// This function run the WFC for iteration number of times, for different tile sizes.
// Component returns how many times for iteration number of sizes it was successful
protected override void SolveInstance(IGH_DataAccess DA)
{
GH_PatternsFromSample gh_patterns = new GH_PatternsFromSample();
DA.GetData <GH_PatternsFromSample>(0, ref gh_patterns);
double iterations = 0;
DA.GetData <double>(1, ref iterations);
bool backtrack = false;
DA.GetData <bool>(2, ref backtrack);
var patterns = gh_patterns.Value.Patterns;
var weights = gh_patterns.Value.TilesWeights;
var N = gh_patterns.Value.N;
List <WaveCollapseHistoryElement> outputs = new List <WaveCollapseHistoryElement>();
var return_value = new GH_WaveCollapseResults();
List <int> successfulRuns = new List <int>();
List <int> outputSizes = new List <int>();
var sb = getContradictionData(outputSizes, (int)iterations, patterns, N, weights, ref successfulRuns);
string filePath = @"R:\csv\asd2_14_26.csv";
System.IO.File.WriteAllText(filePath, sb.ToString());
DA.SetDataList(0, successfulRuns);
DA.SetDataList(1, outputSizes);
}
protected override void SolveInstance(IGH_DataAccess DA)
{
GH_PatternsFromSample gh_patterns = new GH_PatternsFromSample();
DA.GetData <GH_PatternsFromSample>(0, ref gh_patterns);
List <Point3d> wavePoints = new List <Point3d>();
DA.GetDataList <Point3d>(1, wavePoints);
double dataSize = 0;
DA.GetData <double>(2, ref dataSize);
bool backtrack = false;
DA.GetData <bool>(3, ref backtrack);
double iterations = 0;
DA.GetData <double>(4, ref iterations);
var patterns = gh_patterns.Value.Patterns;
var weights = gh_patterns.Value.TilesWeights;
var N = gh_patterns.Value.N;
// Get width and height based on 2d array of points
int width = Utils.GetNumberofPointsInOneDimension(wavePoints[0].X, wavePoints[wavePoints.Count - 1].X);
int height = Utils.GetNumberofPointsInOneDimension(wavePoints[0].Y, wavePoints[wavePoints.Count - 1].Y);
List <WaveCollapseHistoryElement> outputs = new List <WaveCollapseHistoryElement>();
var return_value = new GH_WaveCollapseResults();
for (int i = 0; i < (int)dataSize; i++)
{
// RUN WAVEFUNCION COLLAPSE
var wfc = new WaveFunctionCollapseRunner();
var history = wfc.Run(patterns, N, width, height, weights, backtrack, (int)iterations);
if (history.Elements.Count == 0)
{
continue;
}
var historyEndElement = history.Elements[history.Elements.Count - 1];
outputs.Add(historyEndElement);
return_value.Value.AddToList(historyEndElement);
}
if (true)
{
DA.SetData(0, return_value);
}
else
{
AddRuntimeMessage(GH_RuntimeMessageLevel.Error, "Check the inputs you idiot!");
}
}
protected override void SolveInstance(IGH_DataAccess DA)
{
// Get patterns from sample
GH_PatternsFromSample gh_patterns = new GH_PatternsFromSample();
DA.GetData <GH_PatternsFromSample>(0, ref gh_patterns);
pManager.AddPointParameter("Wave", "", "", GH_ParamAccess.list);
pManager.AddBooleanParameter("Backtrack", "", "", GH_ParamAccess.item);
pManager.AddNumberParameter("Iterations", "", "", GH_ParamAccess.item);
}
// INSIDE
protected override void SolveInstance(IGH_DataAccess DA)
{
GH_PatternsFromSample gh_patterns = new GH_PatternsFromSample();
DA.GetData <GH_PatternsFromSample>(0, ref gh_patterns);
List <Point3d> wavePoints = new List <Point3d>();
DA.GetDataList <Point3d>(1, wavePoints);
bool backtrack = false;
DA.GetData <bool>(2, ref backtrack);
double iterations = 0;
DA.GetData <double>(3, ref iterations);
