public void MU2c5pTest()
{
double[,] matrExpected = new double[5, 2];
matrExpected[0,0] = 0.99362303;
matrExpected[0,1] = 0.00637697;
matrExpected[1,0] = 0.00113771;
matrExpected[1,1] = 0.99886229;
matrExpected[2,0] = 0.00093486;
matrExpected[2,1] = 0.99906514;
matrExpected[3,0] = 0.99770535;
matrExpected[3,1] = 0.00229465;
matrExpected[4,0] = 0.98516935;
matrExpected[4,1] = 0.01483065;
FuzzyCMean fcm = new FuzzyCMean();
PointRGB[] p = new PointRGB[5];
PointRGB[] c = new PointRGB[2];
c[0] = new PointRGB(245, 14, 45);
c[1] = new PointRGB(56, 78, 134);
p[0] = new PointRGB(203, 171, 184);
p[1] = new PointRGB(72, 162, 213);
p[2] = new PointRGB(73, 143, 165);
p[3] = new PointRGB(210, 212, 187);
p[4] = new PointRGB(198, 214, 103);
double[,] matr = fcm.distributeOverMatrixU(p, c, 1.5);
for (int i = 0; i < p.Length; i++)
{
for (int j = 0; j < c.Length; j++)
{
Assert.IsTrue((matr[i, j] - matrExpected[i, j] < 0.0001) || (Math.Abs(matr[i, j] + matrExpected[i, j] - 1) < 0.0001));
}
}
}
public void MU2c6pTest()
{
double[,] matrExpected = new double[6, 2];
matrExpected[0,0] = 0.00833090;
matrExpected[0,1] = 0.99166910;
matrExpected[1,0] = 0.98813468;
matrExpected[1,1] = 0.01186532;
matrExpected[2,0] = 0.99991329;
matrExpected[2,1] = 0.00008671;
matrExpected[3,0] = 0.00256154;
matrExpected[3,1] = 0.99743846;
matrExpected[4,0] = 0.01959954;
matrExpected[4,1] = 0.98040046;
matrExpected[5,0] = 0.98262987;
matrExpected[5,1] = 0.01737013;
FuzzyCMean fcm = new FuzzyCMean();
PointRGB[] p = new PointRGB[6];
PointRGB[] c = new PointRGB[2];
c[0] = new PointRGB(245, 14, 45);
c[1] = new PointRGB(56, 78, 134);
p[0] = new PointRGB(203, 171, 184);
p[1] = new PointRGB(72, 162, 213);
p[2] = new PointRGB(73, 143, 165);
p[3] = new PointRGB(210, 212, 187);
p[4] = new PointRGB(198, 214, 103);
p[5] = new PointRGB(107, 113, 140);
double[,] matr = fcm.distributeOverMatrixU(p, c, 1.5);
for (int i = 0; i < p.Length; i++)
{
for (int j = 0; j < c.Length; j++)
{
Assert.IsTrue((matr[i, j] - matrExpected[i, j] < 0.0001) || (Math.Abs(matr[i, j] + matrExpected[i, j] - 1) < 0.0001));
}
}
}
public PointRGB[] generateRandomPoints(int count)
{
PointRGB[] points = new PointRGB[count];
for (int i = 0; i < count; i++)
{
PointRGB p = new PointRGB(rand.Next(20, 235), rand.Next(20, 235), rand.Next(20, 235));
points[i] = p;
}
return points;
}
public double[,] distributeOverMatrixU(PointRGB[] arr, PointRGB[] centers, double m)
{
MatrixU = fillUMatrix(arr.Length, centers.Length);
double previousDecisionValue = 0;
double currentDecisionValue = 1;
double sum;
int pointsCount = arr.Length;
int clustersCount = centers.Length;
for (int a = 0; a < max_cycles_count && (Math.Abs(previousDecisionValue - currentDecisionValue) > e); a++)
{
previousDecisionValue = currentDecisionValue;
centers = calculateCenters(MatrixU, m, arr);
for (int i = 0; i < pointsCount; i++)
{
for (int j = 0; j < clustersCount; j++)
{
double distance = evklidDistance3D(arr[i], centers[j]);
MatrixU[i, j] = Math.Pow(1 / distance, 2 / (m - 1));
}
sum = 0;
for (int j = 0; j < clustersCount; j++)
{
sum += MatrixU[i, j];
}
for (int j = 0; j < clustersCount; j++)
{
MatrixU[i, j] = MatrixU[i, j] / sum;
}
}
currentDecisionValue = calculateDecisionFunction(arr, centers, MatrixU);
}
newCenters = centers;
return MatrixU;
}
public void MU3c10pTest()
{
double[,] matrExpected = new double[10, 3];
matrExpected[0,0] = 0.00207611;
matrExpected[0,1] = 0.00211681;
matrExpected[0,2] = 0.99580708;
matrExpected[1,0] = 0.04862492;
matrExpected[1,1] = 0.86031170;
matrExpected[1,2] = 0.09106338;
matrExpected[2,0] = 0.00279667;
matrExpected[2,1] = 0.99480518;
matrExpected[2,2] = 0.00239814;
matrExpected[3,0] = 0.00302810;
matrExpected[3,1] = 0.00455935;
matrExpected[3,2] = 0.99241255;
