[issue18900] Add the random.distrib module

2013-09-07 Thread Serhiy Storchaka 

Changes by Serhiy Storchaka storch...@gmail.com:


--
stage:  - committed/rejected
status: pending - closed

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[issue18900] Add the random.distrib module

2013-09-02 Thread Serhiy Storchaka 

Serhiy Storchaka added the comment:

 In light of Raymond's comments on code bloat in issue18844, perhaps this 
 module could be added to PyPi to see whether or not there's interest in this 
 kind of functionality?

Agree. At first look there are no module which provides such features on PyPI. 
On the second hand NumpPy provides efficient C-implemented functions which are 
2-10 times faster than proposed pure Python iterators. Due to this fact I 
withdraw my proposition. Anyone who need a performance in random generation 
with specific distribution can use NumPy.

--
resolution:  - rejected
status: open - pending

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[issue18900] Add the random.distrib module

2013-09-01 Thread Serhiy Storchaka 

New submission from Serhiy Storchaka:

In some functions in the random module checking input arguments and 
precomputation takes a considerable portion of time. Here is a sample 
implementation of new random.distrib module which provides alternative faster 
interface to generating of random distributed values. It contains generators 
which generates values with same distributions as functions with same name in 
the random module.

Benchmark results:

random distrib
random() 0.061   0.055  1.12
randrange(0, 100, 5) 1.494   0.620  2.41
randint(1, 100)  1.283   0.551  2.33
uniform(-10.0, 10.0) 0.332   0.121  2.73
triangular(0.0, 10.0, 6.0)   0.661   0.317  2.09
gauss(5.0, 2.0)  0.707   0.280  2.53
normalvariate(5.0, 2.0)  0.867   0.553  1.57
lognormvariate(5.0, 2.0) 1.078   0.640  1.68
expovariate(0.1,)0.508   0.293  1.73
vonmisesvariate(1.0, 1.0)1.201   0.671  1.79
gammavariate(0.35, 1.45) 1.117   0.508  2.20
betavariate(2.71828, 3.14159)2.868   1.776  1.61
paretovariate(5.0,)  0.493   0.238  2.07
weibullvariate(1.0, 3.0) 0.670   0.402  1.67
choice([0, 1, 2, 3, 4, 5, 6...   0.887   0.594  1.49

Distrib functions are 1.5-2.8 times faster than random functions. Weighted 
choice() function (see issue18844) can be even dozens times faster (depends on 
size of the input).

In additional some random generators (i.e. gauss()) looks simpler when 
implemented as generators. distrib.gauss() is twice faster than 
distrib.normalvariate() (both generates numbers with same distribution) and I 
think some other generators can be implemented more efficient in generator 
style.

--
components: Library (Lib)
files: distrib.py
messages: 196727
nosy: mark.dickinson, rhettinger, serhiy.storchaka
priority: normal
severity: normal
status: open
title: Add the random.distrib module
type: enhancement
versions: Python 3.4
Added file: http://bugs.python.org/file31549/distrib.py

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[issue18900] Add the random.distrib module

2013-09-01 Thread Serhiy Storchaka 

Changes by Serhiy Storchaka storch...@gmail.com:


Added file: http://bugs.python.org/file31550/distrib_bench.py

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[issue18900] Add the random.distrib module

2013-09-01 Thread Madison May 

Madison May added the comment:

I like the core idea of a family of random generators, but it feels like a new 
module that's nearly identical to random introduces a lot of repeated code.

Perhaps adding an additional optional arg ('generator=False', for example) to 
these functions in the random module would be a bit simpler.

--
nosy: +madison.may

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[issue18900] Add the random.distrib module

2013-09-01 Thread Antoine Pitrou 

Changes by Antoine Pitrou pit...@free.fr:


--
nosy: +tim.peters

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[issue18900] Add the random.distrib module

2013-09-01 Thread Serhiy Storchaka 

Serhiy Storchaka added the comment:

Of course if this idea will be accepted we can turn current functions in the 
random module into wrappers around generators from the distrib module.

E.g.:

def triangular(self, *args, **kwargs):
return next(triangular(*args, random=self, **kwargs))

--

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[issue18900] Add the random.distrib module

2013-09-01 Thread Madison May 

Madison May added the comment:

 ...we can turn current functions in the random module into wrappers 
 around generators from the distrib module.

Makes sense.

In light of Raymond's comments on code bloat in issue18844, perhaps this module 
could be added to PyPi to see whether or not there's interest in this kind of 
functionality?

--

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