Vbench performance benchmarks for NumPy

vb_random

numpy.random.binomial(10,0.5, size=(100,100))

Benchmark setup

import numpy

Benchmark statement

numpy.random.binomial(10,0.5, size=(100,100))

Performance graph

_images/numpy.random.binomial_10_0.5__size=_100_100__.png

numpy.random.normal(size=(100,100))

Benchmark setup

import numpy

Benchmark statement

numpy.random.normal(size=(100,100))

Performance graph

_images/numpy.random.normal_size=_100_100__.png

numpy.random.poisson(10,size=(100,100))

Benchmark setup

import numpy

Benchmark statement

numpy.random.poisson(10,size=(100,100))

Performance graph

_images/numpy.random.poisson_10_size=_100_100__.png

numpy.random.uniform(size=(100,100))

Benchmark setup

import numpy

Benchmark statement

numpy.random.uniform(size=(100,100))

Performance graph

_images/numpy.random.uniform_size=_100_100__.png

numpy.random.weibull(1, size=(100,100))

Benchmark setup

import numpy

Benchmark statement

numpy.random.weibull(1, size=(100,100))

Performance graph

_images/numpy.random.weibull_1__size=_100_100__.png

vb_random_shuffle100000

Benchmark setup

import numpy
a=numpy.arange(100000)

Benchmark statement

numpy.random.shuffle(a)

Performance graph

_images/vb_random_shuffle100000.png