public double FindPoints(double x, double y, Mapack.Matrix coef)
{
double p = 0;
double[][] xArray = new double[1][];
for (int i = 0; i < xArray.Length; i++)
{
xArray[i] = new double[4];
}
xArray[0][0] = 1;
xArray[0][1] = x;
xArray[0][2] = Math.Pow(x, 2);
xArray[0][3] = Math.Pow(x, 3);
double[][] yArray = new double[4][];
for (int i = 0; i < yArray.Length; i++)
{
yArray[i] = new double[1];
}
yArray[0][0] = 1;
yArray[1][0] = y;
yArray[2][0] = Math.Pow(y, 2);
yArray[3][0] = Math.Pow(y, 3);
Mapack.Matrix xMatrix = new Mapack.Matrix(xArray);
Mapack.Matrix yMatrix = new Mapack.Matrix(yArray);
Mapack.Matrix res = Mapack.Matrix.Multiply(xMatrix, coef);
res = Mapack.Matrix.Multiply(res, yMatrix);
p = res.Determinant;
return(p);
}
//function
public override double[] propagate(double[] Bids)
{
Mapack.Matrix BidM = new Matrix(new double[][] { Bids });
//sanity check
try{
if (Bids.Length != W1.Rows)
{
throw new Exception("The number of bids and weights does not match");
}
}
catch (Exception e)
{
Console.WriteLine(e.Message);
}
Mapack.Matrix ProtoProbs = BidM * W1;
double SigmaSum = 0;
for (int i = 0; i < ProtoProbs.Columns; i++)
{
double d = Math.Exp(ProtoProbs[0, i]);
ProtoProbs[0, i] = d;
SigmaSum += d;
}
double[] Probabilities = new double[ProtoProbs.Columns];
for (int i = 0; i < ProtoProbs.Columns; i++)
{
Probabilities[i] = ProtoProbs[0, i] / (1 + SigmaSum);
}
return(Probabilities);
}
//*function
public void CSVtoMAT(ref StreamReader SR, ref Mapack.Matrix W)
{
string line = " ";
List <string[]> LineList = new List <string[]>();
while (!SR.EndOfStream && !line.Contains("nextmatrix"))
{
line = SR.ReadLine();
if (line.Contains(","))
{
LineList.Add(line.Split(','));
}
}
int Row = LineList.Count;
int Col = LineList[0].Length;
W = new Matrix(Row, Col);
int R = 0;
int C = 0;
foreach (string[] ln in LineList)
{
foreach (string cell in ln)
{
W[R, C] = Double.Parse(cell);
C++;
}
R++;
C = 0;
}
}
public BicubicInterpolator()
{
fixedArray[0] = new double[] { 1, 0, 0, 0 };
fixedArray[1] = new double[] { 0, 0, 1, 0 };
fixedArray[2] = new double[] { -3, 3, -2, -1 };
fixedArray[3] = new double[] { 2, -2, 1, 1 };
fixed1 = new Mapack.Matrix(fixedArray);
fixed2 = fixed1.Transpose();
coefficient = new Mapack.Matrix(4, 4);
}
public int[,] constructFourByFour(int[,] pixelArray)
{
bool start_new_row = false;
bool sec_iteration_new_row = false;
int row_index = 0;
int col_index = 0;
int new_row = 0;
int new_col = 0;
int[,] doubled_image = new int[2 * pixelArray.GetLength(0), 2 * pixelArray.GetLength(1)];;
while (row_index + fourGrid.GetLength(0) <= pixelArray.GetLength(0))
{
while (col_index + fourGrid.GetLength(1) <= pixelArray.GetLength(1))
{
for (int i = 0; i < fourGrid.GetLength(0); i++)
{
for (int j = 0; j < fourGrid.GetLength(1); j++)
{
fourGrid[i, j] = pixelArray[i + row_index, j + col_index];
}
}
//gridCount++;
//Console.WriteLine("Grid " + gridCount + " :");
//printArray(fourGrid);
//Console.WriteLine("");
double[][] complex = constrComplexMatrix(fourGrid);
Mapack.Matrix comp = new Mapack.Matrix(complex);
coefficient = Mapack.Matrix.Multiply(fixed1, comp);
coefficient = Mapack.Matrix.Multiply(coefficient, fixed2);
// Console.WriteLine("Fixed 1:\n " + fixed1.ToString());
//Console.WriteLine("Complex : \n" + comp.ToString());
//Console.WriteLine("Fixed 2: \n" + fixed2.ToString());//; coefficient.ToString());
//Console.WriteLine("Coefficients:\n " + coefficient.ToString());
//if(new_row >= 39 || new_col >= 39){
// break;
//}
