1*c4762a1bSJed Brown 2*c4762a1bSJed Brown static char help[] ="Solves a simple time-dependent linear PDE (the heat equation).\n\ 3*c4762a1bSJed Brown Input parameters include:\n\ 4*c4762a1bSJed Brown -m <points>, where <points> = number of grid points\n\ 5*c4762a1bSJed Brown -time_dependent_rhs : Treat the problem as having a time-dependent right-hand side\n\ 6*c4762a1bSJed Brown -debug : Activate debugging printouts\n\ 7*c4762a1bSJed Brown -nox : Deactivate x-window graphics\n\n"; 8*c4762a1bSJed Brown 9*c4762a1bSJed Brown /* 10*c4762a1bSJed Brown Concepts: TS^time-dependent linear problems 11*c4762a1bSJed Brown Concepts: TS^heat equation 12*c4762a1bSJed Brown Concepts: TS^diffusion equation 13*c4762a1bSJed Brown Processors: 1 14*c4762a1bSJed Brown */ 15*c4762a1bSJed Brown 16*c4762a1bSJed Brown /* ------------------------------------------------------------------------ 17*c4762a1bSJed Brown 18*c4762a1bSJed Brown This program solves the one-dimensional heat equation (also called the 19*c4762a1bSJed Brown diffusion equation), 20*c4762a1bSJed Brown u_t = u_xx, 21*c4762a1bSJed Brown on the domain 0 <= x <= 1, with the boundary conditions 22*c4762a1bSJed Brown u(t,0) = 1, u(t,1) = 1, 23*c4762a1bSJed Brown and the initial condition 24*c4762a1bSJed Brown u(0,x) = cos(6*pi*x) + 3*cos(2*pi*x). 25*c4762a1bSJed Brown This is a linear, second-order, parabolic equation. 26*c4762a1bSJed Brown 27*c4762a1bSJed Brown We discretize the right-hand side using finite differences with 28*c4762a1bSJed Brown uniform grid spacing h: 29*c4762a1bSJed Brown u_xx = (u_{i+1} - 2u_{i} + u_{i-1})/(h^2) 30*c4762a1bSJed Brown We then demonstrate time evolution using the various TS methods by 31*c4762a1bSJed Brown running the program via 32*c4762a1bSJed Brown ex3 -ts_type <timestepping solver> 33*c4762a1bSJed Brown 34*c4762a1bSJed Brown We compare the approximate solution with the exact solution, given by 35*c4762a1bSJed Brown u_exact(x,t) = exp(-36*pi*pi*t) * cos(6*pi*x) + 36*c4762a1bSJed Brown 3*exp(-4*pi*pi*t) * cos(2*pi*x) 37*c4762a1bSJed Brown 38*c4762a1bSJed Brown Notes: 39*c4762a1bSJed Brown This code demonstrates the TS solver interface to two variants of 40*c4762a1bSJed Brown linear problems, u_t = f(u,t), namely 41*c4762a1bSJed Brown - time-dependent f: f(u,t) is a function of t 42*c4762a1bSJed Brown - time-independent f: f(u,t) is simply just f(u) 43*c4762a1bSJed Brown 44*c4762a1bSJed Brown The parallel version of this code is ts/tutorials/ex4.c 45*c4762a1bSJed Brown 46*c4762a1bSJed Brown ------------------------------------------------------------------------- */ 47*c4762a1bSJed Brown 48*c4762a1bSJed Brown /* 49*c4762a1bSJed Brown Include "petscts.h" so that we can use TS solvers. Note that this file 50*c4762a1bSJed Brown automatically includes: 51*c4762a1bSJed Brown petscsys.h - base PETSc routines petscvec.h - vectors 52*c4762a1bSJed Brown petscmat.h - matrices 53*c4762a1bSJed Brown petscis.h - index sets petscksp.h - Krylov subspace methods 54*c4762a1bSJed Brown petscviewer.h - viewers petscpc.h - preconditioners 55*c4762a1bSJed Brown petscksp.h - linear solvers petscsnes.h - nonlinear solvers 56*c4762a1bSJed Brown */ 57*c4762a1bSJed Brown #include <petscts.h> 58*c4762a1bSJed Brown #include <petscdraw.h> 59*c4762a1bSJed Brown 60*c4762a1bSJed Brown /* 61*c4762a1bSJed Brown User-defined application context - contains data needed by the 62*c4762a1bSJed Brown application-provided call-back routines. 