Actual source code: vinv.c
1: /*
2: Some useful vector utility functions.
3: */
4: #include <../src/vec/vec/impls/mpi/pvecimpl.h>
6: /*@
7: VecStrideSet - Sets a subvector of a vector defined
8: by a starting point and a stride with a given value
10: Logically Collective
12: Input Parameters:
13: + v - the vector
14: . start - starting point of the subvector (defined by a stride)
15: - s - value to set for each entry in that subvector
17: Level: advanced
19: Notes:
20: One must call `VecSetBlockSize()` before this routine to set the stride
21: information, or use a vector created from a multicomponent `DMDA`.
23: This will only work if the desire subvector is a stride subvector
25: .seealso: `Vec`, `VecNorm()`, `VecStrideGather()`, `VecStrideScatter()`, `VecStrideMin()`, `VecStrideMax()`, `VecStrideScale()`
26: @*/
27: PetscErrorCode VecStrideSet(Vec v, PetscInt start, PetscScalar s)
28: {
29: PetscInt i, n, bs;
30: PetscScalar *x;
32: PetscFunctionBegin;
35: PetscCall(VecGetLocalSize(v, &n));
36: PetscCall(VecGetBlockSize(v, &bs));
37: PetscCheck(start >= 0, PETSC_COMM_SELF, PETSC_ERR_ARG_OUTOFRANGE, "Negative start %" PetscInt_FMT, start);
38: PetscCheck(start < bs, PETSC_COMM_SELF, PETSC_ERR_ARG_OUTOFRANGE, "Start of stride subvector (%" PetscInt_FMT ") is too large for stride. Have you set the vector blocksize (%" PetscInt_FMT ") correctly with VecSetBlockSize()?", start, bs);
39: PetscCall(VecGetArray(v, &x));
40: for (i = start; i < n; i += bs) x[i] = s;
41: PetscCall(VecRestoreArray(v, &x));
42: PetscFunctionReturn(PETSC_SUCCESS);
43: }
45: /*@
46: VecStrideScale - Scales a subvector of a vector defined
47: by a starting point and a stride.
49: Logically Collective
51: Input Parameters:
52: + v - the vector
53: . start - starting point of the subvector (defined by a stride)
54: - scale - value to multiply each subvector entry by
56: Level: advanced
58: Notes:
59: One must call `VecSetBlockSize()` before this routine to set the stride
60: information, or use a vector created from a multicomponent `DMDA`.
62: This will only work if the desire subvector is a stride subvector
64: .seealso: `Vec`, `VecNorm()`, `VecStrideGather()`, `VecStrideScatter()`, `VecStrideMin()`, `VecStrideMax()`
65: @*/
66: PetscErrorCode VecStrideScale(Vec v, PetscInt start, PetscScalar scale)
67: {
68: PetscInt i, n, bs;
69: PetscScalar *x;
71: PetscFunctionBegin;
75: PetscCall(VecGetLocalSize(v, &n));
76: PetscCall(VecGetBlockSize(v, &bs));
77: PetscCheck(start >= 0, PETSC_COMM_SELF, PETSC_ERR_ARG_OUTOFRANGE, "Negative start %" PetscInt_FMT, start);
78: PetscCheck(start < bs, PETSC_COMM_SELF, PETSC_ERR_ARG_OUTOFRANGE, "Start of stride subvector (%" PetscInt_FMT ") is too large for stride. Have you set the vector blocksize (%" PetscInt_FMT ") correctly with VecSetBlockSize()?", start, bs);
79: PetscCall(VecGetArray(v, &x));
80: for (i = start; i < n; i += bs) x[i] *= scale;
81: PetscCall(VecRestoreArray(v, &x));
82: PetscFunctionReturn(PETSC_SUCCESS);
83: }
85: /*@
86: VecStrideNorm - Computes the norm of subvector of a vector defined
87: by a starting point and a stride.
89: Collective
91: Input Parameters:
92: + v - the vector
93: . start - starting point of the subvector (defined by a stride)
94: - ntype - type of norm, one of `NORM_1`, `NORM_2`, `NORM_INFINITY`
96: Output Parameter:
97: . nrm - the norm
99: Level: advanced
101: Notes:
102: One must call `VecSetBlockSize()` before this routine to set the stride
103: information, or use a vector created from a multicomponent `DMDA`.
105: If x is the array representing the vector x then this computes the norm
106: of the array (x[start],x[start+stride],x[start+2*stride], ....)
108: This is useful for computing, say the norm of the pressure variable when
109: the pressure is stored (interlaced) with other variables, say density etc.
111: This will only work if the desire subvector is a stride subvector
113: .seealso: `Vec`, `VecNorm()`, `VecStrideGather()`, `VecStrideScatter()`, `VecStrideMin()`, `VecStrideMax()`
114: @*/
115: PetscErrorCode VecStrideNorm(Vec v, PetscInt start, NormType ntype, PetscReal *nrm)
116: {
117: PetscInt i, n, bs;
118: const PetscScalar *x;
119: PetscReal tnorm;
121: PetscFunctionBegin;
125: PetscAssertPointer(nrm, 4);
126: PetscCall(VecGetLocalSize(v, &n));
127: PetscCall(VecGetBlockSize(v, &bs));
128: PetscCheck(start >= 0, PETSC_COMM_SELF, PETSC_ERR_ARG_OUTOFRANGE, "Negative start %" PetscInt_FMT, start);
129: PetscCheck(start < bs, PETSC_COMM_SELF, PETSC_ERR_ARG_OUTOFRANGE, "Start of stride subvector (%" PetscInt_FMT ") is too large for stride. Have you set the vector blocksize (%" PetscInt_FMT ") correctly with VecSetBlockSize()?", start, bs);
130: PetscCall(VecGetArrayRead(v, &x));
131: if (ntype == NORM_2) {
132: PetscScalar sum = 0.0;
133: for (i = start; i < n; i += bs) sum += x[i] * (PetscConj(x[i]));
134: tnorm = PetscRealPart(sum);
135: PetscCallMPI(MPIU_Allreduce(&tnorm, nrm, 1, MPIU_REAL, MPIU_SUM, PetscObjectComm((PetscObject)v)));
136: *nrm = PetscSqrtReal(*nrm);
137: } else if (ntype == NORM_1) {
138: tnorm = 0.0;
139: for (i = start; i < n; i += bs) tnorm += PetscAbsScalar(x[i]);
140: PetscCallMPI(MPIU_Allreduce(&tnorm, nrm, 1, MPIU_REAL, MPIU_SUM, PetscObjectComm((PetscObject)v)));
141: } else if (ntype == NORM_INFINITY) {
142: tnorm = 0.0;
143: for (i = start; i < n; i += bs) {
144: if (PetscAbsScalar(x[i]) > tnorm) tnorm = PetscAbsScalar(x[i]);
145: }
146: PetscCallMPI(MPIU_Allreduce(&tnorm, nrm, 1, MPIU_REAL, MPIU_MAX, PetscObjectComm((PetscObject)v)));
147: } else SETERRQ(PetscObjectComm((PetscObject)v), PETSC_ERR_ARG_UNKNOWN_TYPE, "Unknown norm type");
148: PetscCall(VecRestoreArrayRead(v, &x));
149: PetscFunctionReturn(PETSC_SUCCESS);
150: }
152: /*@
153: VecStrideMax - Computes the maximum of subvector of a vector defined
154: by a starting point and a stride and optionally its location.
156: Collective
158: Input Parameters:
159: + v - the vector
160: - start - starting point of the subvector (defined by a stride)
162: Output Parameters:
163: + idex - the location where the maximum occurred (pass `NULL` if not required)
164: - nrm - the maximum value in the subvector
166: Level: advanced
168: Notes:
169: One must call `VecSetBlockSize()` before this routine to set the stride
170: information, or use a vector created from a multicomponent `DMDA`.
172: If xa is the array representing the vector x, then this computes the max
173: of the array (xa[start],xa[start+stride],xa[start+2*stride], ....)
175: This is useful for computing, say the maximum of the pressure variable when
176: the pressure is stored (interlaced) with other variables, e.g., density, etc.
177: This will only work if the desire subvector is a stride subvector.
179: .seealso: `Vec`, `VecMax()`, `VecStrideNorm()`, `VecStrideGather()`, `VecStrideScatter()`, `VecStrideMin()`
180: @*/
181: PetscErrorCode VecStrideMax(Vec v, PetscInt start, PetscInt *idex, PetscReal *nrm)
182: {
183: PetscInt i, n, bs, id = -1;
184: const PetscScalar *x;
185: PetscReal max = PETSC_MIN_REAL;
187: PetscFunctionBegin;
190: PetscAssertPointer(nrm, 4);
191: PetscCall(VecGetLocalSize(v, &n));
192: PetscCall(VecGetBlockSize(v, &bs));
193: PetscCheck(start >= 0, PETSC_COMM_SELF, PETSC_ERR_ARG_OUTOFRANGE, "Negative start %" PetscInt_FMT, start);
194: PetscCheck(start < bs, PETSC_COMM_SELF, PETSC_ERR_ARG_WRONG, "Start of stride subvector (%" PetscInt_FMT ") is too large for stride. Have you set the vector blocksize (%" PetscInt_FMT ") correctly with VecSetBlockSize()?", start, bs);
195: PetscCall(VecGetArrayRead(v, &x));
196: for (i = start; i < n; i += bs) {
197: if (PetscRealPart(x[i]) > max) {
198: max = PetscRealPart(x[i]);
199: id = i;
200: }
201: }
202: PetscCall(VecRestoreArrayRead(v, &x));
203: #if defined(PETSC_HAVE_MPIUNI)
204: *nrm = max;
205: if (idex) *idex = id;
206: #else
207: if (!idex) {
208: PetscCallMPI(MPIU_Allreduce(&max, nrm, 1, MPIU_REAL, MPIU_MAX, PetscObjectComm((PetscObject)v)));
209: } else {
210: struct {
211: PetscReal v;
212: PetscInt i;
213: } in, out;
214: PetscInt rstart;
216: PetscCall(VecGetOwnershipRange(v, &rstart, NULL));
217: in.v = max;
218: in.i = rstart + id;
219: PetscCallMPI(MPIU_Allreduce(&in, &out, 1, MPIU_REAL_INT, MPIU_MAXLOC, PetscObjectComm((PetscObject)v)));
220: *nrm = out.v;
221: *idex = out.i;
222: }
223: #endif
224: PetscFunctionReturn(PETSC_SUCCESS);
225: }
227: /*@
228: VecStrideMin - Computes the minimum of subvector of a vector defined
229: by a starting point and a stride and optionally its location.
