1e27a552bSJed Brown /* 261692a83SJed Brown Code for timestepping with Rosenbrock W methods 3e27a552bSJed Brown 4e27a552bSJed Brown Notes: 5e27a552bSJed Brown The general system is written as 6e27a552bSJed Brown 761692a83SJed Brown G(t,X,Xdot) = F(t,X) 8e27a552bSJed Brown 961692a83SJed Brown where G represents the stiff part of the physics and F represents the non-stiff part. 1061692a83SJed Brown This method is designed to be linearly implicit on G and can use an approximate and lagged Jacobian. 11e27a552bSJed Brown 12e27a552bSJed Brown */ 13e27a552bSJed Brown #include <private/tsimpl.h> /*I "petscts.h" I*/ 14e27a552bSJed Brown 1561692a83SJed Brown #include <../src/mat/blockinvert.h> 1661692a83SJed Brown 1761692a83SJed Brown static const TSRosWType TSRosWDefault = TSROSW2P; 18e27a552bSJed Brown static PetscBool TSRosWRegisterAllCalled; 19e27a552bSJed Brown static PetscBool TSRosWPackageInitialized; 20e27a552bSJed Brown 2161692a83SJed Brown typedef struct _RosWTableau *RosWTableau; 2261692a83SJed Brown struct _RosWTableau { 23e27a552bSJed Brown char *name; 24e27a552bSJed Brown PetscInt order; /* Classical approximation order of the method */ 25e27a552bSJed Brown PetscInt s; /* Number of stages */ 2661692a83SJed Brown PetscReal *A; /* Propagation table, strictly lower triangular */ 2761692a83SJed Brown PetscReal *Gamma; /* Stage table, lower triangular with nonzero diagonal */ 28c17803e7SJed Brown PetscBool *GammaZeroDiag; /* Diagonal entries that are zero in stage table Gamma, vector indicating explicit statages */ 2961692a83SJed Brown PetscReal *b; /* Step completion table */ 30fe7e6d57SJed Brown PetscReal *bembed; /* Step completion table for embedded method of order one less */ 3161692a83SJed Brown PetscReal *ASum; /* Row sum of A */ 3261692a83SJed Brown PetscReal *GammaSum; /* Row sum of Gamma, only needed for non-autonomous systems */ 3361692a83SJed Brown PetscReal *At; /* Propagation table in transformed variables */ 3461692a83SJed Brown PetscReal *bt; /* Step completion table in transformed variables */ 35fe7e6d57SJed Brown PetscReal *bembedt; /* Step completion table of order one less in transformed variables */ 3661692a83SJed Brown PetscReal *GammaInv; /* Inverse of Gamma, used for transformed variables */ 37*8d59e960SJed Brown PetscReal ccfl; /* Placeholder for CFL coefficient relative to forward Euler */ 38e27a552bSJed Brown }; 3961692a83SJed Brown typedef struct _RosWTableauLink *RosWTableauLink; 4061692a83SJed Brown struct _RosWTableauLink { 4161692a83SJed Brown struct _RosWTableau tab; 4261692a83SJed Brown RosWTableauLink next; 43e27a552bSJed Brown }; 4461692a83SJed Brown static RosWTableauLink RosWTableauList; 45e27a552bSJed Brown 46e27a552bSJed Brown typedef struct { 4761692a83SJed Brown RosWTableau tableau; 4861692a83SJed Brown Vec *Y; /* States computed during the step, used to complete the step */ 49e27a552bSJed Brown Vec Ydot; /* Work vector holding Ydot during residual evaluation */ 5061692a83SJed Brown Vec Ystage; /* Work vector for the state value at each stage */ 5161692a83SJed Brown Vec Zdot; /* Ydot = Zdot + shift*Y */ 5261692a83SJed Brown Vec Zstage; /* Y = Zstage + Y */ 531c3436cfSJed Brown PetscScalar *work; /* Scalar work space of length number of stages, used to prepare VecMAXPY() */ 54e27a552bSJed Brown PetscReal shift; 55e27a552bSJed Brown PetscReal stage_time; 56c17803e7SJed Brown PetscReal stage_explicit; /* Flag indicates that the current stage is explicit */ 5761692a83SJed Brown PetscBool recompute_jacobian; /* Recompute the Jacobian at each stage, default is to freeze the Jacobian at the start of each step */ 581c3436cfSJed Brown PetscBool step_taken; /* ts->vec_sol has been advanced to the end of the current time step */ 59e27a552bSJed Brown } TS_RosW; 60e27a552bSJed Brown 61fe7e6d57SJed Brown /*MC 62fe7e6d57SJed Brown TSROSW2M - Two stage second order L-stable Rosenbrock-W scheme. 63fe7e6d57SJed Brown 64fe7e6d57SJed Brown Only an approximate Jacobian is needed. By default, it is only recomputed once per step. This method is a reflection of TSROSW2P. 65fe7e6d57SJed Brown 66fe7e6d57SJed Brown Level: intermediate 67fe7e6d57SJed Brown 68fe7e6d57SJed Brown .seealso: TSROSW 69fe7e6d57SJed Brown M*/ 70fe7e6d57SJed Brown 71fe7e6d57SJed Brown /*MC 72fe7e6d57SJed Brown TSROSW2P - Two stage second order L-stable Rosenbrock-W scheme. 73fe7e6d57SJed Brown 74fe7e6d57SJed Brown Only an approximate Jacobian is needed. By default, it is only recomputed once per step. This method is a reflection of TSROSW2M. 75fe7e6d57SJed Brown 76fe7e6d57SJed Brown Level: intermediate 77fe7e6d57SJed Brown 78fe7e6d57SJed Brown .seealso: TSROSW 79fe7e6d57SJed Brown M*/ 80fe7e6d57SJed Brown 81fe7e6d57SJed Brown /*MC 82fe7e6d57SJed Brown TSROSWRA3PW - Three stage third order Rosenbrock-W scheme for PDAE of index 1. 83fe7e6d57SJed Brown 84fe7e6d57SJed Brown Only an approximate Jacobian is needed. By default, it is only recomputed once per step. 85fe7e6d57SJed Brown 86fe7e6d57SJed Brown This is strongly A-stable with R(infty) = 0.73. The embedded method of order 2 is strongly A-stable with R(infty) = 0.73. 87fe7e6d57SJed Brown 88fe7e6d57SJed Brown References: 89fe7e6d57SJed Brown Rang and Angermann, New Rosenbrock-W methods of order 3 for partial differential algebraic equations of index 1, 2005. 90fe7e6d57SJed Brown 91fe7e6d57SJed Brown Level: intermediate 92fe7e6d57SJed Brown 93fe7e6d57SJed Brown .seealso: TSROSW 94fe7e6d57SJed Brown M*/ 95fe7e6d57SJed Brown 96fe7e6d57SJed Brown /*MC 97fe7e6d57SJed Brown TSROSWRA34PW2 - Four stage third order L-stable Rosenbrock-W scheme for PDAE of index 1. 98fe7e6d57SJed Brown 99fe7e6d57SJed Brown Only an approximate Jacobian is needed. By default, it is only recomputed once per step. 100fe7e6d57SJed Brown 101fe7e6d57SJed Brown This is strongly A-stable with R(infty) = 0. The embedded method of order 2 is strongly A-stable with R(infty) = 0.48. 102fe7e6d57SJed Brown 103fe7e6d57SJed Brown References: 104fe7e6d57SJed Brown Rang and Angermann, New Rosenbrock-W methods of order 3 for partial differential algebraic equations of index 1, 2005. 