matrExpected[4,0] = 0.01634000;
matrExpected[4,1] = 0.02473899;
matrExpected[4,2] = 0.95892102;
matrExpected[5,0] = 0.10414700;
matrExpected[5,1] = 0.87619866;
matrExpected[5,2] = 0.01965435;
matrExpected[6,0] = 0.00237029;
matrExpected[6,1] = 0.99606029;
matrExpected[6,2] = 0.00156942;
matrExpected[7,0] = 0.15594909;
matrExpected[7,1] = 0.80011012;
matrExpected[7,2] = 0.04394078;
matrExpected[8,0] = 0.02205131;
matrExpected[8,1] = 0.01168445;
matrExpected[8,2] = 0.96626424;
matrExpected[9,0] = 0.99983770;
matrExpected[9,1] = 0.00010124;
matrExpected[9,2] = 0.00006106;
FuzzyCMean fcm = new FuzzyCMean();
PointRGB[] p = new PointRGB[10];
PointRGB[] c = new PointRGB[3];
c[0] = new PointRGB(245, 14, 45);
c[1] = new PointRGB(56, 78, 134);
c[2] = new PointRGB(20, 25, 68);
p[0] = new PointRGB(203, 171, 184);
p[1] = new PointRGB(72, 162, 213);
p[2] = new PointRGB(73, 143, 165);
p[3] = new PointRGB(210, 212, 187);
p[4] = new PointRGB(198, 214, 103);
p[5] = new PointRGB(107, 113, 140);
p[6] = new PointRGB(59, 153, 112);
p[7] = new PointRGB(38, 121, 43);
p[8] = new PointRGB(193, 144, 149);
p[9] = new PointRGB(160, 45, 120);
double[,] matr = fcm.distributeOverMatrixU(p, c, 1.5);
for (int i = 0; i < p.Length; i++)
{
for (int j = 0; j < c.Length; j++)
{
Assert.IsTrue((matr[i, j] - matrExpected[i, j] < 0.0001) || (Math.Abs(matr[i, j] + matrExpected[i, j] - 1) < 0.0001));
}
}
}
public void MU3c9pTest()
{
double[,] matrExpected = new double[9, 3];
matrExpected[0,0] = 0.00392690;
matrExpected[0,1] = 0.00067333;
matrExpected[0,2] = 0.99539977;
matrExpected[1,0] = 0.97633035;
matrExpected[1,1] = 0.01134808;
matrExpected[1,2] = 0.01232157;
matrExpected[2,0] = 0.99971304;
matrExpected[2,1] = 0.00022717;
matrExpected[2,2] = 0.00005979;
matrExpected[3,0] = 0.00669097;
matrExpected[3,1] = 0.00152497;
matrExpected[3,2] = 0.99178406;
matrExpected[4,0] = 0.02290245;
matrExpected[4,1] = 0.01418927;
matrExpected[4,2] = 0.96290828;
matrExpected[5,0] = 0.90399009;
matrExpected[5,1] = 0.07025695;
matrExpected[5,2] = 0.02575295;
matrExpected[6,0] = 0.18064114;
matrExpected[6,1] = 0.81296270;
matrExpected[6,2] = 0.00639616;
matrExpected[7,0] = 0.00367131;
matrExpected[7,1] = 0.99562017;
matrExpected[7,2] = 0.00070852;
matrExpected[8,0] = 0.01868184;
matrExpected[8,1] = 0.00418239;
matrExpected[8,2] = 0.97713577;
FuzzyCMean fcm = new FuzzyCMean();
PointRGB[] p = new PointRGB[9];
PointRGB[] c = new PointRGB[3];
c[0] = new PointRGB(245, 14, 45);
c[1] = new PointRGB(56, 78, 134);
c[2] = new PointRGB(20, 25, 68);
p[0] = new PointRGB(203, 171, 184);
p[1] = new PointRGB(72, 162, 213);
p[2] = new PointRGB(73, 143, 165);
p[3] = new PointRGB(210, 212, 187);
p[4] = new PointRGB(198, 214, 103);
p[5] = new PointRGB(107, 113, 140);
p[6] = new PointRGB(59, 153, 112);
p[7] = new PointRGB(38, 121, 43);
p[8] = new PointRGB(193, 144, 149);
double[,] matr = fcm.distributeOverMatrixU(p, c, 1.5);
for (int i = 0; i < p.Length; i++)
{
for (int j = 0; j < c.Length; j++)
{
Assert.IsTrue((matr[i, j] - matrExpected[i, j] < 0.0001) || (Math.Abs(matr[i, j] + matrExpected[i, j] - 1) < 0.0001));
}
}
}
public double evklidDistance3D(PointRGB pointA, PointRGB pointB)
{
double distance1 = Math.Pow((pointA.R - pointB.R),2);
double distance2 = Math.Pow((pointA.G - pointB.G),2);
double distance3 = Math.Pow((pointA.B - pointB.B),2);
double distance = distance1 + distance2 + distance3;
return Math.Sqrt(distance);
}
public void MU4c10pTest()
{
double[,] matrExpected = new double[10, 4];
matrExpected[0,0] = 0.00387958;
matrExpected[0,1] = 0.00215156;
matrExpected[0,2] = 0.00067191;
matrExpected[0,3] = 0.99329695;
matrExpected[1,0] = 0.97685574;
matrExpected[1,1] = 0.00464232;
matrExpected[1,2] = 0.00887049;
matrExpected[1,3] = 0.00963144;
matrExpected[2,0] = 0.99961964;
