}/**/
for (int inner = 0; inner < 1; inner++)
{
var Ukx = skx.FE_inded(WX, WY, g.Genom, SelectedUs, penal);
var ke = skx.KE;
double c = 0.0;
double[] dc = new double[WX * WY];
for (int elx = 0; elx < WX; elx++)
{
for (int ely = 0; ely < WY; ely++)
{
int n1 = (WY + 1) * elx + ely;
int n2 = (WY + 1) * (elx + 1) + ely;
var edof = np.array(2 * n1, 2 * n1 + 1, 2 * n2, 2 * n2 + 1, 2 * n2 + 2, 2 * n2 + 3, 2 * n1 + 2, 2 * n1 + 3);
double[] Ue = new double[8];
for (int i = 0; i < edof.size; i++)
{
Ue[i] = Ukx[edof[i]];
}
double xp = Math.Pow(g.Genom[ely + elx * WY], penal);
double[] KEUe = MatrixMath.MatVecProd(ke, Ue);
double UEKUE = 0;
for (int i = 0; i < KEUe.Length; i++)
{
UEKUE += Ue[i] * KEUe[i];
}
c += xp * UEKUE;
dc[ely + elx * WY] = -penal *Math.Pow(g.Genom[ely + elx * WY], penal - 1) * UEKUE;
}
}
dc = skx.Check(WX, WY, 1.5, g.Genom, dc);
g.Genom = skx.OC(WX, WY, g.Genom, volfraq, dc);
}
return(AFC.ToArray());
}
public static double[] Test_eval_simp(Genome <double> g, int WX, int WY, double volfraq, double f1, double f2, double f3)
{
double[] retval = new double[1];
int penal = 3;
KXMSolvers skx = new KXMSolvers();
var U = skx.FE(WX, WY, g.Genom, penal);
var ke = skx.KE;
double c = 0.0;
double[] dc = new double[WX * WY];
for (int elx = 0; elx < WX; elx++)
{
for (int ely = 0; ely < WY; ely++)
{
int n1 = (WY + 1) * elx + ely;
int n2 = (WY + 1) * (elx + 1) + ely;
var edof = np.array(2 * n1, 2 * n1 + 1, 2 * n2, 2 * n2 + 1, 2 * n2 + 2, 2 * n2 + 3, 2 * n1 + 2, 2 * n1 + 3);
double[] Ue = new double[8];
for (int i = 0; i < edof.size; i++)
{
Ue[i] = U[edof[i]];
}
double xp = Math.Pow(g.Genom[ely + elx * WY], penal);
double[] KEUe = MatrixMath.MatVecProd(ke, Ue);
double UEKUE = 0;
for (int i = 0; i < KEUe.Length; i++)
{
UEKUE += Ue[i] * KEUe[i];
}
c += xp * UEKUE;
dc[ely + elx * WY] = -penal *Math.Pow(g.Genom[ely + elx *WY], penal - 1) * UEKUE;
}
}
dc = skx.Check(WX, WY, 1.5, g.Genom, dc);
g.Genom = skx.OC(WX, WY, g.Genom, volfraq, dc);
double sumV = 0;
foreach (var gg in g.Genom)
{
sumV += (double)gg;
}
sumV = sumV - WX * WY * volfraq;
retval[0] = c;
return(retval);
}
public static double Test_eval(Genome <double> g, int WX, int WY, double volfraq)
{
double retval = 0.0f;
int penal = 3;
KXMSolvers skx = new KXMSolvers();
var U = skx.FE(WX, WY, g.Genom, penal);
var ke = skx.KE;
double c = 0.0;
for (int elx = 0; elx < WX; elx++)
{
for (int ely = 0; ely < WY; ely++)
{
int n1 = (WY + 1) * elx + ely;
int n2 = (WY + 1) * (elx + 1) + ely;
var edof = np.array(2 * n1, 2 * n1 + 1, 2 * n2, 2 * n2 + 1, 2 * n2 + 2, 2 * n2 + 3, 2 * n1 + 2, 2 * n1 + 3);
double[] Ue = new double[8];
for (int i = 0; i < edof.size; i++)
{
Ue[i] = U[edof[i]];
}
double xp = Math.Pow(g.Genom[ely + elx * WY], penal);