105fe7e6d57SJed Brown 106fe7e6d57SJed Brown Level: intermediate 107fe7e6d57SJed Brown 108fe7e6d57SJed Brown .seealso: TSROSW 109fe7e6d57SJed Brown M*/ 110fe7e6d57SJed Brown 111e27a552bSJed Brown #undef __FUNCT__ 112e27a552bSJed Brown #define __FUNCT__ "TSRosWRegisterAll" 113e27a552bSJed Brown /*@C 114e27a552bSJed Brown TSRosWRegisterAll - Registers all of the additive Runge-Kutta implicit-explicit methods in TSRosW 115e27a552bSJed Brown 116e27a552bSJed Brown Not Collective, but should be called by all processes which will need the schemes to be registered 117e27a552bSJed Brown 118e27a552bSJed Brown Level: advanced 119e27a552bSJed Brown 120e27a552bSJed Brown .keywords: TS, TSRosW, register, all 121e27a552bSJed Brown 122e27a552bSJed Brown .seealso: TSRosWRegisterDestroy() 123e27a552bSJed Brown @*/ 124e27a552bSJed Brown PetscErrorCode TSRosWRegisterAll(void) 125e27a552bSJed Brown { 126e27a552bSJed Brown PetscErrorCode ierr; 127e27a552bSJed Brown 128e27a552bSJed Brown PetscFunctionBegin; 129e27a552bSJed Brown if (TSRosWRegisterAllCalled) PetscFunctionReturn(0); 130e27a552bSJed Brown TSRosWRegisterAllCalled = PETSC_TRUE; 131e27a552bSJed Brown 132e27a552bSJed Brown { 13361692a83SJed Brown const PetscReal g = 1. + 1./PetscSqrtReal(2.0); 134e27a552bSJed Brown const PetscReal 13561692a83SJed Brown A[2][2] = {{0,0}, {1.,0}}, 13661692a83SJed Brown Gamma[2][2] = {{g,0}, {-2.*g,g}}, 1371c3436cfSJed Brown b[2] = {0.5,0.5}, 1381c3436cfSJed Brown b1[2] = {1.0,0.0}; 1391c3436cfSJed Brown ierr = TSRosWRegister(TSROSW2P,2,2,&A[0][0],&Gamma[0][0],b,b1);CHKERRQ(ierr); 140e27a552bSJed Brown } 141e27a552bSJed Brown { 14261692a83SJed Brown const PetscReal g = 1. - 1./PetscSqrtReal(2.0); 143e27a552bSJed Brown const PetscReal 14461692a83SJed Brown A[2][2] = {{0,0}, {1.,0}}, 14561692a83SJed Brown Gamma[2][2] = {{g,0}, {-2.*g,g}}, 1461c3436cfSJed Brown b[2] = {0.5,0.5}, 1471c3436cfSJed Brown b1[2] = {1.0,0.0}; 1481c3436cfSJed Brown ierr = TSRosWRegister(TSROSW2M,2,2,&A[0][0],&Gamma[0][0],b,b1);CHKERRQ(ierr); 149fe7e6d57SJed Brown } 150fe7e6d57SJed Brown { 151fe7e6d57SJed Brown const PetscReal g = 7.8867513459481287e-01; 152fe7e6d57SJed Brown const PetscReal 153fe7e6d57SJed Brown A[3][3] = {{0,0,0}, 154fe7e6d57SJed Brown {1.5773502691896257e+00,0,0}, 155fe7e6d57SJed Brown {0.5,0,0}}, 156fe7e6d57SJed Brown Gamma[3][3] = {{g,0,0}, 157fe7e6d57SJed Brown {-1.5773502691896257e+00,g,0}, 158fe7e6d57SJed Brown {-6.7075317547305480e-01,1.7075317547305482e-01,g}}, 159fe7e6d57SJed Brown b[3] = {1.0566243270259355e-01,4.9038105676657971e-02,8.4529946162074843e-01}, 160fe7e6d57SJed Brown b2[3] = {-1.7863279495408180e-01,1./3.,8.4529946162074843e-01}; 161fe7e6d57SJed Brown ierr = TSRosWRegister(TSROSWRA3PW,3,3,&A[0][0],&Gamma[0][0],b,b2);CHKERRQ(ierr); 162fe7e6d57SJed Brown } 163fe7e6d57SJed Brown { 164fe7e6d57SJed Brown const PetscReal g = 4.3586652150845900e-01; 165fe7e6d57SJed Brown const PetscReal 166fe7e6d57SJed Brown A[4][4] = {{0,0,0,0}, 167fe7e6d57SJed Brown {8.7173304301691801e-01,0,0,0}, 168fe7e6d57SJed Brown {8.4457060015369423e-01,-1.1299064236484185e-01,0,0}, 169fe7e6d57SJed Brown {0,0,1.,0}}, 170fe7e6d57SJed Brown Gamma[4][4] = {{g,0,0,0}, 171fe7e6d57SJed Brown {-8.7173304301691801e-01,g,0,0}, 172fe7e6d57SJed Brown {-9.0338057013044082e-01,5.4180672388095326e-02,g,0}, 173fe7e6d57SJed Brown {2.4212380706095346e-01,-1.2232505839045147e+00,5.4526025533510214e-01,g}}, 174fe7e6d57SJed Brown b[4] = {2.4212380706095346e-01,-1.2232505839045147e+00,1.5452602553351020e+00,4.3586652150845900e-01}, 175fe7e6d57SJed Brown b2[4] = {3.7810903145819369e-01,-9.6042292212423178e-02,5.0000000000000000e-01,2.1793326075422950e-01}; 176fe7e6d57SJed Brown ierr = TSRosWRegister(TSROSWRA34PW2,3,4,&A[0][0],&Gamma[0][0],b,b2);CHKERRQ(ierr); 177e27a552bSJed Brown } 178e27a552bSJed Brown PetscFunctionReturn(0); 179e27a552bSJed Brown } 180e27a552bSJed Brown 181e27a552bSJed Brown #undef __FUNCT__ 182e27a552bSJed Brown #define __FUNCT__ "TSRosWRegisterDestroy" 183e27a552bSJed Brown /*@C 184e27a552bSJed Brown TSRosWRegisterDestroy - Frees the list of schemes that were registered by TSRosWRegister(). 185e27a552bSJed Brown 186e27a552bSJed Brown Not Collective 187e27a552bSJed Brown 188e27a552bSJed Brown Level: advanced 189e27a552bSJed Brown 190e27a552bSJed Brown .keywords: TSRosW, register, destroy 191e27a552bSJed Brown .seealso: TSRosWRegister(), TSRosWRegisterAll(), TSRosWRegisterDynamic() 192e27a552bSJed Brown @*/ 193e27a552bSJed Brown PetscErrorCode TSRosWRegisterDestroy(void) 194e27a552bSJed Brown { 195e27a552bSJed Brown PetscErrorCode ierr; 19661692a83SJed Brown RosWTableauLink link; 197e27a552bSJed Brown 198e27a552bSJed Brown PetscFunctionBegin; 19961692a83SJed Brown while ((link = RosWTableauList)) { 20061692a83SJed Brown RosWTableau t = &link->tab; 20161692a83SJed Brown RosWTableauList = link->next; 20261692a83SJed Brown ierr = PetscFree5(t->A,t->Gamma,t->b,t->ASum,t->GammaSum);CHKERRQ(ierr); 203c17803e7SJed Brown ierr = PetscFree4(t->At,t->bt,t->GammaInv,t->GammaZeroDiag);CHKERRQ(ierr); 204fe7e6d57SJed Brown ierr = PetscFree2(t->bembed,t->bembedt);CHKERRQ(ierr); 205e27a552bSJed Brown ierr = PetscFree(t->name);CHKERRQ(ierr); 206e27a552bSJed Brown ierr = PetscFree(link);CHKERRQ(ierr); 207e27a552bSJed Brown } 208e27a552bSJed Brown TSRosWRegisterAllCalled = PETSC_FALSE; 209e27a552bSJed Brown PetscFunctionReturn(0); 210e27a552bSJed Brown } 211e27a552bSJed Brown 212e27a552bSJed Brown #undef __FUNCT__ 213e27a552bSJed Brown #define __FUNCT__ "TSRosWInitializePackage" 214e27a552bSJed Brown /*@C 215e27a552bSJed Brown TSRosWInitializePackage - This function initializes everything in the TSRosW package. It is called 216e27a552bSJed Brown from PetscDLLibraryRegister() when using dynamic libraries, and on the first call to TSCreate_RosW() 217e27a552bSJed Brown when using static libraries. 