matrExpected[2,1] = 0.00006380;
matrExpected[2,2] = 0.00025060;
matrExpected[2,3] = 0.00006596;
matrExpected[3,0] = 0.00672350;
matrExpected[3,1] = 0.00272701;
matrExpected[3,2] = 0.00152073;
matrExpected[3,3] = 0.98902876;
matrExpected[4,0] = 0.02216181;
matrExpected[4,1] = 0.01461795;
matrExpected[4,2] = 0.01398775;
matrExpected[4,3] = 0.94923249;
matrExpected[5,0] = 0.78676442;
matrExpected[5,1] = 0.10765810;
matrExpected[5,2] = 0.07725820;
matrExpected[5,3] = 0.02831929;
matrExpected[6,0] = 0.16933353;
matrExpected[6,1] = 0.00768052;
matrExpected[6,2] = 0.81656147;
matrExpected[6,3] = 0.00642447;
matrExpected[7,0] = 0.00347393;
matrExpected[7,1] = 0.00199645;
matrExpected[7,2] = 0.99382238;
matrExpected[7,3] = 0.00070724;
matrExpected[8,0] = 0.01741314;
matrExpected[8,1] = 0.02373964;
matrExpected[8,2] = 0.00408662;
matrExpected[8,3] = 0.95476060;
matrExpected[9,0] = 0.00000049;
matrExpected[9,1] = 0.99999885;
matrExpected[9,2] = 0.00000032;
matrExpected[9,3] = 0.00000033;
FuzzyCMean fcm = new FuzzyCMean();
PointRGB[] p = new PointRGB[10];
PointRGB[] c = new PointRGB[4];
c[0] = new PointRGB(245, 14, 45);
c[1] = new PointRGB(56, 78, 134);
c[2] = new PointRGB(20, 25, 68);
c[3] = new PointRGB(125, 100, 30);
p[0] = new PointRGB(203, 171, 184);
p[1] = new PointRGB(72, 162, 213);
p[2] = new PointRGB(73, 143, 165);
p[3] = new PointRGB(210, 212, 187);
p[4] = new PointRGB(198, 214, 103);
p[5] = new PointRGB(107, 113, 140);
p[6] = new PointRGB(59, 153, 112);
p[7] = new PointRGB(38, 121, 43);
p[8] = new PointRGB(193, 144, 149);
p[9] = new PointRGB(160, 45, 120);
double[,] matr = fcm.distributeOverMatrixU(p, c, 1.5);
for (int i = 0; i < p.Length; i++)
{
for (int j = 0; j < c.Length; j++)
{
Assert.IsTrue((matr[i, j] - matrExpected[i, j] < 0.0001) || (Math.Abs(matr[i, j] + matrExpected[i, j] - 1) < 0.0001));
}
}
}
public void MU4c9pTest()
{
double[,] matrExpected = new double[9, 4];
matrExpected[0,0] = 0.99379413;
matrExpected[0,1] = 0.00312986;
matrExpected[0,2] = 0.00268497;
matrExpected[0,3] = 0.00039104;
matrExpected[1,0] = 0.00076141;
matrExpected[1,1] = 0.99446683;
matrExpected[1,2] = 0.00445659;
matrExpected[1,3] = 0.00031518;
matrExpected[2,0] = 0.00149362;
matrExpected[2,1] = 0.82210063;
matrExpected[2,2] = 0.17460307;
matrExpected[2,3] = 0.00180267;
matrExpected[3,0] = 0.98836640;
matrExpected[3,1] = 0.00610111;
matrExpected[3,2] = 0.00462978;
matrExpected[3,3] = 0.00090270;
matrExpected[4,0] = 0.94361224;
matrExpected[4,1] = 0.01690011;
matrExpected[4,2] = 0.03066885;
matrExpected[4,3] = 0.00881880;
matrExpected[5,0] = 0.00524505;
matrExpected[5,1] = 0.03630806;
matrExpected[5,2] = 0.95317084;
matrExpected[5,3] = 0.00527605;
matrExpected[6,0] = 0.00286831;
matrExpected[6,1] = 0.03732810;
matrExpected[6,2] = 0.92023653;
matrExpected[6,3] = 0.03956705;
matrExpected[7,0] = 0.00000000;
matrExpected[7,1] = 0.00000000;
matrExpected[7,2] = 0.00000000;
matrExpected[7,3] = NaN;
matrExpected[8,0] = 0.96625578;
matrExpected[8,1] = 0.01144212;
matrExpected[8,2] = 0.01987430;
matrExpected[8,3] = 0.00242780;
FuzzyCMean fcm = new FuzzyCMean();
PointRGB[] p = new PointRGB[9];
PointRGB[] c = new PointRGB[4];
c[0] = new PointRGB(245, 14, 45);
c[1] = new PointRGB(56, 78, 134);
c[2] = new PointRGB(20, 25, 68);
c[3] = new PointRGB(125, 100, 30);
p[0] = new PointRGB(203, 171, 184);
p[1] = new PointRGB(72, 162, 213);
p[2] = new PointRGB(73, 143, 165);
p[3] = new PointRGB(210, 212, 187);
p[4] = new PointRGB(198, 214, 103);
p[5] = new PointRGB(107, 113, 140);
p[6] = new PointRGB(59, 153, 112);
p[7] = new PointRGB(38, 121, 43);
p[8] = new PointRGB(193, 144, 149);
double[,] matr = fcm.distributeOverMatrixU(p, c, 1.5);
for (int i = 0; i < p.Length; i++)
{
for (int j = 0; j < c.Length; j++)
{
