public void Run(Cells cells, CellularAutomataRules rules)
{
_cells = cells;
_ptOffset = CalculateOffset();
Rules = (rules != null) ? rules : _rules;
_timer.Start();
}
private void ExportAsAnimatedGifWorker(string outputFilePath, ProgressBox box,
int numFramesPreamble, int numFrames)
{
Cells cells = _genAlg.CaSettings.GetInitialCells(_genAlg.GaSettings.InitialStateDistribution);
CellularAutomataRules rules = ctrlCellularAutomata.Rules;
NeighborhoodFunction function = _genAlg.CaSettings.NeighborhoodFunction;
CellPainter painter = _genAlg.CaSettings.CellStructure.Painter;
for (int i = 0; i < numFramesPreamble; i++)
{
cells = cells.ApplyRules(rules, function);
box.Invoke(
new Action(
() => box.Increment()
)
);
}
using (FileStream fs = new FileStream(outputFilePath, FileMode.Create))
using (GifEncoder encoder = new GifEncoder(fs, cells.Columns * 2, cells.Rows * 2))
{
Bitmap bmp = new Bitmap(cells.Columns * 2, cells.Rows * 2);
Point offset = new Point(0, 0);
for (int i = 0; i < numFrames; i++)
{
painter.PaintBitmap(bmp, cells, offset, ctrlCellularAutomata.Colors);
encoder.AddFrame(Image.FromHbitmap(bmp.GetHbitmap()), 0, 0, new TimeSpan(0));
cells = cells.ApplyRules(rules, function);
box.Increment();
}
}
box.Finish();
}
public Cells ApplyRules(CellularAutomataRules rules, NeighborhoodFunction func)
{
Cells cells = (Cells) this.Clone();
for (int row = 0; row < Rows; row++)
for (int col = 0; col < Columns; col++)
cells[col, row] = rules.GetSuccessorState(this[col, row], func.Map(this.Neighbors(col, row), rules.NumStates));
return cells;
}
private void SaveRules(string fileName)
{
CellularAutomataRules rules = _genAlg.CurrentRules;
var settingsCa = _genAlg.CaSettings;
var saveData = new RulesSaveData(settingsCa, rules.StateTable);
saveData.Save(fileName);
}
private void GenerateNewCa()
{
if (PreviousGeneration == null)
{
_currentCa = _settingsCa.GetRandomRules(_settingsGa.StateTableDistribution);
}
else
{
_currentCa = GenerateChildCa(PreviousGeneration);
}
}
public Cells ApplyRules(CellularAutomataRules rules, NeighborhoodFunction func)
{
Cells cells = (Cells)this.Clone();
for (int row = 0; row < Rows; row++)
{
for (int col = 0; col < Columns; col++)
{
cells[col, row] = rules.GetSuccessorState(this[col, row], func.Map(this.Neighbors(col, row), rules.NumStates));
}
}
return(cells);
}
public override CellularAutomataRules Generate(List<CellularAutomataRules> parents)
{
if (parents.Count() != NumParents || !parents[0].HasSameDimensions(parents[1]))
throw new ArgumentException();
var child = new CellularAutomataRules(parents[0].Range, parents[0].NumStates);
var rndParent = RulesDistribution(parents);
for (int row = 0; row < child.NumStates; row++)
{
CellularAutomataRules parent = rndParent.Next();
for (int col = 0; col < child.Range; col++)
child[col, row] = parent[col, row];
}
return child;
}
public override CellularAutomataRules Mutate(CellularAutomataRules ca, GeneticAlgorithmSettings settings)
{
var mutant = new CellularAutomataRules(ca);
int n = Util.RndUniformInt((int)(ca.Range * ca.NumStates * settings.MutationTemperature)) + 1;
for (int i = 0; i < n; i++)
{
int row = Util.RndUniformInt(ca.NumStates);
int col = Util.RndUniformInt(ca.Range);
mutant[col, row] = settings.StateTableDistribution.Next();
}
return(mutant);
}
public override CellularAutomataRules Mutate(CellularAutomataRules ca, GeneticAlgorithmSettings settings)
{
var mutant = new CellularAutomataRules(ca);
int n = Util.RndUniformInt((int)(ca.NumStates * settings.MutationTemperature)) + 1;