231: Collective
233: Input Parameters:
234: + v - the vector
235: - start - starting point of the subvector (defined by a stride)
237: Output Parameters:
238: + idex - the location where the minimum occurred. (pass `NULL` if not required)
239: - nrm - the minimum value in the subvector
241: Level: advanced
243: Notes:
244: One must call `VecSetBlockSize()` before this routine to set the stride
245: information, or use a vector created from a multicomponent `DMDA`.
247: If xa is the array representing the vector x, then this computes the min
248: of the array (xa[start],xa[start+stride],xa[start+2*stride], ....)
250: This is useful for computing, say the minimum of the pressure variable when
251: the pressure is stored (interlaced) with other variables, e.g., density, etc.
252: This will only work if the desire subvector is a stride subvector.
254: .seealso: `Vec`, `VecMin()`, `VecStrideNorm()`, `VecStrideGather()`, `VecStrideScatter()`, `VecStrideMax()`
255: @*/
256: PetscErrorCode VecStrideMin(Vec v, PetscInt start, PetscInt *idex, PetscReal *nrm)
257: {
258: PetscInt i, n, bs, id = -1;
259: const PetscScalar *x;
260: PetscReal min = PETSC_MAX_REAL;
262: PetscFunctionBegin;
265: PetscAssertPointer(nrm, 4);
266: PetscCall(VecGetLocalSize(v, &n));
267: PetscCall(VecGetBlockSize(v, &bs));
268: PetscCheck(start >= 0, PETSC_COMM_SELF, PETSC_ERR_ARG_OUTOFRANGE, "Negative start %" PetscInt_FMT, start);
269: PetscCheck(start < bs, PETSC_COMM_SELF, PETSC_ERR_ARG_WRONG, "Start of stride subvector (%" PetscInt_FMT ") is too large for stride. Have you set the vector blocksize (%" PetscInt_FMT ") correctly with VecSetBlockSize()?", start, bs);
270: PetscCall(VecGetArrayRead(v, &x));
271: for (i = start; i < n; i += bs) {
272: if (PetscRealPart(x[i]) < min) {
273: min = PetscRealPart(x[i]);
274: id = i;
275: }
276: }
277: PetscCall(VecRestoreArrayRead(v, &x));
278: #if defined(PETSC_HAVE_MPIUNI)
279: *nrm = min;
280: if (idex) *idex = id;
281: #else
282: if (!idex) {
283: PetscCallMPI(MPIU_Allreduce(&min, nrm, 1, MPIU_REAL, MPIU_MIN, PetscObjectComm((PetscObject)v)));
284: } else {
285: struct {
286: PetscReal v;
287: PetscInt i;
288: } in, out;
289: PetscInt rstart;
291: PetscCall(VecGetOwnershipRange(v, &rstart, NULL));
292: in.v = min;
293: in.i = rstart + id;
294: PetscCallMPI(MPIU_Allreduce(&in, &out, 1, MPIU_REAL_INT, MPIU_MINLOC, PetscObjectComm((PetscObject)v)));
295: *nrm = out.v;
296: *idex = out.i;
297: }
298: #endif
299: PetscFunctionReturn(PETSC_SUCCESS);
300: }
302: /*@
303: VecStrideSum - Computes the sum of subvector of a vector defined
304: by a starting point and a stride.
306: Collective
308: Input Parameters:
309: + v - the vector
310: - start - starting point of the subvector (defined by a stride)
312: Output Parameter:
313: . sum - the sum
315: Level: advanced
317: Notes:
318: One must call `VecSetBlockSize()` before this routine to set the stride
319: information, or use a vector created from a multicomponent `DMDA`.
321: If x is the array representing the vector x then this computes the sum
322: of the array (x[start],x[start+stride],x[start+2*stride], ....)
324: .seealso: `Vec`, `VecSum()`, `VecStrideGather()`, `VecStrideScatter()`, `VecStrideMin()`, `VecStrideMax()`
325: @*/
326: PetscErrorCode VecStrideSum(Vec v, PetscInt start, PetscScalar *sum)
327: {
328: PetscInt i, n, bs;
329: const PetscScalar *x;
330: PetscScalar local_sum = 0.0;
332: PetscFunctionBegin;
335: PetscAssertPointer(sum, 3);
336: PetscCall(VecGetLocalSize(v, &n));
337: PetscCall(VecGetBlockSize(v, &bs));
338: PetscCheck(start >= 0, PETSC_COMM_SELF, PETSC_ERR_ARG_OUTOFRANGE, "Negative start %" PetscInt_FMT, start);
339: PetscCheck(start < bs, PETSC_COMM_SELF, PETSC_ERR_ARG_OUTOFRANGE, "Start of stride subvector (%" PetscInt_FMT ") is too large for stride. Have you set the vector blocksize (%" PetscInt_FMT ") correctly with VecSetBlockSize()?", start, bs);
340: PetscCall(VecGetArrayRead(v, &x));
341: for (i = start; i < n; i += bs) local_sum += x[i];
342: PetscCallMPI(MPIU_Allreduce(&local_sum, sum, 1, MPIU_SCALAR, MPIU_SUM, PetscObjectComm((PetscObject)v)));
343: PetscCall(VecRestoreArrayRead(v, &x));
344: PetscFunctionReturn(PETSC_SUCCESS);
345: }
347: /*@
348: VecStrideScaleAll - Scales the subvectors of a vector defined
349: by a starting point and a stride.
351: Logically Collective
353: Input Parameters:
354: + v - the vector
355: - scales - values to multiply each subvector entry by
357: Level: advanced
359: Notes:
360: One must call `VecSetBlockSize()` before this routine to set the stride
361: information, or use a vector created from a multicomponent `DMDA`.
363: The dimension of scales must be the same as the vector block size
365: .seealso: `Vec`, `VecNorm()`, `VecStrideScale()`, `VecScale()`, `VecStrideGather()`, `VecStrideScatter()`, `VecStrideMin()`, `VecStrideMax()`
366: @*/
367: PetscErrorCode VecStrideScaleAll(Vec v, const PetscScalar *scales)
368: {
369: PetscInt i, j, n, bs;
370: PetscScalar *x;
372: PetscFunctionBegin;
374: PetscAssertPointer(scales, 2);
375: PetscCall(VecGetLocalSize(v, &n));
376: PetscCall(VecGetBlockSize(v, &bs));
377: PetscCall(VecGetArray(v, &x));
378: /* need to provide optimized code for each bs */
379: for (i = 0; i < n; i += bs) {
380: for (j = 0; j < bs; j++) x[i + j] *= scales[j];
381: }
382: PetscCall(VecRestoreArray(v, &x));
383: PetscFunctionReturn(PETSC_SUCCESS);
384: }
386: /*@
387: VecStrideNormAll - Computes the norms of subvectors of a vector defined
388: by a starting point and a stride.
390: Collective
392: Input Parameters:
393: + v - the vector
394: - ntype - type of norm, one of `NORM_1`, `NORM_2`, `NORM_INFINITY`
396: Output Parameter:
397: . nrm - the norms
399: Level: advanced
401: Notes:
402: One must call `VecSetBlockSize()` before this routine to set the stride
403: information, or use a vector created from a multicomponent `DMDA`.
405: If x is the array representing the vector x then this computes the norm
406: of the array (x[start],x[start+stride],x[start+2*stride], ....) for each start < stride
408: The dimension of nrm must be the same as the vector block size
410: This will only work if the desire subvector is a stride subvector
412: .seealso: `Vec`, `VecNorm()`, `VecStrideGather()`, `VecStrideScatter()`, `VecStrideMin()`, `VecStrideMax()`
413: @*/
414: PetscErrorCode VecStrideNormAll(Vec v, NormType ntype, PetscReal nrm[])
415: {
416: PetscInt i, j, n, bs;
417: const PetscScalar *x;
418: PetscReal tnorm[128];
419: MPI_Comm comm;
420: PetscMPIInt ibs;
422: PetscFunctionBegin;
425: PetscAssertPointer(nrm, 3);
426: PetscCall(VecGetLocalSize(v, &n));
427: PetscCall(VecGetArrayRead(v, &x));
428: PetscCall(PetscObjectGetComm((PetscObject)v, &comm));
430: PetscCall(VecGetBlockSize(v, &bs));
431: PetscCheck(bs <= 128, comm, PETSC_ERR_SUP, "Currently supports only blocksize up to 128");
432: PetscCall(PetscMPIIntCast(bs, &ibs));
433: if (ntype == NORM_2) {
434: PetscScalar sum[128];
435: for (j = 0; j < bs; j++) sum[j] = 0.0;
436: for (i = 0; i < n; i += bs) {
437: for (j = 0; j < bs; j++) sum[j] += x[i + j] * (PetscConj(x[i + j]));
438: }
439: for (j = 0; j < bs; j++) tnorm[j] = PetscRealPart(sum[j]);
441: PetscCallMPI(MPIU_Allreduce(tnorm, nrm, ibs, MPIU_REAL, MPIU_SUM, comm));
442: for (j = 0; j < bs; j++) nrm[j] = PetscSqrtReal(nrm[j]);
443: } else if (ntype == NORM_1) {
444: for (j = 0; j < bs; j++) tnorm[j] = 0.0;
446: for (i = 0; i < n; i += bs) {
447: for (j = 0; j < bs; j++) tnorm[j] += PetscAbsScalar(x[i + j]);
448: }
450: PetscCallMPI(MPIU_Allreduce(tnorm, nrm, ibs, MPIU_REAL, MPIU_SUM, comm));
451: } else if (ntype == NORM_INFINITY) {
452: PetscReal tmp;
453: for (j = 0; j < bs; j++) tnorm[j] = 0.0;
455: for (i = 0; i < n; i += bs) {
456: for (j = 0; j < bs; j++) {
457: if ((tmp = PetscAbsScalar(x[i + j])) > tnorm[j]) tnorm[j] = tmp;
458: /* check special case of tmp == NaN */
459: if (tmp != tmp) {
460: tnorm[j] = tmp;
461: break;
462: }
463: }
464: }
465: PetscCallMPI(MPIU_Allreduce(tnorm, nrm, ibs, MPIU_REAL, MPIU_MAX, comm));
466: } else SETERRQ(PetscObjectComm((PetscObject)v), PETSC_ERR_ARG_UNKNOWN_TYPE, "Unknown norm type");
467: PetscCall(VecRestoreArrayRead(v, &x));
468: PetscFunctionReturn(PETSC_SUCCESS);
469: }
471: /*@
472: VecStrideMaxAll - Computes the maximums of subvectors of a vector defined
473: by a starting point and a stride and optionally its location.
