PERF: Add accurate performance measurement

Add accurate performance measurement

Author: bashtage

ci/performance.py

@@ -0,0 +1,87 @@
+from collections import OrderedDict
+
+import timeit
+
+import numpy as np
+import pandas as pd
+from randomstate.prng import (mt19937, sfmt, dsfmt, xoroshiro128plus,
+                              xorshift1024, pcg64)
+
+REPS = 3
+SIZE = 100000
+SETUP = """
+import numpy
+from numpy import array, random
+from randomstate.prng import (mt19937, sfmt, dsfmt, xoroshiro128plus,
+                              xorshift1024, pcg64)
+import randomstate
+import randomstate.prng
+
+rs = {prng}.RandomState(123456)
+f = rs.__getattribute__('{fn}')
+args = {args}
+"""
+prngs = (np.random, mt19937, sfmt, dsfmt, xoroshiro128plus, xorshift1024, pcg64)
+functions = {'randint': {'low': 2 ** 31, 'dtype': 'uint32'},
+             'random_sample': {},
+             'random_raw': {'output': False},
+             'standard_exponential': {},
+             'standard_gamma': {'shape': 2.4},
+             'standard_normal': {'method': 'zig'},
+             'multinomial': {'n': 20, 'pvals': [1.0 / 6.0] * np.ones(6)},
+             'negative_binomial': {'n': 5, 'p': 0.16},
+             'poisson': {'lam': 3.0},
+             'complex_normal': {'gamma': 2 + 0j, 'relation': 1 + 0.5j, 'method': 'zig'},
+             'laplace': {'loc': 1, 'scale': 3},
+             'binomial': {'n': 35, 'p': 0.25}}
+
+
+def timer(prng: str, fn: str, args: dict):
+    if prng == 'random':
+        # Differences with NumPy
+        if fn in ('random_raw', 'complex_normal'):
+            return np.nan
+        if fn == 'standard_normal':
+            args = {k: v for k, v in args.items() if k != 'method'}
+    elif prng == 'mt19937' and fn == 'random_raw':  # To make comparable
+        args['size'] = 2 * args['size']
+    setup = SETUP.format(prng=prng, fn=fn, args=args)
+    return min(timeit.Timer('f(**args)', setup=setup).repeat(10, REPS)) / SIZE / REPS
+
+
+results = OrderedDict()
+for prng in prngs:
+    name = prng.__name__.split('.')[-1]
+    speeds = OrderedDict()
+    for fn, args in functions.items():
+        args['size'] = SIZE
+        speeds[fn] = np.round(timer(name, fn, args) * 10 ** 9, 2)
+    results[name] = pd.Series(speeds)
+    print(name)
+    print(results[name])
+
+results = pd.DataFrame(results)
+results = results.loc[results.mean(1).sort_values().index]
+
+index = {'randint': 'Random Integers',
+         'random_sample': 'Uniforms',
+         'random_raw': 'Raw',
+         'standard_exponential': 'Exponential',
+         'standard_gamma': 'Gamma',
+         'standard_normal': 'Normal',
+         'multinomial': 'Multinomial',
+         'negative_binomial': 'Neg. Binomial',
+         'poisson': 'Poisson',
+         'complex_normal': 'Complex Normal',
+         'laplace': 'Laplace',
+         'binomial': 'Binomial'}
+
+cols = {'sfmt': 'SFMT', 'dsfmt': 'dSFMT',
+        'xoroshiro128plus': 'xoroshirt128+',
+        'xorshift1024': 'xorshift1024', 'pcg64': 'PCG64',
+        'mt19937': 'MT19937', 'random': 'NumPy MT19937'}
+
+results.columns = [cols[c] for c in results]
+results.index = [index[i] for i in results.index]
+
+print(results)

doc/source/change-log.rst

@@ -5,6 +5,7 @@ Change Log
 
 Since Version 1.13
 ------------------
+* Add SIMD-oriented Fast Mersenne Twister (`SFMT <http://www.math.sci.hiroshima-u.ac.jp/~m-mat/MT/SFMT/>`) generator.
 * Add complex normal (:meth:`~randomstate.prng.mt19937.complex_normal`)
 
 Version 1.13

doc/source/index.rst

@@ -127,6 +127,7 @@ Individual Pseudo Random Number Generators
 
    MT19937 <mt19937>
    dSFMT <dsfmt>
+   SFMT <sfmt>
    XorShift128+ <xorshift128>
    XoroShiro128+ <xoroshiro128plus>
    XorShift1024* <xorshift1024>

doc/source/performance.rst

@@ -0,0 +1,3 @@
+Performance
+-----------
+

doc/source/sfmt.rst

@@ -0,0 +1,84 @@
+SFMT Randomstate
+****************
+
+.. currentmodule:: randomstate.prng.sfmt
+
+Random generator
+================
+.. autoclass::
+   RandomState
+
+.. autosummary::
+   :toctree: generated/
+
+   seed
+   get_state
+   set_state
+
+Simple random data
+==================
+.. autosummary::
+   :toctree: generated/
+
+   rand
+   randn
+   randint
+   random_integers
+   random_sample
+   random
+   ranf
+   sample
+   choice
+   bytes
+   random_uintegers
+   random_raw
+
+Permutations
+============
+.. autosummary::
+   :toctree: generated/
+
+   shuffle
+   permutation
+
+Distributions
+=============
+.. autosummary::
+   :toctree: generated/
+
+   beta
+   binomial
+   chisquare
+   complex_normal
+   dirichlet
+   exponential
+   f
+   gamma
+   geometric
+   gumbel
+   hypergeometric
+   laplace
+   logistic
+   lognormal
+   logseries
+   multinomial
+   multivariate_normal
+   negative_binomial
+   noncentral_chisquare
+   noncentral_f
+   normal
+   pareto
+   poisson
+   power
+   rayleigh
+   standard_cauchy
+   standard_exponential
+   standard_gamma
+   standard_normal
+   standard_t
+   triangular
+   uniform
+   vonmises
+   wald
+   weibull
+   zipf