63*c4762a1bSJed Brown */ 64*c4762a1bSJed Brown typedef struct { 65*c4762a1bSJed Brown Vec solution; /* global exact solution vector */ 66*c4762a1bSJed Brown PetscInt m; /* total number of grid points */ 67*c4762a1bSJed Brown PetscReal h; /* mesh width h = 1/(m-1) */ 68*c4762a1bSJed Brown PetscBool debug; /* flag (1 indicates activation of debugging printouts) */ 69*c4762a1bSJed Brown PetscViewer viewer1,viewer2; /* viewers for the solution and error */ 70*c4762a1bSJed Brown PetscReal norm_2,norm_max; /* error norms */ 71*c4762a1bSJed Brown } AppCtx; 72*c4762a1bSJed Brown 73*c4762a1bSJed Brown /* 74*c4762a1bSJed Brown User-defined routines 75*c4762a1bSJed Brown */ 76*c4762a1bSJed Brown extern PetscErrorCode InitialConditions(Vec,AppCtx*); 77*c4762a1bSJed Brown extern PetscErrorCode RHSMatrixHeat(TS,PetscReal,Vec,Mat,Mat,void*); 78*c4762a1bSJed Brown extern PetscErrorCode Monitor(TS,PetscInt,PetscReal,Vec,void*); 79*c4762a1bSJed Brown extern PetscErrorCode ExactSolution(PetscReal,Vec,AppCtx*); 80*c4762a1bSJed Brown 81*c4762a1bSJed Brown int main(int argc,char **argv) 82*c4762a1bSJed Brown { 83*c4762a1bSJed Brown AppCtx appctx; /* user-defined application context */ 84*c4762a1bSJed Brown TS ts; /* timestepping context */ 85*c4762a1bSJed Brown Mat A; /* matrix data structure */ 86*c4762a1bSJed Brown Vec u; /* approximate solution vector */ 87*c4762a1bSJed Brown PetscReal time_total_max = 100.0; /* default max total time */ 88*c4762a1bSJed Brown PetscInt time_steps_max = 100; /* default max timesteps */ 89*c4762a1bSJed Brown PetscDraw draw; /* drawing context */ 90*c4762a1bSJed Brown PetscErrorCode ierr; 91*c4762a1bSJed Brown PetscInt steps,m; 92*c4762a1bSJed Brown PetscMPIInt size; 93*c4762a1bSJed Brown PetscBool flg; 94*c4762a1bSJed Brown PetscReal dt,ftime; 95*c4762a1bSJed Brown 96*c4762a1bSJed Brown /* - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 97*c4762a1bSJed Brown Initialize program and set problem parameters 98*c4762a1bSJed Brown - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - */ 99*c4762a1bSJed Brown 100*c4762a1bSJed Brown ierr = PetscInitialize(&argc,&argv,(char*)0,help);if (ierr) return ierr; 101*c4762a1bSJed Brown ierr = MPI_Comm_size(PETSC_COMM_WORLD,&size);CHKERRQ(ierr); 102*c4762a1bSJed Brown if (size != 1) SETERRQ(PETSC_COMM_WORLD,PETSC_ERR_WRONG_MPI_SIZE,"This is a uniprocessor example only!"); 103*c4762a1bSJed Brown 104*c4762a1bSJed Brown m = 60; 105*c4762a1bSJed Brown ierr = PetscOptionsGetInt(NULL,NULL,"-m",&m,NULL);CHKERRQ(ierr); 106*c4762a1bSJed Brown ierr = PetscOptionsHasName(NULL,NULL,"-debug",&appctx.debug);CHKERRQ(ierr); 107*c4762a1bSJed Brown appctx.m = m; 108*c4762a1bSJed Brown appctx.h = 1.0/(m-1.0); 109*c4762a1bSJed Brown appctx.norm_2 = 0.0; 110*c4762a1bSJed Brown appctx.norm_max = 0.0; 111*c4762a1bSJed Brown 112*c4762a1bSJed Brown ierr = PetscPrintf(PETSC_COMM_SELF,"Solving a linear TS problem on 1 processor\n");CHKERRQ(ierr); 113*c4762a1bSJed Brown 114*c4762a1bSJed Brown /* - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 115*c4762a1bSJed Brown Create vector data structures 116*c4762a1bSJed Brown - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - */ 117*c4762a1bSJed Brown 118*c4762a1bSJed Brown /* 119*c4762a1bSJed Brown Create vector data structures for approximate and exact solutions 120*c4762a1bSJed Brown */ 121*c4762a1bSJed Brown ierr = VecCreateSeq(PETSC_COMM_SELF,m,&u);CHKERRQ(ierr); 122*c4762a1bSJed Brown ierr = VecDuplicate(u,&appctx.solution);CHKERRQ(ierr); 123*c4762a1bSJed Brown 124*c4762a1bSJed Brown /* - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 125*c4762a1bSJed Brown Set up displays to show graphs of the solution and error 126*c4762a1bSJed Brown - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - */ 127*c4762a1bSJed Brown 128*c4762a1bSJed Brown ierr = PetscViewerDrawOpen(PETSC_COMM_SELF,0,"",80,380,400,160,&appctx.viewer1);CHKERRQ(ierr); 129*c4762a1bSJed Brown ierr = PetscViewerDrawGetDraw(appctx.viewer1,0,&draw);CHKERRQ(ierr); 130*c4762a1bSJed Brown ierr = PetscDrawSetDoubleBuffer(draw);CHKERRQ(ierr); 131*c4762a1bSJed Brown ierr = PetscViewerDrawOpen(PETSC_COMM_SELF,0,"",80,0,400,160,&appctx.viewer2);CHKERRQ(ierr); 132*c4762a1bSJed Brown ierr = PetscViewerDrawGetDraw(appctx.viewer2,0,&draw);CHKERRQ(ierr); 133*c4762a1bSJed Brown ierr = PetscDrawSetDoubleBuffer(draw);CHKERRQ(ierr); 134*c4762a1bSJed Brown 135*c4762a1bSJed Brown /* - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 136*c4762a1bSJed Brown Create timestepping solver context 137*c4762a1bSJed Brown - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - */ 138*c4762a1bSJed Brown 139*c4762a1bSJed Brown ierr = TSCreate(PETSC_COMM_SELF,&ts);CHKERRQ(ierr); 140*c4762a1bSJed Brown ierr = TSSetProblemType(ts,TS_LINEAR);CHKERRQ(ierr); 141*c4762a1bSJed Brown 142*c4762a1bSJed Brown /* - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 143*c4762a1bSJed Brown Set optional user-defined monitoring routine 144*c4762a1bSJed Brown - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - */ 145*c4762a1bSJed Brown 146*c4762a1bSJed Brown ierr = TSMonitorSet(ts,Monitor,&appctx,NULL);CHKERRQ(ierr); 147*c4762a1bSJed Brown 148*c4762a1bSJed Brown /* - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 149*c4762a1bSJed Brown 150*c4762a1bSJed Brown Create matrix data structure; set matrix evaluation routine. 151*c4762a1bSJed Brown - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - */ 152*c4762a1bSJed Brown 153*c4762a1bSJed Brown ierr = MatCreate(PETSC_COMM_SELF,&A);CHKERRQ(ierr); 154*c4762a1bSJed Brown ierr = MatSetSizes(A,PETSC_DECIDE,PETSC_DECIDE,m,m);CHKERRQ(ierr); 155*c4762a1bSJed Brown ierr = MatSetFromOptions(A);CHKERRQ(ierr); 156*c4762a1bSJed Brown ierr = MatSetUp(A);CHKERRQ(ierr); 157*c4762a1bSJed Brown 158*c4762a1bSJed Brown ierr = PetscOptionsHasName(NULL,NULL,"-time_dependent_rhs",&flg);CHKERRQ(ierr); 159*c4762a1bSJed Brown if (flg) { 160*c4762a1bSJed Brown /* 161*c4762a1bSJed Brown For linear problems with a time-dependent f(u,t) in the equation 162*c4762a1bSJed Brown u_t = f(u,t), the user provides the discretized right-hand-side 163*c4762a1bSJed Brown as a time-dependent matrix. 164*c4762a1bSJed Brown */ 165*c4762a1bSJed Brown ierr = TSSetRHSFunction(ts,NULL,TSComputeRHSFunctionLinear,&appctx);CHKERRQ(ierr); 166*c4762a1bSJed Brown ierr = TSSetRHSJacobian(ts,A,A,RHSMatrixHeat,&appctx);CHKERRQ(ierr); 167*c4762a1bSJed Brown } else { 168*c4762a1bSJed Brown /* 169*c4762a1bSJed Brown For linear problems with a time-independent f(u) in the equation 170*c4762a1bSJed Brown u_t = f(u), the user provides the discretized right-hand-side 171*c4762a1bSJed Brown as a matrix only once, and then sets a null matrix evaluation 172*c4762a1bSJed Brown routine. 