475: Collective
477: Input Parameter:
478: . v - the vector
480: Output Parameters:
481: + idex - the location where the maximum occurred (not supported, pass `NULL`,
482: if you need this, send mail to petsc-maint@mcs.anl.gov to request it)
483: - nrm - the maximum values of each subvector
485: Level: advanced
487: Notes:
488: One must call `VecSetBlockSize()` before this routine to set the stride
489: information, or use a vector created from a multicomponent `DMDA`.
491: The dimension of nrm must be the same as the vector block size
493: .seealso: `Vec`, `VecMax()`, `VecStrideNorm()`, `VecStrideGather()`, `VecStrideScatter()`, `VecStrideMin()`
494: @*/
495: PetscErrorCode VecStrideMaxAll(Vec v, PetscInt idex[], PetscReal nrm[])
496: {
497: PetscInt i, j, n, bs;
498: const PetscScalar *x;
499: PetscReal max[128], tmp;
500: MPI_Comm comm;
501: PetscMPIInt ibs;
503: PetscFunctionBegin;
505: PetscAssertPointer(nrm, 3);
506: PetscCheck(!idex, PETSC_COMM_SELF, PETSC_ERR_SUP, "No support yet for returning index; send mail to petsc-maint@mcs.anl.gov asking for it");
507: PetscCall(VecGetLocalSize(v, &n));
508: PetscCall(VecGetArrayRead(v, &x));
509: PetscCall(PetscObjectGetComm((PetscObject)v, &comm));
511: PetscCall(VecGetBlockSize(v, &bs));
512: PetscCheck(bs <= 128, comm, PETSC_ERR_SUP, "Currently supports only blocksize up to 128");
513: PetscCall(PetscMPIIntCast(bs, &ibs));
515: if (!n) {
516: for (j = 0; j < bs; j++) max[j] = PETSC_MIN_REAL;
517: } else {
518: for (j = 0; j < bs; j++) max[j] = PetscRealPart(x[j]);
520: for (i = bs; i < n; i += bs) {
521: for (j = 0; j < bs; j++) {
522: if ((tmp = PetscRealPart(x[i + j])) > max[j]) max[j] = tmp;
523: }
524: }
525: }
526: PetscCallMPI(MPIU_Allreduce(max, nrm, ibs, MPIU_REAL, MPIU_MAX, comm));
528: PetscCall(VecRestoreArrayRead(v, &x));
529: PetscFunctionReturn(PETSC_SUCCESS);
530: }
532: /*@
533: VecStrideMinAll - Computes the minimum of subvector of a vector defined
534: by a starting point and a stride and optionally its location.
536: Collective
538: Input Parameter:
539: . v - the vector
541: Output Parameters:
542: + idex - the location where the minimum occurred (not supported, pass `NULL`,
543: if you need this, send mail to petsc-maint@mcs.anl.gov to request it)
544: - nrm - the minimums of each subvector
546: Level: advanced
548: Notes:
549: One must call `VecSetBlockSize()` before this routine to set the stride
550: information, or use a vector created from a multicomponent `DMDA`.
552: The dimension of `nrm` must be the same as the vector block size
554: .seealso: `Vec`, `VecMin()`, `VecStrideNorm()`, `VecStrideGather()`, `VecStrideScatter()`, `VecStrideMax()`
555: @*/
556: PetscErrorCode VecStrideMinAll(Vec v, PetscInt idex[], PetscReal nrm[])
557: {
558: PetscInt i, n, bs, j;
559: const PetscScalar *x;
560: PetscReal min[128], tmp;
561: MPI_Comm comm;
562: PetscMPIInt ibs;
564: PetscFunctionBegin;
566: PetscAssertPointer(nrm, 3);
567: PetscCheck(!idex, PETSC_COMM_SELF, PETSC_ERR_SUP, "No support yet for returning index; send mail to petsc-maint@mcs.anl.gov asking for it");
568: PetscCall(VecGetLocalSize(v, &n));
569: PetscCall(VecGetArrayRead(v, &x));
570: PetscCall(PetscObjectGetComm((PetscObject)v, &comm));
572: PetscCall(VecGetBlockSize(v, &bs));
573: PetscCheck(bs <= 128, comm, PETSC_ERR_SUP, "Currently supports only blocksize up to 128");
574: PetscCall(PetscMPIIntCast(bs, &ibs));
576: if (!n) {
577: for (j = 0; j < bs; j++) min[j] = PETSC_MAX_REAL;
578: } else {
579: for (j = 0; j < bs; j++) min[j] = PetscRealPart(x[j]);
581: for (i = bs; i < n; i += bs) {
582: for (j = 0; j < bs; j++) {
583: if ((tmp = PetscRealPart(x[i + j])) < min[j]) min[j] = tmp;
584: }
585: }
586: }
587: PetscCallMPI(MPIU_Allreduce(min, nrm, ibs, MPIU_REAL, MPIU_MIN, comm));
589: PetscCall(VecRestoreArrayRead(v, &x));
590: PetscFunctionReturn(PETSC_SUCCESS);
591: }
593: /*@
594: VecStrideSumAll - Computes the sums of subvectors of a vector defined by a stride.
596: Collective
598: Input Parameter:
599: . v - the vector
601: Output Parameter:
602: . sums - the sums
604: Level: advanced
606: Notes:
607: One must call `VecSetBlockSize()` before this routine to set the stride
608: information, or use a vector created from a multicomponent `DMDA`.
610: If x is the array representing the vector x then this computes the sum
611: of the array (x[start],x[start+stride],x[start+2*stride], ....) for each start < stride
613: .seealso: `Vec`, `VecSum()`, `VecStrideGather()`, `VecStrideScatter()`, `VecStrideMin()`, `VecStrideMax()`
614: @*/
615: PetscErrorCode VecStrideSumAll(Vec v, PetscScalar sums[])
616: {
617: PetscInt i, j, n, bs;
618: const PetscScalar *x;
619: PetscScalar local_sums[128];
620: MPI_Comm comm;
621: PetscMPIInt ibs;
623: PetscFunctionBegin;
625: PetscAssertPointer(sums, 2);
626: PetscCall(VecGetLocalSize(v, &n));
627: PetscCall(VecGetArrayRead(v, &x));
628: PetscCall(PetscObjectGetComm((PetscObject)v, &comm));
630: PetscCall(VecGetBlockSize(v, &bs));
631: PetscCheck(bs <= 128, comm, PETSC_ERR_SUP, "Currently supports only blocksize up to 128");
632: PetscCall(PetscMPIIntCast(bs, &ibs));
634: for (j = 0; j < bs; j++) local_sums[j] = 0.0;
635: for (i = 0; i < n; i += bs) {
636: for (j = 0; j < bs; j++) local_sums[j] += x[i + j];
637: }
638: PetscCallMPI(MPIU_Allreduce(local_sums, sums, ibs, MPIU_SCALAR, MPIU_SUM, comm));
640: PetscCall(VecRestoreArrayRead(v, &x));
641: PetscFunctionReturn(PETSC_SUCCESS);
642: }
644: /*@
645: VecStrideGatherAll - Gathers all the single components from a multi-component vector into
646: separate vectors.
648: Collective
650: Input Parameters:
651: + v - the vector
652: - addv - one of `ADD_VALUES`, `INSERT_VALUES`, `MAX_VALUES`
654: Output Parameter:
655: . s - the location where the subvectors are stored
657: Level: advanced
659: Notes:
660: One must call `VecSetBlockSize()` before this routine to set the stride
661: information, or use a vector created from a multicomponent `DMDA`.
663: If x is the array representing the vector x then this gathers
664: the arrays (x[start],x[start+stride],x[start+2*stride], ....)
