Date: 2021-09-20T09:43:37+00:00

Actual source code: fnlog.c
slepc-3.15.2 2021-09-20
Report Typos and Errors

      1: /*
      2:    - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
      3:    SLEPc - Scalable Library for Eigenvalue Problem Computations
      4:    Copyright (c) 2002-2021, Universitat Politecnica de Valencia, Spain

      6:    This file is part of SLEPc.
      7:    SLEPc is distributed under a 2-clause BSD license (see LICENSE).
      8:    - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
      9: */
     10: /*
     11:    Logarithm function  log(x)
     12: */

     14: #include <slepc/private/fnimpl.h>
     15: #include <slepcblaslapack.h>

     17: PetscErrorCode FNEvaluateFunction_Log(FN fn,PetscScalar x,PetscScalar *y)
     18: {
     20: #if !defined(PETSC_USE_COMPLEX)
     21:   if (x<0.0) SETERRQ(PETSC_COMM_SELF,1,"Function not defined in the requested value");
     22: #endif
     23:   *y = PetscLogScalar(x);
     24:   return(0);
     25: }

     27: PetscErrorCode FNEvaluateDerivative_Log(FN fn,PetscScalar x,PetscScalar *y)
     28: {
     30:   if (x==0.0) SETERRQ(PETSC_COMM_SELF,1,"Derivative not defined in the requested value");
     31: #if !defined(PETSC_USE_COMPLEX)
     32:   if (x<0.0) SETERRQ(PETSC_COMM_SELF,1,"Derivative not defined in the requested value");
     33: #endif
     34:   *y = 1.0/x;
     35:   return(0);
     36: }

     38: /*
     39:    Block structure of a quasitriangular matrix T. Returns a list of n-1 numbers, where
     40:    structure(j) encodes the block type of the j:j+1,j:j+1 diagonal block as one of:
     41:       0 - not the start of a block
     42:       1 - start of a 2x2 triangular block
     43:       2 - start of a 2x2 quasi-triangular (full) block
     44: */
     45: static PetscErrorCode qtri_struct(PetscBLASInt n,PetscScalar *T,PetscBLASInt ld,PetscInt *structure)
     46: {
     47:   PetscBLASInt j;

     50: #if defined(PETSC_USE_COMPLEX)
     51:   for (j=0;j<n-1;j++) structure[j] = 1;
     52: #else
     53:   if (n==1) return(0);
     54:   else if (n==2) {
     55:     structure[0] = (T[1]==0.0)? 1: 2;
     56:     return(0);
     57:   }
     58:   j = 0;
     59:   while (j<n-2) {
     60:     if (T[j+1+j*ld] != 0.0) { /* Start of a 2x2 full block */
     61:       structure[j++] = 2;
     62:       structure[j++] = 0;
     63:     } else if (T[j+1+j*ld] == 0.0 && T[j+2+(j+1)*ld] == 0.0) { /* Start of a 2x2 triangular block */
     64:       structure[j++] = 1;
     65:     } else { /* Next block must start a 2x2 full block */
     66:       structure[j++] = 0;
     67:     }
     68:   }
     69:   if (T[n-1+(n-2)*ld] != 0.0) { /* 2x2 full block at the end */
     70:     structure[n-2] = 2;
     71:   } else if (structure[n-3] == 0 || structure[n-3] == 1) {
     72:     structure[n-2] = 1;
     73:   }
     74: #endif
     75:   return(0);
     76: }

     78: /*
     79:    Compute scaling parameter (s) and order of Pade approximant (m).
     80:    wr,wi is overwritten. Required workspace is 3*n*n.
     81:    On output, Troot contains the sth square root of T.
     82: */
     83: static PetscErrorCode FNlogm_params(FN fn,PetscBLASInt n,PetscScalar *T,PetscBLASInt ld,PetscScalar *wr,PetscScalar *wi,PetscInt maxroots,PetscInt *s,PetscInt *m,PetscScalar *Troot,PetscScalar *work)
     84: {
     85:   PetscErrorCode  ierr;
     86:   PetscInt        i,j,k,p,s0;
     87:   PetscReal       inrm,eta,a2,a3,a4,d2,d3,d4,d5;
     88:   PetscScalar     *TrootmI=work+2*n*n;
     89:   PetscBool       foundm=PETSC_FALSE,more;
     90:   PetscRandom     rand;
     91:   const PetscReal xvals[] = { 1.586970738772063e-005, 2.313807884242979e-003, 1.938179313533253e-002,
     92:        6.209171588994762e-002, 1.276404810806775e-001, 2.060962623452836e-001, 2.879093714241194e-001 };
     93:   const PetscInt  mmax=sizeof(xvals)/sizeof(xvals[0]);

