Actual source code: ex51.c

  1: static char help[] = "This example solves a linear system in parallel with KSP.  The matrix\n\
  2: uses arbitrary order polynomials for finite elements on the unit square.  To test the parallel\n\
  3: matrix assembly, the matrix is intentionally laid out across processors\n\
  4: differently from the way it is assembled.  Input arguments are:\n\
  5:   -m <size> -p <order> : mesh size and polynomial order\n\n";

  7: /* Contributed by Travis Austin <austin@txcorp.com>, 2010.
  8:    based on src/ksp/ksp/tutorials/ex3.c
  9:  */

 11: #include <petscksp.h>

 13: /* Declare user-defined routines */
 14: static PetscReal      src(PetscReal, PetscReal);
 15: static PetscReal      ubdy(PetscReal, PetscReal);
 16: static PetscReal      polyBasisFunc(PetscInt, PetscInt, PetscReal *, PetscReal);
 17: static PetscReal      derivPolyBasisFunc(PetscInt, PetscInt, PetscReal *, PetscReal);
 18: static PetscErrorCode Form1DElementMass(PetscReal, PetscInt, PetscReal *, PetscReal *, PetscScalar *);
 19: static PetscErrorCode Form1DElementStiffness(PetscReal, PetscInt, PetscReal *, PetscReal *, PetscScalar *);
 20: static PetscErrorCode Form2DElementMass(PetscInt, PetscScalar *, PetscScalar *);
 21: static PetscErrorCode Form2DElementStiffness(PetscInt, PetscScalar *, PetscScalar *, PetscScalar *);
 22: static PetscErrorCode FormNodalRhs(PetscInt, PetscReal, PetscReal, PetscReal, PetscReal *, PetscScalar *);
 23: static PetscErrorCode FormNodalSoln(PetscInt, PetscReal, PetscReal, PetscReal, PetscReal *, PetscScalar *);
 24: static void           leggaulob(PetscReal, PetscReal, PetscReal[], PetscReal[], PetscInt);
 25: static void           qAndLEvaluation(PetscInt, PetscReal, PetscReal *, PetscReal *, PetscReal *);

 27: int main(int argc, char **args)
 28: {
 29:   PetscInt     p = 2, m = 5;
 30:   PetscInt     num1Dnodes, num2Dnodes;
 31:   PetscScalar *Ke1D, *Ke2D, *Me1D, *Me2D;
 32:   PetscScalar *r, *ue, val;
 33:   Vec          u, ustar, b, q;
 34:   Mat          A, Mass;
 35:   KSP          ksp;
 36:   PetscInt     M, N;
 37:   PetscMPIInt  rank, size;
 38:   PetscReal    x, y, h, norm;
 39:   PetscInt    *idx, indx, count, *rows, i, j, k, start, end, its;
 40:   PetscReal   *rowsx, *rowsy;
 41:   PetscReal   *gllNode, *gllWgts;

 43:   PetscFunctionBeginUser;
 44:   PetscCall(PetscInitialize(&argc, &args, NULL, help));
 45:   PetscOptionsBegin(PETSC_COMM_WORLD, NULL, "Options for p-FEM", "");
 46:   PetscCall(PetscOptionsInt("-m", "Number of elements in each direction", "None", m, &m, NULL));
 47:   PetscCall(PetscOptionsInt("-p", "Order of each element (tensor product basis)", "None", p, &p, NULL));
 48:   PetscOptionsEnd();
 49:   PetscCheck(p > 0, PETSC_COMM_SELF, PETSC_ERR_USER, "Option -p value should be greater than zero");
 50:   N = (p * m + 1) * (p * m + 1); /* dimension of matrix */
 51:   M = m * m;                     /* number of elements */
 52:   h = 1.0 / m;                   /* mesh width */
 53:   PetscCallMPI(MPI_Comm_rank(PETSC_COMM_WORLD, &rank));
 54:   PetscCallMPI(MPI_Comm_size(PETSC_COMM_WORLD, &size));

 56:   /* Create stiffness matrix */
 57:   PetscCall(MatCreate(PETSC_COMM_WORLD, &A));
 58:   PetscCall(MatSetSizes(A, PETSC_DECIDE, PETSC_DECIDE, N, N));
 59:   PetscCall(MatSetFromOptions(A));
 60:   PetscCall(MatSetUp(A));

