Variable initialisation

Variables in BOUT++ are not initialised automatically, but must be explicitly given a value. For example the following code declares a Field3D variable then attempts to access a particular element:

Field3D f;    // Declare a variable
f(0,0,0) = 1.0;  // Error!

This results in an error because the data array to store values in f has not been allocated. Allocating data can be done in several ways:

  1. Initialise with a value:

    Field3D f = 0.0; // Allocates memory, fills with zeros
    f(0,0,0) = 1.0; // ok

    This cannot be done at a global scope, since it requires the mesh to already exist and have a defined size.

  2. Set to a scalar value:

    Field3D f;
    f = 0.0; // Allocates memory, fills with zeros
    f(0,0,0) = 1.0; // ok

    Note that setting a field equal to another field has the effect of making both fields share the same underlying data. This behaviour is similar to how NumPy arrays behave in Python.

    Field3D g = 0.0;  // Allocates memory, fills with zeros
    Field3D f = g; // f now shares memory with g
    f(0,0,0) = 1.0; // g also modified

    To ensure that a field has a unique underlying memory array call the Field3D::allocate() method before writing to individual indices.

  3. Use Field3D::allocate() to allocate memory:

    Field3D f;
    f.allocate(); // Allocates memory, values undefined
    f(0,0,0) = 1.0; // ok

In a BOUT++ simulation some variables are typically evolved in time. The initialisation of these variables is handled by the time integration solver.

Initialisation of time evolved variables

Each variable being evolved has its own section, with the same name as the output data. For example, the high-\(\beta\) model has variables “P”, “jpar”, and “U”, and so has sections [P], [jpar], [U] (not case sensitive).


The recommended way to initialise a variable is to use the function option for each variable:

function = 1 + gauss(x-0.5)*gauss(y)*sin(z)

This evaluates an analytic expression to initialise the \(P\) variable. Expressions can include the usual operators (+,-,*,/), including ^ for exponents. The following values are also already defined:

Name Description
x \(x\) position between \(0\) and \(1\)
y \(y\) position between \(0\) and \(2\pi\) (excluding the last point)
z \(z\) position between \(0\) and \(2\pi\) (excluding the last point)
pi π \(3.1415\ldots\)

Table: Initialisation expression values

By default, \(x\) is defined as i / (nx - 2*MXG), where MXG is the width of the boundary region, by default 2. Hence \(x\) actually goes from 0 on the leftmost point to (nx-1)/(nx-4) on the rightmost point. This is not a particularly good definition, but for most cases its sufficient to create some initial profiles. For some problems like island reconnection simulations, it’s useful to define \(x\) in a particular way which is more symmetric than the default. To do this, set in BOUT.inp

symmetricGlobalX = true

This will change the definition of \(x\) to i / (nx - 1), so \(x\) is then between \(0\) and \(1\) everywhere.

By default the expressions are evaluated in a field-aligned coordinate system, i.e. if you are using the [mesh] option paralleltransform = shifted, the input f will have f = fromFieldAligned(f) applied before being returned. To switch off this behaviour and evaluate the input expressions in coordinates with orthogonal x-z (i.e. toroidal \(\{\psi,\theta,\phi\}\) coordinates when using paralleltransform = shifted), set in BOUT.inp

transform_from_field_aligned = false

The functions in Table 1 are also available in expressions.

Table 1 Initialisation expression functions
Name Description
abs(x) Absolute value \(|x|\)
asin(x), acos(x), atan(x), atan(y,x) Inverse trigonometric functions
ballooning(x) Ballooning transform ((1), Fig. 3)
ballooning(x,n) Ballooning transform, using \(n\) terms (default 3)
cos(x) Cosine
cosh(x) Hyperbolic cosine
exp(x) Exponential
tanh(x) Hyperbolic tangent
gauss(x) Gaussian \(\exp(-x^2/2) / \sqrt{2\pi}\)
gauss(x, w) Gaussian \(\exp[-x^2/(2w^2)] / (w\sqrt{2\pi})\)
H(x) Heaviside function: \(1\) if \(x > 0\) otherwise \(0\)
log(x) Natural logarithm
max(x,y,...) Maximum (variable arguments)
min(x,y,...) Minimum (variable arguments)
mixmode(x) A mixture of Fourier modes
mixmode(x, seed) seed determines random phase (default 0.5)
power(x,y) Exponent \(x^y\)
sin(x) Sine
sinh(x) Hyperbolic sine
sqrt(x) \(\sqrt{x}\)
tan(x) Tangent
erf(x) The error function
TanhHat(x, width, centre, steepness) The hat function \(\frac{1}{2}(\tanh[s (x-[c-\frac{w}{2}])]\) \(- \tanh[s (x-[c+\frac{w}{2}])] )\)
fmod(x) The modulo operator, returns floating point remainder