665: for start=0,1,2,...bs-1
667: The parallel layout of the vector and the subvector must be the same;
668: i.e., nlocal of v = stride*(nlocal of s)
670: Not optimized; could be easily
672: .seealso: `Vec`, `VecStrideNorm()`, `VecStrideScatter()`, `VecStrideMin()`, `VecStrideMax()`, `VecStrideGather()`,
673: `VecStrideScatterAll()`
674: @*/
675: PetscErrorCode VecStrideGatherAll(Vec v, Vec s[], InsertMode addv)
676: {
677: PetscInt i, n, n2, bs, j, k, *bss = NULL, nv, jj, nvc;
678: PetscScalar **y;
679: const PetscScalar *x;
681: PetscFunctionBegin;
683: PetscAssertPointer(s, 2);
685: PetscCall(VecGetLocalSize(v, &n));
686: PetscCall(VecGetLocalSize(s[0], &n2));
687: PetscCall(VecGetArrayRead(v, &x));
688: PetscCall(VecGetBlockSize(v, &bs));
689: PetscCheck(bs > 0, PETSC_COMM_SELF, PETSC_ERR_ARG_WRONGSTATE, "Input vector does not have a valid blocksize set");
691: PetscCall(PetscMalloc2(bs, &y, bs, &bss));
692: nv = 0;
693: nvc = 0;
694: for (i = 0; i < bs; i++) {
695: PetscCall(VecGetBlockSize(s[i], &bss[i]));
696: if (bss[i] < 1) bss[i] = 1; /* if user never set it then assume 1 Re: [PETSC #8241] VecStrideGatherAll */
697: PetscCall(VecGetArray(s[i], &y[i]));
698: nvc += bss[i];
699: nv++;
700: PetscCheck(nvc <= bs, PETSC_COMM_SELF, PETSC_ERR_ARG_INCOMP, "Number of subvectors in subvectors > number of vectors in main vector");
701: if (nvc == bs) break;
702: }
704: n = n / bs;
706: jj = 0;
707: if (addv == INSERT_VALUES) {
708: for (j = 0; j < nv; j++) {
709: for (k = 0; k < bss[j]; k++) {
710: for (i = 0; i < n; i++) y[j][i * bss[j] + k] = x[bs * i + jj + k];
711: }
712: jj += bss[j];
713: }
714: } else if (addv == ADD_VALUES) {
715: for (j = 0; j < nv; j++) {
716: for (k = 0; k < bss[j]; k++) {
717: for (i = 0; i < n; i++) y[j][i * bss[j] + k] += x[bs * i + jj + k];
718: }
719: jj += bss[j];
720: }
721: #if !defined(PETSC_USE_COMPLEX)
722: } else if (addv == MAX_VALUES) {
723: for (j = 0; j < nv; j++) {
724: for (k = 0; k < bss[j]; k++) {
725: for (i = 0; i < n; i++) y[j][i * bss[j] + k] = PetscMax(y[j][i * bss[j] + k], x[bs * i + jj + k]);
726: }
727: jj += bss[j];
728: }
729: #endif
730: } else SETERRQ(PetscObjectComm((PetscObject)v), PETSC_ERR_ARG_UNKNOWN_TYPE, "Unknown norm type");
732: PetscCall(VecRestoreArrayRead(v, &x));
733: for (i = 0; i < nv; i++) PetscCall(VecRestoreArray(s[i], &y[i]));
735: PetscCall(PetscFree2(y, bss));
736: PetscFunctionReturn(PETSC_SUCCESS);
737: }
739: /*@
740: VecStrideScatterAll - Scatters all the single components from separate vectors into
741: a multi-component vector.
743: Collective
745: Input Parameters:
746: + s - the location where the subvectors are stored
747: - addv - one of `ADD_VALUES`, `INSERT_VALUES`, `MAX_VALUES`
749: Output Parameter:
750: . v - the multicomponent vector
752: Level: advanced
754: Notes:
755: One must call `VecSetBlockSize()` before this routine to set the stride
756: information, or use a vector created from a multicomponent `DMDA`.
758: The parallel layout of the vector and the subvector must be the same;
759: i.e., nlocal of v = stride*(nlocal of s)
761: Not optimized; could be easily
763: .seealso: `Vec`, `VecStrideNorm()`, `VecStrideScatter()`, `VecStrideMin()`, `VecStrideMax()`, `VecStrideGather()`,
765: @*/
766: PetscErrorCode VecStrideScatterAll(Vec s[], Vec v, InsertMode addv)
767: {
768: PetscInt i, n, n2, bs, j, jj, k, *bss = NULL, nv, nvc;
769: PetscScalar *x;
770: PetscScalar const **y;
772: PetscFunctionBegin;
774: PetscAssertPointer(s, 1);
776: PetscCall(VecGetLocalSize(v, &n));
777: PetscCall(VecGetLocalSize(s[0], &n2));
778: PetscCall(VecGetArray(v, &x));
779: PetscCall(VecGetBlockSize(v, &bs));
780: PetscCheck(bs > 0, PETSC_COMM_SELF, PETSC_ERR_ARG_WRONGSTATE, "Input vector does not have a valid blocksize set");
782: PetscCall(PetscMalloc2(bs, (PetscScalar ***)&y, bs, &bss));
783: nv = 0;
784: nvc = 0;
785: for (i = 0; i < bs; i++) {
786: PetscCall(VecGetBlockSize(s[i], &bss[i]));
787: if (bss[i] < 1) bss[i] = 1; /* if user never set it then assume 1 Re: [PETSC #8241] VecStrideGatherAll */
788: PetscCall(VecGetArrayRead(s[i], &y[i]));
789: nvc += bss[i];
790: nv++;
791: PetscCheck(nvc <= bs, PETSC_COMM_SELF, PETSC_ERR_ARG_INCOMP, "Number of subvectors in subvectors > number of vectors in main vector");
792: if (nvc == bs) break;
793: }
795: n = n / bs;
797: jj = 0;
798: if (addv == INSERT_VALUES) {
799: for (j = 0; j < nv; j++) {
800: for (k = 0; k < bss[j]; k++) {
801: for (i = 0; i < n; i++) x[bs * i + jj + k] = y[j][i * bss[j] + k];
802: }
803: jj += bss[j];
804: }
805: } else if (addv == ADD_VALUES) {
806: for (j = 0; j < nv; j++) {
807: for (k = 0; k < bss[j]; k++) {
808: for (i = 0; i < n; i++) x[bs * i + jj + k] += y[j][i * bss[j] + k];
809: }
810: jj += bss[j];
811: }
812: #if !defined(PETSC_USE_COMPLEX)
813: } else if (addv == MAX_VALUES) {
814: for (j = 0; j < nv; j++) {
815: for (k = 0; k < bss[j]; k++) {
816: for (i = 0; i < n; i++) x[bs * i + jj + k] = PetscMax(x[bs * i + jj + k], y[j][i * bss[j] + k]);
817: }
818: jj += bss[j];
819: }
820: #endif
821: } else SETERRQ(PetscObjectComm((PetscObject)v), PETSC_ERR_ARG_UNKNOWN_TYPE, "Unknown norm type");
823: PetscCall(VecRestoreArray(v, &x));
824: for (i = 0; i < nv; i++) PetscCall(VecRestoreArrayRead(s[i], &y[i]));
825: PetscCall(PetscFree2(*(PetscScalar ***)&y, bss));
826: PetscFunctionReturn(PETSC_SUCCESS);
827: }
829: /*@
830: VecStrideGather - Gathers a single component from a multi-component vector into
831: another vector.
833: Collective
835: Input Parameters:
836: + v - the vector
837: . start - starting point of the subvector (defined by a stride)
838: - addv - one of `ADD_VALUES`, `INSERT_VALUES`, `MAX_VALUES`
840: Output Parameter:
841: . s - the location where the subvector is stored
843: Level: advanced
845: Notes:
846: One must call `VecSetBlockSize()` before this routine to set the stride
847: information, or use a vector created from a multicomponent `DMDA`.
849: If x is the array representing the vector x then this gathers
850: the array (x[start],x[start+stride],x[start+2*stride], ....)
852: The parallel layout of the vector and the subvector must be the same;
853: i.e., nlocal of v = stride*(nlocal of s)
855: Not optimized; could be easily
857: .seealso: `Vec`, `VecStrideNorm()`, `VecStrideScatter()`, `VecStrideMin()`, `VecStrideMax()`, `VecStrideGatherAll()`,
858: `VecStrideScatterAll()`
859: @*/
860: PetscErrorCode VecStrideGather(Vec v, PetscInt start, Vec s, InsertMode addv)
861: {
862: PetscFunctionBegin;
866: PetscCheck(start >= 0, PETSC_COMM_SELF, PETSC_ERR_ARG_OUTOFRANGE, "Negative start %" PetscInt_FMT, start);
867: PetscCheck(start < v->map->bs, PETSC_COMM_SELF, PETSC_ERR_ARG_OUTOFRANGE, "Start of stride subvector (%" PetscInt_FMT ") is too large for stride. Have you set the vector blocksize (%" PetscInt_FMT ") correctly with VecSetBlockSize()?", start,
868: v->map->bs);
869: PetscUseTypeMethod(v, stridegather, start, s, addv);
870: PetscFunctionReturn(PETSC_SUCCESS);
871: }
873: /*@
874: VecStrideScatter - Scatters a single component from a vector into a multi-component vector.
876: Collective
878: Input Parameters:
879: + s - the single-component vector
880: . start - starting point of the subvector (defined by a stride)
881: - addv - one of `ADD_VALUES`, `INSERT_VALUES`, `MAX_VALUES`
883: Output Parameter:
884: . v - the location where the subvector is scattered (the multi-component vector)
886: Level: advanced
888: Notes:
889: One must call `VecSetBlockSize()` on the multi-component vector before this
890: routine to set the stride information, or use a vector created from a multicomponent `DMDA`.
