int main(int argc, char *argv[])
{
struct matrix_t *matrixA;
struct sparse_matrix_t *sparseA;
struct vector_t *x, *b;
lsqr_input *input;
lsqr_output *output;
lsqr_work *work; /* zone temoraire de travail */
lsqr_func *func; /* func->mat_vec_prod -> APROD */
/* cmd line arg */
char *matrix_filename = NULL;
char *vector_filename = NULL;
char *sol_filename = NULL;
int max_iter = -1;
float damping = 0;
if (argc != 4) {
fprintf(stderr, "%s matrixfile vectorfile solutionfile\n",
argv[0]);
exit(1);
}
matrix_filename = strdup(argv[1]);
vector_filename = strdup(argv[2]);
sol_filename = strdup(argv[3]);
/* read the matrix */
matrixA = read_matrix(matrix_filename);
fprintf(stderr, "read*matrix: ok (size=%ldx%ld, %ld elements)\n",
matrixA->nb_line, matrixA->nb_col,
matrixA->nb_line * matrixA->nb_col);
sparseA = sparsify(matrixA, SPARSE_COL_LINK);
b = read_simple_vector(vector_filename);
/*************************************************/
/* check compatibility between matrix and vector */
/*************************************************/
if (sparseA->nb_line != b->length) {
fprintf(stderr,
"Error, check your matrix/vector sizes (%ld/%ld)\n",
sparseA->nb_line, b->length);
exit(1);
}
/* init vector solution to zero */
x = new_vector(sparseA->nb_col);
/* catch Ctrl-C signal */
signal(SIGINT, emergency_halt);
/*************************************************************/
/* solve A.x = B */
/*************************************************************/
/* LSQR alloc */
alloc_lsqr_mem(&input, &output, &work, &func,
sparseA->nb_line, sparseA->nb_col);
fprintf(stderr, "alloc_lsqr_mem : ok\n");
/* defines the routine Mat.Vect to use */
func->mat_vec_prod = sparseMATRIXxVECTOR;
/* Set the input parameters for LSQR */
input->num_rows = sparseA->nb_line;
input->num_cols = sparseA->nb_col;
input->rel_mat_err = .0;
input->rel_rhs_err = .0;
input->cond_lim = .0;
input->lsqr_fp_out = stdout;
input->rhs_vec = (dvec *) b;
input->sol_vec = (dvec *) x; /* initial guess */
input->damp_val = damping;
if (max_iter == -1) {
input->max_iter = 4 * (sparseA->nb_col);
} else {
input->max_iter = max_iter;
}
/* resolution du systeme Ax=b */
lsqr(input, output, work, func, sparseA);
write_vector((struct vector_t *) output->sol_vec, sol_filename);
free_lsqr_mem(input, output, work, func);
free_matrix(matrixA);
/* check A^t.A */
/*
* { struct sparse_matrix_t *AtA; AtA = AtransA (sparseA);
* write_sparse_matrix(AtA, "AtA"); write_sparse_matrix(sparseA,
* "A"); free_sparse_matrix (AtA);
*
* } */
free_sparse_matrix(sparseA);
return (1);
}
float
optimize_smoothness(WPt& worlds_pts, const IntensityPerImage& left_intensities, const IntensityPerImage& right_intensities)
{
// copy to globals
//assert(fromVector.size() == toVector.size());
//assert(fromVector.size() >= 3);
//_fromVector = fromVector;
// worlds_pts.resize(3);
if (worlds_pts.size() < 3) {
// too little points to opitimize
return -1;
}
double max_z = -DBL_MAX;
for (auto w = 0; w < worlds_pts.size();++w) {
max_z = std::max(max_z, worlds_pts[w][2]);
// max_z = std::max(max_z, (worlds_pts[w][1]));
}
double adjustment_rate = 1;
std::vector<double> lambdas;
lambdas.resize(worlds_pts.size() - 2);
for (auto w = 0; w < worlds_pts.size();++w) {
if (((w - 1) >= 0) && ((w) < (worlds_pts.size() - 1))) {
double z_top = worlds_pts[w - 1][2];
double z_bottom = worlds_pts[w + 1][2];
double z_0 = worlds_pts[w][2];
// double z_top = worlds_pts[w - 1][1];
// double z_bottom = worlds_pts[w + 1][1];
// double z_0 = worlds_pts[w][1];
// double delta_z = ((z_top - z_bottom) + (z_0 - z_top) - (z_bottom - z_0)) / max_z;
double delta_z = ((z_0 - z_top) - (z_bottom - z_0)) / max_z;