For field-aligned tokamak simulations, the Y direction is along the field and in the core this will have a discontinuity at the twist-shift location where field-lines are matched onto each other. To handle this, the ballooning function applies a truncated Ballooning transformation to construct a smooth initial perturbation:

(1)\[U_0^{balloon} = \sum_{i=-N}^N F(x)G(y + 2\pi i)H(z + q2\pi i)\]
Initial profiles

Fig. 3 Initial profiles in twist-shifted grid. Left: Without ballooning transform, showing discontinuity at the matching location Right: with ballooning transform

There is an example code test-ballooning which compares methods of setting initial conditions with the ballooning transform.

The mixmode(x) function is a mixture of Fourier modes of the form:

\[\mathrm{mixmode}(x) = \sum_{i=1}^{14} \frac{1}{(1 + |i-4|)^2}\cos[ix + \phi(i, \mathrm{seed})]\]

where \(\phi\) is a random phase between \(-\pi\) and \(+\pi\), which depends on the seed. The factor in front of each term is chosen so that the 4th harmonic (\(i=4\)) has the highest amplitude. This is useful mainly for initialising turbulence simulations, where a mixture of mode numbers is desired.

Initalising variables with the FieldFactory class

This class provides a way to generate a field with a specified form. For example to create a variable var from options we could write

FieldFactory f(mesh);
Field2D var = f.create2D("var");

This will look for an option called “var”, and use that expression to initialise the variable var. This could then be set in the BOUT.inp file or on the command line.

var = gauss(x-0.5,0.2)*gauss(y)*sin(3*z)

To do this, FieldFactory implements a recursive descent parser to turn a string containing something like "gauss(x-0.5,0.2)*gauss(y)*sin(3*z)" into values in a Field3D or Field2D object. Examples are given in the test-fieldfactory example:

FieldFactory f(mesh);
Field2D b = f.create2D("1 - x");
Field3D d = f.create3D("gauss(x-0.5,0.2)*gauss(y)*sin(z)");

This is done by creating a tree of FieldGenerator objects which then generate the field values:

class FieldGenerator {
  virtual ~FieldGenerator() { }
  virtual FieldGenerator* clone(const list<FieldGenerator*> args) {return NULL;}
  virtual BoutReal generate(int x, int y, int z) = 0;

All classes inheriting from FieldGenerator must implement a FieldGenerator::generate() function, which returns the value at the given (x,y,z) position. Classes should also implement a FieldGenerator::clone() function, which takes a list of arguments and creates a new instance of its class. This takes as input a list of other FieldGenerator objects, allowing a variable number of arguments.

The simplest generator is a fixed numerical value, which is represented by a FieldValue object:

class FieldValue : public FieldGenerator {
  FieldValue(BoutReal val) : value(val) {}
  BoutReal generate(int x, int y, int z) { return value; }
  BoutReal value;

Adding a new function

To add a new function to the FieldFactory, a new FieldGenerator class must be defined. Here we will use the example of the sinh function, implemented using a class FieldSinh. This takes a single argument as input, but FieldPI takes no arguments, and FieldGaussian takes either one or two. Study these after reading this to see how these are handled.

First, edit src/field/fieldgenerators.hxx and add a class definition:

class FieldSinh : public FieldGenerator {
  FieldSinh(FieldGenerator* g) : gen(g) {}
  ~FieldSinh() {if(gen) delete gen;}

  FieldGenerator* clone(const list<FieldGenerator*> args);
  BoutReal generate(int x, int y, int z);
  FieldGenerator *gen;

The gen member is used to store the input argument, and to make sure it’s deleted properly we add some code to the destructor. The constructor takes a single input, the FieldGenerator argument to the sinh function, which is stored in the member gen .

