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jrtechs-RandomScripts
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Created plotting graph for the genetic algorithm.

pull/18/head
jrtechs 5 years ago
parent
98bd2dd1c4
commit
4376164ab8
1 changed files with 182 additions and 3 deletions
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  1. +182
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      geneticAlgorithm/geneticAlgo.html

+ 182
- 3
geneticAlgorithm/geneticAlgo.html View File

@ -1,5 +1,14 @@
<html> <html>
<head> <head>
<script type="text/javascript" src="https://www.gstatic.com/charts/loader.js"></script>
<script
src="https://code.jquery.com/jquery-3.3.1.slim.min.js"
integrity="sha256-3edrmyuQ0w65f8gfBsqowzjJe2iM6n0nKciPUp8y+7E="
crossorigin="anonymous">
</script>
<link href="https://stackpath.bootstrapcdn.com/bootstrap/4.3.1/css/bootstrap.min.css" rel="stylesheet" integrity="sha384-ggOyR0iXCbMQv3Xipma34MD+dH/1fQ784/j6cY/iJTQUOhcWr7x9JvoRxT2MZw1T" crossorigin="anonymous">
<script> <script>
class Gene class Gene
{ {
@ -201,7 +210,7 @@
}; };
const runGeneticOptimization = function(geneticChromosome, constFunction,
const runGeneticOptimization = function(geneticChromosome, costFunction,
populationSize, maxGenerations, populationSize, maxGenerations,
desiredCost, mutationRate, keepNumber, desiredCost, mutationRate, keepNumber,
newBloodNumber) newBloodNumber)
@ -218,7 +227,7 @@
matePopulation(population, populationSize); matePopulation(population, populationSize);
newBlood(population, newBloodNumber); newBlood(population, newBloodNumber);
mutatePopulation(population, mutationRate); mutatePopulation(population, mutationRate);
let generationResult = naturalSelection(population, keepNumber, constFunction);
let generationResult = naturalSelection(population, keepNumber, costFunction);
if(bestCost > generationResult.bestFit) if(bestCost > generationResult.bestFit)
{ {
@ -235,19 +244,189 @@
return bestChromosome; return bestChromosome;
}; };
let genericChromosomeG, costFunctionG,
populationSizeG, maxGenerationsG,
desiredCostG, mutationRateG, keepNumberG,
newBloodNumberG, populationG, generationG,
bestCostG = Number.MAX_VALUE, bestChromosomeG = genericChromosomeG;
const runGeneticOptimizationforGraph = function()
{
let generationResult = naturalSelection(populationG, keepNumberG, costFunctionG);
if(bestCostG > generationResult.bestFit)
{
bestChromosomeG = generationResult.bestChrom;
bestCostG = generationResult.bestFit;
}
populationG = generationResult.survivors;
generationG++;
console.log("Generation " + generationG + " Best Cost: " + bestCostG);
console.log(generationResult);
matePopulation(populationG, populationSizeG);
newBlood(populationG, newBloodNumberG);
mutatePopulation(populationG, mutationRateG);
createGraph();
};
const createGraph = function()
{
var dataPoints = [];
console.log(dataPoints);
var data = new google.visualization.DataTable();
data.addColumn('number', 'Gene 1');
data.addColumn('number', 'Gene 2');
for(let i = 0; i < populationG.length; i++)
{
data.addRow([populationG[i].getGenes()[0].getRealValue(),
populationG[i].getGenes()[1].getRealValue()]);
}
var options = {
title: 'Genetic Evolution On Two Genes Generation: ' + generationG,
hAxis: {title: 'Gene 1', minValue: 0, maxValue: 10},
vAxis: {title: 'Gene 2', minValue: 0, maxValue: 10},
};
var chart = new google.visualization.ScatterChart(document.getElementById('chart_div'));
chart.draw(data, options);
};
let gene1 = new Gene(1,10,10); let gene1 = new Gene(1,10,10);
let gene2 = new Gene(1,10,0.4); let gene2 = new Gene(1,10,0.4);
let geneList = [gene1, gene2]; let geneList = [gene1, gene2];
let exampleOrganism = new Chromosome(geneList); let exampleOrganism = new Chromosome(geneList);
runGeneticOptimization(exampleOrganism, basicCostFunction, 100, 50, 0.01, 0.3, 20, 10);
genericChromosomeG = exampleOrganism;
costFunctionG = basicCostFunction;
populationSizeG = 100;
maxGenerationsG = 30;
desiredCostG = 0.00001;
mutationRateG = 0.3;
keepNumberG = 30;
newBloodNumberG = 10;
generationG = 0;
function resetPopulation()
{
autoRunning = false;
$("#runAutoOptimizer").val("Auto Run");
populationSizeG = $("#populationSize").val();
mutationRateG = $("#mutationRate").val();
keepNumberG = $("#survivalSize").val();
newBloodNumberG = $("#newBlood").val();
generationG = 0;
populationG = createRandomPopulation(genericChromosomeG, populationSizeG);
createGraph();
}
populationG = createRandomPopulation(genericChromosomeG, populationSizeG);
window.onload = function () {
google.charts.load('current', {'packages':['corechart']}).then(function()
{
createGraph();
})
};
let autoRunning = false;
function runAutoOptimizer()
{
if(autoRunning === true)
{
runGeneticOptimizationforGraph();
setTimeout(runAutoOptimizer, 1000);
}
}
function startStopAutoRun()
{
autoRunning = !autoRunning;
if(autoRunning)
{
$("#runAutoOptimizer").val("Stop Auto Run");
}
else
{
$("#runAutoOptimizer").val("Resume Auto Run");
}
runAutoOptimizer();
}
//runGeneticOptimization(exampleOrganism, basicCostFunction, 100, 50, 0.01, 0.3, 20, 10);
</script> </script>
</head> </head>
<body> <body>
<div id="chart_div" style="width: 900px; height: 500px;"></div>
<input class='btn btn-primary' id="runOptimizer" onclick='runGeneticOptimizationforGraph()' type="button" value="Next Generation">
<input class='btn btn-primary' id="runAutoOptimizer" onclick='startStopAutoRun()' type="button" value="Auto Run">
<div class="card">
<div class="card-header">
<h2>Population Variables</h2>
</div>
<div class="card-body">
<div class="row p-2">
<div class="col">
<label for="populationSize">Population Size</label>
<input type="text" class="form-control" id="populationSize" placeholder="Population Size" required>
</div>
<div class="col">
<label for="populationSize">Survival Size</label>
<input type="text" class="form-control" id="survivalSize" placeholder="Survival Size" required>
</div>
</div>
<div class="row p-2">
<div class="col">
<label for="populationSize">Mutation Rate</label>
<input type="text" class="form-control" id="mutationRate" placeholder="Mutation Rate" required>
</div>
<div class="col">
<label for="populationSize">New Organisms Per Generation</label>
<input type="text" class="form-control" id="newBlood" placeholder="New Organisms" required>
</div>
</div>
<br>
<input class='btn btn-primary' id="reset" onclick='resetPopulation()' type="button" value="Reset Population">
</div>
</div>
</body> </body>

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