218e27a552bSJed Brown 219e27a552bSJed Brown Input Parameter: 220e27a552bSJed Brown path - The dynamic library path, or PETSC_NULL 221e27a552bSJed Brown 222e27a552bSJed Brown Level: developer 223e27a552bSJed Brown 224e27a552bSJed Brown .keywords: TS, TSRosW, initialize, package 225e27a552bSJed Brown .seealso: PetscInitialize() 226e27a552bSJed Brown @*/ 227e27a552bSJed Brown PetscErrorCode TSRosWInitializePackage(const char path[]) 228e27a552bSJed Brown { 229e27a552bSJed Brown PetscErrorCode ierr; 230e27a552bSJed Brown 231e27a552bSJed Brown PetscFunctionBegin; 232e27a552bSJed Brown if (TSRosWPackageInitialized) PetscFunctionReturn(0); 233e27a552bSJed Brown TSRosWPackageInitialized = PETSC_TRUE; 234e27a552bSJed Brown ierr = TSRosWRegisterAll();CHKERRQ(ierr); 235e27a552bSJed Brown ierr = PetscRegisterFinalize(TSRosWFinalizePackage);CHKERRQ(ierr); 236e27a552bSJed Brown PetscFunctionReturn(0); 237e27a552bSJed Brown } 238e27a552bSJed Brown 239e27a552bSJed Brown #undef __FUNCT__ 240e27a552bSJed Brown #define __FUNCT__ "TSRosWFinalizePackage" 241e27a552bSJed Brown /*@C 242e27a552bSJed Brown TSRosWFinalizePackage - This function destroys everything in the TSRosW package. It is 243e27a552bSJed Brown called from PetscFinalize(). 244e27a552bSJed Brown 245e27a552bSJed Brown Level: developer 246e27a552bSJed Brown 247e27a552bSJed Brown .keywords: Petsc, destroy, package 248e27a552bSJed Brown .seealso: PetscFinalize() 249e27a552bSJed Brown @*/ 250e27a552bSJed Brown PetscErrorCode TSRosWFinalizePackage(void) 251e27a552bSJed Brown { 252e27a552bSJed Brown PetscErrorCode ierr; 253e27a552bSJed Brown 254e27a552bSJed Brown PetscFunctionBegin; 255e27a552bSJed Brown TSRosWPackageInitialized = PETSC_FALSE; 256e27a552bSJed Brown ierr = TSRosWRegisterDestroy();CHKERRQ(ierr); 257e27a552bSJed Brown PetscFunctionReturn(0); 258e27a552bSJed Brown } 259e27a552bSJed Brown 260e27a552bSJed Brown #undef __FUNCT__ 261e27a552bSJed Brown #define __FUNCT__ "TSRosWRegister" 262e27a552bSJed Brown /*@C 26361692a83SJed Brown TSRosWRegister - register a Rosenbrock W scheme by providing the entries in the Butcher tableau and optionally embedded approximations and interpolation 264e27a552bSJed Brown 265e27a552bSJed Brown Not Collective, but the same schemes should be registered on all processes on which they will be used 266e27a552bSJed Brown 267e27a552bSJed Brown Input Parameters: 268e27a552bSJed Brown + name - identifier for method 269e27a552bSJed Brown . order - approximation order of method 270e27a552bSJed Brown . s - number of stages, this is the dimension of the matrices below 27161692a83SJed Brown . A - Table of propagated stage coefficients (dimension s*s, row-major), strictly lower triangular 27261692a83SJed Brown . Gamma - Table of coefficients in implicit stage equations (dimension s*s, row-major), lower triangular with nonzero diagonal 273fe7e6d57SJed Brown . b - Step completion table (dimension s) 274fe7e6d57SJed Brown - bembed - Step completion table for a scheme of order one less (dimension s, PETSC_NULL if no embedded scheme is available) 275e27a552bSJed Brown 276e27a552bSJed Brown Notes: 27761692a83SJed Brown Several Rosenbrock W methods are provided, this function is only needed to create new methods. 278e27a552bSJed Brown 279e27a552bSJed Brown Level: advanced 280e27a552bSJed Brown 281e27a552bSJed Brown .keywords: TS, register 282e27a552bSJed Brown 283e27a552bSJed Brown .seealso: TSRosW 284e27a552bSJed Brown @*/ 285e27a552bSJed Brown PetscErrorCode TSRosWRegister(const TSRosWType name,PetscInt order,PetscInt s, 286fe7e6d57SJed Brown const PetscReal A[],const PetscReal Gamma[],const PetscReal b[],const PetscReal bembed[]) 287e27a552bSJed Brown { 288e27a552bSJed Brown PetscErrorCode ierr; 28961692a83SJed Brown RosWTableauLink link; 29061692a83SJed Brown RosWTableau t; 29161692a83SJed Brown PetscInt i,j,k; 29261692a83SJed Brown PetscScalar *GammaInv; 293e27a552bSJed Brown 294e27a552bSJed Brown PetscFunctionBegin; 295fe7e6d57SJed Brown PetscValidCharPointer(name,1); 296fe7e6d57SJed Brown PetscValidPointer(A,4); 297fe7e6d57SJed Brown PetscValidPointer(Gamma,5); 298fe7e6d57SJed Brown PetscValidPointer(b,6); 299fe7e6d57SJed Brown if (bembed) PetscValidPointer(bembed,7); 300fe7e6d57SJed Brown 301e27a552bSJed Brown ierr = PetscMalloc(sizeof(*link),&link);CHKERRQ(ierr); 302e27a552bSJed Brown ierr = PetscMemzero(link,sizeof(*link));CHKERRQ(ierr); 303e27a552bSJed Brown t = &link->tab; 304e27a552bSJed Brown ierr = PetscStrallocpy(name,&t->name);CHKERRQ(ierr); 305e27a552bSJed Brown t->order = order; 306e27a552bSJed Brown t->s = s; 30761692a83SJed Brown ierr = PetscMalloc5(s*s,PetscReal,&t->A,s*s,PetscReal,&t->Gamma,s,PetscReal,&t->b,s,PetscReal,&t->ASum,s,PetscReal,&t->GammaSum);CHKERRQ(ierr); 308c17803e7SJed Brown ierr = PetscMalloc4(s*s,PetscReal,&t->At,s,PetscReal,&t->bt,s*s,PetscReal,&t->GammaInv,s,PetscBool,&t->GammaZeroDiag);CHKERRQ(ierr); 309e27a552bSJed Brown ierr = PetscMemcpy(t->A,A,s*s*sizeof(A[0]));CHKERRQ(ierr); 31061692a83SJed Brown ierr = PetscMemcpy(t->Gamma,Gamma,s*s*sizeof(Gamma[0]));CHKERRQ(ierr); 31161692a83SJed Brown ierr = PetscMemcpy(t->b,b,s*sizeof(b[0]));CHKERRQ(ierr); 312fe7e6d57SJed Brown if (bembed) { 313fe7e6d57SJed Brown ierr = PetscMalloc2(s,PetscReal,&t->bembed,s,PetscReal,&t->bembedt);CHKERRQ(ierr); 314fe7e6d57SJed Brown ierr = PetscMemcpy(t->bembed,bembed,s*sizeof(bembed[0]));CHKERRQ(ierr); 315fe7e6d57SJed Brown } 31661692a83SJed Brown for (i=0; i<s; i++) { 31761692a83SJed Brown t->ASum[i] = 0; 31861692a83SJed Brown t->GammaSum[i] = 0; 31961692a83SJed Brown for (j=0; j<s; j++) { 32061692a83SJed Brown t->ASum[i] += A[i*s+j]; 321fe7e6d57SJed Brown t->GammaSum[i] += Gamma[i*s+j]; 32261692a83SJed Brown } 32361692a83SJed Brown } 32461692a83SJed Brown ierr = PetscMalloc(s*s*sizeof(PetscScalar),&GammaInv);CHKERRQ(ierr); /* Need to use Scalar for inverse, then convert back to Real */ 32561692a83SJed Brown for (i=0; i<s*s; i++) GammaInv[i] = Gamma[i]; 326fd96d5b0SEmil Constantinescu for (i=0; i<s; i++) { 327fd96d5b0SEmil Constantinescu if (Gamma[i*s+i] == 0.0) { 328fd96d5b0SEmil Constantinescu GammaInv[i*s+i] = 1.0; 329c17803e7SJed Brown t->GammaZeroDiag[i] = PETSC_TRUE; 330fd96d5b0SEmil Constantinescu } else { 331c17803e7SJed Brown t->GammaZeroDiag[i] = PETSC_FALSE; 332fd96d5b0SEmil Constantinescu } 333fd96d5b0SEmil Constantinescu } 334fd96d5b0SEmil Constantinescu 33561692a83SJed Brown switch (s) { 33661692a83SJed Brown case 1: GammaInv[0] = 1./GammaInv[0]; break; 33761692a83SJed Brown case 2: ierr = Kernel_A_gets_inverse_A_2(GammaInv,0);CHKERRQ(ierr); break; 33861692a83SJed Brown case 3: ierr = Kernel_A_gets_inverse_A_3(GammaInv,0);CHKERRQ(ierr); break; 33961692a83SJed Brown case 4: ierr = Kernel_A_gets_inverse_A_4(GammaInv,0);CHKERRQ(ierr); break; 34061692a83SJed Brown case 5: { 34161692a83SJed Brown PetscInt ipvt5[5]; 34261692a83SJed Brown MatScalar work5[5*5]; 34361692a83SJed Brown ierr = Kernel_A_gets_inverse_A_5(GammaInv,ipvt5,work5,0);CHKERRQ(ierr); break; 34461692a83SJed Brown } 34561692a83SJed Brown case 6: ierr = Kernel_A_gets_inverse_A_6(GammaInv,0);CHKERRQ(ierr); break; 34661692a83SJed Brown case 7: ierr = Kernel_A_gets_inverse_A_7(GammaInv,0);CHKERRQ(ierr); break; 34761692a83SJed Brown default: SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_SUP,"Not implemented for %D stages",s); 34861692a83SJed Brown } 34961692a83SJed Brown for (i=0; i<s*s; i++) t->GammaInv[i] = PetscRealPart(GammaInv[i]); 35061692a83SJed Brown ierr = PetscFree(GammaInv);CHKERRQ(ierr); 35161692a83SJed Brown for (i=0; i<s; i++) { 35261692a83SJed Brown for (j=0; j<s; j++) { 35361692a83SJed Brown t->At[i*s+j] = 0; 35461692a83SJed Brown for (k=0; k<s; k++) { 35561692a83SJed Brown t->At[i*s+j] += t->A[i*s+k] * t->GammaInv[k*s+j]; 35661692a83SJed Brown } 35761692a83SJed Brown } 35861692a83SJed Brown t->bt[i] = 0; 35961692a83SJed Brown for (j=0; j<s; j++) { 36061692a83SJed Brown t->bt[i] += t->b[j] * t->GammaInv[j*s+i]; 36161692a83SJed Brown } 362fe7e6d57SJed Brown if (bembed) { 363fe7e6d57SJed Brown t->bembedt[i] = 0; 364fe7e6d57SJed Brown for (j=0; j<s; j++) { 365fe7e6d57SJed Brown t->bembedt[i] += t->bembed[j] * t->GammaInv[j*s+i]; 366fe7e6d57SJed Brown } 367fe7e6d57SJed Brown } 36861692a83SJed Brown } 369*8d59e960SJed Brown t->ccfl = 1.0; /* Fix this */ 370*8d59e960SJed Brown 37161692a83SJed Brown link->next = RosWTableauList; 37261692a83SJed Brown RosWTableauList = link; 373e27a552bSJed Brown PetscFunctionReturn(0); 374e27a552bSJed Brown } 375e27a552bSJed Brown 376e27a552bSJed Brown #undef __FUNCT__ 3771c3436cfSJed Brown #define __FUNCT__ "TSEvaluateStep_RosW" 3781c3436cfSJed Brown /* 3791c3436cfSJed Brown The step completion formula is 3801c3436cfSJed Brown 3811c3436cfSJed Brown x1 = x0 + b^T Y 3821c3436cfSJed Brown 3831c3436cfSJed Brown where Y is the multi-vector of stages corrections. This function can be called before or after ts->vec_sol has been 3841c3436cfSJed Brown updated. Suppose we have a completion formula b and an embedded formula be of different order. We can write 3851c3436cfSJed Brown 3861c3436cfSJed Brown x1e = x0 + be^T Y 3871c3436cfSJed Brown = x1 - b^T Y + be^T Y 3881c3436cfSJed Brown = x1 + (be - b)^T Y 3891c3436cfSJed Brown 3901c3436cfSJed Brown so we can evaluate the method of different order even after the step has been optimistically completed. 3911c3436cfSJed Brown */ 3921c3436cfSJed Brown static PetscErrorCode TSEvaluateStep_RosW(TS ts,PetscInt order,Vec X,PetscBool *done) 3931c3436cfSJed Brown { 3941c3436cfSJed Brown TS_RosW *ros = (TS_RosW*)ts->data; 3951c3436cfSJed Brown RosWTableau tab = ros->tableau; 3961c3436cfSJed Brown PetscScalar *w = ros->work; 3971c3436cfSJed Brown PetscInt i; 3981c3436cfSJed Brown PetscErrorCode ierr; 3991c3436cfSJed Brown 4001c3436cfSJed Brown PetscFunctionBegin; 4011c3436cfSJed Brown if (order == tab->order) { 4021c3436cfSJed Brown if (ros->step_taken) {ierr = VecCopy(ts->vec_sol,X);CHKERRQ(ierr);} 4031c3436cfSJed Brown else { 4041c3436cfSJed Brown ierr = VecCopy(ts->vec_sol,X);CHKERRQ(ierr); 4051c3436cfSJed Brown ierr = VecMAXPY(X,tab->s,tab->bt,ros->Y);CHKERRQ(ierr); 4061c3436cfSJed Brown } 4071c3436cfSJed Brown if (done) *done = PETSC_TRUE; 4081c3436cfSJed Brown PetscFunctionReturn(0); 4091c3436cfSJed Brown } else if (order == tab->order-1) { 4101c3436cfSJed Brown if (!tab->bembedt) goto unavailable; 4111c3436cfSJed Brown if (ros->step_taken) { 4121c3436cfSJed Brown for (i=0; i<tab->s; i++) w[i] = tab->bembedt[i] - tab->bt[i]; 4131c3436cfSJed Brown ierr = VecCopy(ts->vec_sol,X);CHKERRQ(ierr); 4141c3436cfSJed Brown ierr = VecMAXPY(X,tab->s,w,ros->Y);CHKERRQ(ierr); 4151c3436cfSJed Brown } else { 4161c3436cfSJed Brown ierr = VecCopy(ts->vec_sol,X);CHKERRQ(ierr); 4171c3436cfSJed Brown ierr = VecMAXPY(X,tab->s,tab->bembedt,ros->Y);CHKERRQ(ierr); 4181c3436cfSJed Brown } 4191c3436cfSJed Brown if (done) *done = PETSC_TRUE; 4201c3436cfSJed Brown PetscFunctionReturn(0); 4211c3436cfSJed Brown } 4221c3436cfSJed Brown unavailable: 4231c3436cfSJed Brown if (done) *done = PETSC_FALSE; 4241c3436cfSJed Brown else SETERRQ3(((PetscObject)ts)->comm,PETSC_ERR_SUP,"Rosenbrock-W '%s' of order %D cannot evaluate step at order %D",tab->name,tab->order,order); 4251c3436cfSJed Brown PetscFunctionReturn(0); 4261c3436cfSJed Brown } 4271c3436cfSJed Brown 4281c3436cfSJed Brown #undef __FUNCT__ 429e27a552bSJed Brown #define __FUNCT__ "TSStep_RosW" 430e27a552bSJed Brown static PetscErrorCode TSStep_RosW(TS ts) 431e27a552bSJed Brown { 43261692a83SJed Brown TS_RosW *ros = (TS_RosW*)ts->data; 43361692a83SJed Brown RosWTableau tab = ros->tableau; 434e27a552bSJed Brown const PetscInt s = tab->s; 4351c3436cfSJed Brown const PetscReal *At = tab->At,*Gamma = tab->Gamma,*ASum = tab->ASum,*GammaInv = tab->GammaInv; 436c17803e7SJed Brown const PetscBool *GammaZeroDiag = tab->GammaZeroDiag; 43761692a83SJed Brown PetscScalar *w = ros->work; 43861692a83SJed Brown Vec *Y = ros->Y,Zdot = ros->Zdot,Zstage = ros->Zstage; 439e27a552bSJed Brown SNES snes; 4401c3436cfSJed Brown TSAdapt adapt; 4411c3436cfSJed Brown PetscInt i,j,its,lits,reject,next_scheme; 442cdbf8f93SLisandro Dalcin PetscReal next_time_step; 4431c3436cfSJed Brown PetscBool accept; 444e27a552bSJed Brown PetscErrorCode ierr; 445e27a552bSJed Brown 446e27a552bSJed Brown PetscFunctionBegin; 447e27a552bSJed Brown ierr = TSGetSNES(ts,&snes);CHKERRQ(ierr); 448cdbf8f93SLisandro Dalcin next_time_step = ts->time_step; 4491c3436cfSJed Brown accept = PETSC_TRUE; 4501c3436cfSJed Brown ros->step_taken = PETSC_FALSE; 451e27a552bSJed Brown 4521c3436cfSJed Brown for (reject=0; reject<ts->max_reject; reject++,ts->reject++) { 4531c3436cfSJed Brown const PetscReal h = ts->time_step; 454e27a552bSJed Brown for (i=0; i<s; i++) { 4551c3436cfSJed Brown ros->stage_time = ts->ptime + h*ASum[i]; 456c17803e7SJed Brown if (GammaZeroDiag[i]) { 