 62:   /* Create matrix  */
 63:   PetscCall(MatCreate(PETSC_COMM_WORLD, &Mass));
 64:   PetscCall(MatSetSizes(Mass, PETSC_DECIDE, PETSC_DECIDE, N, N));
 65:   PetscCall(MatSetFromOptions(Mass));
 66:   PetscCall(MatSetUp(Mass));
 67:   start = rank * (M / size) + ((M % size) < rank ? (M % size) : rank);
 68:   end   = start + M / size + ((M % size) > rank);

 70:   /* Allocate element stiffness matrices */
 71:   num1Dnodes = (p + 1);
 72:   num2Dnodes = num1Dnodes * num1Dnodes;

 74:   PetscCall(PetscMalloc1(num1Dnodes * num1Dnodes, &Me1D));
 75:   PetscCall(PetscMalloc1(num1Dnodes * num1Dnodes, &Ke1D));
 76:   PetscCall(PetscMalloc1(num2Dnodes * num2Dnodes, &Me2D));
 77:   PetscCall(PetscMalloc1(num2Dnodes * num2Dnodes, &Ke2D));
 78:   PetscCall(PetscMalloc1(num2Dnodes, &idx));
 79:   PetscCall(PetscMalloc1(num2Dnodes, &r));
 80:   PetscCall(PetscMalloc1(num2Dnodes, &ue));

 82:   /* Allocate quadrature and create stiffness matrices */
 83:   PetscCall(PetscMalloc1(p + 1, &gllNode));
 84:   PetscCall(PetscMalloc1(p + 1, &gllWgts));
 85:   leggaulob(0.0, 1.0, gllNode, gllWgts, p); /* Get GLL nodes and weights */
 86:   PetscCall(Form1DElementMass(h, p, gllNode, gllWgts, Me1D));
 87:   PetscCall(Form1DElementStiffness(h, p, gllNode, gllWgts, Ke1D));
 88:   PetscCall(Form2DElementMass(p, Me1D, Me2D));
 89:   PetscCall(Form2DElementStiffness(p, Ke1D, Me1D, Ke2D));

 91:   /* Assemble matrix */
 92:   for (i = start; i < end; i++) {
 93:     indx = 0;
 94:     for (k = 0; k < (p + 1); ++k) {
 95:       for (j = 0; j < (p + 1); ++j) idx[indx++] = p * (p * m + 1) * (i / m) + p * (i % m) + k * (p * m + 1) + j;
 96:     }
 97:     PetscCall(MatSetValues(A, num2Dnodes, idx, num2Dnodes, idx, Ke2D, ADD_VALUES));
 98:     PetscCall(MatSetValues(Mass, num2Dnodes, idx, num2Dnodes, idx, Me2D, ADD_VALUES));
 99:   }
100:   PetscCall(MatAssemblyBegin(A, MAT_FINAL_ASSEMBLY));
101:   PetscCall(MatAssemblyEnd(A, MAT_FINAL_ASSEMBLY));
102:   PetscCall(MatAssemblyBegin(Mass, MAT_FINAL_ASSEMBLY));
103:   PetscCall(MatAssemblyEnd(Mass, MAT_FINAL_ASSEMBLY));

105:   PetscCall(PetscFree(Me1D));
106:   PetscCall(PetscFree(Ke1D));
107:   PetscCall(PetscFree(Me2D));
108:   PetscCall(PetscFree(Ke2D));

110:   /* Create right-hand side and solution vectors */
111:   PetscCall(VecCreate(PETSC_COMM_WORLD, &u));
112:   PetscCall(VecSetSizes(u, PETSC_DECIDE, N));
113:   PetscCall(VecSetFromOptions(u));
114:   PetscCall(PetscObjectSetName((PetscObject)u, "Approx. Solution"));
115:   PetscCall(VecDuplicate(u, &b));
116:   PetscCall(PetscObjectSetName((PetscObject)b, "Right hand side"));
117:   PetscCall(VecDuplicate(u, &q));
118:   PetscCall(PetscObjectSetName((PetscObject)q, "Right hand side 2"));
119:   PetscCall(VecDuplicate(b, &ustar));