     96:   PetscRandomCreate(PETSC_COMM_SELF,&rand);
     97:   /* get initial s0 so that T^(1/2^s0) < xvals(mmax) */
     98:   *s = 0;
     99:   do {
    100:     inrm = SlepcAbsEigenvalue(wr[0]-PetscRealConstant(1.0),wi[0]);
    101:     for (i=1;i<n;i++) inrm = PetscMax(inrm,SlepcAbsEigenvalue(wr[i]-PetscRealConstant(1.0),wi[i]));
    102:     if (inrm < xvals[mmax-1]) break;
    103:     for (i=0;i<n;i++) {
    104: #if defined(PETSC_USE_COMPLEX)
    105:       wr[i] = PetscSqrtScalar(wr[i]);
    106: #else
    107: #if defined(PETSC_HAVE_COMPLEX)
    108:       PetscComplex z = PetscSqrtComplex(PetscCMPLX(wr[i],wi[i]));
    109:       wr[i] = PetscRealPartComplex(z);
    110:       wi[i] = PetscImaginaryPartComplex(z);
    111: #else
    112:       SETERRQ(PETSC_COMM_SELF,1,"This operation requires a compiler with C99 or C++ complex support");
    113: #endif
    114: #endif
    115:     }
    116:     *s = *s + 1;
    117:   } while (*s<maxroots);
    118:   s0 = *s;
    119:   if (*s == maxroots) { PetscInfo(fn,"Too many matrix square roots\n"); }

    121:   /* Troot = T */
    122:   for (j=0;j<n;j++) {
    123:     PetscArraycpy(Troot+j*ld,T+j*ld,PetscMin(j+2,n));
    124:   }
    125:   for (k=1;k<=PetscMin(*s,maxroots);k++) {
    126:     FNSqrtmSchur(fn,n,Troot,ld,PETSC_FALSE);
    127:   }
    128:   /* Compute value of s and m needed */
    129:   /* TrootmI = Troot - I */
    130:   for (j=0;j<n;j++) {
    131:     PetscArraycpy(TrootmI+j*ld,Troot+j*ld,PetscMin(j+2,n));
    132:     TrootmI[j+j*ld] -= 1.0;
    133:   }
    134:   SlepcNormAm(n,TrootmI,2,work,rand,&d2);
    135:   d2 = PetscPowReal(d2,1.0/2.0);
    136:   SlepcNormAm(n,TrootmI,3,work,rand,&d3);
    137:   d3 = PetscPowReal(d3,1.0/3.0);
    138:   a2 = PetscMax(d2,d3);
    139:   if (a2 <= xvals[1]) {
    140:     *m = (a2 <= xvals[0])? 1: 2;
    141:     foundm = PETSC_TRUE;
    142:   }
    143:   p = 0;
    144:   while (!foundm) {
    145:     more = PETSC_FALSE;  /* More norm checks needed */
    146:     if (*s > s0) {
    147:       SlepcNormAm(n,TrootmI,3,work,rand,&d3);
    148:       d3 = PetscPowReal(d3,1.0/3.0);
    149:     }
    150:     SlepcNormAm(n,TrootmI,4,work,rand,&d4);
    151:     d4 = PetscPowReal(d4,1.0/4.0);
    152:     a3 = PetscMax(d3,d4);
    153:     if (a3 <= xvals[mmax-1]) {
    154:       for (j=2;j<mmax;j++) if (a3 <= xvals[j]) break;
    155:       if (j <= 5) {
    156:         *m = j+1;
    157:         break;
    158:       } else if (a3/2.0 <= xvals[4] && p < 2) {
    159:         more = PETSC_TRUE;
    160:         p = p + 1;
    161:       }
    162:     }
    163:     if (!more) {
    164:       SlepcNormAm(n,TrootmI,5,work,rand,&d5);
    165:       d5 = PetscPowReal(d5,1.0/5.0);
    166:       a4 = PetscMax(d4,d5);
    167:       eta = PetscMin(a3,a4);
    168:       if (eta <= xvals[mmax-1]) {
    169:         for (j=5;j<mmax;j++) if (eta <= xvals[j]) break;
    170:         *m = j + 1;
    171:         break;
    172:       }
    173:     }
    174:     if (*s == maxroots) {
    175:       PetscInfo(fn,"Too many matrix square roots\n");
    176:       *m = mmax;  /* No good value found so take largest */
    177:       break;
    178:     }
    179:     FNSqrtmSchur(fn,n,Troot,ld,PETSC_FALSE);
    180:     /* TrootmI = Troot - I */
    181:     for (j=0;j<n;j++) {
    182:       PetscArraycpy(TrootmI+j*ld,Troot+j*ld,PetscMin(j+2,n));
    183:       TrootmI[j+j*ld] -= 1.0;
    184:     }
    185:     *s = *s + 1;
    186:   }
    187:   PetscRandomDestroy(&rand);
    188:   return(0);
    189: }