if (sec_iteration_new_row && start_new_row)
{
doubled_image[new_row, new_col] = check_range((int)Math.Ceiling(FindPoints(0.5, 0.5, coefficient)));
doubled_image[new_row + 1, new_col] = check_range((int)Math.Ceiling(FindPoints(0.5, 1, coefficient)));
doubled_image[new_row, new_col + 1] = check_range((int)Math.Ceiling(FindPoints(1, 0.5, coefficient)));
doubled_image[new_row + 1, new_col + 1] = fourGrid[2, 2];
new_col += 2;
}
else if ((new_row == 0 && new_col == 0) || start_new_row)
{
if (start_new_row)
{
doubled_image[new_row, new_col] = check_range((int)Math.Ceiling(FindPoints(0, 0.5, coefficient)));
doubled_image[new_row + 1, new_col] = fourGrid[2, 1];
doubled_image[new_row, new_col + 1] = check_range((int)Math.Ceiling(FindPoints(0.5, 0.5, coefficient)));
doubled_image[new_row + 1, new_col + 1] = check_range((int)Math.Ceiling(FindPoints(0.5, 1, coefficient)));
doubled_image[new_row, new_col + 2] = check_range((int)Math.Ceiling(FindPoints(1, 0.5, coefficient)));
doubled_image[new_row + 1, new_col + 2] = fourGrid[2, 2];
new_col += 3;
sec_iteration_new_row = true;
}
else
{
doubled_image[new_row, new_col] = fourGrid[1, 1];
doubled_image[new_row + 1, new_col] = check_range((int)Math.Ceiling(FindPoints(0, 0.5, coefficient)));
doubled_image[new_row + 2, new_col] = fourGrid[2, 1];
doubled_image[new_row, new_col + 1] = check_range((int)Math.Ceiling(FindPoints(0.5, 0, coefficient)));
doubled_image[new_row + 1, new_col + 1] = check_range((int)Math.Ceiling(FindPoints(0.5, 0.5, coefficient)));
doubled_image[new_row + 2, new_col + 1] = check_range((int)Math.Ceiling(FindPoints(0.5, 1, coefficient)));
doubled_image[new_row, new_col + 2] = fourGrid[1, 2];
doubled_image[new_row + 1, new_col + 2] = check_range((int)Math.Ceiling(FindPoints(1, 0.5, coefficient)));
doubled_image[new_row + 2, new_col + 2] = fourGrid[2, 2];
new_col += 3;
}
// start_new_row = false;
}
else
{
doubled_image[new_row, new_col] = check_range((int)Math.Ceiling(FindPoints(0.5, 0, coefficient)));
doubled_image[new_row + 1, new_col] = check_range((int)Math.Ceiling(FindPoints(0.5, 0.5, coefficient)));
doubled_image[new_row + 2, new_col] = check_range((int)Math.Ceiling(FindPoints(0.5, 1, coefficient)));
doubled_image[new_row, new_col + 1] = fourGrid[1, 2];
doubled_image[new_row + 1, new_col + 1] = check_range((int)Math.Ceiling(FindPoints(1, 0.5, coefficient)));
doubled_image[new_row + 2, new_col + 1] = fourGrid[2, 2];
new_col += 2;
}
col_index++;
}
row_index++;
if (start_new_row)
{
new_row += 2;
}
else
{
new_row += 3;
}
start_new_row = true;
sec_iteration_new_row = false;
col_index = 0;
new_col = 0;
}
return(doubled_image);
}
/// <summary>Construct singular value decomposition.</summary>
public SingularValueDecomposition(Matrix value)
{
if (value == null)
{
throw new ArgumentNullException("value");
}
Matrix copy = (Matrix) value.Clone();
double[][] a = copy.Array;
m = value.Rows;
n = value.Columns;
int nu = Math.Min(m,n);
s = new double [Math.Min(m+1,n)];
U = new Matrix(m, nu);
V = new Matrix(n, n);
double[][] u = U.Array;
double[][] v = V.Array;
double[] e = new double [n];
double[] work = new double [m];
bool wantu = true;
bool wantv = true;
// Reduce A to bidiagonal form, storing the diagonal elements in s and the super-diagonal elements in e.
int nct = Math.Min(m-1,n);
int nrt = Math.Max(0,Math.Min(n-2,m));
for (int k = 0; k < Math.Max(nct,nrt); k++)
{
if (k < nct)
{
// Compute the transformation for the k-th column and place the k-th diagonal in s[k].