121:   /* Assemble nodal right-hand side and soln vector  */
122:   for (i = start; i < end; i++) {
123:     x    = h * (i % m);
124:     y    = h * (i / m);
125:     indx = 0;
126:     for (k = 0; k < (p + 1); ++k) {
127:       for (j = 0; j < (p + 1); ++j) idx[indx++] = p * (p * m + 1) * (i / m) + p * (i % m) + k * (p * m + 1) + j;
128:     }
129:     PetscCall(FormNodalRhs(p, x, y, h, gllNode, r));
130:     PetscCall(FormNodalSoln(p, x, y, h, gllNode, ue));
131:     PetscCall(VecSetValues(q, num2Dnodes, idx, r, INSERT_VALUES));
132:     PetscCall(VecSetValues(ustar, num2Dnodes, idx, ue, INSERT_VALUES));
133:   }
134:   PetscCall(VecAssemblyBegin(q));
135:   PetscCall(VecAssemblyEnd(q));
136:   PetscCall(VecAssemblyBegin(ustar));
137:   PetscCall(VecAssemblyEnd(ustar));

139:   PetscCall(PetscFree(idx));
140:   PetscCall(PetscFree(r));
141:   PetscCall(PetscFree(ue));

143:   /* Get FE right-hand side vector */
144:   PetscCall(MatMult(Mass, q, b));

146:   /* Modify matrix and right-hand side for Dirichlet boundary conditions */
147:   PetscCall(PetscMalloc1(4 * p * m, &rows));
148:   PetscCall(PetscMalloc1(4 * p * m, &rowsx));
149:   PetscCall(PetscMalloc1(4 * p * m, &rowsy));
150:   for (i = 0; i < p * m + 1; i++) {
151:     rows[i]                  = i; /* bottom */
152:     rowsx[i]                 = (i / p) * h + gllNode[i % p] * h;
153:     rowsy[i]                 = 0.0;
154:     rows[3 * p * m - 1 + i]  = (p * m) * (p * m + 1) + i; /* top */
155:     rowsx[3 * p * m - 1 + i] = (i / p) * h + gllNode[i % p] * h;
156:     rowsy[3 * p * m - 1 + i] = 1.0;
157:   }
158:   count = p * m + 1; /* left side */
159:   indx  = 1;
160:   for (i = p * m + 1; i < (p * m) * (p * m + 1); i += (p * m + 1)) {
161:     rows[count]    = i;
162:     rowsx[count]   = 0.0;
163:     rowsy[count++] = (indx / p) * h + gllNode[indx % p] * h;
164:     indx++;
165:   }
166:   count = 2 * p * m; /* right side */
167:   indx  = 1;
168:   for (i = 2 * p * m + 1; i < (p * m) * (p * m + 1); i += (p * m + 1)) {
169:     rows[count]    = i;
170:     rowsx[count]   = 1.0;
171:     rowsy[count++] = (indx / p) * h + gllNode[indx % p] * h;
172:     indx++;
173:   }
174:   for (i = 0; i < 4 * p * m; i++) {
175:     x   = rowsx[i];
176:     y   = rowsy[i];
177:     val = ubdy(x, y);
178:     PetscCall(VecSetValues(b, 1, &rows[i], &val, INSERT_VALUES));
179:     PetscCall(VecSetValues(u, 1, &rows[i], &val, INSERT_VALUES));
180:   }
181:   PetscCall(MatZeroRows(A, 4 * p * m, rows, 1.0, 0, 0));
182:   PetscCall(PetscFree(rows));
183:   PetscCall(PetscFree(rowsx));
184:   PetscCall(PetscFree(rowsy));

186:   PetscCall(VecAssemblyBegin(u));
187:   PetscCall(VecAssemblyEnd(u));
188:   PetscCall(VecAssemblyBegin(b));
189:   PetscCall(VecAssemblyEnd(b));

191:   /* Solve linear system */
192:   PetscCall(KSPCreate(PETSC_COMM_WORLD, &ksp));
193:   PetscCall(KSPSetOperators(ksp, A, A));
194:   PetscCall(KSPSetInitialGuessNonzero(ksp, PETSC_TRUE));
195:   PetscCall(KSPSetFromOptions(ksp));
196:   PetscCall(KSPSolve(ksp, b, u));

198:   /* Check error */
199:   PetscCall(VecAXPY(u, -1.0, ustar));
200:   PetscCall(VecNorm(u, NORM_2, &norm));
201:   PetscCall(KSPGetIterationNumber(ksp, &its));
202:   PetscCall(PetscPrintf(PETSC_COMM_WORLD, "Norm of error %g Iterations %" PetscInt_FMT "\n", (double)(norm * h), its));

