# User files required for the Fortran code¶

The Makefile in an application directory shows the set of Fortran source code files that are being used. Most of these files are typically in one of the libraries, but a few subroutines must be provided by the user in order to specify the hyperbolic problem to be solved and the initial conditions. Other subroutines may also be provided that are application-specific. This page summarizes some of the most common user-modified routines.

The calling sequence for each subroutine differs with the number of space dimensions. The sample calling sequences shown below are for one space dimension.

The subroutines described below have default versions in the corresponding library and the Makefile can point to these if application-specific versions are not needed.

See the examples in the following directories for additional samples:

$CLAW/classic/examples

$CLAW/amrclaw/examples

$CLAW/geoclaw/examples

You can also browse from the Clawpack Gallery to the README file for an example and then to the source code for the application-specific codes.

## Specifying the initial conditions¶

Calling sequence in 1d:

```
subroutine qinit(meqn,mbc,mx,xlower,dx,q,maux,aux)
```

See the qinit default routines for other calling sequences and the proper declaration of input/output parameters.

Typically every application directory contains a file qinit.f or qinit.f90 that sets the initial conditions, typically in a loop such as:

```
do i=1,mx
xi = xlower + (i-0.5d0)*dx
q(1,i) = xi**2
enddo
```

This loop would set the value of \(q^1\) in the i’th cell to \(x_i^2\) where \(x_i\) is the cell center. For the finite volume methods used in Clawpack, the initial data should really be set to be the cell average of the data over each grid cell, determined by integrating the data for the PDE. If the initial data is given by a smooth function, then evaluating the function at the center of the grid cell generally agrees with the cell average to \({\cal O}(\Delta x^2)\) and is consistent with the second-order accurate high-resolution methods being used in Clawpack.

For a system of more than 1 equation, you must set q(m,i) for m = 1, 2, …, num_eqn.

For adaptive mesh refinement codes, the qinit subroutine will be called for each grid patch at the initial time, so it is always necessary to compute the cell centers based on the information passed in.

## Specifying the Riemann solver¶

The Riemann solver defines the hyperbolic equation that is being solved and does the bulk of the computational work – it is called at every cell interface every time step and returns the information about waves and speeds that is needed to update the solution.

See Riemann solvers for more details about the Riemann solvers.

All of the examples that come with Clawpack use Riemann solvers that are provided in the directory $CLAW/riemann/src, see the Makefile in one of the examples to determine what Riemann solver file(s) are being used (in two and three space dimensions, transverse Riemann solvers are also required).

The directory $CLAW/riemann/src contains Riemann solvers for many applications, including advection, acoustics, shallow water equations, Euler equations, traffic flow, Burgers’ equation, etc.

## Specifying boundary conditions¶

Boundary conditions are set by the library routines:

$CLAW/classic/src/Nd/bcN.f for the classic code (N = 1, 2, 3).

$CLAW/amrclaw/src/Nd/bcNamr.f for the amrclaw code (N = 2, 3).

Several standard choices of boundary condition procedures are provided in these routines – see Boundary conditions for details.

For user-supplied boundary conditions that are not implemented in the library routines, the library routine can be copied to the application directory and changes made as described at User-defined boundary conditions. The Makefile should then be modified to point to the local version.

## Specifying problem-specific data¶

Often an application problem has data or parameters that is most conveniently specified in a user-supplied routine named setprob. There is a library version that does nothing in case one is not specified in the application directory. As usual, the Makefile indicates what file is used.

The setprob subroutine takes no arguments. Data set in setprob is often passed in common blocks to other routines, such as qinit or the Riemann solver. This is appropriate only for data that does not change with time and does not vary in space (e.g. the gravitational constant g in the shallow water equations, or the density and bulk modulus for acoustics in a homogenous medium).

Note that named common blocks must have the same name in each routine where they are used. Check any Riemann solvers you use (including those from $CLAW/riemann/src) to see if they require some parameters to be passed in via a common block. If so, setprob is the place to set them.

For spatially-varying data, see Specifying spatially-varying data using setaux below.

Often setprob is written so that it reads in data values from a file, often called setprob.data. This makes it easier to modify parameter values without recompiling the code. It is also possible to set these values in setrun.py so that this input data is specified in the same file as other input parameters. For a sample, see $CLAW/classic/examples/acoustics_1d_heterogeneous, for example.