173*c4762a1bSJed Brown */ 174*c4762a1bSJed Brown ierr = RHSMatrixHeat(ts,0.0,u,A,A,&appctx);CHKERRQ(ierr); 175*c4762a1bSJed Brown ierr = TSSetRHSFunction(ts,NULL,TSComputeRHSFunctionLinear,&appctx);CHKERRQ(ierr); 176*c4762a1bSJed Brown ierr = TSSetRHSJacobian(ts,A,A,TSComputeRHSJacobianConstant,&appctx);CHKERRQ(ierr); 177*c4762a1bSJed Brown } 178*c4762a1bSJed Brown 179*c4762a1bSJed Brown /* - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 180*c4762a1bSJed Brown Set solution vector and initial timestep 181*c4762a1bSJed Brown - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - */ 182*c4762a1bSJed Brown 183*c4762a1bSJed Brown dt = appctx.h*appctx.h/2.0; 184*c4762a1bSJed Brown ierr = TSSetTimeStep(ts,dt);CHKERRQ(ierr); 185*c4762a1bSJed Brown ierr = TSSetSolution(ts,u);CHKERRQ(ierr); 186*c4762a1bSJed Brown 187*c4762a1bSJed Brown /* - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 188*c4762a1bSJed Brown Customize timestepping solver: 189*c4762a1bSJed Brown - Set the solution method to be the Backward Euler method. 190*c4762a1bSJed Brown - Set timestepping duration info 191*c4762a1bSJed Brown Then set runtime options, which can override these defaults. 192*c4762a1bSJed Brown For example, 193*c4762a1bSJed Brown -ts_max_steps <maxsteps> -ts_max_time <maxtime> 194*c4762a1bSJed Brown to override the defaults set by TSSetMaxSteps()/TSSetMaxTime(). 195*c4762a1bSJed Brown - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - */ 196*c4762a1bSJed Brown 197*c4762a1bSJed Brown ierr = TSSetMaxSteps(ts,time_steps_max);CHKERRQ(ierr); 198*c4762a1bSJed Brown ierr = TSSetMaxTime(ts,time_total_max);CHKERRQ(ierr); 199*c4762a1bSJed Brown ierr = TSSetExactFinalTime(ts,TS_EXACTFINALTIME_STEPOVER);CHKERRQ(ierr); 200*c4762a1bSJed Brown ierr = TSSetFromOptions(ts);CHKERRQ(ierr); 201*c4762a1bSJed Brown 202*c4762a1bSJed Brown /* - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 203*c4762a1bSJed Brown Solve the problem 204*c4762a1bSJed Brown - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - */ 205*c4762a1bSJed Brown 206*c4762a1bSJed Brown /* 207*c4762a1bSJed Brown Evaluate initial conditions 208*c4762a1bSJed Brown */ 209*c4762a1bSJed Brown ierr = InitialConditions(u,&appctx);CHKERRQ(ierr); 210*c4762a1bSJed Brown 211*c4762a1bSJed Brown /* 212*c4762a1bSJed Brown Run the timestepping solver 213*c4762a1bSJed Brown */ 214*c4762a1bSJed Brown ierr = TSSolve(ts,u);CHKERRQ(ierr); 215*c4762a1bSJed Brown ierr = TSGetSolveTime(ts,&ftime);CHKERRQ(ierr); 216*c4762a1bSJed Brown ierr = TSGetStepNumber(ts,&steps);CHKERRQ(ierr); 217*c4762a1bSJed Brown 218*c4762a1bSJed Brown /* - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 219*c4762a1bSJed Brown View timestepping solver info 220*c4762a1bSJed Brown - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - */ 221*c4762a1bSJed Brown 222*c4762a1bSJed Brown ierr = PetscPrintf(PETSC_COMM_SELF,"avg. error (2 norm) = %g, avg. error (max norm) = %g\n",(double)(appctx.norm_2/steps),(double)(appctx.norm_max/steps));CHKERRQ(ierr); 223*c4762a1bSJed Brown ierr = TSView(ts,PETSC_VIEWER_STDOUT_SELF);CHKERRQ(ierr); 224*c4762a1bSJed Brown 225*c4762a1bSJed Brown /* - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 226*c4762a1bSJed Brown Free work space. All PETSc objects should be destroyed when they 227*c4762a1bSJed Brown are no longer needed. 