double[] KEUe = MatrixMath.MatVecProd(ke, Ue);
double UEKUE = 0;
for (int i = 0; i < KEUe.Length; i++)
{
UEKUE += Ue[i] * KEUe[i];
}
c += xp * UEKUE;
}
}
// g.Genom = skx.Check(WX, WY, 1.5, g.Genom);
double sumV = 0;
foreach (var gg in g.Genom)
{
sumV += (double)gg;
}
sumV = sumV - WX * WY * volfraq;
retval = c * c + sumV * sumV * 2.0;
return(retval);
}
/**/
public static double Test_eval_weave(Genome <int> g, int WX, int WY, double volfraq)
{
double retval = 0;
int penal = 3;
var ge = convertWeaverToField(g, WX, WY);
KXMSolvers skx = new KXMSolvers();
var U = skx.FE(WX, WY, ge, penal);
var ke = skx.KE;
double c = 0.0;
for (int elx = 0; elx < WX; elx++)
{
for (int ely = 0; ely < WY; ely++)
{
int n1 = (WY + 1) * elx + ely;
int n2 = (WY + 1) * (elx + 1) + ely;
var edof = np.array(2 * n1, 2 * n1 + 1, 2 * n2, 2 * n2 + 1, 2 * n2 + 2, 2 * n2 + 3, 2 * n1 + 2, 2 * n1 + 3);
double[] Ue = new double[8];
for (int i = 0; i < edof.size; i++)
{
Ue[i] = U[edof[i]];
}
double xp = Math.Pow(ge[ely + elx * WY], penal);
double[] KEUe = MatrixMath.MatVecProd(ke, Ue);
double UEKUE = 0;
for (int i = 0; i < KEUe.Length; i++)
{
UEKUE += Ue[i] * KEUe[i];
}
c += xp * UEKUE;
}
}
double sumV = ge.Sum();
sumV = sumV - (double)(WX * WY) * volfraq;
retval = c * c * 1.0 + sumV * sumV * 0.0;
return(retval);
}
public double[] Modal(int nelx,
int nely,
double[] x,
double p,
double q,
out double[,] V)
{
var ke = K_Plain_strain(1e10, 0.3);
var me = M_Plain_strain(1000, 1);
int N = 2 * (nelx + 1) * (nely + 1);
double[][] K = new double[N][];
double[][] M = new double[N][];
for (int i = 0; i < N; i++)
{
K[i] = new double[N];
M[i] = new double[N];
}
for (int elx = 0; elx < nelx; elx++)
{
for (int ely = 0; ely < nely; ely++)
{
int n1 = (nely + 1) * elx + ely;
int n2 = (nely + 1) * (elx + 1) + ely;
var edof = np.array(2 * n1, 2 * n1 + 1, 2 * n2, 2 * n2 + 1, 2 * n2 + 2, 2 * n2 + 3, 2 * n1 + 2, 2 * n1 + 3);
for (int i = 0; i < edof.size; i++)
{
for (int j = 0; j < edof.size; j++)
{
K[edof[i]][edof[j]] = K[edof[i]][edof[j]] + Math.Pow(x[ely + elx * (nely)], p) * ke[i][j];
M[edof[i]][edof[j]] = M[edof[i]][edof[j]] + Math.Pow(x[ely + elx * (nely)], q) * me[i][j];
}
}
}
}
int[] inds = new int[4 * (nely + 1)];
//left and right border fix
for (int i = 0; i < 2 * (nely + 1); i++)
{
inds[i] = i;
inds[i + 2 * (nely + 1)] = N - 2 * (nely + 1) + i - 1;
}
double[,] Kmm = MatrixMath.To2D <double>(K);
double[,] Mmm = MatrixMath.To2D <double>(M);
Kmm = MatrixMath.CrossOut(Kmm, inds);
Mmm = MatrixMath.CrossOut(Mmm, inds);
int reducedN = Kmm.GetLength(0);
double[] wr = new double[reducedN];
//solve
alglib.smatrixgevd(Kmm, reducedN, false, Mmm, false, 1, 1, out wr, out V);
for (int i = 0; i < V.GetLength(0); i++)
{
for (int j = 0; j < V.GetLength(1); j++)
