This page explains how to configure the custom user submodule to your needs and run your own setup.
To start navigate to any directory of your choosing and call the
setuplegolas.py setup script.
See the installation guide
for more information.
When running the setup script and no parfile is found you are asked if you want to copy over a default template. You’ll need this file for the basic Legolas configuration, so please do so. Take a look at the different parameter options as well. Configure this file to your needs.
The smod_user_defined.f08 submodule
In this module you will set up your equilibrium configuration. You can either choose to copy over the default template
from the legolas
src directory, or create your own. Both are fine, as long as the file is named
and the general template looks like this:
submodule (mod_equilibrium) smod_user_defined implicit none contains module subroutine user_defined_eq() ! your setup end subroutine user_defined_eq end submodule smod_user_defined
This is all that’s needed. The
mod_equilibrium statement between brackets refers to the parent module,
which contains the interface of the subroutines that are implemented in their respective submodules.
This also implies that you have access to all global
use statements in the
mod_equilibrium module, without
having to explicitly import them.
In what follows all code samples go inside the
user_defined_eq() subroutine, since this is the only routine you
need to configure yourself.
Setting the grid
You have several options here. Either you hardcode the grid parameters yourself, setting
to fixed values. However, in some use cases it may be necessary to vary grid parameters as part of parametric studies.
We therefore provided the
allow_geometry_override subroutine, which can be used to set default values that can be
overridden through the parfile.
Note: The variables
x_end and the subroutine
call initialise_grid() are all known
in the parent module and don’t have to be imported explicitly.
Option 1: full override
call allow_geometry_override(default_geometry='cylindrical', & default_x_start=0.0d0, & default_x_end=1.0d0)
Option 2: partial override
x_end = 1.0d0 call allow_geometry_override(default_geometry="Cartesian", default_x_start=0.0d0)
Option 3: hardcoded
geometry = "Cartesian" x_start = 0.0d0 x_end = 1.0d0
In the first option above you can switch between
cylindrical geometries and custom grid boundaries
solely using the parfile, while in option 2 you can only modify the outer grid boundary. Option 3 does not allow for
an override at all.
After these three variables are set, you tell the code it should initialise the grid through
which allocates the arrays and initialises the grid, geometry scale factor and Gaussian grid.
Legolas uses a dedicated module which contains a multitude of variables that you can use in your setups.
For a comprehensive list we refer to this page.
You can use all of these in your setups, but note that these should be explicitly imported (except for
An example is given below.
Note: The variables
k3 are known in the parent module. All other parameters you want
to use should be explicitly imported.
use mod_equilibrium_params, only: alpha, beta, p1 if (use_defaults) then k2 = 0.0d0 k3 = 1.0d0 alpha = 1.0d0 beta = 5.0d0 p1 = 1.0d0 / 2.0d0 end if
This example uses the variables
p1 from the list and wraps them in the
This means that Legolas will use those values as a default if the
paramlist namelist is not present in the parfile.
use_defaults is set to
.false. you have to specify them in the
paramlist, where you choose values for these
variables. If you forget to set a variable that you use later on its value will be
NaN, meaning the code will catch it
during the pre-run checks and warn you.
Note: All public variables/subroutine defined in
mod_units are known to the parent module and
do not have to be imported explicitly in the submodule.
Specifying the unit normalisations can either be done through the parfile (the
unitslist) or in the submodule
directly. This is only relevant if you include radiative cooling, thermal conduction or (temperature-dependent)
resistivity, since these units are used to re-dimensionalise the variables for the corresponding calculations and/or
table lookups. To set the units you can do, for example
use_cgs = .true. call set_normalisations(new_unit_density=1.6727d-15, & new_unit_magneticfield=22.5d0, & new_unit_length=1.0d10)
which sets values in cgs units, if you set
use_cgs = .false. these are interpreted as SI units. Instead of specifying
new_unit_density you can choose a reference temperature
see units for more information.
Including additional physics
Note: You can set everything here either in the parfile or in the submodule. In case of the latter,
known in the parent module. Variables like
fixed_eta_value and related ones on the other hand
must be imported explicitly.
Including additional physics in your setup is quite straightforward: you set the corresponding logical to
set up the additional variables.
In the case of resistivity you have two options after setting
resistivity = .true.:
- A constant value over the entire grid (with a possible drop-off near the edges,
see the physicslist namelist). Set
use_fixed_resistivity = .true.and specify
- A realistic temperature-dependent resistivity profile based on the Spitzer resistivity. Here it suffices
to only specify
resistivity = .true., since
.false.by default. It’s perhaps a good idea to specify unit normalisations in this case, if the default ones are not sufficient to your needs.
thermal_conduction = .true.. This is analogous to resistivity, in the sense that you can either specify a
constant value for the parallel and perpendicular components (separately), or use a fully realistic profile that
depends on density, temperature and magnetic field. The constant values are controlled through the variables
fixed_tc_para_value for the parallel thermal conduction component, and through
fixed_tc_perp_value for the perpendicular component. If you use the realistic profile
you should set unit normalisations.
radiative_cooling = .true. and specify the cooling curve, see the physicslist
for possible options. For radiative cooling we only have a temperature-dependent profile due to the use of realistic
cooling tables, hence you should set unit normalisations when you use this.
flow = .true. and specify the various velocity components in the corresponding fields. See below.
external_gravity = .true. and specify the gravity component in the corresponding field. See below.