228*c4762a1bSJed Brown - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - */ 229*c4762a1bSJed Brown 230*c4762a1bSJed Brown ierr = TSDestroy(&ts);CHKERRQ(ierr); 231*c4762a1bSJed Brown ierr = MatDestroy(&A);CHKERRQ(ierr); 232*c4762a1bSJed Brown ierr = VecDestroy(&u);CHKERRQ(ierr); 233*c4762a1bSJed Brown ierr = PetscViewerDestroy(&appctx.viewer1);CHKERRQ(ierr); 234*c4762a1bSJed Brown ierr = PetscViewerDestroy(&appctx.viewer2);CHKERRQ(ierr); 235*c4762a1bSJed Brown ierr = VecDestroy(&appctx.solution);CHKERRQ(ierr); 236*c4762a1bSJed Brown 237*c4762a1bSJed Brown /* 238*c4762a1bSJed Brown Always call PetscFinalize() before exiting a program. This routine 239*c4762a1bSJed Brown - finalizes the PETSc libraries as well as MPI 240*c4762a1bSJed Brown - provides summary and diagnostic information if certain runtime 241*c4762a1bSJed Brown options are chosen (e.g., -log_view). 242*c4762a1bSJed Brown */ 243*c4762a1bSJed Brown ierr = PetscFinalize(); 244*c4762a1bSJed Brown return ierr; 245*c4762a1bSJed Brown } 246*c4762a1bSJed Brown /* --------------------------------------------------------------------- */ 247*c4762a1bSJed Brown /* 248*c4762a1bSJed Brown InitialConditions - Computes the solution at the initial time. 249*c4762a1bSJed Brown 250*c4762a1bSJed Brown Input Parameter: 251*c4762a1bSJed Brown u - uninitialized solution vector (global) 252*c4762a1bSJed Brown appctx - user-defined application context 253*c4762a1bSJed Brown 254*c4762a1bSJed Brown Output Parameter: 255*c4762a1bSJed Brown u - vector with solution at initial time (global) 256*c4762a1bSJed Brown */ 257*c4762a1bSJed Brown PetscErrorCode InitialConditions(Vec u,AppCtx *appctx) 258*c4762a1bSJed Brown { 259*c4762a1bSJed Brown PetscScalar *u_localptr,h = appctx->h; 260*c4762a1bSJed Brown PetscInt i; 261*c4762a1bSJed Brown PetscErrorCode ierr; 262*c4762a1bSJed Brown 263*c4762a1bSJed Brown /* 264*c4762a1bSJed Brown Get a pointer to vector data. 265*c4762a1bSJed Brown - For default PETSc vectors, VecGetArray() returns a pointer to 266*c4762a1bSJed Brown the data array. Otherwise, the routine is implementation dependent. 267*c4762a1bSJed Brown - You MUST call VecRestoreArray() when you no longer need access to 268*c4762a1bSJed Brown the array. 269*c4762a1bSJed Brown - Note that the Fortran interface to VecGetArray() differs from the 270*c4762a1bSJed Brown C version. See the users manual for details. 271*c4762a1bSJed Brown */ 272*c4762a1bSJed Brown ierr = VecGetArray(u,&u_localptr);CHKERRQ(ierr); 273*c4762a1bSJed Brown 274*c4762a1bSJed Brown /* 275*c4762a1bSJed Brown We initialize the solution array by simply writing the solution 276*c4762a1bSJed Brown directly into the array locations. Alternatively, we could use 277*c4762a1bSJed Brown VecSetValues() or VecSetValuesLocal(). 278*c4762a1bSJed Brown */ 279*c4762a1bSJed Brown for (i=0; i<appctx->m; i++) u_localptr[i] = PetscCosScalar(PETSC_PI*i*6.*h) + 3.*PetscCosScalar(PETSC_PI*i*2.*h); 280*c4762a1bSJed Brown 281*c4762a1bSJed Brown /* 282*c4762a1bSJed Brown Restore vector 283*c4762a1bSJed Brown */ 284*c4762a1bSJed Brown ierr = VecRestoreArray(u,&u_localptr);CHKERRQ(ierr); 285*c4762a1bSJed Brown 286*c4762a1bSJed Brown /* 287*c4762a1bSJed Brown Print debugging information if desired 288*c4762a1bSJed Brown */ 289*c4762a1bSJed Brown if (appctx->debug) { 290*c4762a1bSJed Brown printf("initial guess vector\n"); 291*c4762a1bSJed Brown ierr = VecView(u,PETSC_VIEWER_STDOUT_SELF);CHKERRQ(ierr); 292*c4762a1bSJed Brown } 293*c4762a1bSJed Brown 294*c4762a1bSJed Brown return 0; 295*c4762a1bSJed