{
V[i, j] = Math.Cos(wr[i]) * V[i, j];
}
}
V = MatrixMath.FillOnWeird(V, inds);
return(wr);
}
public double[] FE(int nelx, int nely, double[] x, double p)
{
var ke = KE;
int N = 2 * (nelx + 1) * (nely + 1);
double[][] K_m = new double[N][];
for (int i = 0; i < N; i++)
{
K_m[i] = new double[N];
}
for (int elx = 0; elx < nelx; elx++)
{
for (int ely = 0; ely < nely; ely++)
{
int n1 = (nely + 1) * elx + ely;
int n2 = (nely + 1) * (elx + 1) + ely;
var edof = np.array(2 * n1, 2 * n1 + 1, 2 * n2, 2 * n2 + 1, 2 * n2 + 2, 2 * n2 + 3, 2 * n1 + 2, 2 * n1 + 3);
for (int i = 0; i < edof.size; i++)
{
for (int j = 0; j < edof.size; j++)
{
K_m[edof[i]][edof[j]] = K_m[edof[i]][edof[j]] + Math.Pow(x[ely + elx * (nely)], p) * ke[i][j]; //?diagonal
}
}
}
}
int[] inds = new int[2 * (nely + 1)];
//left and right border fix
for (int i = 0; i < 2 * (nely + 1); i++)
{
inds[i] = i;
}
Random r = new Random(123);
double[,] Kmm = MatrixMath.To2D <double>(K_m);
Kmm = MatrixMath.CrossOut(Kmm, inds);
int reducedN = Kmm.GetLength(0);
double[] F = new double[reducedN];
double[] X = new double[N];
for (int i = 0; i < nely; i++)
{
F[(2 * nely + 1) * nelx + i * 2 - 1] = -1;
}
F[reducedN - nely - 1] = r.NextDouble();
alglib.rmatrixsolvefast(Kmm, reducedN, ref F, out _);
int c = 0;
for (int i = 0; i < N; i++)
{
if (c < inds.Length && inds[c] == i)
{
X[i] = 0;
c++;
}
else
{
X[i] = F[i - c];
}
}
return(X);
}
public double[] FE_inded(int nelx, int nely, double[] x, Dictionary <int, double> f_map, double p)
{
var ke = KE;
int N = 2 * (nelx + 1) * (nely + 1);
double[][] K_m = new double[N][];
for (int i = 0; i < N; i++)
{
K_m[i] = new double[N];
}
for (int elx = 0; elx < nelx; elx++)
{
for (int ely = 0; ely < nely; ely++)
{
int n1 = (nely + 1) * elx + ely;
int n2 = (nely + 1) * (elx + 1) + ely;
var edof = np.array(2 * n1, 2 * n1 + 1, 2 * n2, 2 * n2 + 1, 2 * n2 + 2, 2 * n2 + 3, 2 * n1 + 2, 2 * n1 + 3);
for (int i = 0; i < edof.size; i++)
{
for (int j = 0; j < edof.size; j++)
{
K_m[edof[i]][edof[j]] = K_m[edof[i]][edof[j]] + Math.Pow(x[ely + elx * (nely)], p) * ke[i][j]; //?diagonal
}
}
}
}
int[] inds = new int[2 * (nely + 1)];
//left and right border fix
for (int i = 0; i < 2 * (nely + 1); i++)
{
inds[i] = i;
}
Random r = new Random(123);
double[,] Kmm = MatrixMath.To2D <double>(K_m);
Kmm = MatrixMath.CrossOut(Kmm, inds);
int reducedN = Kmm.GetLength(0);
List <double> F_full = Enumerable.Repeat(0.0, N).ToList();
double[] X = new double[N];
double[] F = new double[reducedN];
//index crossout
int c = 0;
foreach (var q in f_map)
{
F_full[q.Key] = q.Value;
}
for (int i = 0; i < N; i++)
{
if (c < inds.Length && inds[c] == i)
{
c++;
}
else
{
F[i - c] = F_full[i];
}
}
// F[reducedN -1] = -1e6;