// double delta_z = 0;
double omega_i = std::min(left_intensities[w], right_intensities[w]);
omega_i /= 255.0;
// omega_i = 1.0;
// double lambda_i = (1.0 - delta_z) * omega_i * adjustment_rate;
double lambda_i = 0.99;
lambdas[w - 1] = lambda_i;
double y_top = worlds_pts[w - 1][1];
double y_bottom = worlds_pts[w + 1][1];
double y_0 = worlds_pts[w][1];
double y = worlds_pts[w][1];
double y_prime = w;
}
}
#ifdef DEBUG
for (auto i = 0u; i < lambdas.size(); ++i) {
std::cout << std::setprecision(15) << lambdas[i] << std::endl;
}
#endif
// allocate to globals
lambdas_g = lambdas;
// allocate structures for sparse linear least squares
//printf("\tallocating for sparse linear least squares "
//"(%i vectors)...\n", fromVector.size());
int num_rows = worlds_pts.size() - 2;
int num_cols = worlds_pts.size();
lsqr_input *input = NULL;
lsqr_output *output = NULL;
lsqr_work *work = NULL;
lsqr_func *func = NULL;
alloc_lsqr_mem(&input, &output, &work, &func, num_rows, num_cols);
input->num_rows = num_rows;
input->num_cols = num_cols;
input->damp_val = 0.0;
input->rel_mat_err = 0.0;
input->rel_rhs_err = 0.0;
input->cond_lim = 0.0;
input->max_iter = 10*input->num_cols;
input->lsqr_fp_out = NULL;
func->mat_vec_prod = lsqr_eval_for_opt;
// set rhs vec
for (auto j = 0; j < num_rows; ++j) {
// input->rhs_vec->elements[j] = (1.0 - lambdas[j]) * worlds_pts[j+1][1];
input->rhs_vec->elements[j] = (1.0 - lambdas[j]) * worlds_pts[j+1][2];
}
// set initial sol vec
for (auto i = 0u; i<num_cols; i++) {
// input->sol_vec->elements[i] = worlds_pts[i][1];
input->sol_vec->elements[i] = 0;
}
// call sparse linear least squares!
printf("\t\tstarting (rows=%i, cols=%i)...\n", num_rows, num_cols);
lsqr(input, output, work, func, NULL);
double error = output->resid_norm;
printf("\t\ttermination reason = %i\n", output->term_flag);
printf("\t\tnum function calls = %i\n", output->num_iters);
printf("\t\tremaining error = %lf\n", error);
if (worlds_pts.size() > 0) {
// double y_prev = worlds_pts[0][1];
double y_prev = worlds_pts[0][2];
for (auto i = 1u; i < worlds_pts.size() - 1; ++i) {
// auto& y = worlds_pts[i][1];
auto& y = worlds_pts[i][2];
y = output->sol_vec->elements[i];
double y_diff = y - y_prev;
std::cout << "y difference " << i << " : "<< y_diff << std::endl;
y_prev = y;
}
auto i = worlds_pts.size() - 1;
// auto& y = worlds_pts[i][1];
auto& y = worlds_pts[i][2];
double y_diff = y - y_prev;
std::cout << "y difference " << i << " : "<< y_diff << std::endl;
}
// free memory
free_lsqr_mem(input, output, work, func);
return (error);
}
int main(int argc, char *argv[])
{
struct sparse_matrix_t *sparseA = NULL;
struct vector_t *b = NULL;
struct vector_t *x;
struct mesh_t *mesh;
char *xml_output;
long int *compress2fat = NULL;
struct vector_t *solution;
struct vector_t *std_error_sol;
long int fat_sol_nb_col;
lsqr_input *input;
lsqr_output *output;
lsqr_work *work; /* zone temoraire de travail */
lsqr_func *func; /* func->mat_vec_prod -> APROD */
/* cmd line arg */
char *mesh_filename = NULL;
char *importfilename = NULL;
char *output_filename = NULL;
char *sol_error_filename = NULL;
char *log_filename = NULL;
char *output_type = NULL;
int max_iter;
double damping, grad_damping;
int use_ach = 0; /* ACH : tele-seismic inversion tomography */
int check_sparse = 0; /* check sparse matrix disable by default */
/* velocity model */
char *vmodel = NULL;
struct velocity_model_t *vm = NULL;
struct mesh_t **imported_mesh = NULL;
char **xmlfilelist = NULL;
int nb_xmlfile = 0;
int i, j;
int nb_irm = 0;
struct irm_t **irm = NULL;
int *nb_metacell = NULL;
FILE *logfd;
/*************************************************************/
