static ERL_NIF_TERM
max(ErlNifEnv *env, int32_t argc, const ERL_NIF_TERM *argv) {
ErlNifBinary matrix;
float max;
float *matrix_data;
(void)(argc);
if (!enif_inspect_binary(env, argv[0], &matrix)) return enif_make_badarg(env);
matrix_data = (float *) matrix.data;
max = matrix_max(matrix_data);
return enif_make_double(env, max);
}
/*! @brief Compute matrix infinite norm
@param matrix Matrix for which we want the infinite norm
@return Infinite norm of matrix
*/
double matrix_norm_inf (struct Matrix *matrix)
{
size_t j = 0;
// Norm
double m_norm = 0;
// Vector of the max values of each cols
struct Matrix_max *m_vector = NULL;
if (!matrix)
{
printf("matrix_norm_inf: Matrix not allocated\n");
return 0;
}
m_vector = matrix_max(matrix);
// Compute infinite matrix norm
for (j = 0; j < matrix->nc; j++)
m_norm += m_vector->matrix->data[0][j];
matrix_max_destroy(&m_vector);
return m_norm;
}
/*! @brief Function which compute
the reduce row echelon form of a matrix.
This function doesn't work as expected
and isn't complete.
@param matrix Matrix for which to compute the rref
@return The reduce row echelon form of the matrix
*/
void matrix_rref_gauss_octave (struct Matrix *matrix)
{
size_t m_row = 0, m_col = 0, k = 0, e = 0, u = 0, maxi = 0, m = 0;
size_t i = 0, j = 0;
double eps = 2.2e-16, tolerance = 0;
// Matrix with zeros
struct Matrix *m_used = NULL;
struct Matrix_max *m_max = NULL;
// Temp matrix
double *line = NULL;
if (!matrix)
{
printf("matrix_rref_gauss: Matrix not allocated\n");
return;
}
// max (rows, cols)
// we compare rows and cols
if (matrix->nr > matrix->nc)
maxi = matrix->nr;
else if (matrix->nr < matrix->nc)
maxi = matrix->nc;
else
maxi = matrix->nr;
tolerance = eps * maxi * matrix_norm_inf (matrix);
// Matrix with zeros
m_used = matrix_create(1, matrix->nc);
for (m_col = 0; m_col < matrix->nc; m_col++)
{
m_max = matrix_max(matrix);
// index du maximum
m = m_max->index;
// pivot
m_max->index = m_max->index + m_row - 1;
if (m_max->matrix->data[0][m] < tolerance)
{
// A (r:rows, c) = zeros (rows-r+1, 1);
for (i = m_row; i < matrix->nr; i++)
matrix->data[i][m_col] = 0;
}
else
{
// keep track of bound variables
m_used->data[0][m_col] = 1;
// Swap current row and pivot row
line = matrix->data[i];
matrix->data[i] = matrix->data[m_max->index];
matrix->data[m_max->index] = line;
// Normalize pivot row
for (j = m_col; j < matrix->nc; j++)
// A (r, c:cols) = A (r, c:cols) / A (r, c);
matrix->data[m_row][j] = matrix->data[m_row][j]
/ matrix->data[m_row][m_col];
// Eliminate the current column
for (i = 0; i < m_row; i++)
{
for (j = m_col; j < matrix->nc; j++)
matrix->data[i][j] = matrix->data[i][j]
- matrix->data[i][m_col]
* matrix->data[m_row][j];
}
for (i = m_row+1; i < matrix->nr; i++)
{
for (j = m_col; j < matrix->nc; j++)
matrix->data[i][j] = matrix->data[i][j]
- matrix->data[i][m_col]
* matrix->data[m_row][j];
}
// Check if done
if (++m_row == matrix->nr)
break;
}
/*
else
## Swap current row and pivot row
A ([pivot, r], c:cols) = A ([r, pivot], c:cols);
## Normalize pivot row
A (r, c:cols) = A (r, c:cols) / A (r, c);
## Eliminate the current column
ridx = [1:r-1, r+1:rows];
A (ridx, c:cols) = A (ridx, c:cols) - A (ridx, c) * A(r, c:cols);
## Check if done
if (r++ == rows)
break;
endif
endif
endfor
k = find (used);
*/
}
}
