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SYMMLQ function finished. Debuggin in process

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This commit is contained in:
Dongryeol Lee
2008-02-06 19:08:45 +00:00
parent a92719092f
commit 36769a2bc5
2 changed files with 136 additions and 25 deletions
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fastlib2/contrib/dongryel/regression/local_linear_krylov.h
+12
View File
@@ -331,6 +331,18 @@ class LocalLinearKrylov {
////////// Private Member Functions //////////
void NormalizeMatrixColumnVectors_(Matrix &m, Vector &lengths) {
for(index_t i = 0; i < m.n_cols(); i++) {
double *column_vector = m.GetColumnPtr(i);
lengths[i] = la::LengthEuclidean(row_length_, column_vector);
if(lengths[i] > 0) {
la::Scale(row_length_, 1.0 / lengths[i], column_vector);
}
}
}
/** @brief Compute the L1 norm of the given vector.
*
* @param v The vector for which we want to compute the L1 norm.
fastlib2/contrib/dongryel/regression/local_linear_krylov_solver_impl.h
+124 -25
View File
@@ -559,32 +559,52 @@ void LocalLinearKrylov<TKernel>::FinalizeQueryTreeLanczosMultiplier_
template<typename TKernel>
void LocalLinearKrylov<TKernel>::SolveLeastSquaresByKrylov_() {
// Temporary variables needed for Lanczos iteration...
// Initialize the initial solutions to zero vectors.
solution_vectors_e_.SetZero();
// Temporary variables needed for SYMMLQ iteration...
Matrix previous_lanczos_vectors;
Matrix current_lanczos_vectors;
previous_lanczos_vectors.Init(row_length_, qset_.n_cols());
Matrix v_tilde_mat;
previous_lanczos_vectors.Init(row_length_, qset_.n_cols());
v_tilde_mat.Init(row_length_, qset_.n_cols());
Vector g_double_tilde_vec;
Vector g_vec;
g_double_tilde_vec.Init(qset_.n_cols());
g_vec.Init(qset_.n_cols());
current_lanczos_vectors.Init(row_length_, qset_.n_cols());
Matrix omega;
omega.Init(row_length_, qset_.n_cols());
Vector alpha, beta, rho, previous_rho, lambda;
Vector zeta, previous_zeta;
alpha.Init(qset_.n_cols());
beta.Init(qset_.n_cols());
rho.Init(qset_.n_cols());
previous_rho.Init(qset_.n_cols());
lambda.Init(qset_.n_cols());
zeta.Init(qset_.n_cols());
previous_zeta.Init(qset_.n_cols());
// More temporary variables for SYMMLQ routine...
Vector c_vec, beta_vec, beta_tilde_vec, s_vec;
Matrix w_mat;
c_vec.Init(qset_.n_cols());
beta_vec.Init(qset_.n_cols());
beta_tilde_vec.Init(qset_.n_cols());
s_vec.Init(qset_.n_cols());
w_mat.Init(row_length_, qset_.n_cols());
// Initialize before entering the main iteration... This
// initialization implicitly assumes that initial guess to the
// linear system is the zero vector.
current_lanczos_vectors.CopyValues(vector_e_);
NormalizeMatrixColumnVectors_(current_lanczos_vectors, g_double_tilde_vec);
beta_vec.SetZero();
beta_tilde_vec.SetZero();
c_vec.SetAll(-1);
s_vec.SetZero();
previous_lanczos_vectors.SetZero();
w_mat.CopyValues(current_lanczos_vectors);
g_vec.SetZero();
// Temporary variables to hold dot product ranges for the root nodes
// of the two trees.
DRange root_negative_dot_product_range, root_positive_dot_product_range;
// Initialize the initial solutions to zero vectors.
solution_vectors_e_.SetZero();
// Main iteration of the Lanczos - repeat until "convergence"...
for(index_t m = 0; m < row_length_; m++) {
// Main iteration of the SYMMLQ algorithm - repeat until
// "convergence"...
for(index_t m = 0; m < sqrt(row_length_); m++) {
// Initialize the query tree solution bounds.