204:   PetscCall(PetscFree(gllNode));
205:   PetscCall(PetscFree(gllWgts));

207:   PetscCall(KSPDestroy(&ksp));
208:   PetscCall(VecDestroy(&u));
209:   PetscCall(VecDestroy(&b));
210:   PetscCall(VecDestroy(&q));
211:   PetscCall(VecDestroy(&ustar));
212:   PetscCall(MatDestroy(&A));
213:   PetscCall(MatDestroy(&Mass));

215:   PetscCall(PetscFinalize());
216:   return 0;
217: }

219: /* --------------------------------------------------------------------- */

221: /* 1d element stiffness mass matrix  */
222: static PetscErrorCode Form1DElementMass(PetscReal H, PetscInt P, PetscReal *gqn, PetscReal *gqw, PetscScalar *Me1D)
223: {
224:   PetscInt i, j, k;
225:   PetscInt indx;

227:   PetscFunctionBeginUser;
228:   for (j = 0; j < (P + 1); ++j) {
229:     for (i = 0; i < (P + 1); ++i) {
230:       indx       = j * (P + 1) + i;
231:       Me1D[indx] = 0.0;
232:       for (k = 0; k < (P + 1); ++k) Me1D[indx] += H * gqw[k] * polyBasisFunc(P, i, gqn, gqn[k]) * polyBasisFunc(P, j, gqn, gqn[k]);
233:     }
234:   }
235:   PetscFunctionReturn(PETSC_SUCCESS);
236: }

238: /* --------------------------------------------------------------------- */

240: /* 1d element stiffness matrix for derivative */
241: static PetscErrorCode Form1DElementStiffness(PetscReal H, PetscInt P, PetscReal *gqn, PetscReal *gqw, PetscScalar *Ke1D)
242: {
243:   PetscInt i, j, k;
244:   PetscInt indx;

246:   PetscFunctionBeginUser;
247:   for (j = 0; j < (P + 1); ++j) {
248:     for (i = 0; i < (P + 1); ++i) {
249:       indx       = j * (P + 1) + i;
250:       Ke1D[indx] = 0.0;
251:       for (k = 0; k < (P + 1); ++k) Ke1D[indx] += (1. / H) * gqw[k] * derivPolyBasisFunc(P, i, gqn, gqn[k]) * derivPolyBasisFunc(P, j, gqn, gqn[k]);
252:     }
253:   }
254:   PetscFunctionReturn(PETSC_SUCCESS);
255: }

257: /* --------------------------------------------------------------------- */

259: /* element mass matrix */
260: static PetscErrorCode Form2DElementMass(PetscInt P, PetscScalar *Me1D, PetscScalar *Me2D)
261: {
262:   PetscInt i1, j1, i2, j2;
263:   PetscInt indx1, indx2, indx3;

265:   PetscFunctionBeginUser;
266:   for (j2 = 0; j2 < (P + 1); ++j2) {
267:     for (i2 = 0; i2 < (P + 1); ++i2) {
268:       for (j1 = 0; j1 < (P + 1); ++j1) {
269:         for (i1 = 0; i1 < (P + 1); ++i1) {
270:           indx1       = j1 * (P + 1) + i1;
271:           indx2       = j2 * (P + 1) + i2;
272:           indx3       = (j2 * (P + 1) + j1) * (P + 1) * (P + 1) + (i2 * (P + 1) + i1);
273:           Me2D[indx3] = Me1D[indx1] * Me1D[indx2];
274:         }
275:       }
276:     }
277:   }
278:   PetscFunctionReturn(PETSC_SUCCESS);
279: }

281: /* --------------------------------------------------------------------- */

283: /* element stiffness for Laplacian */
284: static PetscErrorCode Form2DElementStiffness(PetscInt P, PetscScalar *Ke1D, PetscScalar *Me1D, PetscScalar *Ke2D)
285: {
286:   PetscInt i1, j1, i2, j2;
287:   PetscInt indx1, indx2, indx3;