    191: #if !defined(PETSC_USE_COMPLEX)
    192: /*
    193:    Computes a^(1/2^s) - 1 accurately, avoiding subtractive cancellation
    194: */
    195: static PetscScalar sqrt_obo(PetscScalar a,PetscInt s)
    196: {
    197:   PetscScalar val,z0,r;
    198:   PetscReal   angle;
    199:   PetscInt    i,n0;

    202:   if (s == 0) val = a-1.0;
    203:   else {
    204:     n0 = s;
    205:     angle = PetscAtan2Real(PetscImaginaryPart(a),PetscRealPart(a));
    206:     if (angle >= PETSC_PI/2.0) {
    207:       a = PetscSqrtScalar(a);
    208:       n0 = s - 1;
    209:     }
    210:     z0 = a - 1.0;
    211:     a = PetscSqrtScalar(a);
    212:     r = 1.0 + a;
    213:     for (i=0;i<n0-1;i++) {
    214:       a = PetscSqrtScalar(a);
    215:       r = r*(1.0+a);
    216:     }
    217:     val = z0/r;
    218:   }
    219:   PetscFunctionReturn(val);
    220: }
    221: #endif

    223: /*
    224:    Square root of 2x2 matrix T from block diagonal of Schur form. Overwrites T.
    225: */
    226: static PetscErrorCode sqrtm_tbt(PetscScalar *T)
    227: {
    228:   PetscScalar t11,t12,t21,t22,r11,r22;
    229: #if !defined(PETSC_USE_COMPLEX)
    230:   PetscScalar mu;
    231: #endif

    234:   t11 = T[0]; t21 = T[1]; t12 = T[2]; t22 = T[3];
    235:   if (t21 != 0.0) {
    236:     /* Compute square root of 2x2 quasitriangular block */
    237:     /* The algorithm assumes the special structure of real Schur form */
    238: #if defined(PETSC_USE_COMPLEX)
    239:     SETERRQ(PETSC_COMM_SELF,1,"Should not reach this line in complex scalars");
    240: #else
    241:     mu = PetscSqrtReal(-t21*t12);
    242:     if (t11 > 0.0) r11 = PetscSqrtReal((t11+SlepcAbsEigenvalue(t11,mu))/2.0);
    243:     else r11 = mu / PetscSqrtReal(2.0*(-t11+SlepcAbsEigenvalue(t11,mu)));
    244:     T[0] = r11;
    245:     T[1] = t21/(2.0*r11);
    246:     T[2] = t12/(2.0*r11);
    247:     T[3] = r11;
    248: #endif
    249:   } else {
    250:     /* Compute square root of 2x2 upper triangular block */
    251:     r11 = PetscSqrtScalar(t11);
    252:     r22 = PetscSqrtScalar(t22);
    253:     T[0] = r11;
    254:     T[2] = t12/(r11+r22);
    255:     T[3] = r22;
    256:   }
    257:   return(0);
    258: }

    260: #if defined(PETSC_USE_COMPLEX)
    261: /*
    262:    Unwinding number of z
    263: */
    264: PETSC_STATIC_INLINE PetscReal unwinding(PetscScalar z)
    265: {
    266:   PetscReal u;

    269:   u = PetscCeilReal((PetscImaginaryPart(z)-PETSC_PI)/(2.0*PETSC_PI));
    270:   PetscFunctionReturn(u);
    271: }
    272: #endif

    274: /*
    275:    Power of 2-by-2 upper triangular matrix A.
    276:    Returns the (1,2) element of the pth power of A, where p is an arbitrary real number
    277: */
    278: static PetscScalar powerm2by2(PetscScalar A11,PetscScalar A22,PetscScalar A12,PetscReal p)
    279: {
    280:   PetscScalar a1,a2,a1p,a2p,loga1,loga2,w,dd,x12;