892: The parallel layout of the vector and the subvector must be the same;
893: i.e., nlocal of v = stride*(nlocal of s)
895: Not optimized; could be easily
897: .seealso: `Vec`, `VecStrideNorm()`, `VecStrideGather()`, `VecStrideMin()`, `VecStrideMax()`, `VecStrideGatherAll()`,
898: `VecStrideScatterAll()`, `VecStrideSubSetScatter()`, `VecStrideSubSetGather()`
899: @*/
900: PetscErrorCode VecStrideScatter(Vec s, PetscInt start, Vec v, InsertMode addv)
901: {
902: PetscFunctionBegin;
906: PetscCheck(start >= 0, PETSC_COMM_SELF, PETSC_ERR_ARG_OUTOFRANGE, "Negative start %" PetscInt_FMT, start);
907: PetscCheck(start < v->map->bs, PETSC_COMM_SELF, PETSC_ERR_ARG_OUTOFRANGE, "Start of stride subvector (%" PetscInt_FMT ") is too large for stride. Have you set the vector blocksize (%" PetscInt_FMT ") correctly with VecSetBlockSize()?", start,
908: v->map->bs);
909: PetscCall((*v->ops->stridescatter)(s, start, v, addv));
910: PetscFunctionReturn(PETSC_SUCCESS);
911: }
913: /*@
914: VecStrideSubSetGather - Gathers a subset of components from a multi-component vector into
915: another vector.
917: Collective
919: Input Parameters:
920: + v - the vector
921: . nidx - the number of indices
922: . idxv - the indices of the components 0 <= idxv[0] ...idxv[nidx-1] < bs(v), they need not be sorted
923: . idxs - the indices of the components 0 <= idxs[0] ...idxs[nidx-1] < bs(s), they need not be sorted, may be null if nidx == bs(s) or is `PETSC_DETERMINE`
924: - addv - one of `ADD_VALUES`, `INSERT_VALUES`, `MAX_VALUES`
926: Output Parameter:
927: . s - the location where the subvector is stored
929: Level: advanced
931: Notes:
932: One must call `VecSetBlockSize()` on both vectors before this routine to set the stride
933: information, or use a vector created from a multicomponent `DMDA`.
935: The parallel layout of the vector and the subvector must be the same;
937: Not optimized; could be easily
939: .seealso: `Vec`, `VecStrideNorm()`, `VecStrideScatter()`, `VecStrideGather()`, `VecStrideSubSetScatter()`, `VecStrideMin()`, `VecStrideMax()`, `VecStrideGatherAll()`,
940: `VecStrideScatterAll()`
941: @*/
942: PetscErrorCode VecStrideSubSetGather(Vec v, PetscInt nidx, const PetscInt idxv[], const PetscInt idxs[], Vec s, InsertMode addv)
943: {
944: PetscFunctionBegin;
947: if (nidx == PETSC_DETERMINE) nidx = s->map->bs;
948: PetscUseTypeMethod(v, stridesubsetgather, nidx, idxv, idxs, s, addv);
949: PetscFunctionReturn(PETSC_SUCCESS);
950: }
952: /*@
953: VecStrideSubSetScatter - Scatters components from a vector into a subset of components of a multi-component vector.
955: Collective
957: Input Parameters:
958: + s - the smaller-component vector
959: . nidx - the number of indices in idx
960: . idxs - the indices of the components in the smaller-component vector, 0 <= idxs[0] ...idxs[nidx-1] < bs(s) they need not be sorted, may be null if nidx == bs(s) or is `PETSC_DETERMINE`
961: . idxv - the indices of the components in the larger-component vector, 0 <= idx[0] ...idx[nidx-1] < bs(v) they need not be sorted
962: - addv - one of `ADD_VALUES`, `INSERT_VALUES`, `MAX_VALUES`
964: Output Parameter:
965: . v - the location where the subvector is into scattered (the multi-component vector)
967: Level: advanced
969: Notes:
970: One must call `VecSetBlockSize()` on the vectors before this
971: routine to set the stride information, or use a vector created from a multicomponent `DMDA`.
973: The parallel layout of the vector and the subvector must be the same;
975: Not optimized; could be easily
977: .seealso: `Vec`, `VecStrideNorm()`, `VecStrideGather()`, `VecStrideSubSetGather()`, `VecStrideMin()`, `VecStrideMax()`, `VecStrideGatherAll()`,
978: `VecStrideScatterAll()`
979: @*/
980: PetscErrorCode VecStrideSubSetScatter(Vec s, PetscInt nidx, const PetscInt idxs[], const PetscInt idxv[], Vec v, InsertMode addv)
981: {
982: PetscFunctionBegin;
985: if (nidx == PETSC_DETERMINE) nidx = s->map->bs;
986: PetscCall((*v->ops->stridesubsetscatter)(s, nidx, idxs, idxv, v, addv));
987: PetscFunctionReturn(PETSC_SUCCESS);
988: }
990: PetscErrorCode VecStrideGather_Default(Vec v, PetscInt start, Vec s, InsertMode addv)
991: {
992: PetscInt i, n, bs, ns;
993: const PetscScalar *x;
994: PetscScalar *y;
996: PetscFunctionBegin;
997: PetscCall(VecGetLocalSize(v, &n));
998: PetscCall(VecGetLocalSize(s, &ns));
999: PetscCall(VecGetArrayRead(v, &x));
1000: PetscCall(VecGetArray(s, &y));
1002: bs = v->map->bs;
1003: PetscCheck(n == ns * bs, PETSC_COMM_SELF, PETSC_ERR_ARG_OUTOFRANGE, "Subvector length * blocksize %" PetscInt_FMT " not correct for gather from original vector %" PetscInt_FMT, ns * bs, n);
1004: x += start;
1005: n = n / bs;
1007: if (addv == INSERT_VALUES) {
1008: for (i = 0; i < n; i++) y[i] = x[bs * i];
1009: } else if (addv == ADD_VALUES) {
1010: for (i = 0; i < n; i++) y[i] += x[bs * i];
1011: #if !defined(PETSC_USE_COMPLEX)
1012: } else if (addv == MAX_VALUES) {
1013: for (i = 0; i < n; i++) y[i] = PetscMax(y[i], x[bs * i]);
1014: #endif
1015: } else SETERRQ(PetscObjectComm((PetscObject)v), PETSC_ERR_ARG_UNKNOWN_TYPE, "Unknown norm type");
1017: PetscCall(VecRestoreArrayRead(v, &x));
1018: PetscCall(VecRestoreArray(s, &y));
1019: PetscFunctionReturn(PETSC_SUCCESS);
1020: }
1022: PetscErrorCode VecStrideScatter_Default(Vec s, PetscInt start, Vec v, InsertMode addv)
1023: {
1024: PetscInt i, n, bs, ns;
1025: PetscScalar *x;
1026: const PetscScalar *y;
1028: PetscFunctionBegin;
1029: PetscCall(VecGetLocalSize(v, &n));
1030: PetscCall(VecGetLocalSize(s, &ns));
1031: PetscCall(VecGetArray(v, &x));
1032: PetscCall(VecGetArrayRead(s, &y));
1034: bs = v->map->bs;
1035: PetscCheck(n == ns * bs, PETSC_COMM_SELF, PETSC_ERR_ARG_OUTOFRANGE, "Subvector length * blocksize %" PetscInt_FMT " not correct for scatter to multicomponent vector %" PetscInt_FMT, ns * bs, n);
1036: x += start;
1037: n = n / bs;
1039: if (addv == INSERT_VALUES) {
1040: for (i = 0; i < n; i++) x[bs * i] = y[i];
1041: } else if (addv == ADD_VALUES) {
1042: for (i = 0; i < n; i++) x[bs * i] += y[i];
1043: #if !defined(PETSC_USE_COMPLEX)
1044: } else if (addv == MAX_VALUES) {
1045: for (i = 0; i < n; i++) x[bs * i] = PetscMax(y[i], x[bs * i]);
1046: #endif
1047: } else SETERRQ(PetscObjectComm((PetscObject)s), PETSC_ERR_ARG_UNKNOWN_TYPE, "Unknown norm type");
1049: PetscCall(VecRestoreArray(v, &x));
1050: PetscCall(VecRestoreArrayRead(s, &y));
1051: PetscFunctionReturn(PETSC_SUCCESS);
1052: }
1054: PetscErrorCode VecStrideSubSetGather_Default(Vec v, PetscInt nidx, const PetscInt idxv[], const PetscInt idxs[], Vec s, InsertMode addv)
1055: {
1056: PetscInt i, j, n, bs, bss, ns;
1057: const PetscScalar *x;
1058: PetscScalar *y;
1060: PetscFunctionBegin;
1061: PetscCall(VecGetLocalSize(v, &n));
1062: PetscCall(VecGetLocalSize(s, &ns));
1063: PetscCall(VecGetArrayRead(v, &x));
1064: PetscCall(VecGetArray(s, &y));
1066: bs = v->map->bs;
1067: bss = s->map->bs;
1068: n = n / bs;
1070: if (PetscDefined(USE_DEBUG)) {
1071: PetscCheck(n == ns / bss, PETSC_COMM_SELF, PETSC_ERR_ARG_SIZ, "Incompatible layout of vectors");
1072: for (j = 0; j < nidx; j++) {
1073: PetscCheck(idxv[j] >= 0, PETSC_COMM_SELF, PETSC_ERR_ARG_OUTOFRANGE, "idx[%" PetscInt_FMT "] %" PetscInt_FMT " is negative", j, idxv[j]);
1074: PetscCheck(idxv[j] < bs, PETSC_COMM_SELF, PETSC_ERR_ARG_OUTOFRANGE, "idx[%" PetscInt_FMT "] %" PetscInt_FMT " is greater than or equal to vector blocksize %" PetscInt_FMT, j, idxv[j], bs);
1075: }
1076: PetscCheck(idxs || bss == nidx, PETSC_COMM_SELF, PETSC_ERR_ARG_OUTOFRANGE, "Must provide idxs when not gathering into all locations");
1077: }