parse_command_line(argc, argv,
&mesh_filename,
&vmodel,
&importfilename,
&log_filename,
&output_filename, &output_type,
&max_iter,
&damping, &grad_damping, &use_ach, &check_sparse);
if (use_ach) {
fprintf(stderr, "Using ACH tomographic inversion\n");
} else {
fprintf(stderr, "Using STANDARD tomographic inversion\n");
}
/* load the velocity model */
if (vmodel) {
char *myfile;
vm = load_velocity_model(vmodel);
if (!vm) {
fprintf(stderr, "Can not initialize velocity model '%s'\n",
vmodel);
exit(1);
}
myfile = strdup(vmodel);
fprintf(stderr, "Velocity model '%s' loaded\n", basename(myfile));
free(myfile);
} else {
vm = NULL;
}
/* Open log file */
if (!log_filename) {
logfd = stdout;
} else {
if (!(logfd = fopen(log_filename, "w"))) {
perror(log_filename);
exit(1);
}
}
/*check_write_access (output_filename); */
/**************************************/
/* test if we can open file to import */
/**************************************/
if (importfilename) {
xmlfilelist = parse_separated_list(importfilename, ",");
nb_xmlfile = 0;
while (xmlfilelist[nb_xmlfile]) {
if (access(xmlfilelist[nb_xmlfile], R_OK) == -1) {
perror(xmlfilelist[nb_xmlfile]);
exit(1);
}
nb_xmlfile++;
}
} else {
fprintf(stderr, "No file to import ... exiting\n");
exit(0);
}
/****************************/
/* main mesh initialization */
/****************************/
mesh = mesh_init_from_file(mesh_filename);
if (!mesh) {
fprintf(stderr, "Error decoding %s.\n", mesh_filename);
exit(1);
}
fprintf(stderr, "read %s ok\n", mesh_filename);
/*****************************************/
/* check and initialize slice xml files */
/*****************************************/
if (nb_xmlfile) {
int nb_sparse = 0;
int nb_res = 0;
int f;
imported_mesh =
(struct mesh_t **) malloc(sizeof(struct mesh_t *) *
nb_xmlfile);
assert(imported_mesh);
for (i = 0; i < nb_xmlfile; i++) {
imported_mesh[i] = mesh_init_from_file(xmlfilelist[i]);
if (!imported_mesh[i]) {
fprintf(stderr, "Error decoding %s.\n", mesh_filename);
exit(1);
}
for (f = 0; f < NB_MESH_FILE_FORMAT; f++) {
/* mandatory field : res, sparse, and irm if provided */
if (f == RES || f == SPARSE || f == IRM) {
check_files_access(f, imported_mesh[i]->data[f],
xmlfilelist[i]);
}
}
if (imported_mesh[i]->data[SPARSE]) {
nb_sparse += imported_mesh[i]->data[SPARSE]->ndatafile;
}
if (imported_mesh[i]->data[RES]) {
nb_res += imported_mesh[i]->data[RES]->ndatafile;
}
if (imported_mesh[i]->data[IRM]) {
nb_irm += imported_mesh[i]->data[IRM]->ndatafile;
}
}
if (!nb_sparse || !nb_res) {
fprintf(stderr, "Error no sparse or res file available !\n");
exit(0);
}
}
/*********************************************/
/* read and import the sparse(s) matrix(ces) */
/*********************************************/
for (i = 0; i < nb_xmlfile; i++) {
if (!imported_mesh[i]->data[SPARSE]) {
continue;
}
for (j = 0; j < imported_mesh[i]->data[SPARSE]->ndatafile; j++) {
sparseA = import_sparse_matrix(sparseA,
imported_mesh[i]->data[SPARSE]->
filename[j]);
}
}
if (check_sparse) {
if (check_sparse_matrix(sparseA)) {
exit(1);
}
}
/*sparse_compute_length(sparseA, "length1.txt"); */
fat_sol_nb_col = sparseA->nb_col;
show_sparse_stats(sparseA);
/*********************************************/
/* read and import the residual time vector */
/*********************************************/
for (i = 0; i < nb_xmlfile; i++) {
if (!imported_mesh[i]->data[RES]) {
continue;
}
for (j = 0; j < imported_mesh[i]->data[RES]->ndatafile; j++) {
b = import_vector(b, imported_mesh[i]->data[RES]->filename[j]);
}
}
/*************************************************/
/* check compatibility between matrix and vector */
/*************************************************/
