General setup class

class ulula.core.setup_base.Setup(unit_l=1.0, unit_t=1.0, unit_m=1.0)

General setup class

This abstract container must be partially overwritten by child classes, but also contains defaults for a number of standard routines. In particular, the user must implement the routines that provide a short name and that set the initial conditions.

Some optionally overwritten routines determine how plots look and are automatically passed to the plotting functions when using the run() function.

Parameters:

unit_l: float: Code unit for length in units of centimeters.
unit_t: float: Code unit for time in units of seconds.
unit_m: float: Code unit for mass in units of gram.

Methods

`hasUserBoundaryConditions`()	Check whether setup provides BCs
`hasUserUpdateFunction`()	Check whether setup provides update function
`initialConditions`(sim, nx)	Wrapper function to set initial data
`internalEnergyFromTemperature`(T, mu, gamma)	Conversion for isothermal EOS
`plotColorMaps`(q_plot)	Return colormaps for plotted quantities
`plotLimits`(q_plot, plot_geometry)	Return min/max limits for plotted quantities
`setBoundaryConditions`(sim)	Set boundary conditions at run-time
`setInitialConditions`(sim, nx)	Set the initial conditions (must be overwritten)
`shortName`()	Short name for the problem (to be used in output filenames)
`trueSolution`(sim, x, q_plot, plot_geometry)	Return a true solution for this setup
`updateFunction`(sim)	Interact with the simulation at run-time

abstract shortName(): Short name for the problem (to be used in output filenames)

initialConditions(sim, nx)

Wrapper function to set initial data

This function calls the problem-specific setup, which is assumed to set the primitive variables. Those are also converted to conserved variables.

Parameters:

sim: Simulation: Simulation object in which the ICs are to be set
nx: int: Number of cells in the x-direction

abstract setInitialConditions(sim, nx)

Set the initial conditions (must be overwritten)

This function

Parameters:

sim: Simulation: Simulation object in which the ICs are to be set
nx: int: Number of cells in the x-direction

updateFunction(sim)

Interact with the simulation at run-time

If this function is overwritten by a child class, it will be execute by the Ulula simulation before boundary conditions are enforced. During that time, the setup can change the fluid variables in the domain.

Note that the simulation does not check whether what this function does makes any sense! If the function implements unphysical behavior, an unphysical simulation will result. The overwriting function can manipulate either primitive or conserved variables and thus must ensure that primitive and conserved variables are consistent after the function call.

Derived classes should not return any values (and must not return False like this base class implementation, because that value is used to determine whether a user function is provided in a given setup).

Parameters:

sim: Simulation: Simulation object

setBoundaryConditions(sim)

Set boundary conditions at run-time

If this function is overwritten by a child class, it will be execute by the Ulula simulation after the boundary conditions are enforced. During that time, the setup can overwrite the boundary conditions.

Note that the simulation does not check whether what this function does makes any sense! If the function implements unphysical behavior, an unphysical simulation will result. The overwriting function can manipulate either primitive or conserved variables and thus must ensure that primitive and conserved variables are consistent after the function call.

Derived classes should not return any values (and must not return False like this base class implementation, because that value is used to determine whether user BCs are provided in a given setup).

Parameters:

sim: Simulation: Simulation object

hasUserUpdateFunction()

Check whether setup provides update function

A utility function that determines whether a child class has overwritten updateFunction().

Parameters:

has_user_updates: bool: True if an setup implementation is providing a user-defined update function, False otherwise.

hasUserBoundaryConditions()

Check whether setup provides BCs

A utility function that determines whether a child class has overwritten setBoundaryConditions().

Parameters:

has_user_bcs: bool: True if an setup implementation is providing user-defined BCs, False otherwise.

trueSolution(sim, x, q_plot, plot_geometry)

Return a true solution for this setup

If overwritten, this function is passed to the Ulula 1D plotting routine plot1d(). The function must return a list with one element for each of the quantities in q_plot. If an element is None, no solution is plotted. Otherwise the element must be an array with the same dimensions as x_plot. The true solution must be in code units.

Parameters:

sim: Simulation: Simulation object
x: array_like: The coordinates where the true solution is to be computed.
q_plot: array_like: List of quantities for which to return the true solution. Quantities are identified via the short strings given in the fields dictionary.
plot_geometry: str: If the setup is 2D, the type of cut through the domain that the solution is desired for. Can be line or radius (a radially averaged plot from the center). See the documentation of plot1d() for details.

Returns:

solution: array_like: A list of length len(q_plot), with elements that are either None or an array with the same length as x.

plotLimits(q_plot, plot_geometry)

Return min/max limits for plotted quantities

This function can be passed to the Ulula plotting routines. By default, no limits are returned, which means the plotting functions automatically select limits. The limits must be in code units.

Parameters:

q_plot: array_like: List of quantities for which to return the plot limits. Quantities are identified via the short strings given in the fields dictionary.
plot_geometry: str: For 2D plots, this parameter is 2d. For 1D plots in a 1D simulation, it is line. If the setup is 2D but a 1D plot is created, this parameter gives the cut through the domain, which can be line or radius (a radially averaged plot from the center). See the documentation of plot1d() for details.

Returns:

limits_lower: array_like: List of lower limits for the given plot quantities. If None, a limit is chosen automatically. Individual items can also be None.
limits_upper: array_like: List of upper limits for the given plot quantities. If None, a limit is chosen automatically. Individual items can also be None.
log: array_like: List of True/False that determine whether to plot in log space. If None, all quantities are plotted in linear space. If log is chosen, the limits must be positive.

plotColorMaps(q_plot)

Return colormaps for plotted quantities

This function can be passed to the Ulula plotting routines. By default, velocities are plotted with a divergent colormap, whereas density and pressure are plotted with a perceptually uniform colormap.

Parameters:

q_plot: array_like: List of quantities for which to return the colormaps. Quantities are identified via the short strings given in the fields dictionary.

Returns:

cmaps: array_like: List of colormaps for the given quantities. If None, a colormap is chosen automatically. Individual items can also be None.

internalEnergyFromTemperature(T, mu, gamma)

Conversion for isothermal EOS

If we are choosing an isothermal EOS, we need to pass the temperature in the form of an equivalent internal energy in code units, which can be a little tedious to compute. This function takes care of it. The result can be passed as the eint_fixed parameter to the setEquationOfState() function.

Parameters:

T: float: Temperature in Kelvin.
mu: float: Mean particle weight in proton masses.

Returns:

eint: float: Internal energy in code units corresponding to the given temperature.