// Compute 2-norm of k-th column without under/overflow.
s[k] = 0;
for (int i = k; i < m; i++)
{
s[k] = Hypotenuse(s[k],a[i][k]);
}
if (s[k] != 0.0)
{
if (a[k][k] < 0.0)
{
s[k] = -s[k];
}
for (int i = k; i < m; i++)
{
a[i][k] /= s[k];
}
a[k][k] += 1.0;
}
s[k] = -s[k];
}
for (int j = k+1; j < n; j++)
{
if ((k < nct) & (s[k] != 0.0))
{
// Apply the transformation.
double t = 0;
for (int i = k; i < m; i++)
t += a[i][k]*a[i][j];
t = -t/a[k][k];
for (int i = k; i < m; i++)
a[i][j] += t*a[i][k];
}
// Place the k-th row of A into e for the subsequent calculation of the row transformation.
e[j] = a[k][j];
}
if (wantu & (k < nct))
{
// Place the transformation in U for subsequent back
// multiplication.
for (int i = k; i < m; i++)
u[i][k] = a[i][k];
}
if (k < nrt)
{
// Compute the k-th row transformation and place the k-th super-diagonal in e[k].
// Compute 2-norm without under/overflow.
e[k] = 0;
for (int i = k+1; i < n; i++)
{
e[k] = Hypotenuse(e[k],e[i]);
}
if (e[k] != 0.0)
{
if (e[k+1] < 0.0)
e[k] = -e[k];
for (int i = k+1; i < n; i++)
e[i] /= e[k];
e[k+1] += 1.0;
}
e[k] = -e[k];
if ((k+1 < m) & (e[k] != 0.0))
{
// Apply the transformation.
for (int i = k+1; i < m; i++)
work[i] = 0.0;
for (int j = k+1; j < n; j++)
for (int i = k+1; i < m; i++)
work[i] += e[j]*a[i][j];
for (int j = k+1; j < n; j++)
{
double t = -e[j]/e[k+1];
for (int i = k+1; i < m; i++)
a[i][j] += t*work[i];
}
}
if (wantv)
{
// Place the transformation in V for subsequent back multiplication.
for (int i = k+1; i < n; i++)
v[i][k] = e[i];
}
}
}
// Set up the final bidiagonal matrix or order p.
int p = Math.Min(n,m+1);
if (nct < n) s[nct] = a[nct][nct];
if (m < p) s[p-1] = 0.0;
if (nrt+1 < p) e[nrt] = a[nrt][p-1];
e[p-1] = 0.0;
// If required, generate U.
if (wantu)
{
for (int j = nct; j < nu; j++)
{
for (int i = 0; i < m; i++)
u[i][j] = 0.0;
u[j][j] = 1.0;
}
for (int k = nct-1; k >= 0; k--)
{
if (s[k] != 0.0)
{
for (int j = k+1; j < nu; j++)
{
double t = 0;
for (int i = k; i < m; i++)
t += u[i][k]*u[i][j];
t = -t/u[k][k];
for (int i = k; i < m; i++)
u[i][j] += t*u[i][k];
}
for (int i = k; i < m; i++ )
u[i][k] = -u[i][k];
u[k][k] = 1.0 + u[k][k];
for (int i = 0; i < k-1; i++)
u[i][k] = 0.0;
}
else
{
for (int i = 0; i < m; i++)
u[i][k] = 0.0;
u[k][k] = 1.0;
}
}
}
// If required, generate V.
if (wantv)
{
for (int k = n-1; k >= 0; k--)
{
if ((k < nrt) & (e[k] != 0.0))
{
for (int j = k+1; j < nu; j++)
{
double t = 0;
for (int i = k+1; i < n; i++)
t += v[i][k]*v[i][j];
t = -t/v[k+1][k];
for (int i = k+1; i < n; i++)
v[i][j] += t*v[i][k];
}
}
for (int i = 0; i < n; i++)
v[i][k] = 0.0;
v[k][k] = 1.0;
}
}
// Main iteration loop for the singular values.
int pp = p-1;
int iter = 0;
double eps = Math.Pow(2.0,-52.0);
while (p > 0)
{
int k,kase;
// Here is where a test for too many iterations would go.
// This section of the program inspects for
// negligible elements in the s and e arrays. On
// completion the variables kase and k are set as follows.
// kase = 1 if s(p) and e[k-1] are negligible and k<p
// kase = 2 if s(k) is negligible and k<p
// kase = 3 if e[k-1] is negligible, k<p, and s(k), ..., s(p) are not negligible (qr step).
