static public void multiply(ref dense_matrix result, dense_matrix left, sparse_matrix right)
{
int left_height = left.rows, left_width = left.columns;
if (left_width != right._height)
{
throw new ArgumentException("Operand size mismatch");
}
Dictionary <int, double> right_row_ref;
double[] left_row_ref, result_row_ref;
double cur_element;
result.clear(left_height, right._width);
Dictionary <int, double>[] right_contents = right._contents;
for (int cur_row = 0; cur_row < left_height; ++cur_row)
{
left_row_ref = left[cur_row];
result_row_ref = result[cur_row];
for (int sum_index = 0; sum_index < left_width; ++sum_index)
{
cur_element = left_row_ref[sum_index];
right_row_ref = right_contents[sum_index];
foreach (KeyValuePair <int, double> cur_horizontal in right_row_ref)
{
result_row_ref[cur_horizontal.Key] += cur_element * cur_horizontal.Value;
}
}
}
}
static public void multiply(ref dense_matrix result, sparse_matrix left, dense_matrix right)
{
int right_height = right.rows, right_width = right.columns;
if (left._width != right_height)
{
throw new ArgumentException("Operand size mismatch");
}
Dictionary <int, double> left_row_ref;
double[] result_row_ref, right_row_ref;
double cur_element;
result.clear(left._height, right_width);
int left_height = left._height;
Dictionary <int, double>[] left_contents = left._contents;
for (int cur_row = 0; cur_row < left_height; ++cur_row)
{
left_row_ref = left_contents[cur_row];
result_row_ref = result[cur_row];
foreach (KeyValuePair <int, double> cur_diagonal in left_row_ref)
{
cur_element = cur_diagonal.Value;
right_row_ref = right[cur_diagonal.Key];
for (int cur_column = 0; cur_column < right_width; ++cur_column)
{
result_row_ref[cur_column] += cur_element * right_row_ref[cur_column];
}
}
}
}
/*
* public void set_to_identity(int size = 0)
* {
* clear(size);
* for (int cur_element = 0; cur_element < _width; ++cur_element)
* _contents[cur_element][cur_element] = 1.0;
* }
*
* public void copy_from(dense_matrix b)
* {
* if (_width != b._width || _height != b._height)
* clear(b._height, b._width);
*
* double[] cur_row_ref, b_row_ref;
* for (int cur_row = 0; cur_row < _height; ++cur_row)
* {
* cur_row_ref = _contents[cur_row];
* b_row_ref = b._contents[cur_row];
* for (int cur_column = 0; cur_column < _width; ++cur_column)
* cur_row_ref[cur_column] = b_row_ref[cur_column];
* }
* }
*/
public void column_vector_from(dense_matrix b, int column)
{
if (_width != 1 || _height != b._height)
{
clear(b._height, 1);
}
int height = _height;
double[][] contents = _contents, source = b._contents;
for (int cur_row = 0; cur_row < height; ++cur_row)
{
contents[cur_row][0] = source[cur_row][column];
}
}
public static void subtract(dense_matrix minuend, sparse_matrix subtrahend)
{
if (minuend.columns != subtrahend._width || minuend.rows != subtrahend._height)
{
throw new ArgumentException("Attempt to subtract matrix of different size");
}
double[] minuend_row_ref;
Dictionary <int, double> subtrahend_row_ref;
int height = subtrahend._height;
Dictionary <int, double>[] subtrahend_contents = subtrahend._contents;
for (int cur_row = 0; cur_row < height; ++cur_row)
{
minuend_row_ref = minuend[cur_row];
subtrahend_row_ref = subtrahend_contents[cur_row];
foreach (KeyValuePair <int, double> cur_element in subtrahend_row_ref)
{
minuend_row_ref[cur_element.Key] -= cur_element.Value;
}
}
}