public async Task <HeatmapStepCache> CreateCache(DateTime startDate, DateTime endDate, HyperMetadataSet metadataSet, TimeSpan stepLength)
{
_percentageCompleted = 0;
GenerationWasCanceled = false;
GenerationProgress?.Invoke(0);
var newCache = new HeatmapStepCache()
{
MetadataSetId = metadataSet.Id
};
_stepToTasksMappings = new Dictionary <HeatmapCacheStep, MasksHeatmapRenderer>();
var tasks = new List <Task>();
var tasksCompleted = 0;
while (startDate < endDate)
{
var step = new HeatmapCacheStep
{
From = startDate,
To = startDate + stepLength > endDate ? endDate : startDate + stepLength
};
var renderer = new MasksHeatmapRenderer(_store, metadataSet, _heatmapSettings);
renderer.PertcantageProcessedUpdated += (percentageLambda) =>
{
_percentageCompleted += percentageLambda / tasks.Count;
this.GenerationProgress?.Invoke(_percentageCompleted);
};
var task = renderer.RunGenerationAsync(step.From, step.To)
.ContinueWith(t =>
{
tasksCompleted++;
});
_stepToTasksMappings[step] = renderer;
tasks.Add(task);
startDate = startDate + stepLength;
System.Diagnostics.Debug.WriteLine("Cache heatmap task added");
}
await Task.WhenAll(tasks);
newCache.Steps.AddRange(_stepToTasksMappings.Keys);
foreach (var kv in _stepToTasksMappings)
{
var step = kv.Key;
step.ImageData = kv.Value.ImageProp.Value;
}
return(newCache);
}
private void TrainButton_Click(object sender, EventArgs e)
{
int generationSize, proceedToNext, generations, maxScore, gamesToPlay;
double mutationProbability, mutationRate;
if (!int.TryParse(GenerationSize.Text, out generationSize) || generationSize < 1)
{
MessageBox.Show("Generation size must be positive integer.");
return;
}
if (!int.TryParse(ProceedToNext.Text, out proceedToNext) || proceedToNext < 1)
{
MessageBox.Show("Proceed to next size must be positive integer.");
return;
}
if (!int.TryParse(GenerationsCount.Text, out generations) || generations < 1)
{
MessageBox.Show("Maximum count of generations must be positive integer.");
return;
}
if (!int.TryParse(MaxScore.Text, out maxScore) || maxScore < 1)
{
MessageBox.Show("Maximum score must be positive integer.");
return;
}
if (!int.TryParse(GamesToPlay.Text, out gamesToPlay) || gamesToPlay < 1)
{
MessageBox.Show("Games to play must be positive integer.");
return;
}
if (!double.TryParse(MutationProbability.Text, NumberStyles.Any, CultureInfo.InvariantCulture, out mutationProbability) || mutationProbability <= 0 || mutationProbability > 1)
{
MessageBox.Show("Mutation probability must be value between 0 and 1.");
return;
}
if (!double.TryParse(MutationRate.Text, NumberStyles.Any, CultureInfo.InvariantCulture, out mutationRate) || mutationRate <= 0)
{
MessageBox.Show("Mutation rate must be positive value");
return;
}
string[] splittedNeurons = HiddenNeurons.Text.Split(new char[] { ' ' }, StringSplitOptions.RemoveEmptyEntries);
List <int> hiddenNeurons;
try
{
hiddenNeurons = splittedNeurons.Select(x => int.Parse(x)).ToList();
hiddenNeurons.ForEach(x =>
{
if (x < 1)
{
MessageBox.Show("Neurons count in hidden layers must be positive integer");
return;
}
});
}
catch
{
MessageBox.Show("Neurons count in hidden layers must be positive integer");
return;
}
scoreHistory = new List <double>();
GenerationProgress.Maximum = generationSize;
Random r = new Random();
Model defaultModel;
Game etalonGame;
if (GamesComboBox.SelectedItem == GamesComboBox.Items[0])
{
defaultModel = new Model(new NeuralNetwork(4, hiddenNeurons, 1, r), Model.Games.FlappyBird);
etalonGame = new FlappyBird(1, r, false);
}
else
{
MessageBox.Show("Dino is not supported yet");
return;
////defaultModel = new Model(new NeuralNetwork(4, hiddenNeurons, 1, r), Model.Games.FlappyBird);
//etalonGame = new Dino(1, r, false);
}
etalonGame.ControlSize = GameForm.ControlSize;
etalonGame.SetDefaultOptions();
Trainer trainer = new Trainer(defaultModel, etalonGame, generationSize,
proceedToNext, generations, maxScore,
gamesToPlay, mutationProbability, mutationRate, r);
trainer.ModelTested += (obj, value) =>
{
GenerationProgress.Invoke((MethodInvoker)(() =>
{
GenerationProgress.Value = value;
}));
};
trainer.GenerationPassed += GenerationPassed;
TrainButton.Enabled = false;
TrainingParameters.Enabled = false;
thread = new Thread(() => Train(trainer));
thread.Start();
}