457c17803e7SJed Brown ros->stage_explicit = PETSC_TRUE; 458fd96d5b0SEmil Constantinescu ros->shift = 1./h; 459c17803e7SJed Brown } else { 460c17803e7SJed Brown ros->stage_explicit = PETSC_FALSE; 46161692a83SJed Brown ros->shift = 1./(h*Gamma[i*s+i]); 462fd96d5b0SEmil Constantinescu } 46361692a83SJed Brown 46461692a83SJed Brown ierr = VecCopy(ts->vec_sol,Zstage);CHKERRQ(ierr); 46561692a83SJed Brown ierr = VecMAXPY(Zstage,i,&At[i*s+0],Y);CHKERRQ(ierr); 46661692a83SJed Brown 46761692a83SJed Brown for (j=0; j<i; j++) w[j] = 1./h * GammaInv[i*s+j]; 46861692a83SJed Brown ierr = VecZeroEntries(Zdot);CHKERRQ(ierr); 46961692a83SJed Brown ierr = VecMAXPY(Zdot,i,w,Y);CHKERRQ(ierr); 47061692a83SJed Brown 471e27a552bSJed Brown /* Initial guess taken from last stage */ 47261692a83SJed Brown ierr = VecZeroEntries(Y[i]);CHKERRQ(ierr); 47361692a83SJed Brown 47461692a83SJed Brown if (!ros->recompute_jacobian && !i) { 47561692a83SJed Brown ierr = SNESSetLagJacobian(snes,-2);CHKERRQ(ierr); /* Recompute the Jacobian on this solve, but not again */ 47661692a83SJed Brown } 47761692a83SJed Brown 47861692a83SJed Brown ierr = SNESSolve(snes,PETSC_NULL,Y[i]);CHKERRQ(ierr); 479e27a552bSJed Brown ierr = SNESGetIterationNumber(snes,&its);CHKERRQ(ierr); 480e27a552bSJed Brown ierr = SNESGetLinearSolveIterations(snes,&lits);CHKERRQ(ierr); 481e27a552bSJed Brown ts->nonlinear_its += its; ts->linear_its += lits; 482e27a552bSJed Brown } 4831c3436cfSJed Brown ierr = TSEvaluateStep(ts,tab->order,ts->vec_sol,PETSC_NULL);CHKERRQ(ierr); 4841c3436cfSJed Brown ros->step_taken = PETSC_TRUE; 485e27a552bSJed Brown 4861c3436cfSJed Brown /* Register only the current method as a candidate because we're not supporting multiple candidates yet. */ 4871c3436cfSJed Brown ierr = TSGetAdapt(ts,&adapt);CHKERRQ(ierr); 4881c3436cfSJed Brown ierr = TSAdaptCandidatesClear(adapt);CHKERRQ(ierr); 489*8d59e960SJed Brown ierr = TSAdaptCandidateAdd(adapt,tab->name,tab->order,1,tab->ccfl,1.*tab->s,PETSC_TRUE);CHKERRQ(ierr); 4901c3436cfSJed Brown ierr = TSAdaptChoose(adapt,ts,ts->time_step,&next_scheme,&next_time_step,&accept);CHKERRQ(ierr); 4911c3436cfSJed Brown if (accept) { 4921c3436cfSJed Brown /* ignore next_scheme for now */ 493e27a552bSJed Brown ts->ptime += ts->time_step; 494cdbf8f93SLisandro Dalcin ts->time_step = next_time_step; 495e27a552bSJed Brown ts->steps++; 4961c3436cfSJed Brown break; 4971c3436cfSJed Brown } else { /* Roll back the current step */ 4981c3436cfSJed Brown for (i=0; i<s; i++) w[i] = -tab->bt[i]; 4991c3436cfSJed Brown ierr = VecMAXPY(ts->vec_sol,s,w,Y);CHKERRQ(ierr); 5001c3436cfSJed Brown ts->time_step = next_time_step; 5011c3436cfSJed Brown ros->step_taken = PETSC_FALSE; 5021c3436cfSJed Brown } 5031c3436cfSJed Brown } 5041c3436cfSJed Brown 505e27a552bSJed Brown PetscFunctionReturn(0); 506e27a552bSJed Brown } 507e27a552bSJed Brown 508e27a552bSJed Brown #undef __FUNCT__ 509e27a552bSJed Brown #define __FUNCT__ "TSInterpolate_RosW" 510e27a552bSJed Brown static PetscErrorCode TSInterpolate_RosW(TS ts,PetscReal itime,Vec X) 511e27a552bSJed Brown { 51261692a83SJed Brown TS_RosW *ros = (TS_RosW*)ts->data; 513e27a552bSJed Brown 514e27a552bSJed Brown PetscFunctionBegin; 51561692a83SJed Brown SETERRQ1(((PetscObject)ts)->comm,PETSC_ERR_SUP,"TSRosW %s does not have an interpolation formula",ros->tableau->name); 516e27a552bSJed Brown PetscFunctionReturn(0); 517e27a552bSJed Brown } 518e27a552bSJed Brown 519e27a552bSJed Brown /*------------------------------------------------------------*/ 520e27a552bSJed Brown #undef __FUNCT__ 521e27a552bSJed Brown #define __FUNCT__ "TSReset_RosW" 522e27a552bSJed Brown static PetscErrorCode TSReset_RosW(TS ts) 523e27a552bSJed Brown { 52461692a83SJed Brown TS_RosW *ros = (TS_RosW*)ts->data; 525e27a552bSJed Brown PetscInt s; 526e27a552bSJed Brown PetscErrorCode ierr; 527e27a552bSJed Brown 528e27a552bSJed Brown PetscFunctionBegin; 52961692a83SJed Brown if (!ros->tableau) PetscFunctionReturn(0); 53061692a83SJed Brown s = ros->tableau->s; 53161692a83SJed Brown ierr = VecDestroyVecs(s,&ros->Y);CHKERRQ(ierr); 53261692a83SJed Brown ierr = VecDestroy(&ros->Ydot);CHKERRQ(ierr); 53361692a83SJed Brown ierr = VecDestroy(&ros->Ystage);CHKERRQ(ierr); 53461692a83SJed Brown ierr = VecDestroy(&ros->Zdot);CHKERRQ(ierr); 53561692a83SJed Brown ierr = VecDestroy(&ros->Zstage);CHKERRQ(ierr); 53661692a83SJed Brown ierr = PetscFree(ros->work);CHKERRQ(ierr); 537e27a552bSJed Brown PetscFunctionReturn(0); 538e27a552bSJed Brown } 539e27a552bSJed Brown 540e27a552bSJed Brown #undef __FUNCT__ 541e27a552bSJed Brown #define __FUNCT__ "TSDestroy_RosW" 542e27a552bSJed Brown static PetscErrorCode TSDestroy_RosW(TS ts) 543e27a552bSJed Brown { 544e27a552bSJed Brown PetscErrorCode ierr; 545e27a552bSJed Brown 546e27a552bSJed Brown PetscFunctionBegin; 547e27a552bSJed Brown ierr = TSReset_RosW(ts);CHKERRQ(ierr); 548e27a552bSJed Brown ierr = PetscFree(ts->data);CHKERRQ(ierr); 549e27a552bSJed Brown ierr = PetscObjectComposeFunctionDynamic((PetscObject)ts,"TSRosWGetType_C","",PETSC_NULL);CHKERRQ(ierr); 550e27a552bSJed Brown ierr = PetscObjectComposeFunctionDynamic((PetscObject)ts,"TSRosWSetType_C","",PETSC_NULL);CHKERRQ(ierr); 55161692a83SJed Brown ierr = PetscObjectComposeFunctionDynamic((PetscObject)ts,"TSRosWSetRecomputeJacobian_C","",PETSC_NULL);CHKERRQ(ierr); 552e27a552bSJed Brown PetscFunctionReturn(0); 553e27a552bSJed Brown } 554e27a552bSJed Brown 555e27a552bSJed Brown /* 556e27a552bSJed Brown This defines the nonlinear equation that is to be solved with SNES 557e27a552bSJed Brown G(U) = F[t0+Theta*dt, U, (U-U0)*shift] = 0 558e27a552bSJed Brown */ 559e27a552bSJed Brown #undef __FUNCT__ 560e27a552bSJed Brown #define __FUNCT__ "SNESTSFormFunction_RosW" 561e27a552bSJed Brown static PetscErrorCode SNESTSFormFunction_RosW(SNES snes,Vec X,Vec F,TS ts) 562e27a552bSJed Brown { 56361692a83SJed Brown TS_RosW *ros = (TS_RosW*)ts->data; 564e27a552bSJed Brown PetscErrorCode ierr; 565e27a552bSJed Brown 566e27a552bSJed Brown PetscFunctionBegin; 567c17803e7SJed Brown if (ros->stage_explicit) { 568c17803e7SJed Brown ierr = VecAXPBY(ros->Ydot,ros->shift,0.0,X);CHKERRQ(ierr); /* Ydot = shift*X*/ 569c17803e7SJed Brown } else { 