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Distribution Stats & Timer for Testing Non-deterministic Value Generators

Project description

MonkeyScope Beta

Distribution Timer for Non-deterministic Value Generators

Sister Projects:

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.

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:

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

Development Log:

MonkeyScope Beta 0.1.4
  • Minor Bug Fix
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

Project details


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