public NumericMatrix <V> extract(SpreadSheetRange <AI1, AI2> range)
{
// Slice a matrix
AI1 rmin = range.upperLeft.first;
AI2 cmin = range.upperLeft.second;
AI1 rmax = range.lowerRight.first;
AI2 cmax = range.lowerRight.second;
int Rmin = r[rmin]; int Rmax = r[rmax];
int Cmin = c[cmin]; int Cmax = c[cmax];
// Now must find the integer indices corresponding to these
NumericMatrix <V> result = new NumericMatrix <V>(Rmax - Rmin + 1, Cmax - Cmin + 1, Rmin, Cmin);
for (int ri = Rmin; ri <= Rmax; ri++)
{
for (int ci = Cmin; ci <= Cmax; ci++)
{
result[ri, ci] = mat[ri, ci];
}
}
return(result);
}
public AssocMatrix()
{
mat = new NumericMatrix <V>(10, 10);
r = new AssocArray <AI1, int>();
c = new AssocArray <AI2, int>();
keyRows = new Set <AI1>();
keyColumns = new Set <AI2>();
}
public AssocMatrix(AssocMatrix <AI1, AI2, V> mat2)
{
mat = new NumericMatrix <V>(mat2.mat);
r = new AssocArray <AI1, int>(mat2.r);
c = new AssocArray <AI2, int>(mat2.c);
keyRows = new Set <AI1>(mat2.keyRows);
keyColumns = new Set <AI2>(mat2.keyColumns);
}
//Default constructor everything starts at 1 and has length 1
public Tensor()
{
m_tensor = new Array <NumericMatrix <T> >(1, 1);
m_tensor[1] = new NumericMatrix <T>(1, 1, 1, 1);
m_rows = 1;
m_columns = 1;
m_depth = 1;
}
//Constructor with all sizes and startindexes
public Tensor(int rows, int columns, int nthird, int rowStart, int columnStart, int thirdStart)
{
m_tensor = new Array <NumericMatrix <T> >(nthird, thirdStart); // Size nthird, start index
for (int i = m_tensor.MinIndex; i <= m_tensor.MaxIndex; i++)
{
m_tensor[i] = new NumericMatrix <T>(rows, columns, rowStart, columnStart);
}
m_rows = rows;
m_columns = columns;
m_depth = nthird;
}
//Constructor with the ammount of rows, columns and depth, all startindexes are 1.
public Tensor(int rows, int columns, int nthird)
{
m_tensor = new Array <NumericMatrix <T> >(nthird, 1);
for (int i = m_tensor.MinIndex; i <= m_tensor.MaxIndex; i++)
{
m_tensor[i] = new NumericMatrix <T>(rows, columns, 1, 1);
}
m_rows = rows;
m_columns = columns;
m_depth = nthird;
}
// Matrix multiplication
public static NumericMatrix <T> operator *(NumericMatrix <T> m1, NumericMatrix <T> m2)
{
NumericMatrix <T> result = new NumericMatrix <T>(m1.Rows, m2.Columns, m1.MinRowIndex, m1.MinColumnIndex);
if (mulTT == null)
{
mulTT = GenericOperatorFactory <T, T, T, Vector <T> > .Multiply;
}
if (addTT == null)
{
addTT = GenericOperatorFactory <T, T, T, Vector <T> > .Add;
}
/* OLD int i, j, k, l;
*
* for( i = result.MaxRowIndex; i >= result.MinRowIndex; i-- )
* {
* for( j = result.MinColumnIndex; j <= result.MaxColumnIndex; j++ )
* {
* for( k = m1.MinColumnIndex, l = m2.MaxRowIndex; k <= m1.MaxColumnIndex; k++, l-- )
* {
* result[ i, j ] = addTT( result[ i, j ], mulTT( m1[ i, k ], m2[ l, j ] ) );
* }
* }
* }*/
// Index variables must be declared at this scope
int i, j, k;
for (i = result.MinRowIndex; i <= result.MaxRowIndex; i++)
{
for (j = result.MinColumnIndex; j <= result.MaxColumnIndex; j++)
{
result[i, j] = mulTT(m1[i, m1.MinColumnIndex], m2[m2.MinRowIndex, j]);
for (k = m1.MinColumnIndex + 1; k <= m1.MaxColumnIndex; k++)
{
result[i, j] = addTT(result[i, j], mulTT(m1[i, k], m2[k, j]));
}
}
}
return(result);
}
//Copy constructor, does not make a deep copy when the internal types aren't primitive
public Tensor(Tensor <T> tensor)
{
m_tensor = new Array <NumericMatrix <T> >(tensor.m_depth, tensor.MinThirdIndex);
for (int i = m_tensor.MinIndex; i <= m_tensor.MaxIndex; i++)
{
m_tensor[i] = new NumericMatrix <T>(tensor.m_rows, tensor.m_columns, tensor.MinFirstIndex, tensor.MinSecondIndex);
}
for (int i = tensor.MinThirdIndex; i <= tensor.MaxThirdIndex; i++)
{