for (int i = 0; i < n; i++)
{
int rowSrc = Util.RndUniformInt(ca.NumStates);
int rowDest = rowSrc;
while (rowDest == rowSrc)
rowDest = Util.RndUniformInt(ca.NumStates);
for (int column = 0; column < ca.Range; column++)
mutant[column, rowDest] = mutant[column, rowSrc];
}
return mutant;
}
public override CellularAutomataRules Mutate(CellularAutomataRules ca, GeneticAlgorithmSettings settings)
{
var mutant = new CellularAutomataRules(ca);
int n = Util.RndUniformInt((int)(ca.Range * settings.MutationTemperature)) + 1;
for (int i = 0; i < n; i++)
{
int colSrc = Util.RndUniformInt(ca.Range);
int colDest = colSrc;
while (colDest == colSrc)
colDest = Util.RndUniformInt(ca.Range);
for (int row = 0; row < ca.NumStates; row++)
mutant[colDest, row] = mutant[colSrc, row];
}
return mutant;
}
public override CellularAutomataRules Generate(List <CellularAutomataRules> parents)
{
if (parents.Count() != NumParents || !parents[0].HasSameDimensions(parents[1]))
{
throw new ArgumentException();
}
var child = new CellularAutomataRules(parents[0].Range, parents[0].NumStates);
for (int col = 0; col < child.Range; col++)
{
for (int row = 0; row < child.NumStates; row++)
{
child[col, row] = (parents[0][col, row] + parents[1][col, row]) % child.NumStates;
}
}
return(child);
}
public override CellularAutomataRules Mutate(CellularAutomataRules ca, GeneticAlgorithmSettings settings)
{
var mutant = new CellularAutomataRules(ca);
int n = Util.RndUniformInt((int)(10.0 * settings.MutationTemperature)) + 1;
for (int i = 0; i < n; i++)
{
int row, col;
int count = 0;
do
{
row = Util.RndUniformInt(ca.NumStates);
col = Util.RndUniformInt(ca.Range);
} while (mutant[col, row] == 0 && count++ < 20);
mutant[col, row] = 0;
}
return(mutant);
}
public override CellularAutomataRules Mutate(CellularAutomataRules ca, GeneticAlgorithmSettings settings)
{
var mutant = new CellularAutomataRules(ca);
int n = Util.RndUniformInt((int)(ca.Range * settings.MutationTemperature)) + 1;
for (int i = 0; i < n; i++)
{
int colSrc = Util.RndUniformInt(ca.Range);
int colDest = colSrc;
while (colDest == colSrc)
{
colDest = Util.RndUniformInt(ca.Range);
}
for (int row = 0; row < ca.NumStates; row++)
{
mutant[colDest, row] = mutant[colSrc, row];
}
}
return(mutant);
}
public override CellularAutomataRules Mutate(CellularAutomataRules ca, GeneticAlgorithmSettings settings)
{
var mutant = new CellularAutomataRules(ca);
int n = Util.RndUniformInt((int)(ca.NumStates * settings.MutationTemperature)) + 1;
for (int i = 0; i < n; i++)
{
int rowSrc = Util.RndUniformInt(ca.NumStates);
int rowDest = rowSrc;
while (rowDest == rowSrc)
{
rowDest = Util.RndUniformInt(ca.NumStates);
}
for (int column = 0; column < ca.Range; column++)
{
mutant[column, rowDest] = mutant[column, rowSrc];
}
}
return(mutant);
}
public override CellularAutomataRules Generate(List <CellularAutomataRules> parents)
{
if (parents.Count() != NumParents)
{
throw new ArgumentException();
}
var child = new CellularAutomataRules(parents[0].Range, parents[0].NumStates);
var parent = parents[0];
int columns = parents[0].Range;
int halfCols = columns / 2;
for (int row = 0; row < child.NumStates; row++)
{
for (int i = 0; i < halfCols; i++)
{
child[i, row] = parent[i, row];
child[columns - i - 1, row] = parent[i, row];
}
}
return(child);
}
public override CellularAutomataRules Generate(List <CellularAutomataRules> parents)
{
if (parents.Count() != NumParents)
{
throw new ArgumentException();
}
var child = new CellularAutomataRules(parents[0].Range, parents[0].NumStates);