Assert.IsTrue((matr[i, j] - matrExpected[i, j] < 0.0001) || (Math.Abs(matr[i, j] + matrExpected[i, j] - 1) < 0.0001));
}
}
}
public void MU4c7pTest()
{
double[,] matrExpected = new double[7, 4];
matrExpected[0,0] = 0.00052071;
matrExpected[0,1] = 0.00239649;
matrExpected[0,2] = 0.00047349;
matrExpected[0,3] = 0.99660931;
matrExpected[1,0] = 0.99999726;
matrExpected[1,1] = 0.00000011;
matrExpected[1,2] = 0.00000237;
matrExpected[1,3] = 0.00000026;
matrExpected[2,0] = 0.11996475;
matrExpected[2,1] = 0.00113877;
matrExpected[2,2] = 0.87730344;
matrExpected[2,3] = 0.00159304;
matrExpected[3,0] = 0.00043015;
matrExpected[3,1] = 0.00405054;
matrExpected[3,2] = 0.00032687;
matrExpected[3,3] = 0.99519244;
matrExpected[4,0] = 0.00000000;
matrExpected[4,1] = 0.99999991;
matrExpected[4,2] = 0.00000001;
matrExpected[4,3] = 0.00000007;
matrExpected[5,0] = 0.02377465;
matrExpected[5,1] = 0.00445635;
matrExpected[5,2] = 0.96650308;
matrExpected[5,3] = 0.00526593;
matrExpected[6,0] = 0.01743612;
matrExpected[6,1] = 0.00326714;
matrExpected[6,2] = 0.97720220;
matrExpected[6,3] = 0.00209454;
FuzzyCMean fcm = new FuzzyCMean();
PointRGB[] p = new PointRGB[7];
PointRGB[] c = new PointRGB[4];
c[0] = new PointRGB(245, 14, 45);
c[1] = new PointRGB(56, 78, 134);
c[2] = new PointRGB(20, 25, 68);
c[3] = new PointRGB(125, 100, 30);
p[0] = new PointRGB(203, 171, 184);
p[1] = new PointRGB(72, 162, 213);
p[2] = new PointRGB(73, 143, 165);
p[3] = new PointRGB(210, 212, 187);
p[4] = new PointRGB(198, 214, 103);
p[5] = new PointRGB(107, 113, 140);
p[6] = new PointRGB(59, 153, 112);
double[,] matr = fcm.distributeOverMatrixU(p, c, 1.5);
for (int i = 0; i < p.Length; i++)
{
for (int j = 0; j < c.Length; j++)
{
Assert.IsTrue((matr[i, j] - matrExpected[i, j] < 0.0001) || (Math.Abs(matr[i, j] + matrExpected[i, j] - 1) < 0.0001));
}
}
}
public void MU2c10pTest()
{
double[,] matrExpected = new double[10, 2];
matrExpected[0,0] = 0.99778699;
matrExpected[0,1] = 0.00221301;
matrExpected[1,0] = 0.15251194;
matrExpected[1,1] = 0.84748806;
matrExpected[2,0] = 0.00825304;
matrExpected[2,1] = 0.99174696;
matrExpected[3,0] = 0.99309844;
matrExpected[3,1] = 0.00690156;
matrExpected[4,0] = 0.96967201;
matrExpected[4,1] = 0.03032799;
matrExpected[5,0] = 0.00649101;
matrExpected[5,1] = 0.99350899;
matrExpected[6,0] = 0.00444359;
matrExpected[6,1] = 0.99555641;
matrExpected[7,0] = 0.04919440;
matrExpected[7,1] = 0.95080560;
matrExpected[8,0] = 0.99102517;
matrExpected[8,1] = 0.00897483;
matrExpected[9,0] = 0.29283491;
matrExpected[9,1] = 0.70716509;
FuzzyCMean fcm = new FuzzyCMean();
PointRGB[] p = new PointRGB[10];
PointRGB[] c = new PointRGB[2];
c[0] = new PointRGB(245, 14, 45);
c[1] = new PointRGB(56, 78, 134);
p[0] = new PointRGB(203, 171, 184);
p[1] = new PointRGB(72, 162, 213);
p[2] = new PointRGB(73, 143, 165);
p[3] = new PointRGB(210, 212, 187);
p[4] = new PointRGB(198, 214, 103);
p[5] = new PointRGB(107, 113, 140);
p[6] = new PointRGB(59, 153, 112);
p[7] = new PointRGB(38, 121, 43);
p[8] = new PointRGB(193, 144, 149);
p[9] = new PointRGB(160, 45, 120);
double[,] matr = fcm.distributeOverMatrixU(p, c, 1.5);
for (int i = 0; i < p.Length; i++)
{
for (int j = 0; j < c.Length; j++)
{
Assert.IsTrue((matr[i, j] - matrExpected[i, j] < 0.0001) || (Math.Abs(matr[i, j] + matrExpected[i, j] - 1) < 0.0001));
}
}
}
public void MU2c9pTest()
{
double[,] matrExpected = new double[9, 2];
matrExpected[0,0] = 0.00205013;
matrExpected[0,1] = 0.99794987;
matrExpected[1,0] = 0.89007612;
matrExpected[1,1] = 0.10992388;
matrExpected[2,0] = 0.99641480;
matrExpected[2,1] = 0.00358520;
matrExpected[3,0] = 0.00442415;
matrExpected[3,1] = 0.99557585;
matrExpected[4,0] = 0.02523080;
matrExpected[4,1] = 0.97476920;
matrExpected[5,0] = 0.97843406;
matrExpected[5,1] = 0.02156594;
