private static List <LabColor> GenerateSamples(PaletteOptions options)
{
var samples = new List <LabColor>();
var rangeDivider = Math.Pow(options.Samples, 1.0 / 3.0) * 1.001;
var hStep = (options.HueMax - options.HueMin) / rangeDivider;
var cStep = (options.ChromaMax - options.ChromaMin) / rangeDivider;
var lStep = (options.LightMax - options.LightMin) / rangeDivider;
for (double h = options.HueMin; h <= options.HueMax; h += hStep)
{
for (double c = options.ChromaMin; c <= options.ChromaMax; c += cStep)
{
for (double l = options.LightMin; l <= options.LightMax; l += lStep)
{
var color = new HclColor(h, c, l).ToLab();
if (CheckColor(color, options))
{
samples.Add(color);
}
}
}
}
return(samples.Distinct().ToList());
}
public static List <Color> GetPalette(int colorCount, PaletteOptions options = null)
{
if (colorCount < 1)
{
return(new List <Color>());
}
if (options == null)
{
options = new PaletteOptions();
}
if (options.Samples < colorCount * 5)
{
options.Samples = colorCount * 5;
}
;
var samples = GenerateSamples(options);
if (samples.Count < colorCount)
{
throw new Exception("Not enough samples to generate palette, increase sample count.");
}
var sliceSize = samples.Count / colorCount;
var colors = new List <LabColor>();
for (var i = 0; i < samples.Count; i += sliceSize)
{
colors.Add(samples[i]);
if (colors.Count >= colorCount)
{
break;
}
}
for (var step = 1; step <= options.Quality; step++)
{
var zones = GenerateZones(samples, colors);
var lastColors = colors.Select(x => x).ToList();
for (var i = 0; i < zones.Count; i++)
{
var zone = zones[i];
var total = zone.Count;
var lAvg = zone.Sum(x => x.L) / total;
var aAvg = zone.Sum(x => x.A) / total;
var bAvg = zone.Sum(x => x.B) / total;
colors[i] = new LabColor(lAvg, aAvg, bAvg);
}
if (!AreEqualPalettes(lastColors, colors))
{
break;
}
}
colors = SortByContrast(colors);
return(colors.Select((lab) => lab.ToRgb()).ToList());
}
private static bool CheckColor(LabColor color, PaletteOptions options)
{
var rgb = color.ToRgb();
var hcl = color.ToHcl();
var compLab = rgb.ToLab();
var labTolerance = 7;
return(
hcl.H >= options.HueMin &&
hcl.H <= options.HueMax &&
hcl.C >= options.ChromaMin &&
hcl.C <= options.ChromaMax &&
hcl.L >= options.LightMin &&
hcl.L <= options.LightMax &&
compLab.L >= (color.L - labTolerance) &&
compLab.L <= (color.L + labTolerance) &&
compLab.A >= (color.A - labTolerance) &&
compLab.A <= (color.A + labTolerance) &&
compLab.B >= (color.B - labTolerance) &&
compLab.B <= (color.B + labTolerance)
);
}
private List<LabColor> GenerateColorSamples(PaletteOptions options)
{
var samples = new List<LabColor>();
var rangeDivider = Math.Pow(options.Samples, 1.0 / 3.0) * 1.001;
var hStep = (options.HueMax - options.HueMin) / rangeDivider;
var cStep = (options.ChromaMax - options.ChromaMin) / rangeDivider;
var lStep = (options.LightMax - options.LightMin) / rangeDivider;
for (double h = options.HueMin; h <= options.HueMax; h += hStep)
{
for (double c = options.ChromaMin; c <= options.ChromaMax; c += cStep)
{
for (double l = options.LightMin; l <= options.LightMax; l += lStep)
{
var color = new HclColor(h, c, l).ToLab();
if (color.IsValidRgb() && options.ValidateColor(color))
{
samples.Add(color);
}
}
}
}
return samples;
}
public Color[] GenerateKMean(int colorsCount,
PaletteOptions options = null,
ColorDistanceType distanceType = ColorDistanceType.Default)
{
options = options ?? PaletteOptions.GetDefault();
var kMeans = new List<LabColor>();
for (var i = 0; i < colorsCount; i++)
{
var lab = LabColor.GetRandom();
while (!lab.IsValidRgb())
{
lab = LabColor.GetRandom();
}
kMeans.Add(lab);
}
var colorSamples = GenerateColorSamples(options);
// Steps
var steps = options.Quality;
var samplesCount = colorSamples.Count;
var samplesClosest = new int?[samplesCount];
while (steps-- > 0)
{
// kMeans -> Samples Closest
for (var i = 0; i < samplesCount; i++)
{
var lab = colorSamples[i];
var minDistance = double.MaxValue;
for (var j = 0; j < kMeans.Count; j++)
{
var kMean = kMeans[j];
var distance = GetColorDistance(lab, kMean, distanceType);
if (distance < minDistance)
{
minDistance = distance;
samplesClosest[i] = j;
}
}
}
// Samples -> kMeans
var freeColorSamples = colorSamples
.Select((lab) => (LabColor)lab.Clone()) // todo do I really need clone each item?
