)   
test_indexing         79.4000 (16.20)    210.7000 (2.08)     82.5907 (15.51)   
test_list_comp        80.8000 (16.49)    361.4000 (3.56)     85.3600 (16.03)   
-------------------------------------------------------------------------------

--------------------------------------------------------------------------
Name (time in us)    StdDev             Median               IQR          
--------------------------------------------------------------------------
test_generator       1.5265 (1.0)       5.1000 (1.0)      0.1000 (1.0)    
test_loop           10.9756 (7.19)     78.7000 (15.43)    1.5000 (15.00)  
test_indexing        6.8805 (4.51)     80.8000 (15.84)    1.4000 (14.00)  
test_list_comp      12.3128 (8.07)     82.1000 (16.10)    1.5000 (15.00)  
--------------------------------------------------------------------------

-------------------------------------------------------------------------
Name (time in us)    Outliers  OPS (Kops/s)            Rounds  Iterations
-------------------------------------------------------------------------
test_generator      1175;1717      187.8125 (1.0)       39526           1
test_loop            299;1166       12.3151 (0.07)       8217           1
test_indexing         296;828       12.1079 (0.06)       5077           1
test_list_comp       361;1220       11.7151 (0.06)       7408           1
-------------------------------------------------------------------------

Moral of the story: use generator expressions it is about 15 times faster.

"""

import numpy as np


nodes = np.array(
    [
        [0, 0, 0],
        [0.5, 0.5, 0.5],
        [1, 1, 1],
        [2, 2, 2],
        [3, 3, 3],
        [4, 4, 4],
        [5, 5, 5],
        [6, 6, 6],
    ]
)


def test_indexing(benchmark):
    def indexing():
        return np.array(
            [
                np.sqrt(np.sum(np.square(nodes[i + 1] - nodes[i])))
                for i in range(nodes.shape[0] - 1)
            ]
        )

    length = benchmark(indexing)


def test_list_comp(benchmark):
    def list_comp():
        return np.array(
            [
                np.sqrt(np.sum(np.square(end - start)))
                for start, end in zip(nodes[:-1], nodes[1:])
            ]
        )

    length = benchmark(list_comp)


def test_generator(benchmark):
    def generator():
        return np.array(
            (
                np.sqrt(np.sum(np.square(end - start)))
                for start, end in zip(nodes[:-1], nodes[1:])
            )
        )

    length = benchmark(generator)


def test_loop(benchmark):
    def loop():
        length = np.zeros((nodes.shape[0],))
        for i in range(nodes.shape[0] - 1):
            length[i] = np.sqrt(np.sum(np.square(nodes[i + 1] - nodes[i])))
        return length

    length = benchmark(loop)