matrExpected[6,0] = 0.99877772;
matrExpected[6,1] = 0.00122228;
matrExpected[7,0] = 0.95357115;
matrExpected[7,1] = 0.04642885;
matrExpected[8,0] = 0.01179832;
matrExpected[8,1] = 0.98820168;
FuzzyCMean fcm = new FuzzyCMean();
PointRGB[] p = new PointRGB[9];
PointRGB[] c = new PointRGB[2];
c[0] = new PointRGB(245, 14, 45);
c[1] = new PointRGB(56, 78, 134);
p[0] = new PointRGB(203, 171, 184);
p[1] = new PointRGB(72, 162, 213);
p[2] = new PointRGB(73, 143, 165);
p[3] = new PointRGB(210, 212, 187);
p[4] = new PointRGB(198, 214, 103);
p[5] = new PointRGB(107, 113, 140);
p[6] = new PointRGB(59, 153, 112);
p[7] = new PointRGB(38, 121, 43);
p[8] = new PointRGB(193, 144, 149);
double[,] matr = fcm.distributeOverMatrixU(p, c, 1.5);
for (int i = 0; i < p.Length; i++)
{
for (int j = 0; j < c.Length; j++)
{
Assert.IsTrue((matr[i, j] - matrExpected[i, j] < 0.0001) || (Math.Abs(matr[i, j] + matrExpected[i, j] - 1) < 0.0001));
}
}
}
public void MU2c8pTest()
{
double[,] matrExpected = new double[8, 2];
matrExpected[0,0] = 0.00432479;
matrExpected[0,1] = 0.99567521;
matrExpected[1,0] = 0.90018885;
matrExpected[1,1] = 0.09981115;
matrExpected[2,0] = 0.99705224;
matrExpected[2,1] = 0.00294776;
matrExpected[3,0] = 0.00159266;
matrExpected[3,1] = 0.99840734;
matrExpected[4,0] = 0.01994903;
matrExpected[4,1] = 0.98005097;
matrExpected[5,0] = 0.98469110;
matrExpected[5,1] = 0.01530890;
matrExpected[6,0] = 0.99895262;
matrExpected[6,1] = 0.00104738;
matrExpected[7,0] = 0.95934073;
matrExpected[7,1] = 0.04065927;
FuzzyCMean fcm = new FuzzyCMean();
PointRGB[] p = new PointRGB[8];
PointRGB[] c = new PointRGB[2];
c[0] = new PointRGB(245, 14, 45);
c[1] = new PointRGB(56, 78, 134);
p[0] = new PointRGB(203, 171, 184);
p[1] = new PointRGB(72, 162, 213);
p[2] = new PointRGB(73, 143, 165);
p[3] = new PointRGB(210, 212, 187);
p[4] = new PointRGB(198, 214, 103);
p[5] = new PointRGB(107, 113, 140);
p[6] = new PointRGB(59, 153, 112);
p[7] = new PointRGB(38, 121, 43);
double[,] matr = fcm.distributeOverMatrixU(p, c, 1.5);
for (int i = 0; i < p.Length; i++)
{
for (int j = 0; j < c.Length; j++)
{
Assert.IsTrue((matr[i, j] - matrExpected[i, j] < 0.0001) || (Math.Abs(matr[i, j] + matrExpected[i, j] - 1) < 0.0001));
}
}
}
private PointRGB[] calculateCenters(double[,] MatrixU, double m, PointRGB[] points)
{
PointRGB[] MatrixCentroids = new PointRGB[MatrixU.GetLength(0)];
int pointsCount = MatrixU.GetLength(0);
int clustersCount = MatrixU.GetLength(1);
for (int clusterIndex = 0; clusterIndex < clustersCount; clusterIndex++)
{
double tempAr = 0;
double tempBr = 0;
double tempAg = 0;
double tempBg = 0;
double tempAb = 0;
double tempBb = 0;
for (int j = 0; j < pointsCount; j++)
{
tempAr += Math.Pow(MatrixU[j, clusterIndex], m);
tempBr += Math.Pow(MatrixU[j, clusterIndex], m) * points[j].R;
tempAg += Math.Pow(MatrixU[j, clusterIndex], m);
tempBg += Math.Pow(MatrixU[j, clusterIndex], m) * points[j].G;
tempAb += Math.Pow(MatrixU[j, clusterIndex], m);
tempBb += Math.Pow(MatrixU[j, clusterIndex], m) * points[j].B;
}
MatrixCentroids[clusterIndex] = new PointRGB((int)(tempBr / tempAr), (int)(tempBg / tempAg), (int)(tempBb / tempAb));
}
return MatrixCentroids;
}
public void MU4c5pTest()
{
double[,] matrExpected = new double[5, 4];
matrExpected[0,0] = 0.00000001;
matrExpected[0,1] = 0.00000006;
matrExpected[0,2] = 0.99999845;
matrExpected[0,3] = 0.00000148;
matrExpected[1,0] = 0.99668012;
matrExpected[1,1] = 0.00056964;
matrExpected[1,2] = 0.00165252;
matrExpected[1,3] = 0.00109771;
matrExpected[2,0] = 0.99750703;
matrExpected[2,1] = 0.00064009;
matrExpected[2,2] = 0.00118449;
matrExpected[2,3] = 0.00066839;
matrExpected[3,0] = 0.00000001;
matrExpected[3,1] = 0.00000008;
matrExpected[3,2] = 0.00000119;
matrExpected[3,3] = 0.99999873;