alglib.rmatrixsolvefast(Kmm, reducedN, ref F, out _);
//index backfill
c = 0;
for (int i = 0; i < N; i++)
{
if (c < inds.Length && inds[c] == i)
{
X[i] = 0;
c++;
}
else
{
X[i] = F[i - c];
}
}
return(X);
}
public double[] Harmonic(int nelx, int nely, double[] x, double p, double q, double wmega)
{
var ke = K_Plain_strain(1e10, 0.3);
var me = M_Plain_strain(1000, 1);
int N = 2 * (nelx + 1) * (nely + 1);
double[][] K = new double[N][];
double[][] M = new double[N][];
for (int i = 0; i < N; i++)
{
K[i] = new double[N];
M[i] = new double[N];
}
for (int elx = 0; elx < nelx; elx++)
{
for (int ely = 0; ely < nely; ely++)
{
int n1 = (nely + 1) * elx + ely;
int n2 = (nely + 1) * (elx + 1) + ely;
var edof = np.array(2 * n1, 2 * n1 + 1, 2 * n2, 2 * n2 + 1, 2 * n2 + 2, 2 * n2 + 3, 2 * n1 + 2, 2 * n1 + 3);
for (int i = 0; i < edof.size; i++)
{
for (int j = 0; j < edof.size; j++)
{
K[edof[i]][edof[j]] = K[edof[i]][edof[j]] + Math.Pow(x[ely + elx * (nely)], p) * ke[i][j];
M[edof[i]][edof[j]] = M[edof[i]][edof[j]] + Math.Pow(x[ely + elx * (nely)], q) * me[i][j];
}
}
}
}
int[] inds = new int[2 * (nely + 1)];
//left border fix
for (int i = 0; i < 2 * (nely + 1); i++)
{
inds[i] = i;
}
double[,] Kmm = MatrixMath.To2D <double>(K);
double[,] Mmm = MatrixMath.To2D <double>(M);
Kmm = MatrixMath.CrossOut(Kmm, inds);
Mmm = MatrixMath.CrossOut(Mmm, inds);
List <double> X = new List <double>();
int reducedN = Kmm.GetLength(0);
double[,] DSW = new double[reducedN, reducedN];
for (int ik = 0; ik < Kmm.GetLength(0); ik++)
{
for (int jk = 0; jk < Kmm.GetLength(1); jk++)
{
double l = wmega * 2 * Math.PI;
l = l * l;
DSW[ik, jk] = Kmm[ik, jk] - l * Mmm[ik, jk];
}
}
double[] F = new double[reducedN];
double[] U = new double[reducedN];
F[reducedN - 1] = -1e6;
alglib.rmatrixsolve(DSW, reducedN, F, out _, out _, out U);
int c = 0;
for (int i = 0; i < N; i++)
{
if (c < inds.Length && inds[c] == i)
{
X.Add(0);
c++;
}
else
{
X.Add(U[i - c]);
}
}
return(X.ToArray());
}
public static double[,] GoSearch(IProgress <Image> progress, int WX, int WY, double volfraq, IProgress <double> prog)
{
Random r = new Random();
double[,] retval = new double[WX, WY];
QuadTree <double> SearchTree = new QuadTree <double>();
SearchTree.Root.BB = new System.Windows.Rect(0, 0, WX, WY);
SearchTree.Root.NodeValue = 1.0;
List <double> Graph = new List <double>();
float MultySize = 20.0f;
Image MyImage = new Bitmap((int)((WX * 4) * MultySize), (int)((WY * 4) * MultySize));
Graphics g = Graphics.FromImage(MyImage);
for (int h = 0; h < 10000; h++)
{
var SearchRootList = SearchTree.getLeafs();
double step = 0.3 * r.NextDouble() - 0.1;
List <double> Gradient = new List <double>();
retval = convertTree2Mesh(SearchTree, WX, WY);
int penal = 3;