InitializeQueryTreeSolutionBound_(qroot_, current_lanczos_vectors);
@@ -603,12 +623,91 @@ void LocalLinearKrylov<TKernel>::SolveLeastSquaresByKrylov_() {
root_negative_dot_product_range,
root_positive_dot_product_range);
FinalizeQueryTreeLanczosMultiplier_(qroot_);
// Take the dot product between the product above and the current
// lanczos vector.
if(m > 0) {
// Compute v_tilde_mat (the residue after applying the linear
// operator the current Lanczos vector).
la::AddOverwrite(vector_e_, neg_vector_e_, &v_tilde_mat);
for(index_t q = 0; q < qset_.n_cols(); q++) {
double *v_tilde_mat_column = v_tilde_mat.GetColumnPtr(q);
double *previous_lanczos_vector =
previous_lanczos_vectors.GetColumnPtr(q);
double *current_lanczos_vector =
current_lanczos_vectors.GetColumnPtr(q);
la::AddExpert(row_length_, -beta_vec[q], previous_lanczos_vector,
v_tilde_mat_column);
// Compute alpha (a dot product b etween the current Lanczos
// vector and v_tilde vector).
double alpha = la::Dot(row_length_, current_lanczos_vector,
v_tilde_mat_column);
}
}
// Subtract the component of the current Lanczos vector (a form
// of Gram-Schmidt orthogonalization.)
la::AddExpert(row_length_, -alpha, current_lanczos_vector,
v_tilde_mat_column);
// Compute the length of v_tilde_mat_column and store into
// beta_vec.
beta_vec[q] = la::LengthEuclidean(row_length_, v_tilde_mat_column);
// Make a backup copy of the current Lanczos vector.
previous_lanczos_vectors.CopyValues(current_lanczos_vectors);
// Set a new current Lanczos vector based on v_tilde_mat_column
if(beta_vec[q] > 0) {
la::ScaleOverwrite(row_length_, 1.0 / beta_vec[q], v_tilde_mat_column,
current_lanczos_vector);
}
else {
la::ScaleOverwrite(row_length_, 1.0, v_tilde_mat_column,
current_lanczos_vector);
}
// Compute l_1
double l_1 = s_vec[q] * alpha - c_vec[q] * beta_tilde_vec[q];
// Compute l_2
double l_2 = s_vec[q] * beta_vec[q];
// Compute alpha_tilde
double alpha_tilde = -s_vec[q] * beta_tilde_vec[q] - c_vec[q] * alpha;
// Compute beta_tilde
beta_tilde_vec[q] = c_vec[q] * beta_vec[q];
double l_0 = sqrt(alpha_tilde * alpha_tilde + beta_vec[q] * beta_vec[q]);
if(l_0 != 0) {
c_vec[q] = alpha_tilde / l_0;
s_vec[q] = beta_vec[q] / l_0;
}
else {
printf("Warning: Division by zero attempted!\n");
}
double g_tilde = g_double_tilde_vec[q] - l_1 * g_vec[q];
g_double_tilde_vec[q] = -l_2 * g_vec[q];
if(l_0 != 0) {
g_vec[q] = g_tilde / l_0;
}
else {
printf("Warning: Division by zero attempted!\n");
}
// Update solution.
la::AddExpert(row_length_, g_vec[q] * c_vec[q], w_mat.GetColumnPtr(q),
solution_vectors_e_.GetColumnPtr(q));
la::AddExpert(row_length_, g_vec[q] * s_vec[q], current_lanczos_vector,
solution_vectors_e_.GetColumnPtr(q));
la::Scale(row_length_, s_vec[q], w_mat.GetColumnPtr(q));
la::AddExpert(row_length_, -c_vec[q], current_lanczos_vector,
w_mat.GetColumnPtr(q));
} // end of iterating over each query point.
} // end of an iteration of SYMMLQ
}