matrExpected[4,0] = 0.00000001;
matrExpected[4,1] = 0.99999986;
matrExpected[4,2] = 0.00000006;
matrExpected[4,3] = 0.00000008;
FuzzyCMean fcm = new FuzzyCMean();
PointRGB[] p = new PointRGB[5];
PointRGB[] c = new PointRGB[4];
c[0] = new PointRGB(245, 14, 45);
c[1] = new PointRGB(56, 78, 134);
c[2] = new PointRGB(20, 25, 68);
c[3] = new PointRGB(125, 100, 30);
p[0] = new PointRGB(203, 171, 184);
p[1] = new PointRGB(72, 162, 213);
p[2] = new PointRGB(73, 143, 165);
p[3] = new PointRGB(210, 212, 187);
p[4] = new PointRGB(198, 214, 103);
double[,] matr = fcm.distributeOverMatrixU(p, c, 1.5);
for (int i = 0; i < p.Length; i++)
{
for (int j = 0; j < c.Length; j++)
{
Assert.IsTrue((matr[i, j] - matrExpected[i, j] < 0.0001) || (Math.Abs(matr[i, j] + matrExpected[i, j] - 1) < 0.0001));
}
}
}
public void MU4c6pTest()
{
double[,] matrExpected = new double[6, 4];
matrExpected[0,0] = 0.00054555;
matrExpected[0,1] = 0.00077408;
matrExpected[0,2] = 0.00239571;
matrExpected[0,3] = 0.99628466;
matrExpected[1,0] = 0.99394929;
matrExpected[1,1] = 0.00468394;
matrExpected[1,2] = 0.00040216;
matrExpected[1,3] = 0.00096462;
matrExpected[2,0] = 0.92651765;
matrExpected[2,1] = 0.07146868;
matrExpected[2,2] = 0.00083941;
matrExpected[2,3] = 0.00117426;
matrExpected[3,0] = 0.00041649;
matrExpected[3,1] = 0.00040590;
matrExpected[3,2] = 0.00405028;
matrExpected[3,3] = 0.99512733;
matrExpected[4,0] = 0.00000001;
matrExpected[4,1] = 0.00000001;
matrExpected[4,2] = 0.99999991;
matrExpected[4,3] = 0.00000007;
matrExpected[5,0] = 0.00000004;
matrExpected[5,1] = 0.99999996;
matrExpected[5,2] = 0.00000000;
matrExpected[5,3] = 0.00000000;
FuzzyCMean fcm = new FuzzyCMean();
PointRGB[] p = new PointRGB[6];
PointRGB[] c = new PointRGB[4];
c[0] = new PointRGB(245, 14, 45);
c[1] = new PointRGB(56, 78, 134);
c[2] = new PointRGB(20, 25, 68);
c[3] = new PointRGB(125, 100, 30);
p[0] = new PointRGB(203, 171, 184);
p[1] = new PointRGB(72, 162, 213);
p[2] = new PointRGB(73, 143, 165);
p[3] = new PointRGB(210, 212, 187);
p[4] = new PointRGB(198, 214, 103);
p[5] = new PointRGB(107, 113, 140);
double[,] matr = fcm.distributeOverMatrixU(p, c, 1.5);
for (int i = 0; i < p.Length; i++)
{
for (int j = 0; j < c.Length; j++)
{
Assert.IsTrue((matr[i, j] - matrExpected[i, j] < 0.0001) || (Math.Abs(matr[i, j] + matrExpected[i, j] - 1) < 0.0001));
}
}
}
public void MU3c5pTest()
{
double[,] matrExpected = new double[5, 3];
matrExpected[0,0] = 0.00054491;
matrExpected[0,1] = 0.99705121;
matrExpected[0,2] = 0.00240388;
matrExpected[1,0] = 0.99807063;
matrExpected[1,1] = 0.00136826;
matrExpected[1,2] = 0.00056111;
matrExpected[2,0] = 0.99847600;
matrExpected[2,1] = 0.00089631;
matrExpected[2,2] = 0.00062769;
matrExpected[3,0] = 0.00041257;
matrExpected[3,1] = 0.99550742;
matrExpected[3,2] = 0.00408001;
matrExpected[4,0] = 0.00000000;
matrExpected[4,1] = 0.00000002;
matrExpected[4,2] = 0.99999998;
FuzzyCMean fcm = new FuzzyCMean();
PointRGB[] p = new PointRGB[5];
PointRGB[] c = new PointRGB[3];
c[0] = new PointRGB(245, 14, 45);
c[1] = new PointRGB(56, 78, 134);
c[2] = new PointRGB(20, 25, 68);
p[0] = new PointRGB(203, 171, 184);
p[1] = new PointRGB(72, 162, 213);
p[2] = new PointRGB(73, 143, 165);
p[3] = new PointRGB(210, 212, 187);
p[4] = new PointRGB(198, 214, 103);
double[,] matr = fcm.distributeOverMatrixU(p, c, 1.5);
for (int i = 0; i < p.Length; i++)
{
for (int j = 0; j < c.Length; j++)
{
Assert.IsTrue((matr[i, j] - matrExpected[i, j] < 0.0001) || (Math.Abs(matr[i, j] + matrExpected[i, j] - 1) < 0.0001));
}
}
}
public void MU4c8pTest()
{
double[,] matrExpected = new double[8, 4];
matrExpected[0,0] = 0.00589397;
matrExpected[0,1] = 0.00073638;
matrExpected[0,2] = 0.00497074;
matrExpected[0,3] = 0.98839891;