.ToList();
for (var j = 0; j < kMeans.Count; j++)
{
var count = 0;
var candidateKMean = new LabColor();
for (var i = 0; i < colorSamples.Count; i++)
{
if (samplesClosest[i] == j)
{
count++;
var color = colorSamples[i];
candidateKMean.L += color.L;
candidateKMean.A += color.A;
candidateKMean.B += color.B;
}
}
if (count != 0)
{
candidateKMean.L /= count;
candidateKMean.A /= count;
candidateKMean.B /= count;
}
if (count != 0 &&
candidateKMean.IsValidRgb() &&
options.ValidateColor(candidateKMean))
{
kMeans[j] = candidateKMean;
}
else
{
// The candidate kMean is out of the boundaries of the color space, or unfound.
if (freeColorSamples.Count > 0)
{
// We just search for the closest FREE color of the candidate kMean
var minDistance = double.MaxValue;
var closest = -1;
for (var i = 0; i < freeColorSamples.Count; i++)
{
var distance = GetColorDistance(freeColorSamples[i], candidateKMean, distanceType);
if (distance < minDistance)
{
minDistance = distance;
closest = i;
}
}
kMeans[j] = colorSamples[closest];
}
else
{
// Then we just search for the closest color of the candidate kMean
var minDistance = double.MaxValue;
var closest = -1;
for (var i = 0; i < colorSamples.Count; i++)
{
var distance = GetColorDistance(colorSamples[i], candidateKMean, distanceType);
if (distance < minDistance)
{
minDistance = distance;
closest = i;
}
}
kMeans[j] = colorSamples[closest];
}
}
var baseColor = kMeans[j];
freeColorSamples = freeColorSamples
.Where((lab) => !lab.Equals(baseColor))
.ToList();
}
}
return kMeans.Select((lab) => lab.ToRgb()).ToArray();
}
public Color[] GenerateForce(int colorsCount,
PaletteOptions options = null,
ColorDistanceType distanceType = ColorDistanceType.Default)
{
var random = new Random();
var colors = new LabColor[colorsCount];
options = options ?? PaletteOptions.GetDefault();
// Init
for (var i = 0; i < colorsCount; i++)
{
// Find a valid Lab color
var color = LabColor.GetRandom();
while (color.IsValidRgb() || options.ValidateColor(color))
{
color = LabColor.GetRandom();
}
colors[i] = color;
}
// Force vector: repulsion
var repulsion = 100;
var speed = 100;
var steps = options.Quality * 20;
var vectors = new LabVector[colorsCount];
while (steps-- > 0)
{
// Init
for (var i = 0; i < colors.Length; i++)
{
vectors[i] = new LabVector();
}
// Compute Force
for (var i = 0; i < colors.Length; i++)
{
var colorA = colors[i];
for (var j = 0; j < i; j++)
{
var colorB = colors[j];
// repulsion force
var dl = colorA.L - colorB.L;
var da = colorA.A - colorB.A;
var db = colorA.B - colorB.B;
var d = GetColorDistance(colorA, colorB, distanceType);
if (d > 0)
{
var force = repulsion / Math.Pow(d, 2);
vectors[i].dL += dl * force / d;
vectors[i].dA += da * force / d;
vectors[i].dB += db * force / d;
vectors[j].dL -= dl * force / d;
vectors[j].dA -= da * force / d;
vectors[j].dB -= db * force / d;
}
else
{
// Jitter
vectors[j].dL += 2 - 4 * random.NextDouble();
vectors[j].dA += 2 - 4 * random.NextDouble();
vectors[j].dB += 2 - 4 * random.NextDouble();
}
}
}
// Apply Force
for (var i = 0; i < colors.Length; i++)
{
var color = colors[i];
var displacement = speed * vectors[i].Magnitude; ;
if (displacement > 0)
{
var ratio = speed * Math.Min(0.1, displacement) / displacement;
var l = color.L + vectors[i].dL * ratio;
var a = color.A + vectors[i].dA * ratio;
var b = color.B + vectors[i].dB * ratio;
var candidateLab = new LabColor(l, a, b);
if (candidateLab.IsValidRgb() && options.ValidateColor(candidateLab))
{
colors[i] = candidateLab;
}
}
}
}
return colors.Select((lab) => lab.ToRgb()).ToArray();
}
