Statement class

(Shortest import: from brian2.codegen.statements import Statement)

class brian2.codegen.statements.Statement(var, op, expr, comment, dtype, constant=False, subexpression=False, scalar=False)[source]

Bases: object

A single line mathematical statement.

The structure is var op expr.


var : str

The left hand side of the statement, the value being written to.

op : str

The operation, can be any of the standard Python operators (including += etc.) or a special operator := which means you are defining a new symbol (whereas = means you are setting the value of an existing symbol).

expr : str, Expression

The right hand side of the statement.

dtype : dtype

The numpy dtype of the value or array var.

constant : bool, optional

Set this flag to True if the value will not change (only applies for op==':='.

subexpression : bool, optional

Set this flag to True if the variable is a subexpression. In some languages (e.g. Python) you can use this to save a memory copy, because you don’t need to do lhs[:] = rhs but a redefinition lhs = rhs.

scalar : bool, optional

Set this flag to True if var and expr are scalar.


Will compute the following attribute:


True or False depending if the operation is in-place or not.

Boolean simplification notes:

Will initially set the attribute used_boolean_variables to None. This is set by optimise_statements when it is called on a sequence of statements to the list of boolean variables that are used in this expression. In addition, the attribute boolean_simplified_expressions is set to a dictionary with keys consisting of a tuple of pairs (var, value) where var is the name of the boolean variable (will be in used_boolean_variables) and var is True or False. The values of the dictionary are strings representing the simplified version of the expression if each var=value substitution is made for that key. The keys will range over all possible values of the set of boolean variables. The complexity of the original statement is set as the attribute complexity_std, and the complexity of the simplified versions are in the dictionary complexities (with the same keys).

This information can be used to generate code that replaces a complex expression that varies depending on the value of one or more boolean variables with an if/then sequence where each subexpression is simplified. It is optional to use this (e.g. the numpy codegen does not, but the cython one does).