# Design ideas

pyro is written entirely in python (by default, we expect python 3),
with a few low-level routines compiled *just-in-time* by numba for performance. The
`numpy`

package is used for representing arrays throughout the
python code and the `matplotlib`

library is used for
visualization. Finally, `pytest`

is used for unit testing of some
components.

All solvers are written for a 2-d grid. This gives a good balance between complexity and speed.

A paper describing the design philosophy of pyro was accepted to Astronomy & Computing [paper link].

## Directory structure

pyro follows a standard python package structure. The main directory
(called `pyro2/`

for historical reasons) contains:

`docs/`

: The documentation in Sphinx format`examples/`

: Some example notebooks`paper/`

: the original JOSS paper`presentations/`

: some presentations given on pyro in the past`pyro/`

: the main source directory`www/`

: the logo used in the website

It is at this level (`pyro2/`

) that the installation of pyro is done (via `setup.py`

).

`pyro/`

The main code is all contained in the `pyro/`

subdirectory. Here we discuss that.

The files for each solver are in their own sub-directory, with
additional sub-directories for the mesh and utilities. Each solver has
two sub-directories: `problems/`

and `tests/`

. These store the
different problem setups for the solver and reference output for
testing.

The overall structure is:

`advection/`

: The linear advection equation solver using the CTU method. All advection-specific routines live here.`problems/`

: The problem setups for the advection solver.`tests/`

: Reference advection output files for comparison and regression testing.

`advection_fv4/`

: The fourth-order accurate finite-volume advection solver that uses RK4 time integration.`problems/`

: The problem setups for the fourth-order advection solver.`tests/`

: Reference advection output files for comparison and regression testing.

`advection_nonuniform/`

: The solver for advection with a non-uniform velocity field.`problems/`

: The problem setups for the non-uniform advection solver.`tests/`

: Reference advection output files for comparison and regression testing.

`advection_rk/`

: The linear advection equation solver using the method-of-lines approach.`problems/`

: This is a symbolic link to the advection/problems/ directory.`tests/`

: Reference advection output files for comparison and regression testing.

`advection_weno/`

: The method-of-lines WENO solver for linear advection.`problems/`

: This is a symbolic link to the advection/problems/ directory.

`analysis/`

: Various analysis scripts for processing pyro output files.`compressible/`

: The fourth-order accurate finite-volume compressible hydro solver that uses RK4 time integration. This is built from the method of McCourquodale and Colella (2011).`problems/`

: The problem setups for the fourth-order compressible hydrodynamics solver.`tests/`

: Reference compressible hydro output for regression testing.

`compressible_fv4/`

: The compressible hydrodynamics solver using the CTU method. All source files specific to this solver live here.`problems/`

: This is a symbolic link to the compressible/problems/ directory.`tests/`

: Reference compressible hydro output for regression testing.

`compressible_rk/`

: The compressible hydrodynamics solver using method of lines integration.`problems/`

: This is a symbolic link to the compressible/problems/ directory.`tests/`

: Reference compressible hydro output for regression testing.

`compressible_sdc/`

: The fourth-order compressible solver, using spectral-deferred correction (SDC) for the time integration.`problems/`

: This is a symbolic link to the compressible/problems/ directory.`tests/`

: Reference compressible hydro output for regression testing.

`diffusion/`

: The implicit (thermal) diffusion solver. All diffusion-specific routines live here.`problems/`

: The problem setups for the diffusion solver.`tests/`

: Reference diffusion output for regression testing.

`incompressible/`

: The incompressible hydrodynamics solver. All incompressible-specific routines live here.`problems/`

: The problem setups for the incompressible solver.`tests/`

: Reference incompressible hydro output for regression testing.

`lm_atm/`

: The low Mach number hydrodynamics solver for atmospherical flows. All low-Mach-specific files live here.`problems/`

: The problem setups for the low Mach number solver.`tests/`

: Reference low Mach hydro output for regression testing.

`mesh/`

: The main classes that deal with 2-d cell-centered grids and the data that lives on them. All the solvers use these classes to represent their discretized data.`multigrid/`

: The multigrid solver for cell-centered data. This solver is used on its own to illustrate how multigrid works, and directly by the diffusion and incompressible solvers.`problems/`

: The problem setups for when the multigrid solver is used in a stand-alone fashion.`tests/`

: Reference multigrid solver solutions (from when the multigrid solver is used stand-alone) for regression testing.

`particles/`

: The solver for Lagrangian tracer particles.`tests/`

: Particle solver testing.

`swe/`

: The shallow water solver.`problems/`

: The problem setups for the shallow water solver.`tests/`

: Reference shallow water output for regression testing.

`util/`

: Various service modules used by the pyro routines, including runtime parameters, I/O, profiling, and pretty output modes.

## Numba

Numba is used to speed up some critical portions of the code. Numba is
a *just-in-time compiler* for python. When a call is first made to a
function decorated with Numba’s `@njit`

decorator, it is compiled to
machine code ‘just-in-time’ for it to be executed. Once compiled, it
can then run at (near-to) native machine code speed.

We also use Numba’s `cache=True`

option, which means that once the
code is compiled, Numba will write the code into a file-based cache. The next
time you run the same bit of code, Numba will use the saved version rather than
compiling the code again, saving some compilation time at the start of the
simulation.

## Main driver

All the solvers use the same driver, the main `pyro_sim.py`

script,
contained in `pyro2/pyro/`

. The flowchart for the driver is:

parse runtime parameters

setup the grid (

`initialize()`

function from the solver)initialize the data for the desired problem (

`init_data()`

function from the problem)

do any necessary pre-evolution initialization (

`preevolve()`

function from the solver)evolve while t < tmax and n < max_steps

fill boundary conditions (

`fill_BC_all()`

method of the`CellCenterData2d`

class)get the timestep (

`compute_timestep()`

calls the solver’s`method_compute_timestep()`

function from the solver)evolve for a single timestep (

`evolve()`

function from the solver)t = t + dt

output (

`write()`

method of the`CellCenterData2d`

class)visualization (

`dovis()`

function from the solver)

call the solver’s

`finalize()`

function to output any useful information at the end

This format is flexible enough for the advection, compressible,
diffusion, and incompressible evolution solver. Each solver provides a
`Simulation`

class that provides the following methods (note:
inheritance is used, so many of these methods come from the base
`NullSimulation`

class):

`compute_timestep`

: return the timestep based on the solver’s specific needs (through`method_compute_timestep()`

) and timestepping parameters in the driver`dovis`

: performs visualization of the current solution`evolve`

: advances the system of equations through a single timestep`finalize`

: any final clean-ups, printing of analysis hints.`finished`

: return True if we’ve met the stopping criteria for a simulation`initialize`

: sets up the grid and solution variables`method_compute_timestep`

: returns the timestep for evolving the system`preevolve`

: does any initialization to the fluid state that is necessary before the main evolution. Not every solver will need something here.`read_extras`

: read in any solver-specific data from a stored output file`write`

: write the state of the simulation to an HDF5 file`write_extras`

: any solver-specific writing

Each problem setup needs only provide an `init_data()`

function that fills the data in the patch object.