57061692a83SJed Brown ierr = VecWAXPY(ros->Ydot,ros->shift,X,ros->Zdot);CHKERRQ(ierr); /* Ydot = shift*X + Zdot */ 571c17803e7SJed Brown } 57261692a83SJed Brown ierr = VecWAXPY(ros->Ystage,1.0,X,ros->Zstage);CHKERRQ(ierr); /* Ystage = X + Zstage */ 57361692a83SJed Brown ierr = TSComputeIFunction(ts,ros->stage_time,ros->Ystage,ros->Ydot,F,PETSC_FALSE);CHKERRQ(ierr); 574e27a552bSJed Brown PetscFunctionReturn(0); 575e27a552bSJed Brown } 576e27a552bSJed Brown 577e27a552bSJed Brown #undef __FUNCT__ 578e27a552bSJed Brown #define __FUNCT__ "SNESTSFormJacobian_RosW" 579e27a552bSJed Brown static PetscErrorCode SNESTSFormJacobian_RosW(SNES snes,Vec X,Mat *A,Mat *B,MatStructure *str,TS ts) 580e27a552bSJed Brown { 58161692a83SJed Brown TS_RosW *ros = (TS_RosW*)ts->data; 582e27a552bSJed Brown PetscErrorCode ierr; 583e27a552bSJed Brown 584e27a552bSJed Brown PetscFunctionBegin; 58561692a83SJed Brown /* ros->Ydot and ros->Ystage have already been computed in SNESTSFormFunction_RosW (SNES guarantees this) */ 58661692a83SJed Brown ierr = TSComputeIJacobian(ts,ros->stage_time,ros->Ystage,ros->Ydot,ros->shift,A,B,str,PETSC_TRUE);CHKERRQ(ierr); 587e27a552bSJed Brown PetscFunctionReturn(0); 588e27a552bSJed Brown } 589e27a552bSJed Brown 590e27a552bSJed Brown #undef __FUNCT__ 591e27a552bSJed Brown #define __FUNCT__ "TSSetUp_RosW" 592e27a552bSJed Brown static PetscErrorCode TSSetUp_RosW(TS ts) 593e27a552bSJed Brown { 59461692a83SJed Brown TS_RosW *ros = (TS_RosW*)ts->data; 59561692a83SJed Brown RosWTableau tab = ros->tableau; 596e27a552bSJed Brown PetscInt s = tab->s; 597e27a552bSJed Brown PetscErrorCode ierr; 598e27a552bSJed Brown 599e27a552bSJed Brown PetscFunctionBegin; 60061692a83SJed Brown if (!ros->tableau) { 601e27a552bSJed Brown ierr = TSRosWSetType(ts,TSRosWDefault);CHKERRQ(ierr); 602e27a552bSJed Brown } 60361692a83SJed Brown ierr = VecDuplicateVecs(ts->vec_sol,s,&ros->Y);CHKERRQ(ierr); 60461692a83SJed Brown ierr = VecDuplicate(ts->vec_sol,&ros->Ydot);CHKERRQ(ierr); 60561692a83SJed Brown ierr = VecDuplicate(ts->vec_sol,&ros->Ystage);CHKERRQ(ierr); 60661692a83SJed Brown ierr = VecDuplicate(ts->vec_sol,&ros->Zdot);CHKERRQ(ierr); 60761692a83SJed Brown ierr = VecDuplicate(ts->vec_sol,&ros->Zstage);CHKERRQ(ierr); 60861692a83SJed Brown ierr = PetscMalloc(s*sizeof(ros->work[0]),&ros->work);CHKERRQ(ierr); 609e27a552bSJed Brown PetscFunctionReturn(0); 610e27a552bSJed Brown } 611e27a552bSJed Brown /*------------------------------------------------------------*/ 612e27a552bSJed Brown 613e27a552bSJed Brown #undef __FUNCT__ 614e27a552bSJed Brown #define __FUNCT__ "TSSetFromOptions_RosW" 615e27a552bSJed Brown static PetscErrorCode TSSetFromOptions_RosW(TS ts) 616e27a552bSJed Brown { 61761692a83SJed Brown TS_RosW *ros = (TS_RosW*)ts->data; 618e27a552bSJed Brown PetscErrorCode ierr; 61961692a83SJed Brown char rostype[256]; 620e27a552bSJed Brown 621e27a552bSJed Brown PetscFunctionBegin; 622e27a552bSJed Brown ierr = PetscOptionsHead("RosW ODE solver options");CHKERRQ(ierr); 623e27a552bSJed Brown { 62461692a83SJed Brown RosWTableauLink link; 625e27a552bSJed Brown PetscInt count,choice; 626e27a552bSJed Brown PetscBool flg; 627e27a552bSJed Brown const char **namelist; 62861692a83SJed Brown SNES snes; 62961692a83SJed Brown 63061692a83SJed Brown ierr = PetscStrncpy(rostype,TSRosWDefault,sizeof rostype);CHKERRQ(ierr); 63161692a83SJed Brown for (link=RosWTableauList,count=0; link; link=link->next,count++) ; 632e27a552bSJed Brown ierr = PetscMalloc(count*sizeof(char*),&namelist);CHKERRQ(ierr); 63361692a83SJed Brown for (link=RosWTableauList,count=0; link; link=link->next,count++) namelist[count] = link->tab.name; 63461692a83SJed Brown ierr = PetscOptionsEList("-ts_rosw_type","Family of Rosenbrock-W method","TSRosWSetType",(const char*const*)namelist,count,rostype,&choice,&flg);CHKERRQ(ierr); 63561692a83SJed Brown ierr = TSRosWSetType(ts,flg ? namelist[choice] : rostype);CHKERRQ(ierr); 636e27a552bSJed Brown ierr = PetscFree(namelist);CHKERRQ(ierr); 63761692a83SJed Brown 63861692a83SJed Brown ierr = PetscOptionsBool("-ts_rosw_recompute_jacobian","Recompute the Jacobian at each stage","TSRosWSetRecomputeJacobian",ros->recompute_jacobian,&ros->recompute_jacobian,PETSC_NULL);CHKERRQ(ierr); 63961692a83SJed Brown 64061692a83SJed Brown /* Rosenbrock methods are linearly implicit, so set that unless the user has specifically asked for something else */ 64161692a83SJed Brown ierr = TSGetSNES(ts,&snes);CHKERRQ(ierr); 64261692a83SJed Brown if (!((PetscObject)snes)->type_name) { 64361692a83SJed Brown ierr = SNESSetType(snes,SNESKSPONLY);CHKERRQ(ierr); 64461692a83SJed Brown } 64561692a83SJed Brown ierr = SNESSetFromOptions(snes);CHKERRQ(ierr); 646e27a552bSJed Brown } 647e27a552bSJed Brown ierr = PetscOptionsTail();CHKERRQ(ierr); 648e27a552bSJed Brown PetscFunctionReturn(0); 649e27a552bSJed Brown } 650e27a552bSJed Brown 651e27a552bSJed Brown #undef __FUNCT__ 652e27a552bSJed Brown #define __FUNCT__ "PetscFormatRealArray" 653e27a552bSJed Brown static PetscErrorCode PetscFormatRealArray(char buf[],size_t len,const char *fmt,PetscInt n,const PetscReal x[]) 654e27a552bSJed Brown { 655e27a552bSJed Brown PetscErrorCode ierr; 656e408995aSJed Brown PetscInt i; 657e408995aSJed Brown size_t left,count; 658e27a552bSJed Brown char *p; 659e27a552bSJed Brown 660e27a552bSJed Brown PetscFunctionBegin; 661e408995aSJed Brown for (i=0,p=buf,left=len; i<n; i++) { 662e408995aSJed Brown ierr = PetscSNPrintfCount(p,left,fmt,&count,x[i]);CHKERRQ(ierr); 663e27a552bSJed Brown if (count >= left) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Insufficient space in buffer"); 664e27a552bSJed Brown left -= count; 665e27a552bSJed Brown p += count; 666e27a552bSJed Brown *p++ = ' '; 667e27a552bSJed Brown } 668e27a552bSJed Brown p[i ? 