double Fzero = CalcTree(WX, WY, volfraq, retval, penal);
Graph.Insert(0, Fzero);
foreach (var q in SearchRootList)
{
var oldVal = q.NodeValue;
q.NodeValue = Math.Min(1.0, Math.Max(0.001, q.NodeValue + step));
retval = convertTree2Mesh(SearchTree, WX, WY);
double F = CalcTree(WX, WY, volfraq, retval, penal);
double Sum = MatrixMath.To1D(retval).Sum();
Gradient.Add((F - Fzero) / step);
q.NodeValue = oldVal;
///
for (int ix = 0; ix < WX; ix++)
{
for (int iy = 0; iy < WY; iy++)
{
double H = 1.0 - (float)retval[ix, iy];
H = Math.Max(0, Math.Min(1.0, H));
if (double.IsNaN(H))
{
H = 0;
}
H = H * 255;
Color customColor = Color.FromArgb(255, (int)H, (int)H, (int)H);
SolidBrush shadowBrush = new SolidBrush(customColor);
g.FillRectangle(shadowBrush, ix * MultySize, iy * MultySize, MultySize, MultySize);
}
}
for (int ix = 0; ix < WX; ix++)
{
for (int iy = 0; iy < WY; iy++)
{
double H = 1.0 - (float)retval[ix, iy];
H = Math.Max(0, Math.Min(1.0, H));
if (double.IsNaN(H))
{
H = 0;
}
H = H * 255;
Color customColor = Color.FromArgb(255, (int)H, (int)H, (int)H);
SolidBrush shadowBrush = new SolidBrush(customColor);
g.FillRectangle(shadowBrush, ix * MultySize + MultySize * WX + 5, iy * MultySize, MultySize, MultySize);
}
}
progress.Report(MyImage);
}
float dY = 500;
g.FillRectangle(new SolidBrush(Color.White), 0, dY - 150, 500, dY + 150);
g.DrawLine(new Pen(Color.Black, 2), 0, dY, 500, dY);
double data = Graph[Graph.Count - 1];
double olddata = Graph[Graph.Count - 1];
float MaxG = (float)(Graph.Max() + 0.00001f);
Debug.WriteLine(Graph.First());
for (int i = 0; i < Math.Min(500, Graph.Count); i++)
{
if (!double.IsNaN(Graph[i]))
{
data = Graph[i];
g.DrawLine(new Pen(Color.Blue, 2), Math.Min(500, Graph.Count) - i, dY - 150.0f * (float)olddata / MaxG, Math.Min(500, Graph.Count) - i - 1.0f, dY - 150.0f * (float)data / MaxG);
olddata = data;
progress.Report(MyImage);
}
}
SearchRootList = SearchRootList.OrderBy(d => (Gradient[SearchRootList.IndexOf(d)])).ToList();
KXMSolvers kx = new KXMSolvers();
var xnew = kx.OC(Gradient.Count, 1, SearchTree.GetLeafsValues().ToArray(), 0.5, Gradient.ToArray());
double gMx = Gradient.Max();
double gMn = Gradient.Min();
foreach (var q in SearchRootList)
{
double delta = -Gradient[SearchRootList.IndexOf(q)];
if (!q.IsLast)
{
//q.NodeValue = Math.Min(1.0, Math.Max(0.001, xnew[SearchRootList.IndexOf(q)]));
//q.NodeValue = Math.Min(1.0, Math.Max(0.001, q.NodeValue*Math.Sqrt(delta)));
q.NodeValue = Math.Min(1.0, Math.Max(0.001, q.NodeValue + step));
if (Math.Abs(q.NodeValue - 1.0) < 0.1)
{
q.SubDivide(q.NodeValue / 2);
}
break;
}
else
{
q.NodeValue = Math.Min(1.0, Math.Max(0.001, q.NodeValue + step));
}
}
}
g.Dispose();
retval = convertTree2Mesh(SearchTree, WX, WY);
return(retval);
}