Tip: The variable
g in the
mod_equilibrium_params module is usually used if you want to set a constant gravity
Defining the equilibrium state
We are planning a (minor) refactor of some attributes in the (near) future, so keep a look out for changes.
Tip: to make sure your implementation is in order you can do a dry run first (
dry_run = .true. in the parfile)
and plot the equilibrium arrays using Pylbo. Once you’re sure that everything is correct, remove the
dry_run line from
the parfile and you’re good to go.
The final thing that should be done is specifying the actual equilibrium state. The
mod_equilibrium parent module
contains various different types (we call them fields) each containing multiple attributes. For example,
rho_field contains (you guessed it) density-related variables, accessible through
rho_field % rho0 for the regular density and
rho_field % d_rho0_dr for the density derivative.
Analogous for the other fields. The advantage of this is that everything is contained to its particular type,
meaning they can be easily passed to other subroutines, and adding a new attribute is as easy as appending it to the
corresponding type. For a full list of the various fields and attributes see
You only have to specify the
grav_field (the names are self-explanatory);
if a field is not set all attributes are assumed to be zero. For example, if you don’t include flow or gravity, you
don’t have to set those fields explicitly.
Warning: technically you have access to
kappa_field in the submodule, corresponding
to the resistivity, radiative cooling and thermal conduction types. These are set automatically by Legolas
and should not be set manually.
Since equilibrium expressions can be quite complicated, it is best to set everything in a loop where you iterate over the Gaussian grid, NOT over the base grid. The base grid is only used to set up the Gaussian grid, which is where the equilibrium quantities are evaluated in anyway. All field attributes are 1D-arrays, so you can simply iterate over them when setting the equilibrium. In the example below we include flow and a radius-dependent external gravity profile.
Note: as indicated in the warning above you should not set
eta_field manually. There is one exception through,
which concerns the second magnetic field derivatives. These are only used when resistivity is included (hence why they are
a part of
eta_field and not of
B_field) and should be set explicitly if
resistivity = .true..
You can do this through
eta_field % dd_B02_dr and
eta_field % dd_B03_dr.
! specify variables to use later on real(dp) :: x integer :: i ! set the grid variables geometry = "Cartesian" x_start = 0.0d0 x_end = 2.0d0 call initialise_grid() ! loop over the gaussian points do i = 1, gauss_gridpts ! evaluate equilibria in the Gaussian grid x = grid_gauss(i) ! set equilibria + derivatives rho_field % rho0(i) = 5.0d0 - x**2 rho_field % d_rho0_dr(i) = -2.0d0 * x T_field % T0(i) = 2.0d0 ! constant, so no need to set d_T0_dr v_field % v02(i) = x v_field % d_v02_dr(i) = 1.0d0 B_field % B02(i) = sin(x) B_field % d_B02_dr(i) = cos(x) B_field % B03(i) = cos(x) B_field % d_B03_dr(i) = -sin(x) B_field % B0(i) = sqrt(B_field % B02(i)**2 + B_field % B03(i)**2) ! no resistivity, so no second B_field derivatives needed grav_field % grav(i) = 1.0d0 / x**2 end do
dp above denotes the intrinsic double precision
real64 from Fortran
iso_fortran_env, defined in
mod_global_variables. The variables
grid_gauss are known in the parent module and
don’t have to be imported.
If you prefer to work with pressure instead of temperature that is also possible. You can specify a pressure and density profile, and set temperature as such:
real(dp) :: x ! pressure arrays real(dp) :: px(gauss_gridpts), dpx(gauss_gridpts) integer :: i do i = 1, gauss_gridpts x = grid_gauss(i) rho_field % rho0(i) = 5.0d0 - x**2 rho_field % d_rho0_dr(i) = -2.0d0 * x px(i) = 0.5d0 * x dpx(i) = 0.5d0 ! ideal gas law to set temperature, T' = (p'*rho - rho'*p) / rho**2 T_field % T0(i) = px(i) / rho_field % rho0(i) T_field % d_T0_dr(i) = ( dpx(i) * rho_field % rho0(i) & - rho_field % d_rho0_dr(i) * px(i) ) & / rho_field % rho0(i)**2 end do
For more examples you can look at implementation of the various descendants of the
mod_equilibrium parent module.
Note: all equilibria should satisfy the equilibrium conditions. The examples here are only for illustration purposes and do not satisfy those conditions. In principle Legolas will run if your equilibrium does not check out, but you will be warned.