    283:   a1 = A11;
    284:   a2 = A22;
    285:   if (a1 == a2) {
    286:     x12 = p*A12*PetscPowScalarReal(a1,p-1);
    287:   } else if (PetscAbsScalar(a1) < 0.5*PetscAbsScalar(a2) || PetscAbsScalar(a2) < 0.5*PetscAbsScalar(a1)) {
    288:     a1p = PetscPowScalarReal(a1,p);
    289:     a2p = PetscPowScalarReal(a2,p);
    290:     x12 = A12*(a2p-a1p)/(a2-a1);
    291:   } else {  /* Close eigenvalues */
    292:     loga1 = PetscLogScalar(a1);
    293:     loga2 = PetscLogScalar(a2);
    294:     w = PetscAtanhScalar((a2-a1)/(a2+a1));
    295: #if defined(PETSC_USE_COMPLEX)
    296:     w += PETSC_i*PETSC_PI*unwinding(loga2-loga1);
    297: #endif
    298:     dd = 2.0*PetscExpScalar(p*(loga1+loga2)/2.0)*PetscSinhScalar(p*w)/(a2-a1);
    299:     x12 = A12*dd;
    300:   }
    301:   PetscFunctionReturn(x12);
    302: }

    304: /*
    305:    Recomputes diagonal blocks of T = X^(1/2^s) - 1 more accurately
    306: */
    307: static PetscErrorCode recompute_diag_blocks_sqrt(PetscBLASInt n,PetscScalar *Troot,PetscScalar *T,PetscBLASInt ld,PetscInt *blockStruct,PetscInt s)
    308: {
    310:   PetscScalar    A[4],P[4],M[4],Z0[4],det;
    311:   PetscInt       i,j;
    312: #if !defined(PETSC_USE_COMPLEX)
    313:   PetscInt       last_block=0;
    314:   PetscScalar    a;
    315: #endif

    318:   for (j=0;j<n-1;j++) {
    319: #if !defined(PETSC_USE_COMPLEX)
    320:     switch (blockStruct[j]) {
    321:       case 0: /* Not start of a block */
    322:         if (last_block != 0) {
    323:           last_block = 0;
    324:         } else { /* In a 1x1 block */
    325:           a = T[j+j*ld];
    326:           Troot[j+j*ld] = sqrt_obo(a,s);
    327:         }
    328:         break;
    329:       default: /* In a 2x2 block */
    330:         last_block = blockStruct[j];
    331: #endif
    332:         if (s == 0) {
    333:           Troot[j+j*ld]       = T[j+j*ld]-1.0;
    334:           Troot[j+1+j*ld]     = T[j+1+j*ld];
    335:           Troot[j+(j+1)*ld]   = T[j+(j+1)*ld];
    336:           Troot[j+1+(j+1)*ld] = T[j+1+(j+1)*ld]-1.0;
    337:           continue;
    338:         }
    339:         A[0] = T[j+j*ld]; A[1] = T[j+1+j*ld]; A[2] = T[j+(j+1)*ld]; A[3] = T[j+1+(j+1)*ld];
    340:         sqrtm_tbt(A);
    341:         /* Z0 = A - I */
    342:         Z0[0] = A[0]-1.0; Z0[1] = A[1]; Z0[2] = A[2]; Z0[3] = A[3]-1.0;
    343:         if (s == 1) {
    344:           Troot[j+j*ld]       = Z0[0];
    345:           Troot[j+1+j*ld]     = Z0[1];
    346:           Troot[j+(j+1)*ld]   = Z0[2];
    347:           Troot[j+1+(j+1)*ld] = Z0[3];
    348:           continue;
    349:         }
    350:         sqrtm_tbt(A);
    351:         /* P = A + I */
    352:         P[0] = A[0]+1.0; P[1] = A[1]; P[2] = A[2]; P[3] = A[3]+1.0;
    353:         for (i=0;i<s-2;i++) {
    354:           sqrtm_tbt(A);
    355:           /* P = P*(I + A) */
    356:           M[0] = P[0]*(A[0]+1.0)+P[2]*A[1];
    357:           M[1] = P[1]*(A[0]+1.0)+P[3]*A[1];
    358:           M[2] = P[0]*A[2]+P[2]*(A[3]+1.0);
    359:           M[3] = P[1]*A[2]+P[3]*(A[3]+1.0);
    360:           P[0] = M[0]; P[1] = M[1]; P[2] = M[2]; P[3] = M[3];
    361:         }
    362:         /* Troot(j:j+1,j:j+1) = Z0 / P (via Cramer) */
    363:         det = P[0]*P[3]-P[1]*P[2];
    364:         Troot[j+j*ld]       = (Z0[0]*P[3]-P[1]*Z0[2])/det;
    365:         Troot[j+(j+1)*ld]   = (P[0]*Z0[2]-Z0[0]*P[2])/det;
    366:         Troot[j+1+j*ld]     = (Z0[1]*P[3]-P[1]*Z0[3])/det;
    367:         Troot[j+1+(j+1)*ld] = (P[0]*Z0[3]-Z0[1]*P[2])/det;
    368:         /* If block is upper triangular recompute the (1,2) element.
    369:            Skip when T(j,j) or T(j+1,j+1) < 0 since the implementation of atanh is nonstandard */
    370:         if (T[j+1+j*ld]==0.0 && PetscRealPart(T[j+j*ld])>=0.0 && PetscRealPart(T[j+1+(j+1)*ld])>=0.0) {
    371:           Troot[j+(j+1)*ld] = powerm2by2(T[j+j*ld],T[j+1+(j+1)*ld],T[j+(j+1)*ld],1.0/PetscPowInt(2,s));
    372:         }
    373: #if !defined(PETSC_USE_COMPLEX)
    374:     }
    375: #endif
    376:   }
    377: #if !defined(PETSC_USE_COMPLEX)
    378:   /* If last diagonal entry is not in a block it will have been missed */
    379:   if (blockStruct[n-2] == 0) {
    380:     a = T[n-1+(n-1)*ld];
    381:     Troot[n-1+(n-1)*ld] = sqrt_obo(a,s);
    382:   }
    383: #endif
    384:   return(0);
    385: }