if (sparseA->nb_line != b->length) {
fprintf(stderr,
"Error, check your matrix/vector sizes (%ld/%ld)\n",
sparseA->nb_line, b->length);
exit(1);
}
/********************/
/* show memory used */
/********************/
#ifdef __APPLE__
{
struct mstats memusage;
memusage = mstats();
fprintf(stderr, "Memory used: %.2f MBytes\n",
(float) (memusage.bytes_used) / (1024. * 1024));
}
#else
{
struct mallinfo m_info;
m_info = mallinfo();
fprintf(stderr, "Memory used: %.2f MBytes\n",
(float) (m_info.uordblks +
m_info.usmblks) / (1024. * 1024.));
}
#endif
/**************************************/
/* relative traveltime mode */
/**************************************/
if (use_ach) {
int nb_evt_imported = 0;
for (i = 0; i < nb_xmlfile; i++) {
if (!imported_mesh[i]->data[EVT]) {
continue;
}
for (j = 0; j < imported_mesh[i]->data[EVT]->ndatafile; j++) {
relative_tt(sparseA, b,
imported_mesh[i]->data[EVT]->filename[j]);
nb_evt_imported++;
}
}
if (!nb_evt_imported) {
fprintf(stderr,
"Error in ACH mode, can not import any .evt file !\n");
exit(1);
}
}
/************************************************/
/* read the irregular mesh definition if needed */
/* one by layer */
/************************************************/
if (nb_irm) {
int cpt = 0;
struct mesh_offset_t **offset;
int l;
irm = (struct irm_t **) malloc(nb_irm * sizeof(struct irm_t *));
assert(irm);
nb_metacell = (int *) calloc(nb_irm, sizeof(int));
assert(nb_metacell);
make_mesh(mesh);
for (i = 0; i < nb_xmlfile; i++) {
if (!imported_mesh[i]->data[IRM]) {
continue;
}
/* offset between meshes */
offset = compute_mesh_offset(mesh, imported_mesh[i]);
for (l = 0; l < mesh->nlayers; l++) {
if (!offset[l])
continue;
fprintf(stderr,
"\t%s, [%s] offset[layer=%d] : lat=%d lon=%d z=%d\n",
xmlfilelist[i], MESH_FILE_FORMAT[IRM], l,
offset[l]->lat, offset[l]->lon, offset[l]->z);
}
for (j = 0; j < imported_mesh[i]->data[IRM]->ndatafile; j++) {
/* FIXME: read only once the irm file */
irm[cpt] =
read_irm(imported_mesh[i]->data[IRM]->filename[j],
&(nb_metacell[cpt]));
import2mesh_irm_file(mesh,
imported_mesh[i]->data[IRM]->
filename[j], offset);
cpt++;
}
for (l = 0; l < mesh->nlayers; l++) {
if (offset[l])
free(offset[l]);
}
free(offset);
}
metacell_find_neighbourhood(mesh);
}
/*sparse_compute_length(sparseA, "length1.txt"); */
fat_sol_nb_col = sparseA->nb_col;
show_sparse_stats(sparseA);
/***********************/
/* remove empty column */
/***********************/
fprintf(stderr, "starting compression ...\n");
sparse_compress_column(mesh, sparseA, &compress2fat);
if (check_sparse) {
if (check_sparse_matrix(sparseA)) {
exit(1);
}
}
show_sparse_stats(sparseA);
/***************************************/
/* add gradient damping regularisation */
/***************************************/
if (fabs(grad_damping) > 1.e-6) {
int nb_faces = 6; /* 1 cell may have 6 neighbours */
long int nb_lines = 0;
char *regul_name;
fprintf(stdout, "using gradient damping : %f\n", grad_damping);
/* tmp file name */
regul_name = tempnam("/tmp", "regul");
if (!regul_name) {
perror("lsqrsolve: ");
exit(1);
}
if (nb_irm) {
create_regul_DtD_irm(sparseA, compress2fat,
mesh, regul_name, nb_faces,
grad_damping, &nb_lines);
} else {
create_regul_DtD(sparseA, compress2fat,
mesh, regul_name, nb_faces,
grad_damping, &nb_lines);
}
sparse_matrix_resize(sparseA,
sparseA->nb_line + sparseA->nb_col,
sparseA->nb_col);
sparseA = import_sparse_matrix(sparseA, regul_name);
if (check_sparse) {
if (check_sparse_matrix(sparseA)) {
exit(1);
}
}
vector_resize(b, sparseA->nb_line);
unlink(regul_name);
show_sparse_stats(sparseA);
}
/*********************************/
/* the real mesh is no more used */