var patterns = gh_patterns.Value.Patterns;
var weights = gh_patterns.Value.TilesWeights;
var N = gh_patterns.Value.N;
int width = Utils.GetNumberofPointsInOneDimension(wavePoints[0].X, wavePoints[wavePoints.Count - 1].X);
int height = Utils.GetNumberofPointsInOneDimension(wavePoints[0].Y, wavePoints[wavePoints.Count - 1].Y);
// RUN WAVEFUNCION COLLAPSE
var wfc = new WaveFunctionCollapseRunner();
var history = wfc.Run(patterns, N, width, height, weights, backtrack, (int)iterations);
var return_value = new GH_WaveCollapseHistory(history);
var patternsOccurence = wfc.GetPatternCounts();
var collapseAverage = wfc.GetAverageCollapseStep();
if (true)
{
DA.SetData(0, patterns.Count);
DA.SetData(1, return_value);
DA.SetDataList(2, patternsOccurence);
DA.SetData(3, collapseAverage);
}
else
{
AddRuntimeMessage(GH_RuntimeMessageLevel.Error, "Check the inputs you idiot!");
}
}
protected override void SolveInstance(IGH_DataAccess DA)
{
GH_WaveCollapseResults waveCollapseDataset = new GH_WaveCollapseResults();
DA.GetData <GH_WaveCollapseResults>(0, ref waveCollapseDataset);
GH_PatternsFromSample gh_patterns = new GH_PatternsFromSample();
DA.GetData <GH_PatternsFromSample>(1, ref gh_patterns);
string series = "";
DA.GetData <string>(2, ref series);
var waveElements = Utils.GetObservedWave(waveCollapseDataset);
var patterns = Utils.GetPatternsFromSample(gh_patterns);
// Assign generic values for every image
var sampleSuperpositions = waveElements[0].Superpositions;
// Get picture width and height
width = sampleSuperpositions.GetLength(0);
height = sampleSuperpositions.GetLength(1);
// Allocate memory for picture
biteSize = (int)((width * 4) * height);
_imageBuffer = new byte[biteSize];
// Add image from series
for (int i = 0; i < waveElements.Count; i++)
{
var superpositions = waveElements[i].Superpositions;
// Get values for pixels
var pixelsCodes = Utils.GetImageValuesFromWave(superpositions);
// Change to rgb
var pictureRGB = Utils.CellsValuesToRGBColours(pixelsCodes, white, blue, green);
// Plot picture from rgb
Utils.PlotPixelsFromRGB(pictureRGB, _imageBuffer);
// Save ti file
Utils.SaveToPicture(pictureRGB, i, series, _imageBuffer);
}
}
public static PatternFromSampleElement GetPatternsFromSample(GH_PatternsFromSample patternFromSample)
{
var patterns = patternFromSample.Value;
return(patterns);
}
protected override void SolveInstance(IGH_DataAccess DA)
{
// Get wave function collapse data
GH_PatternsFromSample gh_patterns = new GH_PatternsFromSample();
DA.GetData <GH_PatternsFromSample>(0, ref gh_patterns);
List <Point3d> wavePoints = new List <Point3d>();
DA.GetDataList <Point3d>(1, wavePoints);
bool backtrack = false;
DA.GetData <bool>(2, ref backtrack);
double iterations = 0;
DA.GetData <double>(3, ref iterations);
// Get image data.
GH_Image inputImage = new GH_Image();
DA.GetData(4, ref inputImage);
List <double> newWeights = new List <double>();
DA.GetDataList(5, newWeights);
bool applyWeights = false;
DA.GetData(6, ref applyWeights);
// Extract parameters to run Wave Function Collapse.
var patterns = gh_patterns.Value.Patterns;
var weights = gh_patterns.Value.TilesWeights;
var N = gh_patterns.Value.N;
int width = Utils.GetNumberofPointsInOneDimension(wavePoints[0].X, wavePoints[wavePoints.Count - 1].X);
int height = Utils.GetNumberofPointsInOneDimension(wavePoints[0].Y, wavePoints[wavePoints.Count - 1].Y);
// Prepare image data.