    387: /*
    388:    Nodes x and weights w for n-point Gauss-Legendre quadrature (Q is n*n workspace)

    390:    G. H. Golub and J. H. Welsch, Calculation of Gauss quadrature
    391:       rules, Math. Comp., 23(106):221-230, 1969.
    392: */
    393: static PetscErrorCode gauss_legendre(PetscBLASInt n,PetscScalar *x,PetscScalar *w,PetscScalar *Q)
    394: {
    396:   PetscScalar    v,a,*work;
    397:   PetscReal      *eig,dummy;
    398:   PetscBLASInt   k,ld=n,lwork,info;
    399: #if defined(PETSC_USE_COMPLEX)
    400:   PetscReal      *rwork,rdummy;
    401: #endif

    404:   PetscArrayzero(Q,n*n);
    405:   for (k=1;k<n;k++) {
    406:     v = k/PetscSqrtReal(4.0*k*k-1.0);
    407:     Q[k+(k-1)*n] = v;
    408:     Q[(k-1)+k*n] = v;
    409:   }

    411:   /* workspace query and memory allocation */
    412:   lwork = -1;
    413: #if defined(PETSC_USE_COMPLEX)
    414:   PetscStackCallBLAS("LAPACKsyev",LAPACKsyev_("V","L",&n,Q,&ld,&dummy,&a,&lwork,&rdummy,&info));
    415:   PetscBLASIntCast((PetscInt)PetscRealPart(a),&lwork);
    416:   PetscMalloc3(n,&eig,lwork,&work,PetscMax(1,3*n-2),&rwork);
    417: #else
    418:   PetscStackCallBLAS("LAPACKsyev",LAPACKsyev_("V","L",&n,Q,&ld,&dummy,&a,&lwork,&info));
    419:   PetscBLASIntCast((PetscInt)a,&lwork);
    420:   PetscMalloc2(n,&eig,lwork,&work);
    421: #endif

    423:   /* compute eigendecomposition */
    424: #if defined(PETSC_USE_COMPLEX)
    425:   PetscStackCallBLAS("LAPACKsyev",LAPACKsyev_("V","L",&n,Q,&ld,eig,work,&lwork,rwork,&info));
    426: #else
    427:   PetscStackCallBLAS("LAPACKsyev",LAPACKsyev_("V","L",&n,Q,&ld,eig,work,&lwork,&info));
    428: #endif
    429:   SlepcCheckLapackInfo("syev",info);

    431:   for (k=0;k<n;k++) {
    432:     x[k] = eig[k];
    433:     w[k] = 2.0*Q[k*n]*Q[k*n];
    434:   }
    435: #if defined(PETSC_USE_COMPLEX)
    436:   PetscFree3(eig,work,rwork);
    437: #else
    438:   PetscFree2(eig,work);
    439: #endif
    440:   PetscLogFlops(9.0*n*n*n+2.0*n*n*n);
    441:   return(0);
    442: }

    444: /*
    445:    Pade approximation to log(1 + T) via partial fractions
    446: */
    447: static PetscErrorCode pade_approx(PetscBLASInt n,PetscScalar *T,PetscScalar *L,PetscBLASInt ld,PetscInt m,PetscScalar *work)
    448: {
    450:   PetscScalar    *K,*W,*nodes,*wts;
    451:   PetscBLASInt   *ipiv,info;
    452:   PetscInt       i,j,k;