1079: if (addv == INSERT_VALUES) {
1080: if (!idxs) {
1081: for (i = 0; i < n; i++) {
1082: for (j = 0; j < bss; j++) y[bss * i + j] = x[bs * i + idxv[j]];
1083: }
1084: } else {
1085: for (i = 0; i < n; i++) {
1086: for (j = 0; j < bss; j++) y[bss * i + idxs[j]] = x[bs * i + idxv[j]];
1087: }
1088: }
1089: } else if (addv == ADD_VALUES) {
1090: if (!idxs) {
1091: for (i = 0; i < n; i++) {
1092: for (j = 0; j < bss; j++) y[bss * i + j] += x[bs * i + idxv[j]];
1093: }
1094: } else {
1095: for (i = 0; i < n; i++) {
1096: for (j = 0; j < bss; j++) y[bss * i + idxs[j]] += x[bs * i + idxv[j]];
1097: }
1098: }
1099: #if !defined(PETSC_USE_COMPLEX)
1100: } else if (addv == MAX_VALUES) {
1101: if (!idxs) {
1102: for (i = 0; i < n; i++) {
1103: for (j = 0; j < bss; j++) y[bss * i + j] = PetscMax(y[bss * i + j], x[bs * i + idxv[j]]);
1104: }
1105: } else {
1106: for (i = 0; i < n; i++) {
1107: for (j = 0; j < bss; j++) y[bss * i + idxs[j]] = PetscMax(y[bss * i + idxs[j]], x[bs * i + idxv[j]]);
1108: }
1109: }
1110: #endif
1111: } else SETERRQ(PetscObjectComm((PetscObject)v), PETSC_ERR_ARG_UNKNOWN_TYPE, "Unknown norm type");
1113: PetscCall(VecRestoreArrayRead(v, &x));
1114: PetscCall(VecRestoreArray(s, &y));
1115: PetscFunctionReturn(PETSC_SUCCESS);
1116: }
1118: PetscErrorCode VecStrideSubSetScatter_Default(Vec s, PetscInt nidx, const PetscInt idxs[], const PetscInt idxv[], Vec v, InsertMode addv)
1119: {
1120: PetscInt j, i, n, bs, ns, bss;
1121: PetscScalar *x;
1122: const PetscScalar *y;
1124: PetscFunctionBegin;
1125: PetscCall(VecGetLocalSize(v, &n));
1126: PetscCall(VecGetLocalSize(s, &ns));
1127: PetscCall(VecGetArray(v, &x));
1128: PetscCall(VecGetArrayRead(s, &y));
1130: bs = v->map->bs;
1131: bss = s->map->bs;
1132: n = n / bs;
1134: if (PetscDefined(USE_DEBUG)) {
1135: PetscCheck(n == ns / bss, PETSC_COMM_SELF, PETSC_ERR_ARG_SIZ, "Incompatible layout of vectors");
1136: for (j = 0; j < bss; j++) {
1137: if (idxs) {
1138: PetscCheck(idxs[j] >= 0, PETSC_COMM_SELF, PETSC_ERR_ARG_OUTOFRANGE, "idx[%" PetscInt_FMT "] %" PetscInt_FMT " is negative", j, idxs[j]);
1139: PetscCheck(idxs[j] < bs, PETSC_COMM_SELF, PETSC_ERR_ARG_OUTOFRANGE, "idx[%" PetscInt_FMT "] %" PetscInt_FMT " is greater than or equal to vector blocksize %" PetscInt_FMT, j, idxs[j], bs);
1140: }
1141: }
1142: PetscCheck(idxs || bss == nidx, PETSC_COMM_SELF, PETSC_ERR_ARG_OUTOFRANGE, "Must provide idxs when not scattering from all locations");
1143: }
1145: if (addv == INSERT_VALUES) {
1146: if (!idxs) {
1147: for (i = 0; i < n; i++) {
1148: for (j = 0; j < bss; j++) x[bs * i + idxv[j]] = y[bss * i + j];
1149: }
1150: } else {
1151: for (i = 0; i < n; i++) {
1152: for (j = 0; j < bss; j++) x[bs * i + idxv[j]] = y[bss * i + idxs[j]];
1153: }
1154: }
1155: } else if (addv == ADD_VALUES) {
1156: if (!idxs) {
1157: for (i = 0; i < n; i++) {
1158: for (j = 0; j < bss; j++) x[bs * i + idxv[j]] += y[bss * i + j];
1159: }
1160: } else {
1161: for (i = 0; i < n; i++) {
1162: for (j = 0; j < bss; j++) x[bs * i + idxv[j]] += y[bss * i + idxs[j]];
1163: }
1164: }
1165: #if !defined(PETSC_USE_COMPLEX)
1166: } else if (addv == MAX_VALUES) {
1167: if (!idxs) {
1168: for (i = 0; i < n; i++) {
1169: for (j = 0; j < bss; j++) x[bs * i + idxv[j]] = PetscMax(y[bss * i + j], x[bs * i + idxv[j]]);
1170: }
1171: } else {
1172: for (i = 0; i < n; i++) {
1173: for (j = 0; j < bss; j++) x[bs * i + idxv[j]] = PetscMax(y[bss * i + idxs[j]], x[bs * i + idxv[j]]);
1174: }
1175: }
1176: #endif
1177: } else SETERRQ(PetscObjectComm((PetscObject)v), PETSC_ERR_ARG_UNKNOWN_TYPE, "Unknown norm type");
1179: PetscCall(VecRestoreArray(v, &x));
1180: PetscCall(VecRestoreArrayRead(s, &y));
1181: PetscFunctionReturn(PETSC_SUCCESS);
1182: }
1184: static PetscErrorCode VecApplyUnary_Private(Vec v, PetscDeviceContext dctx, const char async_name[], PetscErrorCode (*unary_op)(Vec), PetscScalar (*UnaryFunc)(PetscScalar))
1185: {
1186: PetscFunctionBegin;
1188: PetscCall(VecSetErrorIfLocked(v, 1));
1189: if (dctx) {
1190: PetscErrorCode (*unary_op_async)(Vec, PetscDeviceContext);
1192: PetscCall(PetscObjectQueryFunction((PetscObject)v, async_name, &unary_op_async));
1193: if (unary_op_async) {
1194: PetscCall((*unary_op_async)(v, dctx));
1195: PetscFunctionReturn(PETSC_SUCCESS);
1196: }
1197: }
1198: if (unary_op) {
1200: PetscCall((*unary_op)(v));
1201: } else {
1202: PetscInt n;
1203: PetscScalar *x;
1206: PetscCall(VecGetLocalSize(v, &n));
1207: PetscCall(VecGetArray(v, &x));
1208: for (PetscInt i = 0; i < n; ++i) x[i] = UnaryFunc(x[i]);
1209: PetscCall(VecRestoreArray(v, &x));
1210: }
1211: PetscFunctionReturn(PETSC_SUCCESS);
1212: }
1214: static PetscScalar ScalarReciprocal_Function(PetscScalar x)
1215: {
1216: const PetscScalar zero = 0.0;
1218: return x == zero ? zero : ((PetscScalar)1.0) / x;
1219: }
1221: PetscErrorCode VecReciprocalAsync_Private(Vec v, PetscDeviceContext dctx)
1222: {
1223: PetscFunctionBegin;
1224: PetscCall(PetscLogEventBegin(VEC_Reciprocal, v, NULL, NULL, NULL));
1225: PetscCall(VecApplyUnary_Private(v, dctx, VecAsyncFnName(Reciprocal), v->ops->reciprocal, ScalarReciprocal_Function));
1226: PetscCall(PetscLogEventEnd(VEC_Reciprocal, v, NULL, NULL, NULL));
1227: PetscFunctionReturn(PETSC_SUCCESS);
1228: }
1230: PetscErrorCode VecReciprocal_Default(Vec v)
1231: {
1232: PetscFunctionBegin;
1233: PetscCall(VecApplyUnary_Private(v, NULL, NULL, NULL, ScalarReciprocal_Function));
1234: PetscFunctionReturn(PETSC_SUCCESS);
1235: }
1237: static PetscScalar ScalarExp_Function(PetscScalar x)
1238: {
1239: return PetscExpScalar(x);
1240: }
1242: PetscErrorCode VecExpAsync_Private(Vec v, PetscDeviceContext dctx)
1243: {
1244: PetscFunctionBegin;
1246: PetscCall(VecApplyUnary_Private(v, dctx, VecAsyncFnName(Exp), v->ops->exp, ScalarExp_Function));
1247: PetscFunctionReturn(PETSC_SUCCESS);
1248: }
1250: /*@
1251: VecExp - Replaces each component of a vector by e^x_i
1253: Not Collective
1255: Input Parameter:
1256: . v - The vector
1258: Output Parameter:
1259: . v - The vector of exponents
1261: Level: beginner
1263: .seealso: `Vec`, `VecLog()`, `VecAbs()`, `VecSqrtAbs()`, `VecReciprocal()`
1265: @*/
1266: PetscErrorCode VecExp(Vec v)
1267: {
1268: PetscFunctionBegin;
1269: PetscCall(VecExpAsync_Private(v, NULL));
1270: PetscFunctionReturn(PETSC_SUCCESS);
1271: }
1273: static PetscScalar ScalarLog_Function(PetscScalar x)
1274: {
1275: return PetscLogScalar(x);
1276: }
1278: PetscErrorCode VecLogAsync_Private(Vec v, PetscDeviceContext dctx)
1279: {
1280: PetscFunctionBegin;
1282: PetscCall(VecApplyUnary_Private(v, dctx, VecAsyncFnName(Log), v->ops->log, ScalarLog_Function));
1283: PetscFunctionReturn(PETSC_SUCCESS);
1284: }
1286: /*@
1287: VecLog - Replaces each component of a vector by log(x_i), the natural logarithm
1289: Not Collective
1291: Input Parameter:
1292: . v - The vector
1294: Output Parameter:
1295: . v - The vector of logs
1297: Level: beginner
1299: .seealso: `Vec`, `VecExp()`, `VecAbs()`, `VecSqrtAbs()`, `VecReciprocal()`
1301: @*/
1302: PetscErrorCode VecLog(Vec v)
1303: {
1304: PetscFunctionBegin;
1305: PetscCall(VecLogAsync_Private(v, NULL));
1306: PetscFunctionReturn(PETSC_SUCCESS);
1307: }
1309: static PetscScalar ScalarAbs_Function(PetscScalar x)
1310: {
1311: return PetscAbsScalar(x);
1312: }
1314: PetscErrorCode VecAbsAsync_Private(Vec v, PetscDeviceContext dctx)
1315: {
1316: PetscFunctionBegin;
1318: PetscCall(VecApplyUnary_Private(v, dctx, VecAsyncFnName(Abs), v->ops->abs, ScalarAbs_Function));
1319: PetscFunctionReturn(PETSC_SUCCESS);
1320: }
1322: /*@
1323: VecAbs - Replaces every element in a vector with its absolute value.