Brown } 296*c4762a1bSJed Brown /* --------------------------------------------------------------------- */ 297*c4762a1bSJed Brown /* 298*c4762a1bSJed Brown ExactSolution - Computes the exact solution at a given time. 299*c4762a1bSJed Brown 300*c4762a1bSJed Brown Input Parameters: 301*c4762a1bSJed Brown t - current time 302*c4762a1bSJed Brown solution - vector in which exact solution will be computed 303*c4762a1bSJed Brown appctx - user-defined application context 304*c4762a1bSJed Brown 305*c4762a1bSJed Brown Output Parameter: 306*c4762a1bSJed Brown solution - vector with the newly computed exact solution 307*c4762a1bSJed Brown */ 308*c4762a1bSJed Brown PetscErrorCode ExactSolution(PetscReal t,Vec solution,AppCtx *appctx) 309*c4762a1bSJed Brown { 310*c4762a1bSJed Brown PetscScalar *s_localptr,h = appctx->h,ex1,ex2,sc1,sc2,tc = t; 311*c4762a1bSJed Brown PetscInt i; 312*c4762a1bSJed Brown PetscErrorCode ierr; 313*c4762a1bSJed Brown 314*c4762a1bSJed Brown /* 315*c4762a1bSJed Brown Get a pointer to vector data. 316*c4762a1bSJed Brown */ 317*c4762a1bSJed Brown ierr = VecGetArray(solution,&s_localptr);CHKERRQ(ierr); 318*c4762a1bSJed Brown 319*c4762a1bSJed Brown /* 320*c4762a1bSJed Brown Simply write the solution directly into the array locations. 321*c4762a1bSJed Brown Alternatively, we culd use VecSetValues() or VecSetValuesLocal(). 322*c4762a1bSJed Brown */ 323*c4762a1bSJed Brown ex1 = PetscExpScalar(-36.*PETSC_PI*PETSC_PI*tc); ex2 = PetscExpScalar(-4.*PETSC_PI*PETSC_PI*tc); 324*c4762a1bSJed Brown sc1 = PETSC_PI*6.*h; sc2 = PETSC_PI*2.*h; 325*c4762a1bSJed Brown for (i=0; i<appctx->m; i++) s_localptr[i] = PetscCosScalar(sc1*(PetscReal)i)*ex1 + 3.*PetscCosScalar(sc2*(PetscReal)i)*ex2; 326*c4762a1bSJed Brown 327*c4762a1bSJed Brown /* 328*c4762a1bSJed Brown Restore vector 329*c4762a1bSJed Brown */ 330*c4762a1bSJed Brown ierr = VecRestoreArray(solution,&s_localptr);CHKERRQ(ierr); 331*c4762a1bSJed Brown return 0; 332*c4762a1bSJed Brown } 333*c4762a1bSJed Brown /* --------------------------------------------------------------------- */ 334*c4762a1bSJed Brown /* 335*c4762a1bSJed Brown Monitor - User-provided routine to monitor the solution computed at 336*c4762a1bSJed Brown each timestep. This example plots the solution and computes the 337*c4762a1bSJed Brown error in two different norms. 338*c4762a1bSJed Brown 339*c4762a1bSJed Brown Input Parameters: 340*c4762a1bSJed Brown ts - the timestep context 341*c4762a1bSJed Brown step - the count of the current step (with 0 meaning the 342*c4762a1bSJed Brown initial condition) 343*c4762a1bSJed Brown time - the current time 344*c4762a1bSJed Brown u - the solution at this timestep 345*c4762a1bSJed Brown ctx - the user-provided context for this monitoring routine. 346*c4762a1bSJed Brown In this case we use the application context which contains 347*c4762a1bSJed Brown information about the problem size, workspace and the exact 348*c4762a1bSJed Brown solution. 