289:   PetscFunctionBeginUser;
290:   for (j2 = 0; j2 < (P + 1); ++j2) {
291:     for (i2 = 0; i2 < (P + 1); ++i2) {
292:       for (j1 = 0; j1 < (P + 1); ++j1) {
293:         for (i1 = 0; i1 < (P + 1); ++i1) {
294:           indx1       = j1 * (P + 1) + i1;
295:           indx2       = j2 * (P + 1) + i2;
296:           indx3       = (j2 * (P + 1) + j1) * (P + 1) * (P + 1) + (i2 * (P + 1) + i1);
297:           Ke2D[indx3] = Ke1D[indx1] * Me1D[indx2] + Me1D[indx1] * Ke1D[indx2];
298:         }
299:       }
300:     }
301:   }
302:   PetscFunctionReturn(PETSC_SUCCESS);
303: }

305: /* --------------------------------------------------------------------- */

307: static PetscErrorCode FormNodalRhs(PetscInt P, PetscReal x, PetscReal y, PetscReal H, PetscReal *nds, PetscScalar *r)
308: {
309:   PetscInt i, j, indx;

311:   PetscFunctionBeginUser;
312:   indx = 0;
313:   for (j = 0; j < (P + 1); ++j) {
314:     for (i = 0; i < (P + 1); ++i) {
315:       r[indx] = src(x + H * nds[i], y + H * nds[j]);
316:       indx++;
317:     }
318:   }
319:   PetscFunctionReturn(PETSC_SUCCESS);
320: }

322: /* --------------------------------------------------------------------- */

324: static PetscErrorCode FormNodalSoln(PetscInt P, PetscReal x, PetscReal y, PetscReal H, PetscReal *nds, PetscScalar *u)
325: {
326:   PetscInt i, j, indx;

328:   PetscFunctionBeginUser;
329:   indx = 0;
330:   for (j = 0; j < (P + 1); ++j) {
331:     for (i = 0; i < (P + 1); ++i) {
332:       u[indx] = ubdy(x + H * nds[i], y + H * nds[j]);
333:       indx++;
334:     }
335:   }
336:   PetscFunctionReturn(PETSC_SUCCESS);
337: }

339: /* --------------------------------------------------------------------- */

341: static PetscReal polyBasisFunc(PetscInt order, PetscInt basis, PetscReal *xLocVal, PetscReal xval)
342: {
343:   PetscReal denominator = 1.;
344:   PetscReal numerator   = 1.;
345:   PetscInt  i           = 0;

347:   for (i = 0; i < (order + 1); i++) {
348:     if (i != basis) {
349:       numerator *= (xval - xLocVal[i]);
350:       denominator *= (xLocVal[basis] - xLocVal[i]);
351:     }
352:   }
353:   return numerator / denominator;
354: }

356: /* --------------------------------------------------------------------- */

358: static PetscReal derivPolyBasisFunc(PetscInt order, PetscInt basis, PetscReal *xLocVal, PetscReal xval)
359: {
360:   PetscReal denominator;
361:   PetscReal numerator;
362:   PetscReal numtmp;
363:   PetscInt  i = 0, j = 0;

365:   denominator = 1.;
366:   for (i = 0; i < (order + 1); i++) {
367:     if (i != basis) denominator *= (xLocVal[basis] - xLocVal[i]);
368:   }
369:   numerator = 0.;
370:   for (j = 0; j < (order + 1); ++j) {
371:     if (j != basis) {
372:       numtmp = 1.;
373:       for (i = 0; i < (order + 1); ++i) {
374:         if (i != basis && j != i) numtmp *= (xval - xLocVal[i]);
375:       }
376:       numerator += numtmp;
377:     }
378:   }

380:   return numerator / denominator;
381: }

383: /* --------------------------------------------------------------------- */

385: static PetscReal ubdy(PetscReal x, PetscReal y)
386: {
387:   return x * x * y * y;
388: }

390: static PetscReal src(PetscReal x, PetscReal y)
391: {
392:   return -2. * y * y - 2. * x * x;
393: }
394: /* --------------------------------------------------------------------- */