matrExpected[1,0] = 0.99444553;
matrExpected[1,1] = 0.00031517;
matrExpected[1,2] = 0.00454436;
matrExpected[1,3] = 0.00069494;
matrExpected[2,0] = 0.81493949;
matrExpected[2,1] = 0.00178697;
matrExpected[2,2] = 0.18203872;
matrExpected[2,3] = 0.00123482;
matrExpected[3,0] = 0.00207571;
matrExpected[3,1] = 0.00030712;
matrExpected[3,2] = 0.00156376;
matrExpected[3,3] = 0.99605341;
matrExpected[4,0] = 0.01484821;
matrExpected[4,1] = 0.00774808;
matrExpected[4,2] = 0.02677084;
matrExpected[4,3] = 0.95063288;
matrExpected[5,0] = 0.04218263;
matrExpected[5,1] = 0.00612970;
matrExpected[5,2] = 0.94728849;
matrExpected[5,3] = 0.00439918;
matrExpected[6,0] = 0.03266716;
matrExpected[6,1] = 0.03462654;
matrExpected[6,2] = 0.93055356;
matrExpected[6,3] = 0.00215273;
matrExpected[7,0] = 0.00000000;
matrExpected[7,1] = NaN;
matrExpected[7,2] = 0.00000000;
matrExpected[7,3] = 0.00000000;
FuzzyCMean fcm = new FuzzyCMean();
PointRGB[] p = new PointRGB[8];
PointRGB[] c = new PointRGB[4];
c[0] = new PointRGB(245, 14, 45);
c[1] = new PointRGB(56, 78, 134);
c[2] = new PointRGB(20, 25, 68);
c[3] = new PointRGB(125, 100, 30);
p[0] = new PointRGB(203, 171, 184);
p[1] = new PointRGB(72, 162, 213);
p[2] = new PointRGB(73, 143, 165);
p[3] = new PointRGB(210, 212, 187);
p[4] = new PointRGB(198, 214, 103);
p[5] = new PointRGB(107, 113, 140);
p[6] = new PointRGB(59, 153, 112);
p[7] = new PointRGB(38, 121, 43);
double[,] matr = fcm.distributeOverMatrixU(p, c, 1.5);
for (int i = 0; i < p.Length; i++)
{
for (int j = 0; j < c.Length; j++)
{
Assert.IsTrue((matr[i, j] - matrExpected[i, j] < 0.0001) || (Math.Abs(matr[i, j] + matrExpected[i, j] - 1) < 0.0001));
}
}
}
public void MU3c6pTest()
{
double[,] matrExpected = new double[6, 3];
matrExpected[0,0] = 0.99691133;
matrExpected[0,1] = 0.00239722;
matrExpected[0,2] = 0.00069145;
matrExpected[1,0] = 0.01389251;
matrExpected[1,1] = 0.00579189;
matrExpected[1,2] = 0.98031560;
matrExpected[2,0] = 0.00006546;
matrExpected[2,1] = 0.00004679;
matrExpected[2,2] = 0.99988775;
matrExpected[3,0] = 0.99549822;
matrExpected[3,1] = 0.00405179;
matrExpected[3,2] = 0.00044999;
matrExpected[4,0] = 0.00000007;
matrExpected[4,1] = 0.99999992;
matrExpected[4,2] = 0.00000001;
matrExpected[5,0] = 0.01568172;
matrExpected[5,1] = 0.01327082;
matrExpected[5,2] = 0.97104746;
FuzzyCMean fcm = new FuzzyCMean();
PointRGB[] p = new PointRGB[6];
PointRGB[] c = new PointRGB[3];
c[0] = new PointRGB(245, 14, 45);
c[1] = new PointRGB(56, 78, 134);
c[2] = new PointRGB(20, 25, 68);
p[0] = new PointRGB(203, 171, 184);
p[1] = new PointRGB(72, 162, 213);
p[2] = new PointRGB(73, 143, 165);
p[3] = new PointRGB(210, 212, 187);
p[4] = new PointRGB(198, 214, 103);
p[5] = new PointRGB(107, 113, 140);
double[,] matr = fcm.distributeOverMatrixU(p, c, 1.5);
for (int i = 0; i < p.Length; i++)
{
for (int j = 0; j < c.Length; j++)
{
Assert.IsTrue((matr[i, j] - matrExpected[i, j] < 0.0001) || (Math.Abs(matr[i, j] + matrExpected[i, j] - 1) < 0.0001));
}
}
}
public void MU2c7pTest()
{
double[,] matrExpected = new double[7, 2];
matrExpected[0,0] = 0.00644397;
matrExpected[0,1] = 0.99355603;
matrExpected[1,0] = 0.97325628;
matrExpected[1,1] = 0.02674372;
matrExpected[2,0] = 0.99998356;
matrExpected[2,1] = 0.00001644;
matrExpected[3,0] = 0.00213306;
matrExpected[3,1] = 0.99786694;
matrExpected[4,0] = 0.02069683;
matrExpected[4,1] = 0.97930317;
matrExpected[5,0] = 0.98555014;
matrExpected[5,1] = 0.01444986;
matrExpected[6,0] = 0.99023803;
matrExpected[6,1] = 0.00976197;
FuzzyCMean fcm = new FuzzyCMean();
PointRGB[] p = new PointRGB[7];
PointRGB[] c = new PointRGB[2];
c[0] = new PointRGB(245, 14, 45);
c[1] = new PointRGB(56, 78, 134);
p[0] = new PointRGB(203, 171, 184);
p[1] = new PointRGB(72, 162, 213);
p[2] = new PointRGB(73, 143, 165);
