MonkeyScope 0.1.3

Distribution Stats & Timer for Testing Non-deterministic Value Generators

MonkeyScope Beta

Distribution Timer for Non-deterministic Value Generators

Sister Projects:

• Fortuna: Collection of abstractions to make custom random value generators. https://pypi.org/project/Fortuna/
• Pyewacket: Complete drop-in replacement for the Python3 random module. https://pypi.org/project/Pyewacket/
• RNG: Python3 API for the C++ Random Library. https://pypi.org/project/RNG/

Support these and other random projects: https://www.patreon.com/brokencode

Quick Install

$ pip install MonkeyScope
$ python3
>>> import MonkeyScope ...

Installation may require the following:

• Python 3.7 or later.
• Cython: pip install Cython
• Python3 developer environment, setuptools etc.
• Modern C++17 Compiler and Standard Library.

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MonkeyScope Specifications

• MonkeyScope.distribution_timer(func: staticmethod, *args, **kwargs) -> None
  • Logger for the statistical analysis of non-deterministic output.
  • @param func :: function, method or lambda to analyze. func(*args, **kwargs)
  • @optional_kw num_cycles=10000 :: Total number of samples to use for analysis.
  • @optional_kw post_processor=None :: Used to scale a large set of data into a smaller set of groupings for better visualization of the data, esp. useful for distributions of floats. For many functions in quick_test(), math.floor() is used, for others round() is more appropriate. For more complex post processing - lambdas work nicely. Post processing only affects the distribution, the statistics and performance results are unaffected.
• MonkeyScope.distribution(func: staticmethod, *args, **kwargs) -> None
  • Stats and distribution.
• MonkeyScope.timer(func: staticmethod, *args, **kwargs) -> None
  • Just the function timer.

MonkeyScope Terminal Example

$ python3
Python 3.7.3
>>> import MonkeyScope
>>> import random
>>> MonkeyScope.timer(random.randrange, -10000, 10000, 2)
Typical Timing: 1594 ± 34 ns

MonkeyScope Script Example

import MonkeyScope
import random


MonkeyScope.distribution_timer(random.randint, 1, 10)
MonkeyScope.distribution_timer(random.randrange, 1, 10)
MonkeyScope.distribution_timer(random.randrange, 1, 10, 2)

Typical Script Output

Output Analysis: Random.randint(1, 10)
Typical Timing: 1375 ± 32 ns
Statistics of 1024 samples:
 Minimum: 1
 Median: 6
 Maximum: 10
 Mean: 5.5185546875
 Std Deviation: 2.8455943311882343
Distribution of 102400 samples:
 1: 10.1171875%
 2: 9.943359375%
 3: 9.9541015625%
 4: 9.8916015625%
 5: 10.1318359375%
 6: 10.0361328125%
 7: 9.8681640625%
 8: 10.16796875%
 9: 9.9052734375%
 10: 9.984375%

Output Analysis: Random.randrange(1, 10)
Typical Timing: 1219 ± 35 ns
Statistics of 1024 samples:
 Minimum: 1
 Median: 5
 Maximum: 9
 Mean: 4.9609375
 Std Deviation: 2.531992268646342
Distribution of 102400 samples:
 1: 11.0205078125%
 2: 11.2080078125%
 3: 11.16015625%
 4: 11.08203125%
 5: 11.1484375%
 6: 11.0791015625%
 7: 11.1923828125%
 8: 10.9375%
 9: 11.171875%

Output Analysis: Random.randrange(1, 10, 2)
Typical Timing: 1532 ± 36 ns
Statistics of 1024 samples:
 Minimum: 1
 Median: 5
 Maximum: 9
 Mean: 5.029296875
 Std Deviation: 2.8123316447928097
Distribution of 102400 samples:
 1: 19.984375%
 3: 19.931640625%
 5: 20.1552734375%
 7: 19.93359375%
 9: 19.9951171875%

ToDo List:

0. Improve Documentation
1. Concoct Examples
2. Derive Tests
3. Refactor Inception

Development Log:

MonkeyScope Beta 0.1.3

• Continued Development

MonkeyScope Beta 0.1.2

• Renamed to MonkeyScope

MonkeyTimer Beta 0.0.2

• Changed to c++ compiler

MonkeyTimer Beta 0.0.1

• Initial Project Setup