static char help[] = "Solves a simple time-dependent linear PDE (the heat equation).\n\ Input parameters include:\n\ -m , where = number of grid points\n\ -time_dependent_rhs : Treat the problem as having a time-dependent right-hand side\n\ -debug : Activate debugging printouts\n\ -nox : Deactivate x-window graphics\n\n"; /* ------------------------------------------------------------------------ This program solves the one-dimensional heat equation (also called the diffusion equation), u_t = u_xx, on the domain 0 <= x <= 1, with the boundary conditions u(t,0) = 1, u(t,1) = 1, and the initial condition u(0,x) = cos(6*pi*x) + 3*cos(2*pi*x). This is a linear, second-order, parabolic equation. We discretize the right-hand side using finite differences with uniform grid spacing h: u_xx = (u_{i+1} - 2u_{i} + u_{i-1})/(h^2) We then demonstrate time evolution using the various TS methods by running the program via ex3 -ts_type We compare the approximate solution with the exact solution, given by u_exact(x,t) = exp(-36*pi*pi*t) * cos(6*pi*x) + 3*exp(-4*pi*pi*t) * cos(2*pi*x) Notes: This code demonstrates the TS solver interface to two variants of linear problems, u_t = f(u,t), namely - time-dependent f: f(u,t) is a function of t - time-independent f: f(u,t) is simply just f(u) The parallel version of this code is ts/tutorials/ex4.c ------------------------------------------------------------------------- */ /* Include "petscts.h" so that we can use TS solvers. Note that this file automatically includes: petscsys.h - base PETSc routines petscvec.h - vectors petscmat.h - matrices petscis.h - index sets petscksp.h - Krylov subspace methods petscviewer.h - viewers petscpc.h - preconditioners petscksp.h - linear solvers petscsnes.h - nonlinear solvers */ #include #include /* User-defined application context - contains data needed by the application-provided call-back routines. */ typedef struct { Vec solution; /* global exact solution vector */ PetscInt m; /* total number of grid points */ PetscReal h; /* mesh width h = 1/(m-1) */ PetscBool debug; /* flag (1 indicates activation of debugging printouts) */ PetscViewer viewer1, viewer2; /* viewers for the solution and error */ PetscReal norm_2, norm_max; /* error norms */ } AppCtx; /* User-defined routines */ extern PetscErrorCode InitialConditions(Vec, AppCtx *); extern PetscErrorCode RHSMatrixHeat(TS, PetscReal, Vec, Mat, Mat, void *); extern PetscErrorCode Monitor(TS, PetscInt, PetscReal, Vec, void *); extern PetscErrorCode ExactSolution(PetscReal, Vec, AppCtx *); int main(int argc, char **argv) { AppCtx appctx; /* user-defined application context */ TS ts; /* timestepping context */ Mat A; /* matrix data structure */ Vec u; /* approximate solution vector */ PetscReal time_total_max = 100.0; /* default max total time */ PetscInt time_steps_max = 100; /* default max timesteps */ PetscDraw draw; /* drawing context */ PetscInt steps, m; PetscMPIInt size; PetscBool flg; PetscReal dt, ftime; /* - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - Initialize program and set problem parameters - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - */ PetscFunctionBeginUser; PetscCall(PetscInitialize(&argc, &argv, NULL, help)); PetscCallMPI(MPI_Comm_size(PETSC_COMM_WORLD, &size)); PetscCheck(size == 1, PETSC_COMM_WORLD, PETSC_ERR_WRONG_MPI_SIZE, "This is a uniprocessor example only!"); m = 60; PetscCall(PetscOptionsGetInt(NULL, NULL, "-m", &m, NULL)); PetscCall(PetscOptionsHasName(NULL, NULL, "-debug", &appctx.debug)); appctx.m = m; appctx.h = 1.0 / (m - 1.0); appctx.norm_2 = 0.0; appctx.norm_max = 0.0; PetscCall(PetscPrintf(PETSC_COMM_SELF, "Solving a linear TS problem on 1 processor\n")); /* - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - Create vector data structures - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - */ /* Create vector data structures for approximate and exact solutions */ PetscCall(VecCreateSeq(PETSC_COMM_SELF, m, &u)); PetscCall(VecDuplicate(u, &appctx.solution)); /* - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - Set up displays to show graphs of the solution and error - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - */ PetscCall(PetscViewerDrawOpen(PETSC_COMM_SELF, 0, "", 80, 380, 400, 160, &appctx.viewer1)); PetscCall(PetscViewerDrawGetDraw(appctx.viewer1, 0, &draw)); PetscCall(PetscDrawSetDoubleBuffer(draw)); PetscCall(PetscViewerDrawOpen(PETSC_COMM_SELF, 0, "", 80, 0, 400, 160, &appctx.viewer2)); PetscCall(PetscViewerDrawGetDraw(appctx.viewer2, 0, &draw)); PetscCall(PetscDrawSetDoubleBuffer(draw)); /* - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - Create timestepping solver context - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - */ PetscCall(TSCreate(PETSC_COMM_SELF, &ts)); PetscCall(TSSetProblemType(ts, TS_LINEAR)); /* - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - Set optional user-defined monitoring routine - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - */ PetscCall(TSMonitorSet(ts, Monitor, &appctx, NULL)); /* - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - Create matrix data structure; set matrix evaluation routine. - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - */ PetscCall(MatCreate(PETSC_COMM_SELF, &A)); PetscCall(MatSetSizes(A, PETSC_DECIDE, PETSC_DECIDE, m, m)); PetscCall(MatSetFromOptions(A)); PetscCall(MatSetUp(A)); PetscCall(PetscOptionsHasName(NULL, NULL, "-time_dependent_rhs", &flg)); if (flg) { /* For linear problems with a time-dependent f(u,t) in the equation u_t = f(u,t), the user provides the discretized right-hand side as a time-dependent matrix. */ PetscCall(TSSetRHSFunction(ts, NULL, TSComputeRHSFunctionLinear, &appctx)); PetscCall(TSSetRHSJacobian(ts, A, A, RHSMatrixHeat, &appctx)); } else { /* For linear problems with a time-independent f(u) in the equation u_t = f(u), the user provides the discretized right-hand side as a matrix only once, and then sets a null matrix evaluation routine. */ PetscCall(RHSMatrixHeat(ts, 0.0, u, A, A, &appctx)); PetscCall(TSSetRHSFunction(ts, NULL, TSComputeRHSFunctionLinear, &appctx)); PetscCall(TSSetRHSJacobian(ts, A, A, TSComputeRHSJacobianConstant, &appctx)); } /* - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - Set solution vector and initial timestep - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - */ dt = appctx.h * appctx.h / 2.0; PetscCall(TSSetTimeStep(ts, dt)); PetscCall(TSSetSolution(ts, u)); /* - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - Customize timestepping solver: - Set the solution method to be the Backward Euler method. - Set timestepping duration info Then set runtime options, which can override these defaults. For example, -ts_max_steps -ts_max_time to override the defaults set by TSSetMaxSteps()/TSSetMaxTime(). - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - */ PetscCall(TSSetMaxSteps(ts, time_steps_max)); PetscCall(TSSetMaxTime(ts, time_total_max)); PetscCall(TSSetExactFinalTime(ts, TS_EXACTFINALTIME_STEPOVER)); PetscCall(TSSetFromOptions(ts)); /* - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - Solve the problem - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - */ /* Evaluate initial conditions */ PetscCall(InitialConditions(u, &appctx)); /* Run the timestepping solver */ PetscCall(TSSolve(ts, u)); PetscCall(TSGetSolveTime(ts, &ftime)); PetscCall(TSGetStepNumber(ts, &steps)); /* - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - View timestepping solver info - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - */ PetscCall(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))); PetscCall(TSView(ts, PETSC_VIEWER_STDOUT_SELF)); /* - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - Free