349*c4762a1bSJed Brown */ 350*c4762a1bSJed Brown PetscErrorCode Monitor(TS ts,PetscInt step,PetscReal time,Vec u,void *ctx) 351*c4762a1bSJed Brown { 352*c4762a1bSJed Brown AppCtx *appctx = (AppCtx*) ctx; /* user-defined application context */ 353*c4762a1bSJed Brown PetscErrorCode ierr; 354*c4762a1bSJed Brown PetscReal norm_2,norm_max; 355*c4762a1bSJed Brown 356*c4762a1bSJed Brown /* 357*c4762a1bSJed Brown View a graph of the current iterate 358*c4762a1bSJed Brown */ 359*c4762a1bSJed Brown ierr = VecView(u,appctx->viewer2);CHKERRQ(ierr); 360*c4762a1bSJed Brown 361*c4762a1bSJed Brown /* 362*c4762a1bSJed Brown Compute the exact solution 363*c4762a1bSJed Brown */ 364*c4762a1bSJed Brown ierr = ExactSolution(time,appctx->solution,appctx);CHKERRQ(ierr); 365*c4762a1bSJed Brown 366*c4762a1bSJed Brown /* 367*c4762a1bSJed Brown Print debugging information if desired 368*c4762a1bSJed Brown */ 369*c4762a1bSJed Brown if (appctx->debug) { 370*c4762a1bSJed Brown printf("Computed solution vector\n"); 371*c4762a1bSJed Brown ierr = VecView(u,PETSC_VIEWER_STDOUT_SELF);CHKERRQ(ierr); 372*c4762a1bSJed Brown printf("Exact solution vector\n"); 373*c4762a1bSJed Brown ierr = VecView(appctx->solution,PETSC_VIEWER_STDOUT_SELF);CHKERRQ(ierr); 374*c4762a1bSJed Brown } 375*c4762a1bSJed Brown 376*c4762a1bSJed Brown /* 377*c4762a1bSJed Brown Compute the 2-norm and max-norm of the error 378*c4762a1bSJed Brown */ 379*c4762a1bSJed Brown ierr = VecAXPY(appctx->solution,-1.0,u);CHKERRQ(ierr); 380*c4762a1bSJed Brown ierr = VecNorm(appctx->solution,NORM_2,&norm_2);CHKERRQ(ierr); 381*c4762a1bSJed Brown norm_2 = PetscSqrtReal(appctx->h)*norm_2; 382*c4762a1bSJed Brown ierr = VecNorm(appctx->solution,NORM_MAX,&norm_max);CHKERRQ(ierr); 383*c4762a1bSJed Brown if (norm_2 < 1e-14) norm_2 = 0; 384*c4762a1bSJed Brown if (norm_max < 1e-14) norm_max = 0; 385*c4762a1bSJed Brown 386*c4762a1bSJed Brown ierr = PetscPrintf(PETSC_COMM_WORLD,"Timestep %D: time = %g, 2-norm error = %g, max norm error = %g\n",step,(double)time,(double)norm_2,(double)norm_max);CHKERRQ(ierr); 387*c4762a1bSJed Brown appctx->norm_2 += norm_2; 388*c4762a1bSJed Brown appctx->norm_max += norm_max; 389*c4762a1bSJed Brown 390*c4762a1bSJed Brown /* 391*c4762a1bSJed Brown View a graph of the error 392*c4762a1bSJed Brown */ 393*c4762a1bSJed Brown ierr = VecView(appctx->solution,appctx->viewer1);CHKERRQ(ierr); 394*c4762a1bSJed Brown 395*c4762a1bSJed Brown /* 396*c4762a1bSJed Brown Print debugging information if desired 397*c4762a1bSJed Brown */ 398*c4762a1bSJed Brown if (appctx->debug) { 399*c4762a1bSJed Brown printf("Error vector\n"); 400*c4762a1bSJed Brown ierr = VecView(appctx->solution,PETSC_VIEWER_STDOUT_SELF);CHKERRQ(ierr); 401*c4762a1bSJed Brown } 402*c4762a1bSJed Brown 403*c4762a1bSJed Brown return 0; 404*c4762a1bSJed Brown } 405*c4762a1bSJed Brown /* --------------------------------------------------------------------- */ 406*c4762a1bSJed Brown /* 407*c4762a1bSJed Brown RHSMatrixHeat - User-provided routine to compute the right-hand-side 408*c4762a1bSJed Brown matrix for the heat equation. 409*c4762a1bSJed Brown 410*c4762a1bSJed Brown Input Parameters: 411*c4762a1bSJed Brown ts - the TS context 412*c4762a1bSJed Brown t - current time 413*c4762a1bSJed Brown global_in - global input vector 414*c4762a1bSJed Brown dummy - optional user-defined context, as set by TSetRHSJacobian() 415*c4762a1bSJed Brown 416*c4762a1bSJed Brown Output Parameters: 417*c4762a1bSJed Brown AA - Jacobian matrix 418*c4762a1bSJed Brown BB - optionally different preconditioning matrix 419*c4762a1bSJed Brown str - flag indicating matrix structure 420*c4762a1bSJed Brown 421*c4762a1bSJed Brown Notes: 422*c4762a1bSJed Brown Recall that MatSetValues() uses 0-based row and column numbers 423*c4762a1bSJed Brown in Fortran as well as in C. 424*c4762a1bSJed Brown */ 425*c4762a1bSJed Brown PetscErrorCode RHSMatrixHeat(TS