1325: Logically Collective
1327: Input Parameter:
1328: . v - the vector
1330: Level: intermediate
1332: .seealso: `Vec`, `VecExp()`, `VecSqrtAbs()`, `VecReciprocal()`, `VecLog()`
1333: @*/
1334: PetscErrorCode VecAbs(Vec v)
1335: {
1336: PetscFunctionBegin;
1337: PetscCall(VecAbsAsync_Private(v, NULL));
1338: PetscFunctionReturn(PETSC_SUCCESS);
1339: }
1341: static PetscScalar ScalarConjugate_Function(PetscScalar x)
1342: {
1343: return PetscConj(x);
1344: }
1346: PetscErrorCode VecConjugateAsync_Private(Vec v, PetscDeviceContext dctx)
1347: {
1348: PetscFunctionBegin;
1350: if (PetscDefined(USE_COMPLEX)) PetscCall(VecApplyUnary_Private(v, dctx, VecAsyncFnName(Conjugate), v->ops->conjugate, ScalarConjugate_Function));
1351: PetscFunctionReturn(PETSC_SUCCESS);
1352: }
1354: /*@
1355: VecConjugate - Conjugates a vector. That is, replace every entry in a vector with its complex conjugate
1357: Logically Collective
1359: Input Parameter:
1360: . x - the vector
1362: Level: intermediate
1364: .seealso: [](ch_vectors), `Vec`, `VecSet()`
1365: @*/
1366: PetscErrorCode VecConjugate(Vec x)
1367: {
1368: PetscFunctionBegin;
1369: PetscCall(VecConjugateAsync_Private(x, NULL));
1370: PetscFunctionReturn(PETSC_SUCCESS);
1371: }
1373: static PetscScalar ScalarSqrtAbs_Function(PetscScalar x)
1374: {
1375: return PetscSqrtScalar(ScalarAbs_Function(x));
1376: }
1378: PetscErrorCode VecSqrtAbsAsync_Private(Vec v, PetscDeviceContext dctx)
1379: {
1380: PetscFunctionBegin;
1382: PetscCall(VecApplyUnary_Private(v, dctx, VecAsyncFnName(SqrtAbs), v->ops->sqrt, ScalarSqrtAbs_Function));
1383: PetscFunctionReturn(PETSC_SUCCESS);
1384: }
1386: /*@
1387: VecSqrtAbs - Replaces each component of a vector by the square root of its magnitude.
1389: Not Collective
1391: Input Parameter:
1392: . v - The vector
1394: Level: beginner
1396: Note:
1397: The actual function is sqrt(|x_i|)
1399: .seealso: `Vec`, `VecLog()`, `VecExp()`, `VecReciprocal()`, `VecAbs()`
1401: @*/
1402: PetscErrorCode VecSqrtAbs(Vec v)
1403: {
1404: PetscFunctionBegin;
1405: PetscCall(VecSqrtAbsAsync_Private(v, NULL));
1406: PetscFunctionReturn(PETSC_SUCCESS);
1407: }
1409: static PetscScalar ScalarImaginaryPart_Function(PetscScalar x)
1410: {
1411: const PetscReal imag = PetscImaginaryPart(x);
1413: #if PetscDefined(USE_COMPLEX)
1414: return PetscCMPLX(imag, 0.0);
1415: #else
1416: return imag;
1417: #endif
1418: }
1420: /*@
1421: VecImaginaryPart - Replaces a complex vector with its imaginary part
1423: Collective
1425: Input Parameter:
1426: . v - the vector
1428: Level: beginner
1430: .seealso: `Vec`, `VecNorm()`, `VecRealPart()`
1431: @*/
1432: PetscErrorCode VecImaginaryPart(Vec v)
1433: {
1434: PetscFunctionBegin;
1436: PetscCall(VecApplyUnary_Private(v, NULL, NULL, NULL, ScalarImaginaryPart_Function));
1437: PetscFunctionReturn(PETSC_SUCCESS);
1438: }
1440: static PetscScalar ScalarRealPart_Function(PetscScalar x)
1441: {
1442: const PetscReal real = PetscRealPart(x);
1444: #if PetscDefined(USE_COMPLEX)
1445: return PetscCMPLX(real, 0.0);
1446: #else
1447: return real;
1448: #endif
1449: }
1451: /*@
1452: VecRealPart - Replaces a complex vector with its real part
1454: Collective
1456: Input Parameter:
1457: . v - the vector
1459: Level: beginner
1461: .seealso: `Vec`, `VecNorm()`, `VecImaginaryPart()`
1462: @*/
1463: PetscErrorCode VecRealPart(Vec v)
1464: {
1465: PetscFunctionBegin;
1467: PetscCall(VecApplyUnary_Private(v, NULL, NULL, NULL, ScalarRealPart_Function));
1468: PetscFunctionReturn(PETSC_SUCCESS);
1469: }
1471: /*@
1472: VecDotNorm2 - computes the inner product of two vectors and the 2-norm squared of the second vector
1474: Collective
1476: Input Parameters:
1477: + s - first vector
1478: - t - second vector
1480: Output Parameters:
1481: + dp - s'conj(t)
1482: - nm - t'conj(t)
1484: Level: advanced
1486: Note:
1487: conj(x) is the complex conjugate of x when x is complex
1489: .seealso: `Vec`, `VecDot()`, `VecNorm()`, `VecDotBegin()`, `VecNormBegin()`, `VecDotEnd()`, `VecNormEnd()`
1491: @*/
1492: PetscErrorCode VecDotNorm2(Vec s, Vec t, PetscScalar *dp, PetscReal *nm)
1493: {
1494: PetscScalar work[] = {0.0, 0.0};
1496: PetscFunctionBegin;
1499: PetscAssertPointer(dp, 3);
1500: PetscAssertPointer(nm, 4);
1503: PetscCheckSameTypeAndComm(s, 1, t, 2);
1504: PetscCheck(s->map->N == t->map->N, PETSC_COMM_SELF, PETSC_ERR_ARG_INCOMP, "Incompatible vector global lengths");
1505: PetscCheck(s->map->n == t->map->n, PETSC_COMM_SELF, PETSC_ERR_ARG_INCOMP, "Incompatible vector local lengths");
1507: PetscCall(PetscLogEventBegin(VEC_DotNorm2, s, t, 0, 0));
1508: if (s->ops->dotnorm2) {
1509: PetscUseTypeMethod(s, dotnorm2, t, work, work + 1);
1510: } else {
1511: const PetscScalar *sx, *tx;
1512: PetscInt n;
1514: PetscCall(VecGetLocalSize(s, &n));
1515: PetscCall(VecGetArrayRead(s, &sx));
1516: PetscCall(VecGetArrayRead(t, &tx));
1517: for (PetscInt i = 0; i < n; ++i) {
1518: const PetscScalar txconj = PetscConj(tx[i]);
1520: work[0] += sx[i] * txconj;
1521: work[1] += tx[i] * txconj;
1522: }
1523: PetscCall(VecRestoreArrayRead(t, &tx));
1524: PetscCall(VecRestoreArrayRead(s, &sx));
1525: PetscCallMPI(MPIU_Allreduce(MPI_IN_PLACE, work, 2, MPIU_SCALAR, MPIU_SUM, PetscObjectComm((PetscObject)s)));
1526: PetscCall(PetscLogFlops(4.0 * n));
1527: }
1528: PetscCall(PetscLogEventEnd(VEC_DotNorm2, s, t, 0, 0));
1529: *dp = work[0];
1530: *nm = PetscRealPart(work[1]);
1531: PetscFunctionReturn(PETSC_SUCCESS);
1532: }
1534: /*@
1535: VecSum - Computes the sum of all the components of a vector.
1537: Collective
1539: Input Parameter:
1540: . v - the vector
1542: Output Parameter:
1543: . sum - the result
1545: Level: beginner
1547: .seealso: `Vec`, `VecMean()`, `VecNorm()`
1548: @*/
1549: PetscErrorCode VecSum(Vec v, PetscScalar *sum)
1550: {
1551: PetscScalar tmp = 0.0;
1553: PetscFunctionBegin;
1555: PetscAssertPointer(sum, 2);
1556: if (v->ops->sum) {
1557: PetscUseTypeMethod(v, sum, &tmp);
1558: } else {
1559: const PetscScalar *x;
1560: PetscInt n;
1562: PetscCall(VecGetLocalSize(v, &n));
1563: PetscCall(VecGetArrayRead(v, &x));
1564: for (PetscInt i = 0; i < n; ++i) tmp += x[i];
1565: PetscCall(VecRestoreArrayRead(v, &x));
1566: }
1567: PetscCallMPI(MPIU_Allreduce(MPI_IN_PLACE, &tmp, 1, MPIU_SCALAR, MPIU_SUM, PetscObjectComm((PetscObject)v)));
1568: *sum = tmp;
1569: PetscFunctionReturn(PETSC_SUCCESS);
1570: }
1572: /*@
1573: VecMean - Computes the arithmetic mean of all the components of a vector.
