private void Timer_Tick(object sender, EventArgs e)
{
// This uses the eval's duration, and uses a neural net for the trial tick count. This is to recreate what the training actually sees
try
{
imageInput.Source = null;
canvasMain.Children.Clear();
DateTime now = DateTime.UtcNow;
if (_harness == null || _evalArgs == null)
{
_prevTick = now;
return;
}
// Reset
if (_tickCounter >= _evalArgs.TotalNumberEvaluations)
{
#region reset
if (_experiment != null)
{
NeatGenome winner = _ea.CurrentChampGenome;
_genomeViewer.RefreshView(winner);
if (winner == null)
{
_prevTick = now;
return;
}
bool showedHyper = false;
if (_experiment.IsHyperNEAT)
{
var decoder = _experiment.CreateGenomeDecoder(_hyperneatArgs);
if (decoder is HyperNeatDecoder hyperDecoder)
{
//NOTE: There is a flaw. The INetworkDefinition that this method returns is acyclic, but the method that generates the IBlackBox is CreateSubstrateNetwork_FastCyclicNetwork.
//So that INetworkDefinition seems to be limited or incorrect
//
//Actually, that might not be a flaw. The FastCyclic may be processing the CPPN which is cyclic
var finalPhenome = hyperDecoder.Decode2(winner);
_genomeViewer2.RefreshView(finalPhenome.Item2);
nnViewerHost2.Visibility = Visibility.Visible;
showedHyper = true;
}
}
if (!showedHyper)
{
nnViewerHost2.Visibility = Visibility.Collapsed;
}
if (_experiment.IsHyperNEAT)
{
_winningBrain = _experiment.GetBlackBox(winner, _hyperneatArgs);
}
else
{
_winningBrain = _experiment.GetBlackBox(winner);
}
_winningBrainTime = now;
_harness.ClearItem();
_harness.SetItem(AntPos_Evaluator.GetNewItem(_harness, _evalArgs));
_tickCounter = -1;
}
#endregion
}
// Tell the harness to go
_harness.Tick(_evalArgs.ElapsedTime_Seconds);
_tickCounter++;
var prevPosition = _harness.GetPreviousPosition(_harness.Time - _evalArgs.Delay_Seconds);
var currentPosition = _harness.Item;
#region draw input
double[] inputArr = new double[_harness.InputSizeXY * _harness.InputSizeXY];
AntPos_Evaluator.ClearArray(inputArr);
if (prevPosition != null)
{
double dotRadius = (_harness.VisionSize / _harness.InputSizeXY) * Math.Sqrt(2);
AntPos_Evaluator.ApplyPoint(inputArr, _harness.InputCellCenters, dotRadius, prevPosition.Item2, true);
}
imageInput.Source = UtilityWPF.GetBitmap(inputArr, _harness.InputSizeXY, _harness.InputSizeXY, invert: true);
#endregion
#region draw expected output
double[] expectedOutput = null;
if (currentPosition == null)
{
expectedOutput = AntPos_Evaluator.GetExpectedOutput(null, _harness, _evalArgs);
}
else
{
var currentPos = Tuple.Create(currentPosition, currentPosition.Position, currentPosition.Velocity);
expectedOutput = AntPos_Evaluator.GetExpectedOutput(currentPos, _harness, _evalArgs);
}
imageExpectedOutput.Source = UtilityWPF.GetBitmap(expectedOutput, _harness.OutputSizeXY, _harness.OutputSizeXY, invert: true);
#endregion
#region draw nn output
double[] nnOutput = null;
if (_winningBrain != null)
{
nnOutput = new double[_harness.OutputSizeXY * _harness.OutputSizeXY];
// Brain.Tick
_winningBrain.InputSignalArray.CopyFrom(inputArr, 0);
_winningBrain.Activate();
_winningBrain.OutputSignalArray.CopyTo(nnOutput, 0);
imageNNOutput.Source = UtilityWPF.GetBitmap(nnOutput, _harness.OutputSizeXY, _harness.OutputSizeXY, invert: true);
}
else
{
imageNNOutput.Source = null;
}
#endregion
#region draw error (nn - expected)
double[] error = null;
if (nnOutput != null)
{
error = Enumerable.Range(0, nnOutput.Length).
Select(o => Math.Abs(nnOutput[o] - expectedOutput[o])).