    455:   K     = work;
    456:   W     = work+n*n;
    457:   nodes = work+2*n*n;
    458:   wts   = work+2*n*n+m;
    459:   ipiv  = (PetscBLASInt*)(work+2*n*n+2*m);
    460:   gauss_legendre(m,nodes,wts,L);
    461:   /* Convert from [-1,1] to [0,1] */
    462:   for (i=0;i<m;i++) {
    463:     nodes[i] = (nodes[i]+1.0)/2.0;
    464:     wts[i] = wts[i]/2.0;
    465:   }
    466:   PetscArrayzero(L,n*n);
    467:   for (k=0;k<m;k++) {
    468:     for (i=0;i<n;i++) for (j=0;j<n;j++) K[i+j*ld] = nodes[k]*T[i+j*ld];
    469:     for (i=0;i<n;i++) K[i+i*ld] += 1.0;
    470:     for (i=0;i<n;i++) for (j=0;j<n;j++) W[i+j*ld] = T[i+j*ld];
    471:     PetscStackCallBLAS("LAPACKgesv",LAPACKgesv_(&n,&n,K,&n,ipiv,W,&n,&info));
    472:     for (i=0;i<n;i++) for (j=0;j<n;j++) L[i+j*ld] += wts[k]*W[i+j*ld];
    473:   }
    474:   return(0);
    475: }

    477: /*
    478:    Recomputes diagonal blocks of T = X^(1/2^s) - 1 more accurately
    479: */
    480: static PetscErrorCode recompute_diag_blocks_log(PetscBLASInt n,PetscScalar *L,PetscScalar *T,PetscBLASInt ld,PetscInt *blockStruct)
    481: {
    482:   PetscScalar a1,a2,a12,loga1,loga2,z,dd;
    483:   PetscInt    j;
    484: #if !defined(PETSC_USE_COMPLEX)
    485:   PetscInt    last_block=0;
    486:   PetscScalar f,t;
    487: #endif

    490:   for (j=0;j<n-1;j++) {
    491: #if !defined(PETSC_USE_COMPLEX)
    492:     switch (blockStruct[j]) {
    493:       case 0: /* Not start of a block */
    494:         if (last_block != 0) {
    495:           last_block = 0;
    496:         } else { /* In a 1x1 block */
    497:           L[j+j*ld] = PetscLogScalar(T[j+j*ld]);
    498:         }
    499:         break;
    500:       case 1: /* Start of upper-tri block */
    501:         last_block = 1;
    502: #endif
    503:         a1 = T[j+j*ld];
    504:         a2 = T[j+1+(j+1)*ld];
    505:         loga1 = PetscLogScalar(a1);
    506:         loga2 = PetscLogScalar(a2);
    507:         L[j+j*ld] = loga1;
    508:         L[j+1+(j+1)*ld] = loga2;
    509:         if ((PetscRealPart(a1)<0.0 && PetscImaginaryPart(a1)==0.0) || (PetscRealPart(a2)<0.0 && PetscImaginaryPart(a1)==0.0)) {
    510:          /* Problems with 2 x 2 formula for (1,2) block
    511:             since atanh is nonstandard, just redo diagonal part */
    512:           continue;
    513:         }
    514:         if (a1 == a2) {
    515:           a12 = T[j+(j+1)*ld]/a1;
    516:         } else if (PetscAbsScalar(a1)<0.5*PetscAbsScalar(a2) || PetscAbsScalar(a2)<0.5*PetscAbsScalar(a1)) {
    517:           a12 = T[j+(j+1)*ld]*(loga2-loga1)/(a2-a1);
    518:         } else {  /* Close eigenvalues */
    519:           z = (a2-a1)/(a2+a1);
    520:           dd = 2.0*PetscAtanhScalar(z);
    521: #if defined(PETSC_USE_COMPLEX)
    522:           dd += 2.0*PETSC_i*PETSC_PI*unwinding(loga2-loga1);
    523: #endif
    524:           dd /= (a2-a1);
    525:           a12 = T[j+(j+1)*ld]*dd;
    526:         }
    527:         L[j+(j+1)*ld] = a12;
    528: #if !defined(PETSC_USE_COMPLEX)
    529:         break;
    530:       case 2: /* Start of quasi-tri block */
    531:         last_block = 2;
    532:         f = 0.5*PetscLogScalar(T[j+j*ld]*T[j+j*ld]-T[j+(j+1)*ld]*T[j+1+j*ld]);
    533:         t = PetscAtan2Real(PetscSqrtScalar(-T[j+(j+1)*ld]*T[j+1+j*ld]),T[j+j*ld])/PetscSqrtScalar(-T[j+(j+1)*ld]*T[j+1+j*ld]);
    534:         L[j+j*ld]       = f;
    535:         L[j+1+j*ld]     = t*T[j+1+j*ld];
    536:         L[j+(j+1)*ld]   = t*T[j+(j+1)*ld];
    537:         L[j+1+(j+1)*ld] = f;
    538:     }
    539: #endif
    540:   }
    541:   return(0);
    542: }
    543: /*
    544:  * Matrix logarithm implementation based on algorithm and matlab code by N. Higham and co-authors
    545:  *
    546:  *     H. Al-Mohy and N. J. Higham, "Improved inverse scaling and squaring
    547:  *     algorithms for the matrix logarithm", SIAM J. Sci. Comput. 34(4):C153-C169, 2012.
    548:  */
    549: static PetscErrorCode FNLogmPade(FN fn,PetscBLASInt n,PetscScalar *T,PetscBLASInt ld,PetscBool firstonly)
    550: {
    551: #if !defined(PETSC_HAVE_COMPLEX)
    553:   SETERRQ(PETSC_COMM_SELF,1,"This function requires C99 or C++ complex support");
    554: #else
    556:   PetscBLASInt   k,sdim,lwork,info;
    557:   PetscScalar    *wr,*wi=NULL,*W,*Q,*Troot,*L,*work,one=1.0,zero=0.0,alpha;
    558:   PetscInt       i,j,s=0,m=0,*blockformat;
    559: #if defined(PETSC_USE_COMPLEX)
    560:   PetscReal      *rwork;
    561: #endif