0 : -1] = 0; 669e27a552bSJed Brown PetscFunctionReturn(0); 670e27a552bSJed Brown } 671e27a552bSJed Brown 672e27a552bSJed Brown #undef __FUNCT__ 673e27a552bSJed Brown #define __FUNCT__ "TSView_RosW" 674e27a552bSJed Brown static PetscErrorCode TSView_RosW(TS ts,PetscViewer viewer) 675e27a552bSJed Brown { 67661692a83SJed Brown TS_RosW *ros = (TS_RosW*)ts->data; 67761692a83SJed Brown RosWTableau tab = ros->tableau; 678e27a552bSJed Brown PetscBool iascii; 679e27a552bSJed Brown PetscErrorCode ierr; 680e27a552bSJed Brown 681e27a552bSJed Brown PetscFunctionBegin; 682e27a552bSJed Brown ierr = PetscTypeCompare((PetscObject)viewer,PETSCVIEWERASCII,&iascii);CHKERRQ(ierr); 683e27a552bSJed Brown if (iascii) { 68461692a83SJed Brown const TSRosWType rostype; 685e408995aSJed Brown PetscInt i; 686e408995aSJed Brown PetscReal abscissa[512]; 687e27a552bSJed Brown char buf[512]; 68861692a83SJed Brown ierr = TSRosWGetType(ts,&rostype);CHKERRQ(ierr); 68961692a83SJed Brown ierr = PetscViewerASCIIPrintf(viewer," Rosenbrock-W %s\n",rostype);CHKERRQ(ierr); 690e408995aSJed Brown ierr = PetscFormatRealArray(buf,sizeof buf,"% 8.6f",tab->s,tab->ASum);CHKERRQ(ierr); 69161692a83SJed Brown ierr = PetscViewerASCIIPrintf(viewer," Abscissa of A = %s\n",buf);CHKERRQ(ierr); 692e408995aSJed Brown for (i=0; i<tab->s; i++) abscissa[i] = tab->ASum[i] + tab->Gamma[i]; 693e408995aSJed Brown ierr = PetscFormatRealArray(buf,sizeof buf,"% 8.6f",tab->s,abscissa);CHKERRQ(ierr); 694e408995aSJed Brown ierr = PetscViewerASCIIPrintf(viewer," Abscissa of A+Gamma = %s\n",buf);CHKERRQ(ierr); 695e27a552bSJed Brown } 696e27a552bSJed Brown ierr = SNESView(ts->snes,viewer);CHKERRQ(ierr); 697e27a552bSJed Brown PetscFunctionReturn(0); 698e27a552bSJed Brown } 699e27a552bSJed Brown 700e27a552bSJed Brown #undef __FUNCT__ 701e27a552bSJed Brown #define __FUNCT__ "TSRosWSetType" 702e27a552bSJed Brown /*@C 70361692a83SJed Brown TSRosWSetType - Set the type of Rosenbrock-W scheme 704e27a552bSJed Brown 705e27a552bSJed Brown Logically collective 706e27a552bSJed Brown 707e27a552bSJed Brown Input Parameter: 708e27a552bSJed Brown + ts - timestepping context 70961692a83SJed Brown - rostype - type of Rosenbrock-W scheme 710e27a552bSJed Brown 711e27a552bSJed Brown Level: intermediate 712e27a552bSJed Brown 713e27a552bSJed Brown .seealso: TSRosWGetType() 714e27a552bSJed Brown @*/ 71561692a83SJed Brown PetscErrorCode TSRosWSetType(TS ts,const TSRosWType rostype) 716e27a552bSJed Brown { 717e27a552bSJed Brown PetscErrorCode ierr; 718e27a552bSJed Brown 719e27a552bSJed Brown PetscFunctionBegin; 720e27a552bSJed Brown PetscValidHeaderSpecific(ts,TS_CLASSID,1); 72161692a83SJed Brown ierr = PetscTryMethod(ts,"TSRosWSetType_C",(TS,const TSRosWType),(ts,rostype));CHKERRQ(ierr); 722e27a552bSJed Brown PetscFunctionReturn(0); 723e27a552bSJed Brown } 724e27a552bSJed Brown 725e27a552bSJed Brown #undef __FUNCT__ 726e27a552bSJed Brown #define __FUNCT__ "TSRosWGetType" 727e27a552bSJed Brown /*@C 72861692a83SJed Brown TSRosWGetType - Get the type of Rosenbrock-W scheme 729e27a552bSJed Brown 730e27a552bSJed Brown Logically collective 731e27a552bSJed Brown 732e27a552bSJed Brown Input Parameter: 733e27a552bSJed Brown . ts - timestepping context 734e27a552bSJed Brown 735e27a552bSJed Brown Output Parameter: 73661692a83SJed Brown . rostype - type of Rosenbrock-W scheme 737e27a552bSJed Brown 738e27a552bSJed Brown Level: intermediate 739e27a552bSJed Brown 740e27a552bSJed Brown .seealso: TSRosWGetType() 741e27a552bSJed Brown @*/ 74261692a83SJed Brown PetscErrorCode TSRosWGetType(TS ts,const TSRosWType *rostype) 743e27a552bSJed Brown { 744e27a552bSJed Brown PetscErrorCode ierr; 745e27a552bSJed Brown 746e27a552bSJed Brown PetscFunctionBegin; 747e27a552bSJed Brown PetscValidHeaderSpecific(ts,TS_CLASSID,1); 74861692a83SJed Brown ierr = PetscUseMethod(ts,"TSRosWGetType_C",(TS,const TSRosWType*),(ts,rostype));CHKERRQ(ierr); 749e27a552bSJed Brown PetscFunctionReturn(0); 750e27a552bSJed Brown } 751e27a552bSJed Brown 752e27a552bSJed Brown #undef __FUNCT__ 75361692a83SJed Brown #define __FUNCT__ "TSRosWSetRecomputeJacobian" 754e27a552bSJed Brown /*@C 75561692a83SJed Brown TSRosWSetRecomputeJacobian - Set whether to recompute the Jacobian at each stage. The default is to update the Jacobian once per step. 756e27a552bSJed Brown 757e27a552bSJed Brown Logically collective 758e27a552bSJed Brown 759e27a552bSJed Brown Input Parameter: 760e27a552bSJed Brown + ts - timestepping context 76161692a83SJed Brown - flg - PETSC_TRUE to recompute the Jacobian at each stage 762e27a552bSJed Brown 763e27a552bSJed Brown Level: intermediate 764e27a552bSJed Brown 765e27a552bSJed Brown .seealso: TSRosWGetType() 766e27a552bSJed Brown @*/ 76761692a83SJed Brown PetscErrorCode TSRosWSetRecomputeJacobian(TS ts,PetscBool flg) 768e27a552bSJed Brown { 769e27a552bSJed Brown PetscErrorCode ierr; 770e27a552bSJed Brown 771e27a552bSJed Brown PetscFunctionBegin; 772e27a552bSJed Brown PetscValidHeaderSpecific(ts,TS_CLASSID,1); 77361692a83SJed Brown ierr = PetscTryMethod(ts,"TSRosWSetRecomputeJacobian_C",(TS,PetscBool),(ts,flg));CHKERRQ(ierr); 774e27a552bSJed Brown PetscFunctionReturn(0); 775e27a552bSJed Brown } 776e27a552bSJed Brown 777e27a552bSJed Brown EXTERN_C_BEGIN 778e27a552bSJed Brown #undef __FUNCT__ 779e27a552bSJed Brown #define __FUNCT__ "TSRosWGetType_RosW" 78061692a83SJed Brown PetscErrorCode TSRosWGetType_RosW(TS ts,const TSRosWType *rostype) 781e27a552bSJed Brown { 78261692a83SJed Brown TS_RosW *ros = (TS_RosW*)ts->data; 783e27a552bSJed Brown PetscErrorCode ierr; 784e27a552bSJed Brown 785e27a552bSJed Brown PetscFunctionBegin; 78661692a83SJed Brown if (!ros->tableau) {ierr = TSRosWSetType(ts,TSRosWDefault);CHKERRQ(ierr);} 78761692a83SJed Brown *rostype = ros->tableau->name; 788e27a552bSJed Brown PetscFunctionReturn(0); 789e27a552bSJed Brown } 790e27a552bSJed Brown #undef __FUNCT__ 791e27a552bSJed Brown #define __FUNCT__ "TSRosWSetType_RosW" 79261692a83SJed Brown PetscErrorCode TSRosWSetType_RosW(TS ts,const TSRosWType rostype) 793e27a552bSJed Brown { 79461692a83SJed Brown TS_RosW *ros = (TS_RosW*)ts->data; 795e27a552bSJed Brown PetscErrorCode ierr; 796e27a552bSJed Brown PetscBool match; 79761692a83SJed Brown RosWTableauLink link; 798e27a552bSJed Brown 799e27a552bSJed Brown PetscFunctionBegin; 80061692a83SJed Brown if (ros->tableau) { 80161692a83SJed Brown ierr = PetscStrcmp(ros->tableau->name,rostype,&match);CHKERRQ(ierr); 802e27a552bSJed Brown if (match) PetscFunctionReturn(0); 803e27a552bSJed Brown } 80461692a83SJed Brown for (link = RosWTableauList; link; link=link->next) { 80561692a83SJed Brown ierr = PetscStrcmp(link->tab.name,rostype,&match);CHKERRQ(ierr); 806e27a552bSJed Brown if (match) { 807e27a552bSJed Brown ierr = TSReset_RosW(ts);CHKERRQ(ierr); 80861692a83SJed Brown ros->tableau = &link->tab; 809e27a552bSJed Brown PetscFunctionReturn(0); 810e27a552bSJed Brown } 811e27a552bSJed Brown } 81261692a83SJed Brown SETERRQ1(((PetscObject)ts)->comm,PETSC_ERR_ARG_UNKNOWN_TYPE,"Could not find '%s'",rostype); 813e27a552bSJed Brown PetscFunctionReturn(0); 814e27a552bSJed Brown } 81561692a83SJed Brown 816e27a552bSJed Brown #undef __FUNCT__ 81761692a83SJed Brown #define __FUNCT__ "TSRosWSetRecomputeJacobian_RosW" 81861692a83SJed Brown PetscErrorCode TSRosWSetRecomputeJacobian_RosW(TS ts,PetscBool flg) 819e27a552bSJed Brown { 82061692a83SJed Brown TS_RosW *ros = (TS_RosW*)ts->data; 821e27a552bSJed Brown 822e27a552bSJed Brown PetscFunctionBegin; 82361692a83SJed Brown ros->recompute_jacobian = flg; 824e27a552bSJed Brown PetscFunctionReturn(0); 825e27a552bSJed Brown } 826e27a552bSJed Brown EXTERN_C_END 827e27a552bSJed Brown 828e27a552bSJed Brown /* ------------------------------------------------------------ */ 829e27a552bSJed Brown /*MC 830e27a552bSJed Brown TSRosW - ODE solver using Rosenbrock-W schemes 831e27a552bSJed Brown 832e27a552bSJed Brown These methods are intended for problems with well-separated time scales, especially when a slow scale is strongly 833e27a552bSJed Brown nonlinear such that it is expensive to solve with a fully implicit method. The user should provide the stiff part 834e27a552bSJed Brown of the equation using TSSetIFunction() and the non-stiff part with TSSetRHSFunction(). 835e27a552bSJed Brown 836e27a552bSJed Brown Notes: 83761692a83SJed Brown This method currently only works with autonomous ODE and DAE. 83861692a83SJed Brown 83961692a83SJed Brown Developer notes: 84061692a83SJed Brown Rosenbrock-W methods are typically specified for autonomous ODE 84161692a83SJed Brown 84261692a83SJed Brown $ xdot = f(x) 84361692a83SJed Brown 84461692a83SJed Brown by the stage equations 84561692a83SJed Brown 84661692a83SJed Brown $ k_i = h f(x_0 + sum_j alpha_ij k_j) + h J sum_j gamma_ij k_j 84761692a83SJed Brown 84861692a83SJed Brown and step completion formula 84961692a83SJed Brown 85061692a83SJed Brown $ x_1 = x_0 + sum_j b_j k_j 85161692a83SJed Brown 85261692a83SJed Brown with step size h and coefficients alpha_ij, gamma_ij, and b_i. Implementing the method in this form would require f(x) 85361692a83SJed Brown and the Jacobian J to be available, in addition to the shifted matrix I - h gamma_ii J. Following Hairer and Wanner, 85461692a83SJed Brown we define new variables for the stage equations 85561692a83SJed Brown 85661692a83SJed Brown $ y_i = gamma_ij k_j 85761692a83SJed Brown 85861692a83SJed Brown The k_j can be recovered because Gamma is invertible. Let C be the lower triangular part of Gamma^{-1} and define 85961692a83SJed Brown 86061692a83SJed Brown $ A = Alpha Gamma^{-1}, bt^T = b^T Gamma^{-i} 86161692a83SJed Brown 86261692a83SJed Brown to rewrite the method as 86361692a83SJed Brown 86461692a83SJed Brown $ [M/(h gamma_ii) - J] y_i = f(x_0 + sum_j a_ij y_j) + M sum_j (c_ij/h) y_j 86561692a83SJed Brown $ x_1 = x_0 + sum_j bt_j y_j 86661692a83SJed Brown 86761692a83SJed Brown where we have introduced the mass matrix M. Continue by defining 86861692a83SJed Brown 86961692a83SJed Brown $ ydot_i = 1/(h gamma_ii) y_i - sum_j (c_ij/h) y_j 87061692a83SJed Brown 87161692a83SJed Brown or, more compactly in tensor notation 87261692a83SJed Brown 87361692a83SJed Brown $ Ydot = 1/h (Gamma^{-1} \otimes I) Y . 87461692a83SJed Brown 87561692a83SJed Brown Note that Gamma^{-1} is lower triangular. With this definition of Ydot in terms of known quantities and the current 87661692a83SJed Brown stage y_i, the stage equations reduce to performing one Newton step (typically with a lagged Jacobian) on the 87761692a83SJed Brown equation 87861692a83SJed Brown 87961692a83SJed Brown $ g(x_0 + sum_j a_ij y_j + y_i, ydot_i) = 0 88061692a83SJed Brown 88161692a83SJed Brown with initial guess y_i = 0. 882e27a552bSJed Brown 883e27a552bSJed Brown Level: beginner 884e27a552bSJed Brown 885e27a552bSJed Brown .seealso: TSCreate(), TS, TSSetType(), TSRosWRegister() 886e27a552bSJed Brown 887e27a552bSJed Brown M*/ 888e27a552bSJed Brown EXTERN_C_BEGIN 889e27a552bSJed Brown #undef __FUNCT__ 890e27a552bSJed Brown #define __FUNCT__ "TSCreate_RosW" 891e27a552bSJed Brown PetscErrorCode TSCreate_RosW(TS ts) 892e27a552bSJed Brown { 89361692a83SJed Brown TS_RosW *ros; 894e27a552bSJed Brown PetscErrorCode ierr; 895e27a552bSJed Brown 896e27a552bSJed Brown PetscFunctionBegin; 897e27a552bSJed Brown #if !defined(PETSC_USE_DYNAMIC_LIBRARIES) 898e27a552bSJed Brown ierr = TSRosWInitializePackage(PETSC_NULL);CHKERRQ(ierr); 899e27a552bSJed Brown #endif 900e27a552bSJed Brown 901e27a552bSJed Brown ts->ops->reset = TSReset_RosW; 902e27a552bSJed Brown ts->ops->destroy = TSDestroy_RosW; 903e27a552bSJed Brown ts->ops->view = TSView_RosW; 904e27a552bSJed Brown ts->ops->setup = TSSetUp_RosW; 905e27a552bSJed Brown ts->ops->step = TSStep_RosW; 906e27a552bSJed Brown ts->ops->interpolate = TSInterpolate_RosW; 9071c3436cfSJed Brown ts->ops->evaluatestep = TSEvaluateStep_RosW; 908e27a552bSJed Brown ts->ops->setfromoptions = TSSetFromOptions_RosW; 909e27a552bSJed Brown ts->ops->snesfunction = SNESTSFormFunction_RosW; 910e27a552bSJed Brown ts->ops->snesjacobian = SNESTSFormJacobian_RosW; 911e27a552bSJed Brown 91261692a83SJed Brown ierr = PetscNewLog(ts,TS_RosW,&ros);CHKERRQ(ierr); 91361692a83SJed Brown ts->data = (void*)ros; 914e27a552bSJed Brown 915e27a552bSJed Brown ierr = PetscObjectComposeFunctionDynamic((PetscObject)ts,"TSRosWGetType_C","TSRosWGetType_RosW",TSRosWGetType_RosW);CHKERRQ(ierr); 916e27a552bSJed Brown ierr = PetscObjectComposeFunctionDynamic((PetscObject)ts,"TSRosWSetType_C","TSRosWSetType_RosW",TSRosWSetType_RosW);CHKERRQ(ierr); 91761692a83SJed Brown ierr = PetscObjectComposeFunctionDynamic((PetscObject)ts,"TSRosWSetRecomputeJacobian_C","TSRosWSetRecomputeJacobian_RosW",TSRosWSetRecomputeJacobian_RosW);CHKERRQ(ierr); 918e27a552bSJed Brown PetscFunctionReturn(0); 919e27a552bSJed Brown } 920e27a552bSJed Brown EXTERN_C_END 921