ToArray();
imageError.Source = UtilityWPF.GetBitmap(error, _harness.OutputSizeXY, _harness.OutputSizeXY, invert: true);
}
else
{
imageError.Source = null;
}
#endregion
#region draw actual
// Vision Rectangle
Rectangle visionRect = new Rectangle()
{
Stroke = Brushes.Silver,
StrokeThickness = .3,
Width = _harness.VisionSize,
Height = _harness.VisionSize,
};
Canvas.SetLeft(visionRect, _harness.VisionSize / -2);
Canvas.SetTop(visionRect, _harness.VisionSize / -2);
canvasMain.Children.Add(visionRect);
// Dot Previous
if (prevPosition != null)
{
Ellipse dot = new Ellipse()
{
Fill = new SolidColorBrush(prevPosition.Item1.Color),
Stroke = Brushes.Black,
StrokeThickness = .3,
Width = 2,
Height = 2,
};
Canvas.SetLeft(dot, prevPosition.Item2.X - 1);
Canvas.SetTop(dot, prevPosition.Item2.Y - 1);
canvasMain.Children.Add(dot);
}
// Dot Current
if (currentPosition != null)
{
Ellipse dot = new Ellipse()
{
Fill = new SolidColorBrush(currentPosition.Color),
Stroke = Brushes.White,
StrokeThickness = .3,
Width = 2,
Height = 2,
};
Canvas.SetLeft(dot, currentPosition.Position.X - 1);
Canvas.SetTop(dot, currentPosition.Position.Y - 1);
canvasMain.Children.Add(dot);
}
// Transform
TransformGroup transform = new TransformGroup();
transform.Children.Add(new ScaleTransform(canvasMain.ActualWidth / _harness.MapSize, canvasMain.ActualHeight / _harness.MapSize));
transform.Children.Add(new TranslateTransform(canvasMain.ActualWidth / 2, canvasMain.ActualHeight / 2));
canvasMain.RenderTransform = transform;
#endregion
_prevTick = now;
}
catch (Exception ex)
{
MessageBox.Show(ex.ToString(), this.Title, MessageBoxButton.OK, MessageBoxImage.Error);
}
}
private void Reset2_Click(object sender, RoutedEventArgs e)
{
try
{
// If not hyperneat, just replace with a new net
// If hyperneat, compare other args and retain genomes if the only change is input/output resolution
string prevGenomeXML = null;
if (chkHyperNEAT.IsChecked.Value && _experiment != null && _ea != null)
{
//_ea.Stop(); // currently, Stop just calls RequestPause, so don't use it. There needs to be a dispose that removes the underlying thread
_ea.RequestPauseAndWait();
prevGenomeXML = ExperimentNEATBase.SavePopulation(_ea.GenomeList);
}
RemoveExistingExperiment();
// My stuff
#region harness args
_harnessArgs = new HarnessArgs(
trkMapSize.Value,
trkVisionSize.Value,
trkOutputSize.Value,
trkInputPixels.Value.ToInt_Round(),
trkOutputPixels.Value.ToInt_Round(),
trkDelayBetweenInstances.Value);
#endregion
#region eval args
if (chkRandomStartingConditions.IsChecked.Value)
{
_evalArgs = new EvaluatorArgs(
trkEvalIterations.Value.ToInt_Round(),
trkDelay.Value,
trkEvalElapsedTime.Value,
trkMaxSpeed.Value,
chkBounceOffWalls.IsChecked.Value,
new[] { (TrackedItemType)cboTrackedItemType.SelectedValue },
trkNewItemDuration.Value,
trkNewItemErrorMultiplier.Value,
(ScoreLeftRightBias)cboErrorBias.SelectedValue);
}
else
{
Point position = Math3D.GetRandomVector(_harnessArgs.MapSize / 2).ToPoint2D();
Vector velocity = Math3D.GetRandomVector_Circular(trkMaxSpeed.Value).ToVector2D();
// Don't let the velocity be in the same quadrant as the position (otherwise, you could have something spawn next to a wall, heading
// toward the wall). These if statements force it to cross the x,y axiis
if (Math.Sign(position.X) == Math.Sign(velocity.X))
{
velocity = new Vector(-velocity.X, velocity.Y);
}
if (Math.Sign(position.Y) == Math.Sign(velocity.Y))
{
velocity = new Vector(velocity.X, -velocity.Y);
}
_evalArgs = new EvaluatorArgs(
trkEvalIterations.Value.ToInt_Round(),
trkDelay.Value,
trkEvalElapsedTime.Value,
new[] { Tuple.Create((TrackedItemType)cboTrackedItemType.SelectedValue, position, velocity, chkBounceOffWalls.IsChecked.Value) },
trkNewItemDuration.Value,
trkNewItemErrorMultiplier.Value,
