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from collections import OrderedDict
from timeit import repeat
import numpy as np
import pandas as pd
from numpy.random import MT19937, DSFMT, ThreeFry, Philox, Xoshiro256, \
Xoshiro512
PRNGS = [DSFMT, MT19937, Philox, ThreeFry, Xoshiro256, Xoshiro512]
funcs = {'32-bit Unsigned Ints': 'integers(0, 2**32,size=1000000, dtype="uint32")',
'64-bit Unsigned Ints': 'integers(0, 2**64,size=1000000, dtype="uint64")',
'Uniforms': 'random(size=1000000)',
'Normals': 'standard_normal(size=1000000)',
'Exponentials': 'standard_exponential(size=1000000)',
'Gammas': 'standard_gamma(3.0,size=1000000)',
'Binomials': 'binomial(9, .1, size=1000000)',
'Laplaces': 'laplace(size=1000000)',
'Poissons': 'poisson(3.0, size=1000000)', }
setup = """
from numpy.random import {prng}, Generator
rg = Generator({prng}())
"""
test = "rg.{func}"
table = OrderedDict()
for prng in PRNGS:
print(prng)
col = OrderedDict()
for key in funcs:
t = repeat(test.format(func=funcs[key]),
setup.format(prng=prng().__class__.__name__),
number=1, repeat=3)
col[key] = 1000 * min(t)
col = pd.Series(col)
table[prng().__class__.__name__] = col
npfuncs = OrderedDict()
npfuncs.update(funcs)
npfuncs['32-bit Unsigned Ints'] = 'randint(2**32,dtype="uint32",size=1000000)'
npfuncs['64-bit Unsigned Ints'] = 'tomaxint(size=1000000)'
setup = """
from numpy.random import RandomState
rg = RandomState()
"""
col = {}
for key in npfuncs:
t = repeat(test.format(func=npfuncs[key]),
setup.format(prng=prng().__class__.__name__),
number=1, repeat=3)
col[key] = 1000 * min(t)
table['NumPy'] = pd.Series(col)
table = pd.DataFrame(table)
table = table.reindex(table.mean(1).sort_values().index)
order = np.log(table).mean().sort_values().index
table = table.T
table = table.reindex(order)
table = table.T
print(table.to_csv(float_format='%0.1f'))
rel = table.loc[:, ['NumPy']].values @ np.ones((1, table.shape[1])) / table
rel.pop(rel.columns[0])
rel = rel.T
rel['Overall'] = np.exp(np.log(rel).mean(1))
rel *= 100
rel = np.round(rel)
rel = rel.T
print(rel.to_csv(float_format='%0d'))
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