    564:   lwork = 3*n*n; /* gees needs only 5*n, but work is also passed to FNlogm_params */
    565:   k     = firstonly? 1: n;

    567:   /* compute Schur decomposition A*Q = Q*T */
    568:   PetscCalloc7(n,&wr,n*k,&W,n*n,&Q,n*n,&Troot,n*n,&L,lwork,&work,n-1,&blockformat);
    569: #if !defined(PETSC_USE_COMPLEX)
    570:   PetscMalloc1(n,&wi);
    571:   PetscStackCallBLAS("LAPACKgees",LAPACKgees_("V","N",NULL,&n,T,&ld,&sdim,wr,wi,Q,&ld,work,&lwork,NULL,&info));
    572: #else
    573:   PetscMalloc1(n,&rwork);
    574:   PetscStackCallBLAS("LAPACKgees",LAPACKgees_("V","N",NULL,&n,T,&ld,&sdim,wr,Q,&ld,work,&lwork,rwork,NULL,&info));
    575: #endif
    576:   SlepcCheckLapackInfo("gees",info);

    578: #if !defined(PETSC_USE_COMPLEX)
    579:   /* check for negative real eigenvalues */
    580:   for (i=0;i<n;i++) {
    581:     if (wr[i]<0.0 && wi[i]==0.0) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_SUP,"Matrix has negative real eigenvalue; rerun with complex scalars");
    582:   }
    583: #endif

    585:   /* get block structure of Schur factor */
    586:   qtri_struct(n,T,ld,blockformat);

    588:   /* get parameters */
    589:   FNlogm_params(fn,n,T,ld,wr,wi,100,&s,&m,Troot,work);

    591:   /* compute Troot - I = T(1/2^s) - I more accurately */
    592:   recompute_diag_blocks_sqrt(n,Troot,T,ld,blockformat,s);

    594:   /* compute Pade approximant */
    595:   pade_approx(n,Troot,L,ld,m,work);

    597:   /* scale back up, L = 2^s * L */
    598:   alpha = PetscPowInt(2,s);
    599:   for (i=0;i<n;i++) for (j=0;j<n;j++) L[i+j*ld] *= alpha;

    601:   /* recompute diagonal blocks */
    602:   recompute_diag_blocks_log(n,L,T,ld,blockformat);

    604:   /* backtransform B = Q*L*Q' */
    605:   PetscStackCallBLAS("BLASgemm",BLASgemm_("N","C",&n,&k,&n,&one,L,&ld,Q,&ld,&zero,W,&ld));
    606:   PetscStackCallBLAS("BLASgemm",BLASgemm_("N","N",&n,&k,&n,&one,Q,&ld,W,&ld,&zero,T,&ld));