(ScoreLeftRightBias)cboErrorBias.SelectedValue);
}
#endregion
// SharpNEAT
#region experiment args
_experimentArgs = new ExperimentInitArgs()
{
Description = "Input is a pixel array. Output is a pixel array. The NN needs to watch the object and anticipate where it will be at some fixed time in the future",
InputCount = _harnessArgs.InputSizeXY * _harnessArgs.InputSizeXY,
OutputCount = _harnessArgs.OutputSizeXY * _harnessArgs.OutputSizeXY,
IsHyperNEAT = chkHyperNEAT.IsChecked.Value,
PopulationSize = trkPopulationSize.Value.ToInt_Round(),
SpeciesCount = trkSpeciesCount.Value.ToInt_Round(),
Activation = new ExperimentInitArgs_Activation_CyclicFixedTimesteps()
{
TimestepsPerActivation = trkTimestepsPerActivation.Value.ToInt_Round(),
FastFlag = true
},
Complexity_RegulationStrategy = ComplexityCeilingType.Absolute,
Complexity_Threshold = trkComplexityThreshold.Value.ToInt_Round(),
};
#endregion
#region hyperneat args
_hyperneatArgs = null;
if (chkHyperNEAT.IsChecked.Value)
{
// Use two square sheets
var hyperPoints = HyperNEAT_Args.GetSquareSheets(trkVisionSize.Value, trkOutputSize.Value, _harnessArgs.InputSizeXY, _harnessArgs.OutputSizeXY);
_hyperneatArgs = new HyperNEAT_Args()
{
InputPositions = hyperPoints.inputs,
OutputPositions = hyperPoints.outputs,
};
}
#endregion
#region create harness
_harness = new TrackedItemHarness(_harnessArgs);
_harness.ItemRemoved += (s1, e1) =>
{
_harness.SetItem(AntPos_Evaluator.GetNewItem(_harness, _evalArgs));
};
_harness.SetItem(AntPos_Evaluator.GetNewItem(_harness, _evalArgs));
#endregion
#region create evaluator
AntPos_Evaluator evaluator = new AntPos_Evaluator(_harnessArgs, _evalArgs);
//FitnessInfo score = evaluator.Evaluate(new RandomBlackBoxNetwork(_harness.InputSizeXY * _harness.InputSizeXY, _harness.OutputSizeXY * _harness.OutputSizeXY, true)); // this is a good place to unit test the evaluator
#endregion
#region create experiment
_experiment = new ExperimentNEATBase();
_experiment.Initialize("anticipate position", _experimentArgs, evaluator);
#endregion
#region create evolution algorithm
if (prevGenomeXML == null)
{
if (chkHyperNEAT.IsChecked.Value)
{
_ea = _experiment.CreateEvolutionAlgorithm(_hyperneatArgs);
}
else
{
_ea = _experiment.CreateEvolutionAlgorithm();
}
}
else
{
List <NeatGenome> genomeList;
if (_hyperneatArgs == null)
{
genomeList = ExperimentNEATBase.LoadPopulation(prevGenomeXML, _experimentArgs.Activation, _experimentArgs.InputCount, _experimentArgs.OutputCount);
}
else
{
genomeList = ExperimentNEATBase.LoadPopulation(prevGenomeXML, _experimentArgs.Activation, _hyperneatArgs);
}
// The factory is the same for all items, so just grab the first one
NeatGenomeFactory genomeFactory = genomeList[0].GenomeFactory;
_ea = _experiment.CreateEvolutionAlgorithm(genomeFactory, genomeList, _hyperneatArgs);
}
_ea.UpdateEvent += EA_UpdateEvent;
_ea.PausedEvent += EA_PausedEvent;
#endregion
ShowBestGenome(); // this ensures the neural viewer is created
_winningBrainTime = DateTime.UtcNow - TimeSpan.FromDays(1); // put it way in the past so the first tick will request a new winner
_winningBrain = null;
//_winningBrain = new RandomBlackBoxNetwork(_harness.InputSizeXY * _harness.InputSizeXY, _harness.OutputSizeXY * _harness.OutputSizeXY, true);
_tickCounter = _evalArgs.TotalNumberEvaluations * 2; // force the timer to get the winning NN right away (otherwise it will do a round before refreshing)
_ea.StartContinue(); // this needs to be done last
}
catch (Exception ex)
{
MessageBox.Show(ex.ToString(), this.Title, MessageBoxButton.OK, MessageBoxImage.Error);
}
}
private void Timer_Tick_REAL(object sender, EventArgs e)
{
// This uses actual time elapsed, and runs continuously, grabbing a new neural net every 10 seconds
try
{
imageInput.Source = null;
canvasMain.Children.Clear();
DateTime now = DateTime.UtcNow;
