Equations and namespaces¶
Each Brian object that saves state variables (e.g. NeuronGroup, Synapses, StateMonitor) has a variables attribute, a dictionary mapping variable names to Variable objects (in fact a Variables object, not a simple dictionary). Variable objects contain information about the variable (name, dtype, units) as well as access to the variable’s value via a get_value method. Some will also allow setting the values via a corresponding set_value method. These objects can therefore act as proxies to the variables’ “contents”.
Variable objects provide the “abstract namespace” corresponding to a chunk of “abstract code”, they are all that is needed to check for syntactic correctness, unit consistency, etc.
The namespace attribute of a group can contain information about the external (variable or function) names used in the equations. It specifies a group-specific namespace used for resolving names in that group. At run time, this namespace is combined with a “run namespace”. This namespace is either explicitly provided to the Network.run() method, or the implicit namespace consisting of the locals and globals around the point where the run function is called.
Internally, this is realized via the before_run function. At the start of a run, Network.before_run() calls BrianObject.before_run() of every object in the network with a namespace argument and a level. If the namespace argument is given (even if it is an empty dictionary), it will be used together with any group-specific namespaces for resolving names. If it is not specified or None, the given level will be used to go up in the call frame and determine the respective locals and globals.