//var image = convertImageListToArray(rawImage, width, height);
//var image = Utils.generateRandomImage(width, height);
var image = inputImage.Value.Brightness;
// Run Wave Function Collapse.
var wfc = new WaveFunctionCollapseRunner();
var history = new WaveCollapseHistory();
if (applyWeights)
{
history = wfc.Run(patterns, N, width, height, weights, (int)iterations, backtrack, image, newWeights);
}
else
{
history = wfc.Run(patterns, N, width, height, weights, (int)iterations, backtrack, image);
}
var return_value = new GH_WaveCollapseHistory(history);
DA.SetData(0, return_value);
}
protected override void SolveInstance(IGH_DataAccess DA)
{
string GANresult = "";
DA.GetData(0, ref GANresult);
GH_PatternsFromSample gh_patterns = new GH_PatternsFromSample();
DA.GetData <GH_PatternsFromSample>(1, ref gh_patterns);
Color empty = new Color();
DA.GetData(2, ref empty);
Color half = new Color();
DA.GetData(3, ref half);
Color full = new Color();
DA.GetData(4, ref full);
double width = 0;
DA.GetData(5, ref width);
double height = 0;
DA.GetData(6, ref height);
bool save = false;
DA.GetData(7, ref save);
Bitmap ganImage = (Bitmap)Image.FromFile(GANresult);
var patterns = gh_patterns.Value.Patterns;
var x = patterns[0].MiniTile;
// Folder
DirectoryInfo di = new DirectoryInfo(@"R:\pix2pix\small_images\grasshopper_test");
FileInfo[] Images = di.GetFiles("*.png");
var files = Directory.GetFiles(@"R:\pix2pix\small_images\grasshopper_test", "*.png");
List <float> successRates = new List <float>();
// Rate for one image
for (int i = 0; i < Images.Length; i++)
{
Bitmap image = (Bitmap)Image.FromFile(files[i]);
float resultFromOneImage = getConstrainsRate(image, (int)width, (int)height, empty, half, full, patterns);
successRates.Add(resultFromOneImage);
}
var d = successRates.Sum();
var xd = successRates.Average();
if (save)
{
Utils.SaveConstrainsCheckToFile(xd, successRates);
}
//patternOccurenceInGANResult()
DA.SetData(0, xd);
DA.SetDataList(1, successRates);
}
protected override void SolveInstance(IGH_DataAccess DA)
{
// TILES A: center points
List <Point3d> tilesA = new List <Point3d>();
DA.GetDataList <Point3d>(0, tilesA);
// TILES B: center points
List <Point3d> tilesB = new List <Point3d>();
DA.GetDataList <Point3d>(1, tilesB);
// ALL TILES (A+B+NULL): CENTER POINTS
List <Point3d> allTiles = new List <Point3d>();
DA.GetDataList <Point3d>(2, allTiles);
// tiles SIZE
double tileSize = 0;
DA.GetData(3, ref tileSize);
// rotate bool
// tiles SIZE
bool rotation = false;
DA.GetData(4, ref rotation);
float[] weights = GetWeights(tilesA, tilesB, allTiles);
// tiles for patterns from sample
var halfTilesForPatterns = new List <Point3d>();
var fullTilesForPatterns = new List <Point3d>();
var emptyTilesForPatterns = new List <Point3d>();
PatternFromSampleExtractor patternsToGenerate = new PatternFromSampleExtractor(tilesA, tilesB, allTiles, weights, (int)tileSize, rotation);
var patternsFromSample = patternsToGenerate.Extract();
var result = new PatternFromSampleElement();
result.Patterns = patternsFromSample;
result.UnitElementsOfType0 = tilesA;
result.UnitElementsOfType1 = tilesB;
result.UnitElementsCenters = allTiles;
result.TilesWeights = weights;
result.N = (int)tileSize;
int x = 20, y = 0, z = 0;
for (var i = 0; i < result.Patterns.Count; i++)
{
var pattern = result.Patterns[i];
var instance = pattern.Instantiate(x + i * (int)tileSize * 4, y, z);
halfTilesForPatterns.AddRange(instance[State.HALF_TILE]);
fullTilesForPatterns.AddRange(instance[State.FULL_TILE]);
emptyTilesForPatterns.AddRange(instance[State.EMPTY]);
}
var r = new GH_PatternsFromSample(result);
DA.SetData(0, r);
DA.SetDataList(1, halfTilesForPatterns);
DA.SetDataList(2, fullTilesForPatterns);
DA.SetDataList(3, emptyTilesForPatterns);
}