// kase = 4 if e(p-1) is negligible (convergence).
for (k = p-2; k >= -1; k--)
{
if (k == -1)
break;
if (Math.Abs(e[k]) <= eps*(Math.Abs(s[k]) + Math.Abs(s[k+1])))
{
e[k] = 0.0;
break;
}
}
if (k == p-2)
{
kase = 4;
}
else
{
int ks;
for (ks = p-1; ks >= k; ks--)
{
if (ks == k)
break;
double t = (ks != p ? Math.Abs(e[ks]) : 0.0) + (ks != k+1 ? Math.Abs(e[ks-1]) : 0.0);
if (Math.Abs(s[ks]) <= eps*t)
{
s[ks] = 0.0;
break;
}
}
if (ks == k)
kase = 3;
else if (ks == p-1)
kase = 1;
else
{
kase = 2;
k = ks;
}
}
k++;
// Perform the task indicated by kase.
switch (kase)
{
// Deflate negligible s(p).
case 1:
{
double f = e[p-2];
e[p-2] = 0.0;
for (int j = p-2; j >= k; j--)
{
double t = Hypotenuse(s[j],f);
double cs = s[j]/t;
double sn = f/t;
s[j] = t;
if (j != k)
{
f = -sn*e[j-1];
e[j-1] = cs*e[j-1];
}
if (wantv)
{
for (int i = 0; i < n; i++)
{
t = cs*v[i][j] + sn*v[i][p-1];
v[i][p-1] = -sn*v[i][j] + cs*v[i][p-1];
v[i][j] = t;
}
}
}
}
break;
// Split at negligible s(k).
case 2:
{
double f = e[k-1];
e[k-1] = 0.0;
for (int j = k; j < p; j++)
{
double t = Hypotenuse(s[j],f);
double cs = s[j]/t;
double sn = f/t;
s[j] = t;
f = -sn*e[j];
e[j] = cs*e[j];
if (wantu)
{
for (int i = 0; i < m; i++)
{
t = cs*u[i][j] + sn*u[i][k-1];
u[i][k-1] = -sn*u[i][j] + cs*u[i][k-1];
u[i][j] = t;
}
}
}
}
break;
// Perform one qr step.
case 3:
{
// Calculate the shift.
double scale = Math.Max(Math.Max(Math.Max(Math.Max(Math.Abs(s[p-1]),Math.Abs(s[p-2])),Math.Abs(e[p-2])), Math.Abs(s[k])),Math.Abs(e[k]));
double sp = s[p-1]/scale;
double spm1 = s[p-2]/scale;
double epm1 = e[p-2]/scale;
double sk = s[k]/scale;
double ek = e[k]/scale;
double b = ((spm1 + sp)*(spm1 - sp) + epm1*epm1)/2.0;
double c = (sp*epm1)*(sp*epm1);
double shift = 0.0;
if ((b != 0.0) | (c != 0.0))
{
shift = Math.Sqrt(b*b + c);
if (b < 0.0)
shift = -shift;
shift = c/(b + shift);
}
double f = (sk + sp)*(sk - sp) + shift;
double g = sk*ek;
// Chase zeros.
for (int j = k; j < p-1; j++)
{
double t = Hypotenuse(f,g);
double cs = f/t;
double sn = g/t;
if (j != k)
e[j-1] = t;
f = cs*s[j] + sn*e[j];
e[j] = cs*e[j] - sn*s[j];
g = sn*s[j+1];
s[j+1] = cs*s[j+1];
if (wantv)
{
for (int i = 0; i < n; i++)
{
t = cs*v[i][j] + sn*v[i][j+1];
v[i][j+1] = -sn*v[i][j] + cs*v[i][j+1];
v[i][j] = t;
}
}
t = Hypotenuse(f, g);
cs = f/t;
sn = g/t;
s[j] = t;
f = cs*e[j] + sn*s[j+1];
s[j+1] = -sn*e[j] + cs*s[j+1];
g = sn*e[j+1];
e[j+1] = cs*e[j+1];
if (wantu && (j < m-1))
{
for (int i = 0; i < m; i++)
{
t = cs*u[i][j] + sn*u[i][j+1];
u[i][j+1] = -sn*u[i][j] + cs*u[i][j+1];
u[i][j] = t;
}
}
}
e[p-2] = f;
iter = iter + 1;
}
break;
// Convergence.
case 4:
{
// Make the singular values positive.
if (s[k] <= 0.0)
{
s[k] = (s[k] < 0.0 ? -s[k] : 0.0);
if (wantv)
for (int i = 0; i <= pp; i++)
v[i][k] = -v[i][k];
}
// Order the singular values.
while (k < pp)
{
if (s[k] >= s[k+1])
break;
double t = s[k];
s[k] = s[k+1];
s[k+1] = t;
if (wantv && (k < n-1))
for (int i = 0; i < n; i++)
{
t = v[i][k+1];
v[i][k+1] = v[i][k];
v[i][k] = t;
}
if (wantu && (k < m-1))
for (int i = 0; i < m; i++)
{
t = u[i][k+1];
u[i][k+1] = u[i][k];
u[i][k] = t;
}
k++;
}
iter = 0;
p--;
}
break;
}
}
}