Next edit src/field/fieldgenerators.cxx and add the implementation of the clone and generate functions:

FieldGenerator* FieldSinh::clone(const list<FieldGenerator*> args) {
  if(args.size() != 1) {
    throw ParseException("Incorrect number of arguments to sinh function. Expecting 1, got %d", args.size());

  return new FieldSinh(args.front());

BoutReal FieldSinh::generate(double x, double y, double z, double t) {
  return sinh(gen->generate(x,y,z,t));

The clone function first checks the number of arguments using args.size() . This is used in FieldGaussian to handle different numbers of input, but in this case we throw a ParseException if the number of inputs isn’t one. clone then creates a new FieldSinh object, passing the first argument ( args.front() ) to the constructor (which then gets stored in the gen member variable).

The generate function for sinh just gets the value of the input by calling gen->generate(x,y,z), calculates sinh of it and returns the result.

The clone function means that the parsing code can make copies of any FieldGenerator class if it’s given a single instance to start with. The final step is therefore to give the FieldFactory class an instance of this new generator. Edit the FieldFactory constructor FieldFactory::FieldFactory() in src/field/field_factory.cxx and add the line:

addGenerator("sinh", new FieldSinh(NULL));

That’s it! This line associates the string "sinh" with a FieldGenerator . Even though FieldFactory doesn’t know what type of FieldGenerator it is, it can make more copies by calling the clone member function. This is a useful technique for polymorphic objects in C++ called the “Virtual Constructor” idiom.

Parser internals

When a FieldGenerator is added using the addGenerator function, it is entered into a std::map which maps strings to FieldGenerator objects (include/field_factory.hxx):

map<string, FieldGenerator*> gen;

Parsing a string into a tree of FieldGenerator objects is done by first splitting the string up into separate tokens like operators like ’*’, brackets ’(’, names like ’sinh’ and so on, then recognising patterns in the stream of tokens. Recognising tokens is done in src/field/field_factory.cxx:

char FieldFactory::nextToken() {

This returns the next token, and setting the variable char curtok to the same value. This can be one of:

  • -1 if the next token is a number. The variable BoutReal curval is set to the value of the token
  • -2 for a string (e.g. “sinh”, “x” or “pi”). This includes anything which starts with a letter, and contains only letters, numbers, and underscores. The string is stored in the variable string curident .
  • 0 to mean end of input
  • The character if none of the above. Since letters and numbers are taken care of (see above), this includes brackets and operators like ’+’ and ’-’.

The parsing stage turns these tokens into a tree of FieldGenerator objects, starting with the parse() function:

FieldGenerator* FieldFactory::parse(const string &input) {

which puts the input string into a stream so that nextToken() can use it, then calls the parseExpression() function to do the actual parsing:

FieldGenerator* FieldFactory::parseExpression() {

This breaks down expressions in stages, starting with writing every expression as:

expression := primary [ op primary ]

i.e. a primary expression, and optionally an operator and another primary expression. Primary expressions are handled by the parsePrimary() function, so first parsePrimary() is called, and then parseBinOpRHS which checks if there is an operator, and if so calls parsePrimary() to parse it. This code also takes care of operator precedence by keeping track of the precedence of the current operator. Primary expressions are then further broken down and can consist of either a number, a name (identifier), a minus sign and a primary expression, or brackets around an expression:

primary := number
        := identifier
        := '-' primary
        := '(' expression ')'
        := '[' expression ']'

The minus sign case is needed to handle the unary minus e.g. "-x" . Identifiers are handled in parseIdentifierExpr() which handles either variable names, or functions

identifier := name
           := name '(' expression [ ',' expression [ ',' ... ] ] ')'

i.e. a name, optionally followed by brackets containing one or more expressions separated by commas. names without brackets are treated the same as those with empty brackets, so "x" is the same as "x()". A list of inputs (list<FieldGenerator*> args; ) is created, the gen map is searched to find the FieldGenerator object corresponding to the name, and the list of inputs is passed to the object’s clone function.