/* keep only the light mesh */
/*********************************/
fprintf(stdout,
"Time to free the real mesh and keep only the light structure\n");
free_mesh(mesh);
mesh = mesh_init_from_file(mesh_filename);
if (!mesh) {
fprintf(stderr, "Error decoding %s.\n", mesh_filename);
exit(1);
}
fprintf(stderr, "read %s ok\n", mesh_filename);
/********************************/
/* init vector solution to zero */
/********************************/
x = new_vector(sparseA->nb_col);
/*************************************************************/
/* solve A.x = B */
/* A = ray length in the cells */
/* B = residual travel time observed - computed */
/* x solution to satisfy the lsqr problem */
/*************************************************************/
/* LSQR alloc */
alloc_lsqr_mem(&input, &output, &work, &func, sparseA->nb_line,
sparseA->nb_col);
fprintf(stderr, "alloc_lsqr_mem : ok\n");
/* defines the routine Mat.Vect to use */
func->mat_vec_prod = sparseMATRIXxVECTOR;
/* Set the input parameters for LSQR */
input->num_rows = sparseA->nb_line;
input->num_cols = sparseA->nb_col;
input->rel_mat_err = 1.0e-3; /* in km */
input->rel_rhs_err = 1.0e-2; /* in seconde */
/*input->rel_mat_err = 0.;
input->rel_rhs_err = 0.; */
input->cond_lim = .0;
input->lsqr_fp_out = logfd;
/* input->rhs_vec = (dvec *) b; */
dvec_copy((dvec *) b, input->rhs_vec);
input->sol_vec = (dvec *) x; /* initial guess */
input->damp_val = damping;
if (max_iter == -1) {
input->max_iter = 4 * (sparseA->nb_col);
} else {
input->max_iter = max_iter;
}
/* catch Ctrl-C signal */
signal(SIGINT, emergency_halt);
/******************************/
/* resolution du systeme Ax=b */
/******************************/
lsqr(input, output, work, func, sparseA);
fprintf(stderr, "*** lsqr ended (%ld iter) : %s\n",
output->num_iters, lsqr_msg[output->term_flag]);
if (output->term_flag == 0) { /* solution x=x0 */
exit(0);
}
/* uncompress the solution */
solution = uncompress_column((struct vector_t *) output->sol_vec,
compress2fat, fat_sol_nb_col);
/* uncompress the standard error on solution */
std_error_sol =
uncompress_column((struct vector_t *) output->std_err_vec,
compress2fat, fat_sol_nb_col);
/* if irm file was provided, set the right value to each cell
* from a given metacell
*/
if (irm) {
irm_update(solution, irm, nb_metacell, nb_irm, mesh);
free_irm(irm, nb_irm);
free(nb_metacell);
}
/* write solution */
if (strchr(output_type, 'm')) {
export2matlab(solution, output_filename, mesh, vm,
output->num_iters,
input->damp_val, grad_damping, use_ach);
}
if (strchr(output_type, 's')) {
export2sco(solution, output_filename, mesh, vm,
output->num_iters,
input->damp_val, grad_damping, use_ach);
}
if (strchr(output_type, 'g')) {
/* solution */
export2gmt(solution, output_filename, mesh, vm,
output->num_iters,
input->damp_val, grad_damping, use_ach);
/* error on solution */
sol_error_filename = (char *)
malloc(sizeof(char) *
(strlen(output_filename) + strlen(".err") + 1));
sprintf(sol_error_filename, "%s.err", output_filename);
export2gmt(std_error_sol, sol_error_filename, mesh, vm,
output->num_iters,
input->damp_val, grad_damping, use_ach);
free(sol_error_filename);
}
/* save the xml enrichied with sections */
xml_output = (char *)
malloc((strlen(output_filename) + strlen(".xml") +
1) * sizeof(char));
assert(xml_output);
sprintf(xml_output, "%s.xml", output_filename);
mesh2xml(mesh, xml_output);
free(xml_output);
/******************************************************/
/* variance reduction, ie how the model fits the data */
/* X = the final solution */
/* */
/* ||b-AX||² */
/* VR= 1 - -------- */
/* ||b||² */
/* */