var parent = parents[0];
int rows = parents[0].NumStates;
int halfRows = rows / 2;
for (int i = 0; i < halfRows; i++)
{
for (int col = 0; col < child.Range; col++)
{
child[col, i] = parent[col, i];
child[col, rows - i - 1] = parent[col, i];
}
}
return(child);
}
public abstract CellularAutomataRules Mutate(CellularAutomataRules ca, GeneticAlgorithmSettings settings);
public void Run(Cells cells, CellularAutomataRules rules)
{
_cells = cells;
_ptOffset = CalculateOffset();
Rules = (rules != null) ? rules : _rules;
_timer.Start();
}
internal void Clear()
{
Stop();
Rules = null;
}
public void Start()
{
_generations = new List<Generation>();
_currentCa = _settingsCa.GetRandomRules(_settingsGa.StateTableDistribution);
}
public CellularAutomataRules(CellularAutomataRules ca)
{
_stateTable = (int[, ])ca._stateTable.Clone();
}
public bool HasSameDimensions(CellularAutomataRules r)
{
return NumStates == r.NumStates && Range == r.Range;
}
public override CellularAutomataRules Mutate(CellularAutomataRules ca, GeneticAlgorithmSettings settings)
{
var mutant = new CellularAutomataRules(ca);
int n = Util.RndUniformInt((int)(10.0 * settings.MutationTemperature)) + 1;
for (int i = 0; i < n; i++)
{
int row, col;
int count = 0;
do
{
row = Util.RndUniformInt(ca.NumStates);
col = Util.RndUniformInt(ca.Range);
} while (mutant[col, row] == 0 && count++ < 20);
mutant[col, row] = 0;
}
return mutant;
}
public override CellularAutomataRules Mutate(CellularAutomataRules ca, GeneticAlgorithmSettings settings)
{
return(ca);
}
public abstract CellularAutomataRules Mutate(CellularAutomataRules ca, GeneticAlgorithmSettings settings);
public void LoadRules()
{
OpenFileDialog openFileDialog1 = new OpenFileDialog();
openFileDialog1.Filter = "Lifelike JSON|*.json";
openFileDialog1.FilterIndex = 1;
openFileDialog1.Multiselect = false;
// Call the ShowDialog method to show the dialog box.
DialogResult result = openFileDialog1.ShowDialog();
// Process input if the user clicked OK.
if (result != DialogResult.OK)
{
return;
}
RulesSaveData data = RulesSaveData.Load(openFileDialog1.FileName);
if (data == null)
{
return;
}
CellularAutomataRules rules = new CellularAutomataRules(data.StateTable);
try
{
if (!_genAlg.IsInProgess)
{
ctrlCellularAutomataSettings.Set(data.CellStructure, rules.NumStates, data.NeighborhoodFunction);
ctrlGeneticAlgorithmSettings.SetNumStates(rules.NumStates);
}
else
{
if (_genAlg.CaSettings.NeighborhoodFunction.Name != data.NeighborhoodFunction ||
_genAlg.CaSettings.NumStates != rules.NumStates ||
_genAlg.CaSettings.CellStructure.Name != data.CellStructure)
{
MessageBox.Show(
"Neighbor function, cell structure, and/or number states do not match the currently running genetic algorithm settings",
"Error",
MessageBoxButtons.OK,
MessageBoxIcon.Error
);
return;
}
_genAlg.CurrentRules = rules;
}
if (data.CustomColors != null)
{
Colors = data.CustomColors.Select(
ary => Color.FromArgb(ary[0], ary[1], ary[2])
).ToList();
}
Cells cells = _genAlg.CaSettings.GetInitialCells(_genAlg.GaSettings.InitialStateDistribution);
ctrlCellularAutomata.Run(cells, rules);
}
catch (Exception)
{
MessageBox.Show(
"Invalid CA rules file.",
"Error",
MessageBoxButtons.OK,
MessageBoxIcon.Error
);
}
}
public override CellularAutomataRules Generate(List<CellularAutomataRules> parents)
{
if (parents.Count() != NumParents)
throw new ArgumentException();
var child = new CellularAutomataRules(parents[0].Range, parents[0].NumStates);
var parent = parents[0];
int rows = parents[0].NumStates;
int halfRows = rows / 2;