ts,PetscReal t,Vec X,Mat AA,Mat BB,void *ctx) 426*c4762a1bSJed Brown { 427*c4762a1bSJed Brown Mat A = AA; /* Jacobian matrix */ 428*c4762a1bSJed Brown AppCtx *appctx = (AppCtx*)ctx; /* user-defined application context */ 429*c4762a1bSJed Brown PetscInt mstart = 0; 430*c4762a1bSJed Brown PetscInt mend = appctx->m; 431*c4762a1bSJed Brown PetscErrorCode ierr; 432*c4762a1bSJed Brown PetscInt i,idx[3]; 433*c4762a1bSJed Brown PetscScalar v[3],stwo = -2./(appctx->h*appctx->h),sone = -.5*stwo; 434*c4762a1bSJed Brown 435*c4762a1bSJed Brown /* - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 436*c4762a1bSJed Brown Compute entries for the locally owned part of the matrix 437*c4762a1bSJed Brown - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - */ 438*c4762a1bSJed Brown /* 439*c4762a1bSJed Brown Set matrix rows corresponding to boundary data 440*c4762a1bSJed Brown */ 441*c4762a1bSJed Brown 442*c4762a1bSJed Brown mstart = 0; 443*c4762a1bSJed Brown v[0] = 1.0; 444*c4762a1bSJed Brown ierr = MatSetValues(A,1,&mstart,1,&mstart,v,INSERT_VALUES);CHKERRQ(ierr); 445*c4762a1bSJed Brown mstart++; 446*c4762a1bSJed Brown 447*c4762a1bSJed Brown mend--; 448*c4762a1bSJed Brown v[0] = 1.0; 449*c4762a1bSJed Brown ierr = MatSetValues(A,1,&mend,1,&mend,v,INSERT_VALUES);CHKERRQ(ierr); 450*c4762a1bSJed Brown 451*c4762a1bSJed Brown /* 452*c4762a1bSJed Brown Set matrix rows corresponding to interior data. We construct the 453*c4762a1bSJed Brown matrix one row at a time. 454*c4762a1bSJed Brown */ 455*c4762a1bSJed Brown v[0] = sone; v[1] = stwo; v[2] = sone; 456*c4762a1bSJed Brown for (i=mstart; i<mend; i++) { 457*c4762a1bSJed Brown idx[0] = i-1; idx[1] = i; idx[2] = i+1; 458*c4762a1bSJed Brown ierr = MatSetValues(A,1,&i,3,idx,v,INSERT_VALUES);CHKERRQ(ierr); 459*c4762a1bSJed Brown } 460*c4762a1bSJed Brown 461*c4762a1bSJed Brown /* - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 462*c4762a1bSJed Brown Complete the matrix assembly process and set some options 463*c4762a1bSJed Brown - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - */ 464*c4762a1bSJed Brown /* 465*c4762a1bSJed Brown Assemble matrix, using the 2-step process: 466*c4762a1bSJed Brown MatAssemblyBegin(), MatAssemblyEnd() 467*c4762a1bSJed Brown Computations can be done while messages are in transition 468*c4762a1bSJed Brown by placing code between these two statements. 469*c4762a1bSJed Brown */ 470*c4762a1bSJed Brown ierr = MatAssemblyBegin(A,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 471*c4762a1bSJed Brown ierr = MatAssemblyEnd(A,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 472*c4762a1bSJed Brown 473*c4762a1bSJed Brown /* 474*c4762a1bSJed Brown Set and option to indicate that we will never add a new nonzero location 475*c4762a1bSJed Brown to the matrix. If we do, it will generate an error. 476*c4762a1bSJed Brown */ 477*c4762a1bSJed Brown ierr = MatSetOption(A,MAT_NEW_NONZERO_LOCATION_ERR,PETSC_TRUE);CHKERRQ(ierr); 478*c4762a1bSJed Brown 479*c4762a1bSJed Brown return 0; 480*c4762a1bSJed Brown } 481*c4762a1bSJed Brown 482*c4762a1bSJed Brown /*TEST 483*c4762a1bSJed Brown 484*c4762a1bSJed Brown test: 485*c4762a1bSJed Brown requires: x 486*c4762a1bSJed Brown 487*c4762a1bSJed Brown test: 488*c4762a1bSJed Brown suffix: nox 489*c4762a1bSJed Brown args: -nox 490*c4762a1bSJed Brown 491*c4762a1bSJed Brown TEST*/ 492*c4762a1bSJed Brown 493*c4762a1bSJed Brown 494*c4762a1bSJed Brown 495