396: static void leggaulob(PetscReal x1, PetscReal x2, PetscReal x[], PetscReal w[], PetscInt n)
397: /*******************************************************************************
398: Given the lower and upper limits of integration x1 and x2, and given n, this
399: routine returns arrays x[0..n-1] and w[0..n-1] of length n, containing the abscissas
400: and weights of the Gauss-Lobatto-Legendre n-point quadrature formula.
401: *******************************************************************************/
402: {
403:   PetscInt  m;
404:   PetscReal z1, z, xm, xl, q, qp, Ln, scale;
405:   if (n == 1) {
406:     x[0] = x1; /* Scale the root to the desired interval, */
407:     x[1] = x2; /* and put in its symmetric counterpart.   */
408:     w[0] = 1.; /* Compute the weight */
409:     w[1] = 1.; /* and its symmetric counterpart. */
410:   } else {
411:     x[0] = x1;                 /* Scale the root to the desired interval, */
412:     x[n] = x2;                 /* and put in its symmetric counterpart.   */
413:     w[0] = 2. / (n * (n + 1)); /* Compute the weight */
414:     w[n] = 2. / (n * (n + 1)); /* and its symmetric counterpart. */
415:     m    = (n + 1) / 2;        /* The roots are symmetric, so we only find half of them. */
416:     xm   = 0.5 * (x2 + x1);
417:     xl   = 0.5 * (x2 - x1);
418:     for (PetscInt j = 1; j <= (m - 1); j++) { /* Loop over the desired roots. */
419:       z = -1.0 * PetscCosReal((PETSC_PI * (j + 0.25) / (n)) - (3.0 / (8.0 * n * PETSC_PI)) * (1.0 / (j + 0.25)));
420:       /* Starting with the above approximation to the ith root, we enter */
421:       /* the main loop of refinement by Newton's method.                 */
422:       do {
423:         qAndLEvaluation(n, z, &q, &qp, &Ln);
424:         z1 = z;
425:         z  = z1 - q / qp; /* Newton's method. */
426:       } while (PetscAbsReal(z - z1) > 3.0e-11);
427:       qAndLEvaluation(n, z, &q, &qp, &Ln);
428:       x[j]     = xm + xl * z;                   /* Scale the root to the desired interval, */
429:       x[n - j] = xm - xl * z;                   /* and put in its symmetric counterpart.   */
430:       w[j]     = 2.0 / (n * (n + 1) * Ln * Ln); /* Compute the weight */
431:       w[n - j] = w[j];                          /* and its symmetric counterpart. */
432:     }
433:   }
434:   if (n % 2 == 0) {
435:     qAndLEvaluation(n, 0.0, &q, &qp, &Ln);
436:     x[n / 2] = (x2 - x1) / 2.0;
437:     w[n / 2] = 2.0 / (n * (n + 1) * Ln * Ln);
438:   }
439:   /* scale the weights according to mapping from [-1,1] to [0,1] */
440:   scale = (x2 - x1) / 2.0;
441:   for (PetscInt j = 0; j <= n; ++j) w[j] = w[j] * scale;
442: }

444: /******************************************************************************/
445: static void qAndLEvaluation(PetscInt n, PetscReal x, PetscReal *q, PetscReal *qp, PetscReal *Ln)
446: /*******************************************************************************
447: Compute the polynomial qn(x) = L_{N+1}(x) - L_{n-1}(x) and its derivative in
448: addition to L_N(x) as these are needed for the GLL points.  See the book titled
449: "Implementing Spectral Methods for Partial Differential Equations: Algorithms
450: for Scientists and Engineers" by David A. Kopriva.
451: *******************************************************************************/
452: {
453:   PetscInt k;

455:   PetscReal Lnp;
456:   PetscReal Lnp1, Lnp1p;
457:   PetscReal Lnm1, Lnm1p;
458:   PetscReal Lnm2, Lnm2p;

460:   Lnm1  = 1.0;
461:   *Ln   = x;
462:   Lnm1p = 0.0;
463:   Lnp   = 1.0;

465:   for (k = 2; k <= n; ++k) {
466:     Lnm2  = Lnm1;
467:     Lnm1  = *Ln;
468:     Lnm2p = Lnm1p;
469:     Lnm1p = Lnp;
470:     *Ln   = (2. * k - 1.) / (1.0 * k) * x * Lnm1 - (k - 1.) / (1.0 * k) * Lnm2;
471:     Lnp   = Lnm2p + (2.0 * k - 1) * Lnm1;
472:   }
473:   k     = n + 1;
474:   Lnp1  = (2. * k - 1.) / (1.0 * k) * x * (*Ln) - (k - 1.) / (1.0 * k) * Lnm1;
475:   Lnp1p = Lnm1p + (2.0 * k - 1) * (*Ln);
476:   *q    = Lnp1 - Lnm1;
477:   *qp   = Lnp1p - Lnm1p;
478: }

480: /*TEST

482:    test:
483:       nsize: 2
484:       args: -ksp_monitor

486: TEST*/