/******************************************************/
{
double norm_b;
double norm_b_AX;
double VR; /* variance reduction */
struct vector_t *rhs; /* right hand side */
rhs = new_vector(sparseA->nb_line);
/* use copy */
dvec_copy((dvec *) b, (dvec *) rhs);
norm_b = dvec_norm2((dvec *) rhs);
/* does rhs = rhs + sparseA . output->sol_vec */
/* here rhs is overwritten */
dvec_scale((-1.0), (dvec *) rhs);
sparseMATRIXxVECTOR(0, output->sol_vec, (dvec *) rhs, sparseA);
dvec_scale((-1.0), (dvec *) rhs);
norm_b_AX = dvec_norm2((dvec *) rhs);
VR = 1 - (norm_b_AX * norm_b_AX) / (norm_b * norm_b);
fprintf(stdout, "Variance reduction = %.2f%%\n", VR * 100);
free_vector(rhs);
}
/********/
/* free */
/********/
if (vm) {
free_velocity_model(vm);
}
free_mesh(mesh);
free_sparse_matrix(sparseA);
free_lsqr_mem(input, output, work, func);
free_vector(solution);
free_vector(std_error_sol);
free(compress2fat);
for (i = 0; i < nb_xmlfile; i++) {
free(xmlfilelist[i]);
free_mesh(imported_mesh[i]);
}
free(xmlfilelist);
free(imported_mesh);
return (0);
}
double find_optimal_edge_zero_crossing(std::vector<cv::Point2f>& crossing_points)
{
// copy to globals
//assert(fromVector.size() == toVector.size());
//assert(fromVector.size() >= 3);
//_fromVector = fromVector;
// worlds_pts.resize(3);
if (crossing_points.size() < 3) {
// too little points to opitimize
return -1;
}
#ifdef DEBUG
//for (auto i = 0u; i < lambdas.size(); ++i) {
// std::cout << std::setprecision(15) << lambdas[i] << std::endl;
//}
#endif
// allocate to globals
crossing_points_g = crossing_points;
// allocate structures for sparse linear least squares
//printf("\tallocating for sparse linear least squares "
//"(%i vectors)...\n", fromVector.size());
int num_rows = crossing_points.size();
int num_cols = 3;
lsqr_input *input = NULL;
lsqr_output *output = NULL;
lsqr_work *work = NULL;
lsqr_func *func = NULL;
alloc_lsqr_mem(&input, &output, &work, &func, num_rows, num_cols);
input->num_rows = num_rows;
input->num_cols = num_cols;
input->damp_val = 0.0;
input->rel_mat_err = 0.0;
input->rel_rhs_err = 0.0;
input->cond_lim = 0.0;
input->max_iter = 10*input->num_cols;
input->lsqr_fp_out = NULL;
func->mat_vec_prod = lsqr_eval_for_opt_;
// set rhs vec
for (auto j = 0; j < num_rows; ++j) {
// input->rhs_vec->elements[j] = (1.0 - lambdas[j]) * worlds_pts[j+1][1];
input->rhs_vec->elements[j] = crossing_points[j].y;
}
// set initial sol vec
for (auto i = 0u; i<num_cols; i++) {
// input->sol_vec->elements[i] = worlds_pts[i][1];
input->sol_vec->elements[i] = 0;
}
// call sparse linear least squares!
//printf("\t\tstarting (rows=%i, cols=%i)...\n", num_rows, num_cols);
lsqr(input, output, work, func, NULL);
double error = output->resid_norm;
//printf("\t\ttermination reason = %i\n", output->term_flag);
//printf("\t\tnum function calls = %i\n", output->num_iters);
//printf("\t\tremaining error = %lf\n", error);
double a = input->sol_vec->elements[0];
double b = input->sol_vec->elements[1];
double c = input->sol_vec->elements[2];
// solving for y = 0
double solution = 0.0;
double discriminant = std::pow(b, 2) - (4 * a * c);
if (discriminant < 0) {
// something went wrong
solution = -1;
} else {
double delta = std::sqrt(discriminant);
double sol_1 = ((-1 * b) + delta) / (2 * a);
double sol_2 = ((-1 * b) - delta) / (2 * a);
if (sol_1 <= crossing_points[crossing_points.size() - 1].x &&
sol_1 >= crossing_points[0].x) {
solution = sol_1;
} else if (sol_2 <= crossing_points[crossing_points.size() - 1].x &&
sol_2 >= crossing_points[0].x) {
solution = sol_2;
} else {
// something wrong happened
solution = -1;
}
}
// free memory
free_lsqr_mem(input, output, work, func);
return (solution);
}