## Specifying spatially-varying data using setaux¶

Some problems require specifying spatially varying data, for example the
density and bulk modulus for acoustics in a heterogenous medium might vary
in space and in principle could be different in each grid cell. The best
way to specify such data is by use of *auxiliary arrays* that are created
whenever a grid patch for the solution is created and have the same number
of cells with num_aux components in each cell. The value num_aux is
specified in setrun.py, and the contents of the aux arrays are filled by
a subroutine named setaux, which in one dimension has the calling
sequence:

```
subroutine setaux(mbc,mx,xlower,dx,maux,aux)
```

See the setaux default routines for other calling sequences and the proper declaration of input/output parameters.

If adaptive refinement is being used, then every time a new grid patch is created at any refinement level this subroutine will be called to fill in the corresponding aux arrays. For a sample, see $CLAW/classic/examples/acoustics_1d_heterogeneous, for example.

If the aux arrays need to be time-dependent, the easiest way to adjust them each time step is in the routine b4step described below.

## Using b4step for work to be done before each time step¶

The routine b4stepN is called in N space dimensions (N=1,2,3) just before a time step is taken (and after ghost cells have been filled by the boundary conditions). The library version of this routine does nothing, but this can be modified to do something prior to every time step.

In one dimension the calling sequence is:

```
subroutine b4step1(mbc,mx,meqn,q,xlower,dx,t,dt,maux,aux)
```

See the b4step default routines for other calling sequences and the proper declaration of input/output parameters.

For example, in $CLAW/amrclaw/examples/advection_2d_swirl the advection equation is solved with an advection velocity that varies in time as well as space. This is initialized for each grid patch in setaux, but is adjusted each time step in b4step2.

## Using src for source terms¶

Problems of the form \(q_t(x,t) + f(q(x,t))_x = \psi(q,x,t)\) can be solved using a fractional step approach, as described in Chapter 17 of [LeVeque-FVMHP]. The user can provide a subroutine named srcN in N space dimensions that takes a single time step on the equation \(q_t = \psi\). In one dimension the calling sequence is:

```
subroutine src1(meqn,mbc,mx,xlower,dx,q,maux,aux,t,dt)
```

On output the q array should have been updated by using the input values as initial data for a single step of length dt starting at time t.

See the src default routines for other calling sequences and the proper declaration of input/output parameters.

The library version of srcN does nothing. If you copy this to an application directory and modify for your equation, you must modify the Makefile to point to the local version. You must also set the source_split parameter in setrun.py (see Specifying classic run-time parameters in setrun.py) to either “godunov” or “strang”. In the former case, the 1st order Godunov splitting is used (after each time step on the homogenous hyperbolic equation, a time step of the same length is taken on the source terms). In the latter case the 2nd order Strang splitting is used: the time step on the hyperbolic part is both preceeded and followed by a time step of half the length on the source terms.

For an example where source terms are used, see $CLAW/classic/examples/acoustics_2d_radial/1drad where a one-dimensional acoustic equation with a geometric source term is solved in order to provide a reference solution for the two-dimensional radially symmetric problem solved in $CLAW/classic/examples/acoustics_2d_radial.

## Using src1d for source terms with AMRClaw¶

When the AMRClaw code is used for a problem in 2 or 3 dimensions with source terms, then a subroutine srcN must be provided as described above. In addition, for the AMR procedure to work properly it is also necessary to provide another subroutine src1d with calling sequence:

```
subroutine src1d(meqn,mbc,mx1d,q1d,maux,aux1d,t,dt)
```

See the src1d default routines for other calling sequences and the proper declaration of input/output parameters.

This routine should be a simplified version of src2 or src3 that takes a one-dimensional set of data in q1d rather than a full 2- or 3-dimensional array of data. The input array aux1d has the corresponding set of auxiliary variables in case these are needed in stepping forward with the source terms.

If the source terms depend only on q, it should be easy to adapt src2 to create this routine, simply by looping over i=1:mx1d rather than over a multi-dimensional array.

This routine is used in computing adjustments around a fine grid patch that are needed in order to maintain global conservation after values in a coarser grid cell have been overwritten with the average of the more accurate fine grid values. Adjustment of the coarse grid values in the cells bordering this patch is then required to maintain conservation. This requires solving a set of Riemann problems between fine-grid and coarse-grid values around the edge of the patch and src1d is used in advancing coarse grid values to intermediate time steps.

The code may work fine without applying source terms in this context, so using the dummy library routine src1d might be successful even when source terms are present.