// K-Means Mode
public static bool checkColor2(Vector3 lab, afunction checkColor)
{
// Check that a color is valid: it must verify our checkColor condition, but also be in the color space
//input is lab ?acolor = rgb2lab (acolor);
Vector3 acolor = lab2hcl(lab);
return(!float.IsNaN(acolor[0]) && acolor[0] >= 0 && acolor[1] >= 0 && acolor[2] >= 0 && acolor[0] < 256 && acolor[1] < 256 && acolor[2] < 256 && checkColor(lab));
}
public static bool checkLab(Vector3 lab, afunction checkColor)
{
// It will be necessary to check if a Lab color exists in the rgb space.
//first convert labtorgb
Vector3 acolor = lab2rgb(lab);
//Vector3 acolor = new Vector3(lab[0]*255, lab[1]*255, lab[2]*255);
return(!float.IsNaN(acolor[0]) && acolor[0] >= 0 && acolor[1] >= 0 && acolor[2] >= 0 && acolor[0] < 256 && acolor[1] < 256 && acolor[2] < 256 && checkColor(lab));
}
public static List <Vector3> generate(int colorsCount, afunction checkColor, bool forceMode, int quality, bool ultra_precision = false)
{
// Default
rnd = new System.Random();
if (colorsCount == null)
{
colorsCount = 8;
}
if (checkColor == null)
{
checkColor = testfunction;
}
if (forceMode == null)
{
forceMode = false;
}
if (quality == null)
{
quality = 50;
}
ultra_precision = ultra_precision || false;
int steps = 0;
if (forceMode)
{
// Force Vector Mode
List <Vector3> colors = new List <Vector3>();
// Init
List <Vector3> vectors = new List <Vector3>();
for (int i = 0; i < colorsCount; i++)
{
// Find a valid Lab color
Vector3 acolor = new Vector3(Random.value, 2 * Random.value - 1, 2 * Random.value - 1);
while (!checkLab(acolor, checkColor))
{
acolor = new Vector3(Random.value, 2 * Random.value - 1, 2 * Random.value - 1);
}
colors.Add(acolor);
}
// Force vector: repulsion
float repulsion = 0.3f;
float speed = 0.05f;
steps = quality * 20;
while (steps > 0)
{
// Init
for (int i = 0; i < colors.Count; i++)
{
vectors.Add(new Vector3(0, 0, 0));
//vectors[i] = {dl:0, da:0, db:0};
}
// Compute Force
for (int i = 0; i < colors.Count; i++)
{
Vector3 colorA = colors[i];
for (int j = 0; j < i; j++)
{
Vector3 colorB = colors[j];
// repulsion force
float dl = colorA[0] - colorB[0];
float da = colorA[1] - colorB[1];
float db = colorA[2] - colorB[2];
float d = Mathf.Sqrt(Mathf.Pow(dl, 2) + Mathf.Pow(da, 2) + Mathf.Pow(db, 2));
if (d > 0)
{
float force = repulsion / Mathf.Pow(d, 2);
vectors[i][0] += dl * force / d;
vectors[i][1] += da * force / d;
vectors[i][2] += db * force / d;
vectors[j][0] -= dl * force / d;
vectors[j][1] -= da * force / d;
vectors[j][2] -= db * force / d;
}
else
{
// Jitter
vectors[j][0] += 0.02f - 0.04f * Random.value;
vectors[j][1] += 0.02f - 0.04f * Random.value;
vectors[j][2] += 0.02f - 0.04f * Random.value;
}
}
}
// Apply Force
for (int i = 0; i < colors.Count; i++)
{
Vector3 acolor = colors[i];
float displacement = speed * Mathf.Sqrt(Mathf.Pow(vectors[i].x, 2) + Mathf.Pow(vectors[i].y, 2) + Mathf.Pow(vectors[i].z, 2));
if (displacement > 0)
{
float ratio = speed * Mathf.Min(0.1f, displacement) / displacement;
Vector3 candidateLab = new Vector3(acolor[0] + vectors[i].x * ratio, acolor[1] + vectors[i].y * ratio, acolor[2] + vectors[i].z * ratio);
if (checkLab(candidateLab, checkColor))
{
colors[i] = candidateLab;
}
}
}
steps -= 1;
}
IEnumerable <Vector3> crgb = from c in colors select lab2rgb(c);
return(crgb.ToList());
//return colors.AsEnumerable.Select(c=>lab2rgb(c));
//return colors;//colors.map(function(lab){return chroma.lab(lab[0], lab[1], lab[2]);});
}
else
{
bool init = true;
if (kMeans == null)
{
kMeans = new List <Vector3>();
init = false;
}
//List<Vector3> kMeans = new List<Vector3>();
kmeansClusters = new Dictionary <int, List <int> >();
for (int i = 0; i < colorsCount; i++)
{