    608:   /* flop count: Schur decomposition, and backtransform */
    609:   PetscLogFlops(25.0*n*n*n+4.0*n*n*k);

    611:   PetscFree7(wr,W,Q,Troot,L,work,blockformat);
    612: #if !defined(PETSC_USE_COMPLEX)
    613:   PetscFree(wi);
    614: #else
    615:   PetscFree(rwork);
    616: #endif
    617:   return(0);
    618: #endif
    619: }

    621: PetscErrorCode FNEvaluateFunctionMat_Log_Higham(FN fn,Mat A,Mat B)
    622: {
    624:   PetscBLASInt   n = 0;
    625:   PetscScalar    *T;
    626:   PetscInt       m;

    629:   if (A!=B) { MatCopy(A,B,SAME_NONZERO_PATTERN); }
    630:   MatDenseGetArray(B,&T);
    631:   MatGetSize(A,&m,NULL);
    632:   PetscBLASIntCast(m,&n);
    633:   FNLogmPade(fn,n,T,n,PETSC_FALSE);
    634:   MatDenseRestoreArray(B,&T);
    635:   return(0);
    636: }

    638: PetscErrorCode FNEvaluateFunctionMatVec_Log_Higham(FN fn,Mat A,Vec v)
    639: {
    641:   PetscBLASInt   n = 0;
    642:   PetscScalar    *T;
    643:   PetscInt       m;
    644:   Mat            B;

    647:   FN_AllocateWorkMat(fn,A,&B);
    648:   MatDenseGetArray(B,&T);
    649:   MatGetSize(A,&m,NULL);
    650:   PetscBLASIntCast(m,&n);
    651:   FNLogmPade(fn,n,T,n,PETSC_TRUE);
    652:   MatDenseRestoreArray(B,&T);
    653:   MatGetColumnVector(B,v,0);
    654:   FN_FreeWorkMat(fn,&B);
    655:   return(0);
    656: }

    658: PetscErrorCode FNView_Log(FN fn,PetscViewer viewer)
    659: {
    661:   PetscBool      isascii;
    662:   char           str[50];
    663:   const char     *methodname[] = {
    664:                   "scaling & squaring, [m/m] Pade approximant (Higham)"
    665:   };
    666:   const int      nmeth=sizeof(methodname)/sizeof(methodname[0]);

    669:   PetscObjectTypeCompare((PetscObject)viewer,PETSCVIEWERASCII,&isascii);
    670:   if (isascii) {
    671:     if (fn->beta==(PetscScalar)1.0) {
    672:       if (fn->alpha==(PetscScalar)1.0) {
    673:         PetscViewerASCIIPrintf(viewer,"  Logarithm: log(x)\n");
    674:       } else {
    675:         SlepcSNPrintfScalar(str,sizeof(str),fn->alpha,PETSC_TRUE);
    676:         PetscViewerASCIIPrintf(viewer,"  Logarithm: log(%s*x)\n",str);
    677:       }
    678:     } else {
    679:       SlepcSNPrintfScalar(str,sizeof(str),fn->beta,PETSC_TRUE);
    680:       if (fn->alpha==(PetscScalar)1.0) {
    681:         PetscViewerASCIIPrintf(viewer,"  Logarithm: %s*log(x)\n",str);
    682:       } else {
    683:         PetscViewerASCIIPrintf(viewer,"  Logarithm: %s",str);
    684:         PetscViewerASCIIUseTabs(viewer,PETSC_FALSE);
    685:         SlepcSNPrintfScalar(str,sizeof(str),fn->alpha,PETSC_TRUE);
    686:         PetscViewerASCIIPrintf(viewer,"*log(%s*x)\n",str);
    687:         PetscViewerASCIIUseTabs(viewer,PETSC_TRUE);
    688:       }
    689:     }
    690:     if (fn->method<nmeth) {
    691:       PetscViewerASCIIPrintf(viewer,"  computing matrix functions with: %s\n",methodname[fn->method]);
    692:     }
    693:   }
    694:   return(0);
    695: }

    697: SLEPC_EXTERN PetscErrorCode FNCreate_Log(FN fn)
    698: {
    700:   fn->ops->evaluatefunction          = FNEvaluateFunction_Log;
    701:   fn->ops->evaluatederivative        = FNEvaluateDerivative_Log;
    702:   fn->ops->evaluatefunctionmat[0]    = FNEvaluateFunctionMat_Log_Higham;
    703:   fn->ops->evaluatefunctionmatvec[0] = FNEvaluateFunctionMatVec_Log_Higham;
    704:   fn->ops->view                      = FNView_Log;
    705:   return(0);
    706: }