for (int i = 0; i < halfRows; i++ )
for (int col = 0; col < child.Range; col++)
{
child[col, i] = parent[col, i];
child[col, rows - i - 1] = parent[col, i];
}
return child;
}
public override CellularAutomataRules Generate(List<CellularAutomataRules> parents)
{
if (parents.Count() != NumParents)
throw new ArgumentException();
var child = new CellularAutomataRules(parents[0].Range, parents[0].NumStates);
var parent = parents[0];
int columns = parents[0].Range;
int halfCols = columns / 2;
for (int row = 0; row < child.NumStates; row++)
for (int i = 0; i < halfCols; i++)
{
child[i, row] = parent[i, row];
child[columns - i - 1, row] = parent[i, row];
}
return child;
}
public void Add(CellularAutomataRules rules)
{
_ca.Insert(rules, rules.Fitness);
}
public CellularAutomataRules(CellularAutomataRules ca)
{
_stateTable = (int[,]) ca._stateTable.Clone();
}
public void Add(CellularAutomataRules rules)
{
_ca.Insert(rules, rules.Fitness);
}
public void LoadRules()
{
OpenFileDialog openFileDialog1 = new OpenFileDialog();
openFileDialog1.Filter = "Lifelike JSON|*.json";
openFileDialog1.FilterIndex = 1;
openFileDialog1.Multiselect = false;
// Call the ShowDialog method to show the dialog box.
DialogResult result = openFileDialog1.ShowDialog();
// Process input if the user clicked OK.
if (result != DialogResult.OK)
return;
RulesSaveData data = RulesSaveData.Load(openFileDialog1.FileName);
if (data == null)
return;
CellularAutomataRules rules = new CellularAutomataRules(data.StateTable);
try
{
if (!_genAlg.IsInProgess)
{
ctrlCellularAutomataSettings.Set(data.CellStructure, rules.NumStates, data.NeighborhoodFunction);
ctrlGeneticAlgorithmSettings.SetNumStates(rules.NumStates);
}
else
{
if (_genAlg.CaSettings.NeighborhoodFunction.Name != data.NeighborhoodFunction ||
_genAlg.CaSettings.NumStates != rules.NumStates ||
_genAlg.CaSettings.CellStructure.Name != data.CellStructure)
{
MessageBox.Show(
"Neighbor function, cell structure, and/or number states do not match the currently running genetic algorithm settings",
"Error",
MessageBoxButtons.OK,
MessageBoxIcon.Error
);
return;
}
_genAlg.CurrentRules = rules;
}
if (data.CustomColors != null)
Colors = data.CustomColors.Select(
ary => Color.FromArgb(ary[0], ary[1], ary[2])
).ToList();
Cells cells = _genAlg.CaSettings.GetInitialCells(_genAlg.GaSettings.InitialStateDistribution);
ctrlCellularAutomata.Run(cells, rules);
}
catch (Exception)
{
MessageBox.Show(
"Invalid CA rules file.",
"Error",
MessageBoxButtons.OK,
MessageBoxIcon.Error
);
}
}
public override CellularAutomataRules Mutate(CellularAutomataRules ca, GeneticAlgorithmSettings settings)
{
var mutant = new CellularAutomataRules(ca);
int n = Util.RndUniformInt((int)(ca.Range * ca.NumStates * settings.MutationTemperature))+1;
for (int i = 0; i < n; i++)
{
int row = Util.RndUniformInt(ca.NumStates);
int col = Util.RndUniformInt(ca.Range);
mutant[col, row] = settings.StateTableDistribution.Next();
}
return mutant;
}
public bool HasSameDimensions(CellularAutomataRules r)
{
return(NumStates == r.NumStates && Range == r.Range);
}
public void Start()
{
_generations = new List <Generation>();
_currentCa = _settingsCa.GetRandomRules(_settingsGa.StateTableDistribution);
}
private void GenerateNewCa()
{
if (PreviousGeneration == null)
_currentCa = _settingsCa.GetRandomRules( _settingsGa.StateTableDistribution );
else
_currentCa = GenerateChildCa(PreviousGeneration);
}
public override CellularAutomataRules Mutate(CellularAutomataRules ca, GeneticAlgorithmSettings settings)
{
return ca;
}