impls/pounders/gqt.c

7   PetscInt     i, j;
39       /*  Chose y[i] based on the predicted value of y[j] for j>i */
42       for (j = i + 1; j < n; j++) sm += PetscAbs(z[j] + wm * r[i + ldr * j]);
59     for (j = n - 1; j >= 0; j--) {
61       if (PetscAbs(z[j]) > PetscAbs(r[j + ldr * j])) {
62         temp = PetscMin(0.01, PetscAbs(r[j + ldr * j] / z[j]));
66       if (r[j + ldr * j] == 0) {
67         z[j] = 1.0;
69         z[j] = z[j] / r[j + ldr * j];
71       temp = -z[j];
72       PetscCall(PetscBLASIntCast(j, &blasj));
73       PetscCallBLAS("BLASaxpy", BLASaxpy_(&blasj, &temp, &r[0 + ldr * j], &blas1, z, &blas1));
217   PetscInt     iter, j, rednc, info;
230   for (j = 0; j < n; j++) {
231     x[j] = 0.0;
232     z[j] = 0.0;
237   for (j = 0; j < n - 1; j++) {
238     PetscCall(PetscBLASIntCast(n - j - 1, &iblas));
239     PetscCallBLAS("BLAScopy", BLAScopy_(&iblas, &a[j + lda * (j + 1)], &blaslda, &a[j + 1 + lda * j], &blas1));
245   for (j = 0; j < n; j++) {
246     PetscCallBLAS("BLASasum", wa2[j] = BLASasum_(&blasn, &a[0 + lda * j], &blas1));
248     anorm = PetscMax(anorm, wa2[j]);
250   for (j = 0; j < n; j++) wa2[j] = wa2[j] - PetscAbs(wa1[j]);
257   for (j = 0; j < n; j++) {
258     pars = PetscMax(pars, -wa1[j]);
259     parl = PetscMax(parl, wa1[j] + wa2[j]);
260     paru = PetscMax(paru, -wa1[j] + wa2[j]);
284     for (j = 0; j < n - 1; j++) {
285       PetscCall(PetscBLASIntCast(n - j - 1, &iblas));
286       PetscCallBLAS("BLAScopy", BLAScopy_(&iblas, &a[j + 1 + j * lda], &blas1, &a[j + (j + 1) * lda], &blaslda));
288     for (j = 0; j < n; j++) a[j + j * lda] = wa1[j] + par;
417       for (j = 0; j < n; j++) {
418         PetscCall(PetscBLASIntCast(n - j - 1, &iblas));
419         PetscCallBLAS("BLAScopy", BLAScopy_(&iblas, &a[j + 1 + j * lda], &blas1, &a[j + (j + 1) * lda], &blaslda));