Hi, good morning I have been lately working with the gsl library, using the SVD decomposition, but I am having real trouble, so i thought that i was probably doing something wrong and you could help me.
I need to calculate the pseudoinverse of a mxn matrix with n>m (more columns
than rows), and with that matrix being rank-deficient.
I have created the code, that you can read next, to compute the pseudoinverse
of A. As the gsl library isn't able to make the SVD decomposition of
n<m matrices, I used the transpose of A to compute the pseudoinverse of A as
it follows:
A^T = UDV^T ==> A = VDU^T
pinv(A) = US^(-1)V^T
The pseudoinverse is correct when the A is full-rank, but not when is
rank-deficient. And I don't know what i am doing wrong.
The code I've written is:
int n_fil = 3;
int n_col = 8;
double mat[3][8] = {{ 50,4.5, -23, 12, 1, 0, -1, 0}, // Example
Rank-deficient matrix
{ 1, 2, 3, 4, 5, 1, 0, 0},
{ 2, 4, 6, 8, 10, 2, 0, 0}};
unsigned i = 0;
unsigned j = 0;
gsl_matrix * gA = gsl_matrix_alloc (n_fil, n_col);
for (i = 0; i < n_fil; i++)
for (j = 0; j < n_col; j++)
gsl_matrix_set (gA, i, j, mat[i][j]);
gsl_matrix * gA_t = gsl_matrix_alloc (n_col, n_fil);
gsl_matrix_transpose_memcpy (gA_t, gA); // Computing the
transpose of gA
gsl_matrix * U = gsl_matrix_alloc (n_col, n_fil);
gsl_matrix * V= gsl_matrix_alloc (n_fil, n_fil);
gsl_vector * S = gsl_vector_alloc (n_fil);
// Computing the SVD of the transpose of A
// The matrix 'gA_t' will contain 'U' after the function is called
gsl_vector * work = gsl_vector_alloc (n_fil);
gsl_linalg_SV_decomp (gA_t, V, S, work);
gsl_vector_free(work);
U =gA_t;
//Inverting S//
//----------------------------------------------------------
// Matrix 'S' is diagonal, so it is contained in a vector.
// We operate to convert the vector 'S' into the matrix 'Sp'.
//Then we invert 'Sp' to 'Spu'
//----------------------------------------------------------
gsl_matrix * Sp = gsl_matrix_alloc (n_fil, n_fil);
gsl_matrix_set_zero (Sp);
for (i = 0; i < n_fil; i++)
gsl_matrix_set (Sp, i, i, gsl_vector_get(S, i)); // Vector 'S' to
matrix 'Sp'
gsl_permutation * p = gsl_permutation_alloc (n_fil);
int signum;
gsl_linalg_LU_decomp (Sp, p, &signum); // Computing the LU
decomposition
gsl_matrix * SI = gsl_matrix_alloc (n_fil, n_fil);
gsl_linalg_LU_invert (Sp, p, SI); // Computing the inverse
through LU decomposition
gsl_permutation_free(p);
//end Inverting S//
gsl_matrix * VT = gsl_matrix_alloc (n_fil, n_fil);
gsl_matrix_transpose_memcpy (VT, V); // Tranpose of V
//THE PSEUDOINVERSE//
//----------------------------------------------------------
//Computation of the pseudoinverse of trans(A) as pinv(A) = U·inv(S).trans(V)
with trans(A) = U.S.trans(V)
//----------------------------------------------------------
gsl_matrix * SIpVT = gsl_matrix_alloc (n_fil, n_fil);
gsl_blas_dgemm (CblasNoTrans, CblasNoTrans, // Calculating
inv(S).trans(V)
1.0, SI, VT,
0.0, SIpVT);
gsl_matrix * pinv = gsl_matrix_alloc (n_col, n_fil); // Calculating
U·inv(S).trans(V)
gsl_blas_dgemm (CblasNoTrans, CblasNoTrans,
1.0, U, SIpVT,
0.0, pinv);
gsl_matrix_free(VT);
gsl_matrix_free(SI);
gsl_matrix_free(SIpVT);
gsl_matrix_free(gA_t);
gsl_matrix_free(U);
gsl_matrix_free(gA);
gsl_matrix_free(V);
gsl_vector_free(S);
//end THE PSEUDOINVERSE//
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Linux User 152692
PGP: 0xF944807E
Catalonia
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