Vector3 lab = new Vector3(Random.value, 2 * Random.value - 1, 2 * Random.value - 1);
while (!checkColor2(lab, checkColor)) //chroma.lab(lab)
{
lab = new Vector3(Random.value, 2 * Random.value - 1, 2 * Random.value - 1);
}
if (!init)
{
kMeans.Add(lab);
}
kmeansClusters.Add(i, new List <int>());
}
colorSamples = new List <Vector3>();
samplesClosest = new List <int>();
if (ultra_precision)
{
for (float l = 0; l <= 1; l += 0.01f)
{
for (float a = -1; a <= 1; a += 0.05f)
{
for (float b = -1; b <= 1; b += 0.05f)
{
if (checkColor2(new Vector3(l, a, b), checkColor)) //chroma.lab(l, a, b)
{
colorSamples.Add(new Vector3(l, a, b));
samplesClosest.Add(-1);
}
}
}
}
}
else
{
for (float l = 0; l <= 1; l += 0.05f)
{
for (float a = -1; a <= 1; a += 0.1f)
{
for (float b = -1; b <= 1; b += 0.1f)
{
if (checkColor2(new Vector3(l, a, b), checkColor))
{
colorSamples.Add(new Vector3(l, a, b));
samplesClosest.Add(-1);
}
}
}
}
}
// Steps
steps = quality;
while (steps > 0)
{
// kMeans -> Samples Closest
for (int i = 0; i < colorSamples.Count; i++)
{
Vector3 lab = colorSamples[i];
float minDistance = 1000000;
for (int j = 0; j < kMeans.Count; j++)
{
Vector3 kMean = kMeans[j];
float distance = Mathf.Sqrt(Mathf.Pow(lab[0] - kMean[0], 2) + Mathf.Pow(lab[1] - kMean[1], 2) + Mathf.Pow(lab[2] - kMean[2], 2));
if (distance < minDistance)
{
minDistance = distance;
samplesClosest[i] = j;
}
}
}
// Samples -> kMeans
List <Vector3> freeColorSamples = new List <Vector3>(colorSamples); //colorSamples.slice(0);//copy?
for (int j = 0; j < kMeans.Count; j++)
{
int count = 0;
Vector3 candidateKMean = new Vector3(0, 0, 0);
//Debug.Log ("J "+j.ToString());
//Debug.Log ("Dic "+kmeansClusters.ToString());
for (int i = 0; i < colorSamples.Count; i++)
{
if (samplesClosest[i] == j)
{
count++;
candidateKMean[0] += colorSamples[i][0];
candidateKMean[1] += colorSamples[i][1];
candidateKMean[2] += colorSamples[i][2];
kmeansClusters[j].Add(i);
}
}
if (count != 0)
{
candidateKMean[0] /= count;
candidateKMean[1] /= count;
candidateKMean[2] /= count;
}
//chroma.lab ?
if (count != 0 && checkColor2(new Vector3(candidateKMean[0], candidateKMean[1], candidateKMean[2]), checkColor) && candidateKMean.magnitude != 0)
{
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
float minDistance = 10000000000;
int closest = -1;
for (int i = 0; i < freeColorSamples.Count; i++)
{
float distance = Mathf.Sqrt(Mathf.Pow(freeColorSamples[i][0] - candidateKMean[0], 2) + Mathf.Pow(freeColorSamples[i][1] - candidateKMean[1], 2) + Mathf.Pow(freeColorSamples[i][2] - candidateKMean[2], 2));
if (distance < minDistance)
{
minDistance = distance;
closest = i;
}
}
kMeans[j] = colorSamples[closest];
}
else
{
// Then we just search for the closest color of the candidate kMean
float minDistance = 10000000000;
int closest = -1;
for (int i = 0; i < colorSamples.Count; i++)
{
float distance = Mathf.Sqrt(Mathf.Pow(colorSamples[i][0] - candidateKMean[0], 2) + Mathf.Pow(colorSamples[i][1] - candidateKMean[1], 2) + Mathf.Pow(colorSamples[i][2] - candidateKMean[2], 2));
if (distance < minDistance)
{
minDistance = distance;
closest = i;
}
}
kMeans[j] = colorSamples[closest];
}
}
//Array.ForEach<int>(intArray, PrintSquare);
IEnumerable <Vector3> freeColorSamples1 =
from color in freeColorSamples
where color[0] != kMeans[j][0] ||
color[1] != kMeans[j][1] ||
color[2] != kMeans[j][2]
select color;
freeColorSamples = freeColorSamples1.ToList();
//freeColorSamples = freeColorSamples.filter(function(color){
// return color[0] != kMeans[j][0]
// || color[1] != kMeans[j][1]
// || color[2] != kMeans[j][2];
// });
}
steps -= 1;
}
IEnumerable <Vector3> krgb = from c in kMeans select lab2rgb(c) / 255.0f;
return(krgb.ToList()); // kMeans.map(function(lab){return chroma.lab(lab[0], lab[1], lab[2]);});lab->torgb?
}
}