if (_harness == null)
{
_prevTick = now;
return;
}
// Tell the harness to go
_harness.Tick((now - _prevTick).TotalSeconds);
var prevPosition = _harness.GetPreviousPosition(_harness.Time - _evalArgs.Delay_Seconds);
var currentPosition = _harness.Item;
if (_experiment != null && (_winningBrain == null || (now - _winningBrainTime).TotalSeconds > 10))
{
NeatGenome winner = _ea.CurrentChampGenome;
_genomeViewer.RefreshView(winner);
_winningBrain = _experiment.GetBlackBox(winner);
_winningBrainTime = now;
}
#region draw input
double[] inputArr = new double[_harness.InputSizeXY * _harness.InputSizeXY];
AntPos_Evaluator.ClearArray(inputArr);
if (prevPosition != null)
{
double dotRadius = (_harness.VisionSize / _harness.InputSizeXY) * Math.Sqrt(2);
AntPos_Evaluator.ApplyPoint(inputArr, _harness.InputCellCenters, dotRadius, prevPosition.Item2, true);
}
imageInput.Source = UtilityWPF.GetBitmap(inputArr, _harness.InputSizeXY, _harness.InputSizeXY, invert: true);
#endregion
#region draw expected output
double[] expectedOutput = null;
if (currentPosition == null)
{
expectedOutput = AntPos_Evaluator.GetExpectedOutput(null, _harness, _evalArgs);
}
else
{
var currentPos = Tuple.Create(currentPosition, currentPosition.Position, currentPosition.Velocity);
expectedOutput = AntPos_Evaluator.GetExpectedOutput(currentPos, _harness, _evalArgs);
}
imageExpectedOutput.Source = UtilityWPF.GetBitmap(expectedOutput, _harness.OutputSizeXY, _harness.OutputSizeXY, invert: true);
#endregion
#region draw nn output
double[] nnOutput = null;
if (_winningBrain != null)
{
nnOutput = new double[_harness.OutputSizeXY * _harness.OutputSizeXY];
// Brain.Tick
_winningBrain.InputSignalArray.CopyFrom(inputArr, 0);
_winningBrain.Activate();
_winningBrain.OutputSignalArray.CopyTo(nnOutput, 0);
imageNNOutput.Source = UtilityWPF.GetBitmap(nnOutput, _harness.OutputSizeXY, _harness.OutputSizeXY, invert: true);
}
else
{
imageNNOutput.Source = null;
}
#endregion
#region draw error (nn - expected)
double[] error = null;
if (nnOutput != null)
{
error = Enumerable.Range(0, nnOutput.Length).
Select(o => Math.Abs(nnOutput[o] - expectedOutput[o])).
ToArray();
imageError.Source = UtilityWPF.GetBitmap(error, _harness.OutputSizeXY, _harness.OutputSizeXY, invert: true);
}
else
{
imageError.Source = null;
}
#endregion
#region draw actual
// Vision Rectangle
Rectangle visionRect = new Rectangle()
{
Stroke = Brushes.Silver,
StrokeThickness = .3,
Width = _harness.VisionSize,
Height = _harness.VisionSize,
};
Canvas.SetLeft(visionRect, _harness.VisionSize / -2);
Canvas.SetTop(visionRect, _harness.VisionSize / -2);
canvasMain.Children.Add(visionRect);
// Dot Previous
if (prevPosition != null)
{
Ellipse dot = new Ellipse()
{
Fill = new SolidColorBrush(prevPosition.Item1.Color),
Stroke = Brushes.Black,
StrokeThickness = .3,
Width = 2,
Height = 2,
};
Canvas.SetLeft(dot, prevPosition.Item2.X - 1);
Canvas.SetTop(dot, prevPosition.Item2.Y - 1);
canvasMain.Children.Add(dot);
}
// Dot Current
if (currentPosition != null)
{
Ellipse dot = new Ellipse()
{
Fill = new SolidColorBrush(currentPosition.Color),
Stroke = Brushes.White,
StrokeThickness = .3,
Width = 2,
Height = 2,
};
Canvas.SetLeft(dot, currentPosition.Position.X - 1);
Canvas.SetTop(dot, currentPosition.Position.Y - 1);
canvasMain.Children.Add(dot);
}
// Transform
TransformGroup transform = new TransformGroup();
transform.Children.Add(new ScaleTransform(canvasMain.ActualWidth / _harness.MapSize, canvasMain.ActualHeight / _harness.MapSize));
transform.Children.Add(new TranslateTransform(canvasMain.ActualWidth / 2, canvasMain.ActualHeight / 2));
canvasMain.RenderTransform = transform;
#endregion
_prevTick = now;
}
catch (Exception ex)
{
MessageBox.Show(ex.ToString(), this.Title, MessageBoxButton.OK, MessageBoxImage.Error);
}
}
