Cloned SEACAS for EXODUS library with extra build files for internal package management.
You can not select more than 25 topics Topics must start with a letter or number, can include dashes ('-') and can be up to 35 characters long.
 
 
 
 
 
 

75 lines
2.8 KiB

/*
* Copyright(C) 1999-2020, 2023 National Technology & Engineering Solutions
* of Sandia, LLC (NTESS). Under the terms of Contract DE-NA0003525 with
* NTESS, the U.S. Government retains certain rights in this software.
*
* See packages/seacas/LICENSE for details
*/
#include "defs.h" // for FALSE, TRUE
#include <math.h> // for fabs
/* NOTE: This should only be called if j >= 2. It returns a residual and
the point where the forward and backward recurrences met. */
/* NOTE: The paper has an error in the residual calculation. And the
heuristic of increasing the cut-off for the local maximum
by a factor of 10 when the residual tolerance is not met
appears to work poorly - letting the recursion run further
to find a bigger local max often results in <less> accurate
results. Static cut-off of 1 (recall we set the first element
to 1) worked better. */
/* Finds eigenvector s of T and returns residual norm. */
double bidir(double *alpha, /* vector of Lanczos scalars */
double *beta, /* vector of Lanczos scalars */
int j, /* number of Lanczos iterations taken */
double ritz, /* approximate eigenvalue of T */
double *s, /* approximate eigenvector of T */
double hurdle /* hurdle for local maximum in recurrence */
)
{
int i; /* index */
int k; /* meeting point for bidirect. recurrence */
double sav_val; /* value at meeting point */
int iterate; /* keep iterating? */
double scale; /* scale factor for bidirectional recurrence */
double residual; /* eigen residual */
s[2] = -(alpha[1] - ritz) / beta[2];
i = 3;
iterate = TRUE;
while (i <= j && iterate) {
/* follow the forward recurrence until a local maximum > 1.0 */
s[i] = -((alpha[i - 1] - ritz) * s[i - 1] + beta[i - 1] * s[i - 2]) / beta[i];
if (fabs(s[i - 1]) > hurdle) {
if (fabs(s[i]) < fabs(s[i - 1]) && fabs(s[i - 1]) > fabs(s[i - 2])) {
iterate = FALSE;
k = i - 1;
sav_val = s[k];
}
}
i++;
}
if (!iterate) {
/* we stopped at an intermediate point */
s[j] = 1.0;
s[j - 1] = -(alpha[j] - ritz) / beta[j];
for (i = j; i >= k + 2; i--) {
s[i - 2] = -((alpha[i - 1] - ritz) * s[i - 1] + beta[i] * s[i]) / beta[i - 1];
}
scale = s[k] / sav_val;
for (i = 1; i <= k - 1; i++) {
s[i] = s[i] * scale;
}
/* paper gets this expression wrong */
residual = beta[k] * s[k - 1] + (alpha[k] - ritz) * s[k] + beta[k + 1] * s[k + 1];
}
else {
/* we went all the way forward */
residual = (alpha[j] - ritz) * s[j] + beta[j] * s[j - 1];
}
residual = fabs(residual) / sign_normalize(s, 1, j, j);
return (residual);
}