1575: Collective
1577: Input Parameter:
1578: . v - the vector
1580: Output Parameter:
1581: . mean - the result
1583: Level: beginner
1585: .seealso: `Vec`, `VecSum()`, `VecNorm()`
1586: @*/
1587: PetscErrorCode VecMean(Vec v, PetscScalar *mean)
1588: {
1589: PetscInt n;
1591: PetscFunctionBegin;
1593: PetscAssertPointer(mean, 2);
1594: PetscCall(VecGetSize(v, &n));
1595: PetscCall(VecSum(v, mean));
1596: *mean /= n;
1597: PetscFunctionReturn(PETSC_SUCCESS);
1598: }
1600: PetscErrorCode VecShiftAsync_Private(Vec v, PetscScalar shift, PetscDeviceContext dctx)
1601: {
1602: PetscErrorCode (*shift_async)(Vec, PetscScalar, PetscDeviceContext) = NULL;
1604: PetscFunctionBegin;
1605: if (dctx) {
1606: PetscErrorCode (*shift_async)(Vec, PetscScalar, PetscDeviceContext);
1608: PetscCall(PetscObjectQueryFunction((PetscObject)v, VecAsyncFnName(Shift), &shift_async));
1609: }
1610: if (shift_async) {
1611: PetscCall((*shift_async)(v, shift, dctx));
1612: } else if (v->ops->shift) {
1613: PetscUseTypeMethod(v, shift, shift);
1614: } else {
1615: PetscInt n;
1616: PetscScalar *x;
1618: PetscCall(VecGetLocalSize(v, &n));
1619: PetscCall(VecGetArray(v, &x));
1620: for (PetscInt i = 0; i < n; ++i) x[i] += shift;
1621: PetscCall(VecRestoreArray(v, &x));
1622: PetscCall(PetscLogFlops(n));
1623: }
1624: PetscFunctionReturn(PETSC_SUCCESS);
1625: }
1627: /*@
1628: VecShift - Shifts all of the components of a vector by computing
1629: `x[i] = x[i] + shift`.
1631: Logically Collective
1633: Input Parameters:
1634: + v - the vector
1635: - shift - the shift
1637: Level: intermediate
1639: .seealso: `Vec`, `VecISShift()`
1640: @*/
1641: PetscErrorCode VecShift(Vec v, PetscScalar shift)
1642: {
1643: PetscFunctionBegin;
1646: PetscCall(VecSetErrorIfLocked(v, 1));
1647: if (shift == (PetscScalar)0.0) PetscFunctionReturn(PETSC_SUCCESS);
1648: PetscCall(PetscLogEventBegin(VEC_Shift, v, 0, 0, 0));
1649: PetscCall(VecShiftAsync_Private(v, shift, NULL));
1650: PetscCall(PetscLogEventEnd(VEC_Shift, v, 0, 0, 0));
1651: PetscFunctionReturn(PETSC_SUCCESS);
1652: }
1654: /*@
1655: VecPermute - Permutes a vector in place using the given ordering.
1657: Input Parameters:
1658: + x - The vector
1659: . row - The ordering
1660: - inv - The flag for inverting the permutation
1662: Level: beginner
1664: Note:
1665: This function does not yet support parallel Index Sets with non-local permutations
1667: .seealso: `Vec`, `MatPermute()`
1668: @*/
1669: PetscErrorCode VecPermute(Vec x, IS row, PetscBool inv)
1670: {
1671: PetscScalar *array, *newArray;
1672: const PetscInt *idx;
1673: PetscInt i, rstart, rend;
1675: PetscFunctionBegin;
1678: PetscCall(VecSetErrorIfLocked(x, 1));
1679: PetscCall(VecGetOwnershipRange(x, &rstart, &rend));
1680: PetscCall(ISGetIndices(row, &idx));
1681: PetscCall(VecGetArray(x, &array));
1682: PetscCall(PetscMalloc1(x->map->n, &newArray));
1683: PetscCall(PetscArraycpy(newArray, array, x->map->n));
1684: if (PetscDefined(USE_DEBUG)) {
1685: for (i = 0; i < x->map->n; i++) PetscCheck(!(idx[i] < rstart) && !(idx[i] >= rend), PETSC_COMM_SELF, PETSC_ERR_ARG_CORRUPT, "Permutation index %" PetscInt_FMT " is out of bounds: %" PetscInt_FMT, i, idx[i]);
1686: }
1687: if (!inv) {
1688: for (i = 0; i < x->map->n; i++) array[i] = newArray[idx[i] - rstart];
1689: } else {
1690: for (i = 0; i < x->map->n; i++) array[idx[i] - rstart] = newArray[i];
1691: }
1692: PetscCall(VecRestoreArray(x, &array));
1693: PetscCall(ISRestoreIndices(row, &idx));
1694: PetscCall(PetscFree(newArray));
1695: PetscFunctionReturn(PETSC_SUCCESS);
1696: }
1698: /*@
1699: VecEqual - Compares two vectors. Returns true if the two vectors are either pointing to the same memory buffer,
1700: or if the two vectors have the same local and global layout as well as bitwise equality of all entries.
1701: Does NOT take round-off errors into account.
1703: Collective
1705: Input Parameters:
1706: + vec1 - the first vector
1707: - vec2 - the second vector
1709: Output Parameter:
1710: . flg - `PETSC_TRUE` if the vectors are equal; `PETSC_FALSE` otherwise.
1712: Level: intermediate
1714: .seealso: `Vec`
1715: @*/
1716: PetscErrorCode VecEqual(Vec vec1, Vec vec2, PetscBool *flg)
1717: {
1718: const PetscScalar *v1, *v2;
1719: PetscInt n1, n2, N1, N2;
1720: PetscBool flg1;
1722: PetscFunctionBegin;
1725: PetscAssertPointer(flg, 3);
1726: if (vec1 == vec2) *flg = PETSC_TRUE;
1727: else {
1728: PetscCall(VecGetSize(vec1, &N1));
1729: PetscCall(VecGetSize(vec2, &N2));
1730: if (N1 != N2) flg1 = PETSC_FALSE;
1731: else {
1732: PetscCall(VecGetLocalSize(vec1, &n1));
1733: PetscCall(VecGetLocalSize(vec2, &n2));
1734: if (n1 != n2) flg1 = PETSC_FALSE;
1735: else {
1736: PetscCall(VecGetArrayRead(vec1, &v1));
1737: PetscCall(VecGetArrayRead(vec2, &v2));
1738: PetscCall(PetscArraycmp(v1, v2, n1, &flg1));
1739: PetscCall(VecRestoreArrayRead(vec1, &v1));
1740: PetscCall(VecRestoreArrayRead(vec2, &v2));
1741: }
1742: }
1743: /* combine results from all processors */
1744: PetscCallMPI(MPIU_Allreduce(&flg1, flg, 1, MPI_C_BOOL, MPI_LAND, PetscObjectComm((PetscObject)vec1)));
1745: }
1746: PetscFunctionReturn(PETSC_SUCCESS);
1747: }
1749: /*@
1750: VecUniqueEntries - Compute the number of unique entries, and those entries
1752: Collective
1754: Input Parameter:
1755: . vec - the vector
1757: Output Parameters:
1758: + n - The number of unique entries
1759: - e - The entries, each MPI process receives all the unique entries
1761: Level: intermediate
1763: .seealso: `Vec`
1764: @*/
1765: PetscErrorCode VecUniqueEntries(Vec vec, PetscInt *n, PetscScalar *e[])
1766: {
1767: const PetscScalar *v;
1768: PetscScalar *tmp, *vals;
1769: PetscMPIInt *N, *displs, l;
1770: PetscInt ng, m, i, j, p;
1771: PetscMPIInt size;
1773: PetscFunctionBegin;
1775: PetscAssertPointer(n, 2);
1776: PetscCallMPI(MPI_Comm_size(PetscObjectComm((PetscObject)vec), &size));
1777: PetscCall(VecGetLocalSize(vec, &m));
1778: PetscCall(VecGetArrayRead(vec, &v));
1779: PetscCall(PetscMalloc2(m, &tmp, size, &N));
1780: for (i = 0, l = 0; i < m; ++i) {
1781: /* Can speed this up with sorting */
1782: for (j = 0; j < l; ++j) {
1783: if (v[i] == tmp[j]) break;
1784: }
1785: if (j == l) {
1786: tmp[j] = v[i];
1787: ++l;
1788: }
1789: }
1790: PetscCall(VecRestoreArrayRead(vec, &v));
1791: /* Gather serial results */
1792: PetscCallMPI(MPI_Allgather(&l, 1, MPI_INT, N, 1, MPI_INT, PetscObjectComm((PetscObject)vec)));
1793: for (p = 0, ng = 0; p < size; ++p) ng += N[p];
1794: PetscCall(PetscMalloc2(ng, &vals, size + 1, &displs));
1795: for (p = 1, displs[0] = 0; p <= size; ++p) displs[p] = displs[p - 1] + N[p - 1];
1796: PetscCallMPI(MPI_Allgatherv(tmp, l, MPIU_SCALAR, vals, N, displs, MPIU_SCALAR, PetscObjectComm((PetscObject)vec)));
1797: /* Find unique entries */
1798: #ifdef PETSC_USE_COMPLEX
1799: SETERRQ(PetscObjectComm((PetscObject)vec), PETSC_ERR_SUP, "Does not work with complex numbers");
1800: #else
1801: *n = displs[size];
1802: PetscCall(PetscSortRemoveDupsReal(n, vals));
1803: if (e) {
1804: PetscAssertPointer(e, 3);
1805: PetscCall(PetscMalloc1(*n, e));
1806: for (i = 0; i < *n; ++i) (*e)[i] = vals[i];
1807: }
1808: PetscCall(PetscFree2(vals, displs));
1809: PetscCall(PetscFree2(tmp, N));
1810: PetscFunctionReturn(PETSC_SUCCESS);
1811: #endif
1812: }