for (int j = tensor.MinSecondIndex; j <= tensor.MaxSecondIndex; j++)
{
for (int k = tensor.MinFirstIndex; k <= tensor.MaxFirstIndex; k++)
{
m_tensor[i][k, j] = tensor[i][k, j];
}
}
}
}
// Subtraction
public static NumericMatrix <T> operator -(NumericMatrix <T> m1, NumericMatrix <T> m2)
{
NumericMatrix <T> temp_matrix = new NumericMatrix <T>(m1.Rows, m1.Columns, m1.MinRowIndex, m1.MinColumnIndex);
int i, j;
if (subTT == null)
{
subTT = GenericOperatorFactory <T, T, T, Vector <T> > .Subtract;
}
for (i = m1.MinColumnIndex; i <= m1.MaxColumnIndex; i++)
{
for (j = m1.MinRowIndex; j <= m1.MaxRowIndex; j++)
{
//temp_matrix[ j, i ] = subTT( m1[ j, i ], m2[ j, i ] );
temp_matrix[j, i] = subTT(m1[j, i], m2[j, i]);
}
}
return(temp_matrix);
}
// Scalar multiplication
public static NumericMatrix <T> operator *(T getal, NumericMatrix <T> m)
{
NumericMatrix <T> result = new NumericMatrix <T>(m.Rows, m.Columns, m.MinRowIndex, m.MinColumnIndex);
int i, j;
if (mulTT == null)
{
mulTT = GenericOperatorFactory <T, T, T, Vector <T> > .Multiply;
}
for (i = m.MinRowIndex; i <= m.MaxRowIndex; i++)
{
for (j = m.MinColumnIndex; j <= m.MaxColumnIndex; j++)
{
result[i, j] = mulTT(getal, m[i, j]);
}
}
return(result);
}
// Operators
// Addition
public static NumericMatrix <T> operator +(NumericMatrix <T> m1, NumericMatrix <T> m2)
{
NumericMatrix <T> temp_matrix = new NumericMatrix <T>(m1.Rows, m1.Columns, m1.MinRowIndex, m1.MinColumnIndex);
int i, j;
if (addTT == null)
{
addTT = GenericOperatorFactory <T, T, T, Vector <T> > .Add;
//addTT = new BinaryOperatorT<T, T, T>(GenericOperatorFactory<T, T, T, Vector<T>>.Add);
}
for (i = m1.MinColumnIndex; i <= m1.MaxColumnIndex; i++)
{
for (j = m1.MinRowIndex; j <= m1.MaxRowIndex; j++)
{
temp_matrix[j, i] = addTT(m1[j, i], m2[j, i]);
}
}
return(temp_matrix);
}
// V2
/*
* // Construct the map from a list of names and a REPEATED val
* AssocMatrix(V rowStart, V columnStart, NumericMatrix<V> matrix)
* {
*
* // Must build the associative arrays, they have the same values as the
* // indices in the matrix
*
* VectorCollectionGenerator<V> rowGenerator = new VectorCollectionGenerator<V>();
* rowGenerator.Start = rowStart;
* rowGenerator.Increment = new V();
* rowGenerator.Size = matrix.Rows;
*
* VectorCollectionGenerator<V> columnGenerator = new VectorCollectionGenerator<V>();
* columnGenerator.Start = columnStart;
* columnGenerator.Increment = 1;
* columnGenerator.Size = matrix.Columns;
*
* mat = new NumericMatrix<V>(matrix);
*
* // keyRows = new SetCreator<V, int>.createSet(rowGenerator);
* //keyColumns = new SetCreator<V, int>.createSet(columnGenerator);
*
*
* // Build rows
* int start = mat.MinRowIndex;
* r = new AssocArray<AI1, int> ();
*
* foreach (AI1 row in keyRows)
* {
* r[row] = start;
* start = start + 1;
* }
*
* // Build columns
* start = mat.MinColumnIndex;
* c = new AssocArray<AI2, int>();
*
* foreach (AI2 col in keyColumns)
* {
* c[col] = start;
* start = start + 1;
* }
*
* // NO EXCEPTION HANDLING AT THE MOMENT
* //print(c);
* }
*
*/
public AssocMatrix(Set <AI1> Rnames, Set <AI2> Cnames,
NumericMatrix <V> matrix)
{
keyRows = new Set <AI1>(Rnames);
keyColumns = new Set <AI2>(Cnames);
// Must build the associative arrays, they have the same values as the
// indices in the matrix
//mat = new NumericMatrix<V>(matrix);
mat = matrix;
// Build rows
int start = mat.MinRowIndex;
r = new AssocArray <AI1, int>();
foreach (AI1 row in keyRows)
{
r[row] = start;
start++;
}
// Build columns
start = mat.MinColumnIndex;
c = new AssocArray <AI2, int>();
foreach (AI2 col in keyColumns)
{
c[col] = start;
start++;
}
// NO EXCEPTION HANDLING AT THE MOMENT
//print(c);
}
public NumericMatrix(NumericMatrix <T> source) : base(source)
{
}
