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https://github.com/barrettotte/population-genetics-sim
Simulate basic population genetics on fake creatures' DNA. Concepts of mutation, crossover, fitness distribution covered. Prototype algorithm for ProcJam 2018
https://github.com/barrettotte/population-genetics-sim
genetic-analysis genetics population-genetics python simulation
Last synced: 26 days ago
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Simulate basic population genetics on fake creatures' DNA. Concepts of mutation, crossover, fitness distribution covered. Prototype algorithm for ProcJam 2018
- Host: GitHub
- URL: https://github.com/barrettotte/population-genetics-sim
- Owner: barrettotte
- Created: 2018-10-20T23:24:59.000Z (about 6 years ago)
- Default Branch: master
- Last Pushed: 2018-10-28T18:27:19.000Z (about 6 years ago)
- Last Synced: 2024-01-28T18:46:03.610Z (11 months ago)
- Topics: genetic-analysis, genetics, population-genetics, python, simulation
- Language: Python
- Homepage:
- Size: 94.7 KB
- Stars: 0
- Watchers: 3
- Forks: 0
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
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README
# Population Genetics
Simulate basic population genetics on fake creatures' DNA. Concepts of mutation, crossover, fitness distribution covered
Used for ProcJam 2018, repo located here https://github.com/barrettotte/ProcJam-2018
## Process
* **Initialize** - Population N random DNA
* **Selection** - Evaluate fitness, generate mating pool
* **Reproduction** - Repeat N times, pick parents based on "weighted random" of mating rate
* **Crossover** - Combine DNA through some crossover method
* **Mutation** - Mutate child based on mutation rate
* Add child to new generation
* Discard old population
* Repeat until ideal organism within ideal error is found
### Additional Process
* A percentage of "Top" fitness organisms will asexually reproduce to keep their ideal DNA in the mating pool.
* There is a small chance a random organism will asexually reproduce
* There is a small chance that Parent 1 will not pass any DNA and will be replaced by newly generated DNA.
* An "Ideal Error" was introduced to speed up the algorithm's execution time, since it always got close, but sometimes never made a fitness value of 0.
## Summary
* This script will simulate a generation of "creatures" generation after generation until the ideal color allele is found.
* Each creature has one allele in their "DNA" for color and is passed to offspring based on fundamentals of genetics (crossover, mutation).
* Depending on how close the creature's color allele is to the ideal allele, it is given a fitness value which affects its chances of reproducing with another creature.
* This is meant to be a prototype before ProcJam 2018 to work out any janky behavior before implementing in C# and Unity.
## Sources:
* Basics of bitwise crossover/mutation http://www.obitko.com/tutorials/genetic-algorithms/crossover-mutation.php
* Noun and Adjective Lists https://github.com/aaronbassett/Pass-phrase
## Results
```
Searching for Ideal DNA: {'color': ['00000000', '11111111', '00000000']}
Parameters:
Generation Size: 1000
Mutation Chance: 0.006
Mystery DNA Chance: 0.001
Asexual Reproduction Chance: 0.001
Top Organisms Asexually Reproduce: 0.001
Fitness Weights: [1, 2, 4, 6, 8]
Ideal Organism Allowable Error: 5
Results of Test 01:
The Ideal Organism Found: ID: 00061-00194, Name: determined detail, Fitness: 5
DNA: {'color': ['00000010', '11111110', '00000010']}
Total Generations Created: 61
Total Organisms Created: 61000
Executed for 1.662 seconds
Results of Test 02:
The Ideal Organism Found: ID: 00019-00160, Name: subdued friction, Fitness: 5
DNA: {'color': ['00000001', '11111100', '00000001']}
Total Generations Created: 19
Total Organisms Created: 19000
Executed for 0.522 seconds
Results of Test 03:
The Ideal Organism Found: ID: 00123-00461, Name: jagged growth, Fitness: 5
DNA: {'color': ['00000000', '11111100', '00000010']}
Total Generations Created: 123
Total Organisms Created: 123000
Executed for 3.438 seconds
Results of Test 04:
The Ideal Organism Found: ID: 00085-00707, Name: knowledgeable collar, Fitness: 5
DNA: {'color': ['00000001', '11111011', '00000000']}
Total Generations Created: 85
Total Organisms Created: 85000
Executed for 2.381 seconds
Results of Test 05:
The Ideal Organism Found: ID: 00030-00794, Name: festive agreement, Fitness: 4
DNA: {'color': ['00000001', '11111110', '00000010']}
Total Generations Created: 30
Total Organisms Created: 30000
Executed for 0.835 seconds
Results of Test 06:
The Ideal Organism Found: ID: 00147-00003, Name: auspicious burn, Fitness: 5
DNA: {'color': ['00000001', '11111111', '00000100']}
Total Generations Created: 147
Total Organisms Created: 147000
Executed for 4.258 seconds
Results of Test 07:
The Ideal Organism Found: ID: 00247-00272, Name: snotty number, Fitness: 5
DNA: {'color': ['00000001', '11111100', '00000001']}
Total Generations Created: 247
Total Organisms Created: 247000
Executed for 6.816 seconds
Results of Test 08:
The Ideal Organism Found: ID: 00088-00328, Name: cuddly spark, Fitness: 2
DNA: {'color': ['00000000', '11111110', '00000001']}
Total Generations Created: 88
Total Organisms Created: 88000
Executed for 2.443 seconds
Results of Test 09:
The Ideal Organism Found: ID: 00090-00693, Name: frightened brass, Fitness: 2
DNA: {'color': ['00000000', '11111101', '00000000']}
Total Generations Created: 90
Total Organisms Created: 90000
Executed for 2.547 seconds
Results of Test 10:
The Ideal Organism Found: ID: 00001-00021, Name: macabre government, Fitness: 3
DNA: {'color': ['00000000', '11111111', '00000011']}
Total Generations Created: 1
Total Organisms Created: 1000
Executed for 0.042 seconds
Ran Simulation 10 Time(s).
Average Error - 4.1
Average Execution Time - 2.494
Average Generated Generations - 90.1
Average Generated Organisms - 89100.0
```
## Console Raw