work space. All PETSc objects should be destroyed when they are no longer needed. - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - */ PetscCall(TSDestroy(&ts)); PetscCall(MatDestroy(&A)); PetscCall(VecDestroy(&u)); PetscCall(PetscViewerDestroy(&appctx.viewer1)); PetscCall(PetscViewerDestroy(&appctx.viewer2)); PetscCall(VecDestroy(&appctx.solution)); /* Always call PetscFinalize() before exiting a program. This routine - finalizes the PETSc libraries as well as MPI - provides summary and diagnostic information if certain runtime options are chosen (e.g., -log_view). */ PetscCall(PetscFinalize()); return 0; } /* --------------------------------------------------------------------- */ /* InitialConditions - Computes the solution at the initial time. Input Parameter: u - uninitialized solution vector (global) appctx - user-defined application context Output Parameter: u - vector with solution at initial time (global) */ PetscErrorCode InitialConditions(Vec u, AppCtx *appctx) { PetscScalar *u_localptr, h = appctx->h; PetscInt i; PetscFunctionBeginUser; /* Get a pointer to vector data. - For default PETSc vectors, VecGetArray() returns a pointer to the data array. Otherwise, the routine is implementation dependent. - You MUST call VecRestoreArray() when you no longer need access to the array. - Note that the Fortran interface to VecGetArray() differs from the C version. See the users manual for details. */ PetscCall(VecGetArray(u, &u_localptr)); /* We initialize the solution array by simply writing the solution directly into the array locations. Alternatively, we could use VecSetValues() or VecSetValuesLocal(). */ for (i = 0; i < appctx->m; i++) u_localptr[i] = PetscCosScalar(PETSC_PI * i * 6. * h) + 3. * PetscCosScalar(PETSC_PI * i * 2. * h); /* Restore vector */ PetscCall(VecRestoreArray(u, &u_localptr)); /* Print debugging information if desired */ if (appctx->debug) { printf("initial guess vector\n"); PetscCall(VecView(u, PETSC_VIEWER_STDOUT_SELF)); } PetscFunctionReturn(PETSC_SUCCESS); } /* --------------------------------------------------------------------- */ /* ExactSolution - Computes the exact solution at a given time. Input Parameters: t - current time solution - vector in which exact solution will be computed appctx - user-defined application context Output Parameter: solution - vector with the newly computed exact solution */ PetscErrorCode ExactSolution(PetscReal t, Vec solution, AppCtx *appctx) { PetscScalar *s_localptr, h = appctx->h, ex1, ex2, sc1, sc2, tc = t; PetscInt i; PetscFunctionBeginUser; /* Get a pointer to vector data. */ PetscCall(VecGetArray(solution, &s_localptr)); /* Simply write the solution directly into the array locations. Alternatively, we culd use VecSetValues() or VecSetValuesLocal(). */ ex1 = PetscExpScalar(-36. * PETSC_PI * PETSC_PI * tc); ex2 = PetscExpScalar(-4. * PETSC_PI * PETSC_PI * tc); sc1 = PETSC_PI * 6. * h; sc2 = PETSC_PI * 2. * h; for (i = 0; i < appctx->m; i++) s_localptr[i] = PetscCosScalar(sc1 * (PetscReal)i) * ex1 + 3. * PetscCosScalar(sc2 * (PetscReal)i) * ex2; /* Restore vector */ PetscCall(VecRestoreArray(solution, &s_localptr)); PetscFunctionReturn(PETSC_SUCCESS); } /* --------------------------------------------------------------------- */ /* Monitor - User-provided routine to monitor the solution computed at each timestep. This example plots the solution and computes the error in two different norms. Input Parameters: ts - the timestep context step - the count of the current step (with 0 meaning the initial condition) time - the current time u - the solution at this timestep ctx - the user-provided context for this monitoring routine. In this case we use the application context which contains information about the problem size, workspace and the exact solution. */ PetscErrorCode Monitor(TS ts, PetscInt step, PetscReal time, Vec u, PetscCtx ctx) { AppCtx *appctx = (AppCtx *)ctx; /* user-defined application context */ PetscReal norm_2, norm_max; PetscFunctionBeginUser; /* View a graph of the current iterate */ PetscCall(VecView(u, appctx->viewer2)); /* Compute the exact solution */ PetscCall(ExactSolution(time, appctx->solution, appctx)); /* Print debugging information if desired */ if (appctx->debug) { printf("Computed solution vector\n"); PetscCall(VecView(u, PETSC_VIEWER_STDOUT_SELF)); printf("Exact solution vector\n"); PetscCall(VecView(appctx->solution, PETSC_VIEWER_STDOUT_SELF)); } /* Compute the 2-norm and max-norm of the error */ PetscCall(VecAXPY(appctx->solution, -1.0, u)); PetscCall(VecNorm(appctx->solution, NORM_2, &norm_2)); norm_2 = PetscSqrtReal(appctx->h) * norm_2; PetscCall(VecNorm(appctx->solution, NORM_MAX, &norm_max)); if (norm_2 < 1e-14) norm_2 = 0; if (norm_max < 1e-14) norm_max = 0; PetscCall(PetscPrintf(PETSC_COMM_WORLD, "Timestep %" PetscInt_FMT ": time = %g, 2-norm error = %g, max norm error = %g\n", step, (double)time, (double)norm_2, (double)norm_max)); appctx->norm_2 += norm_2; appctx->norm_max += norm_max; /* View a graph of the error */ PetscCall(VecView(appctx->solution, appctx->viewer1)); /* Print debugging information if desired */ if (appctx->debug) { printf("Error vector\n"); PetscCall(VecView(appctx->solution, PETSC_VIEWER_STDOUT_SELF)); } PetscFunctionReturn(PETSC_SUCCESS); } /* --------------------------------------------------------------------- */ /* RHSMatrixHeat - User-provided routine to compute the right-hand-side matrix for the heat equation. Input Parameters: ts - the TS context t - current time global_in - global input vector dummy - optional user-defined context, as set by TSetRHSJacobian() Output Parameters: AA - Jacobian matrix BB - optionally different matrix used to construct the preconditioner Notes: Recall that MatSetValues() uses 0-based row and column numbers in Fortran as well as in C. */ PetscErrorCode RHSMatrixHeat(TS ts, PetscReal t, Vec X, Mat AA, Mat BB, PetscCtx ctx) { Mat A = AA; /* Jacobian matrix */ AppCtx *appctx = (AppCtx *)ctx; /* user-defined application context */ PetscInt mstart = 0; PetscInt mend = appctx->m; PetscInt i, idx[3]; PetscScalar v[3], stwo = -2. / (appctx->h * appctx->h), sone = -.5 * stwo; PetscFunctionBeginUser; /* - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - Compute entries for the locally owned part of the matrix - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - */ /* Set matrix rows corresponding to boundary data */ mstart = 0; v[0] = 1.0; PetscCall(MatSetValues(A, 1, &mstart, 1, &mstart, v, INSERT_VALUES)); mstart++; mend--; v[0] = 1.0; PetscCall(MatSetValues(A, 1, &mend, 1, &mend, v, INSERT_VALUES)); /* Set matrix rows corresponding to interior data. We construct the matrix one row at a time. */ v[0] = sone; v[1] = stwo; v[2] = sone; for (i = mstart; i < mend; i++) { idx[0] = i - 1; idx[1] = i; idx[2] = i + 1; PetscCall(MatSetValues(A, 1, &i, 3, idx, v, INSERT_VALUES)); } /* - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - Complete the matrix assembly process and set some options - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - */ /* Assemble matrix, using the 2-step process: MatAssemblyBegin(), MatAssemblyEnd() Computations can be done while messages are in transition by placing code between these two statements. */ PetscCall(MatAssemblyBegin(A, MAT_FINAL_ASSEMBLY)); PetscCall(MatAssemblyEnd(A, MAT_FINAL_ASSEMBLY)); /* Set and option to indicate that we will never add a new nonzero location to the matrix. If we do, it will generate an error. */ PetscCall(MatSetOption(A, MAT_NEW_NONZERO_LOCATION_ERR, PETSC_TRUE)); PetscFunctionReturn(PETSC_SUCCESS); } /*TEST test: requires: x test: suffix: nox args: -nox TEST*/