p[3] = new PointRGB(210, 212, 187);
p[4] = new PointRGB(198, 214, 103);
p[5] = new PointRGB(107, 113, 140);
p[6] = new PointRGB(59, 153, 112);
double[,] matr = fcm.distributeOverMatrixU(p, c, 1.5);
for (int i = 0; i < p.Length; i++)
{
for (int j = 0; j < c.Length; j++)
{
Assert.IsTrue((matr[i, j] - matrExpected[i, j] < 0.0001) || (Math.Abs(matr[i, j] + matrExpected[i, j] - 1) < 0.0001));
}
}
}
public void MU3c7pTest()
{
double[,] matrExpected = new double[7, 3];
matrExpected[0,0] = 0.98843361;
matrExpected[0,1] = 0.00521983;
matrExpected[0,2] = 0.00634656;
matrExpected[1,0] = 0.00068811;
matrExpected[1,1] = 0.00456865;
matrExpected[1,2] = 0.99474323;
matrExpected[2,0] = 0.00123014;
matrExpected[2,1] = 0.18585713;
matrExpected[2,2] = 0.81291273;
matrExpected[3,0] = 0.99598016;
matrExpected[3,1] = 0.00170797;
matrExpected[3,2] = 0.00231187;
matrExpected[4,0] = 0.96117425;
matrExpected[4,1] = 0.02477243;
matrExpected[4,2] = 0.01405332;
matrExpected[5,0] = 0.00481470;
matrExpected[5,1] = 0.94922143;
matrExpected[5,2] = 0.04596387;
matrExpected[6,0] = 0.00207998;
matrExpected[6,1] = 0.96659160;
matrExpected[6,2] = 0.03132843;
FuzzyCMean fcm = new FuzzyCMean();
PointRGB[] p = new PointRGB[7];
PointRGB[] c = new PointRGB[3];
c[0] = new PointRGB(245, 14, 45);
c[1] = new PointRGB(56, 78, 134);
c[2] = new PointRGB(20, 25, 68);
p[0] = new PointRGB(203, 171, 184);
p[1] = new PointRGB(72, 162, 213);
p[2] = new PointRGB(73, 143, 165);
p[3] = new PointRGB(210, 212, 187);
p[4] = new PointRGB(198, 214, 103);
p[5] = new PointRGB(107, 113, 140);
p[6] = new PointRGB(59, 153, 112);
double[,] matr = fcm.distributeOverMatrixU(p, c, 1.5);
for (int i = 0; i < p.Length; i++)
{
for (int j = 0; j < c.Length; j++)
{
Assert.IsTrue((matr[i, j] - matrExpected[i, j] < 0.0001) || (Math.Abs(matr[i, j] + matrExpected[i, j] - 1) < 0.0001));
}
}
}
public void MU3c8pTest()
{
double[,] matrExpected = new double[8, 3];
matrExpected[0,0] = 0.00788824;
matrExpected[0,1] = 0.00135257;
matrExpected[0,2] = 0.99075919;
matrExpected[1,0] = 0.97776544;
matrExpected[1,1] = 0.01136476;
matrExpected[1,2] = 0.01086980;
matrExpected[2,0] = 0.99972441;
matrExpected[2,1] = 0.00022717;
matrExpected[2,2] = 0.00004841;
matrExpected[3,0] = 0.00247573;
matrExpected[3,1] = 0.00056425;
matrExpected[3,2] = 0.99696002;
matrExpected[4,0] = 0.01887481;
matrExpected[4,1] = 0.01169394;
matrExpected[4,2] = 0.96943125;
matrExpected[5,0] = 0.91088105;
matrExpected[5,1] = 0.07079251;
matrExpected[5,2] = 0.01832645;
matrExpected[6,0] = 0.18082271;
matrExpected[6,1] = 0.81377982;
matrExpected[6,2] = 0.00539746;
matrExpected[7,0] = 0.00367166;
matrExpected[7,1] = 0.99571614;
matrExpected[7,2] = 0.00061219;
FuzzyCMean fcm = new FuzzyCMean();
PointRGB[] p = new PointRGB[8];
PointRGB[] c = new PointRGB[3];
c[0] = new PointRGB(245, 14, 45);
c[1] = new PointRGB(56, 78, 134);
c[2] = new PointRGB(20, 25, 68);
p[0] = new PointRGB(203, 171, 184);
p[1] = new PointRGB(72, 162, 213);
p[2] = new PointRGB(73, 143, 165);
p[3] = new PointRGB(210, 212, 187);
p[4] = new PointRGB(198, 214, 103);
p[5] = new PointRGB(107, 113, 140);
p[6] = new PointRGB(59, 153, 112);
p[7] = new PointRGB(38, 121, 43);
double[,] matr = fcm.distributeOverMatrixU(p, c, 1.5);
for (int i = 0; i < p.Length; i++)
{
for (int j = 0; j < c.Length; j++)
{
Assert.IsTrue((matr[i, j] - matrExpected[i, j] < 0.0001) || (Math.Abs(matr[i, j] + matrExpected[i, j] - 1) < 0.0001));
}
}
}
private double calculateDecisionFunction(PointRGB[] MatrixPointX, PointRGB[] MatrixCentroids, double[,] MatrixU)
{
double sum = 0;
for (int i = 0; i < MatrixU.GetLength(0); i++)
{
for (int j = 0; j < MatrixU.GetLength(1); j++)
{
sum += MatrixU[i,j] * evklidDistance3D(MatrixCentroids[j], MatrixPointX[i]);
}
}
return sum;
}
