Automatic Model Documentation

class brian.experimental.model_documentation.DocumentWriter

Base class for documenting a network. Already takes care of assigning labels to objects if none are given.

document_connections(connections)

Document the connections of the network (including SpikeMonitor etc. as they are modeled as Connection objects).

document_group(group)

Document a single NeuronGroup group. Will normally be called for every group by document_groups().

document_groups(groups)

Document all NeuronGroup groups. Should normally call document_group() for every group.

document_network(net=None, labels=None, sim=True, groups=True, connections=True, operations=True, graph_connections=False)

Documents the network net, if not network is given, a MagicNetwork is automatically created and documented, i.e. if you are running scripts without any explicit network (you use run(…) instead of net.run(…)), you can simply call writer.document_network().

document_operation(operation)

Document a single NetworkOperation operation. Should normally be called by document_operations() for every operation.

document_operations(operations)

Document all NetworkOperation operations (including StateMonitor etc. as they are modeled as NetworkOperation objects). Should normally call document_operation() for every operation.

document_sim(network)

Document some general properties of the network, e.g. the timestep used in the simulation.

graph_connections(connections, groups)

Draw a graph visualizing the connection structure of the network.

intro()

Is called before any other output function, useful for the start of an HTML or LaTeX document.

outro()

Is called after all other output function, useful for the end of an HTML or LaTeX document.

static to_sympy_expression(eq_string)

Simple helper function for converting an Equation string eq_string (only the right hand side of an equation) into a sympy expression by calling x = Symbol(‘x’) for every variable x in the equation.

class brian.experimental.model_documentation.TextDocumentWriter(**kwargs)

Documents the network by printing to stdout, uses sympy for formatting the equations (including nice Unicode symbols)

class brian.experimental.model_documentation.LaTeXDocumentWriter(**kwargs)

Documents the network by printing LaTeX code to stdout. Prints a full document (i.e. including preamble etc.). The resulting LaTeX file needs the amsmath package.

Note that if you use the graph_connections=True option, you additionally need the tikz and dot2texi packages (part of texlive-core and texlive-pictures on Linux systems) and the dot2tex tool. To make the conversion from dot code to LaTeX automatically happen on document creation you have to pass the –shell-escape option to your LaTeX call, e.g. pdflatex –shell-escape network_doc.tex

static format_equation(lhs, rhs, unit)

Helper function to convert an equation consisting of two strings for the left respectively the right hand side of an equation (lhs and rhs) and a Brian Unit unit into a LaTeX expression aligning on the equality sign for amsmath’s align environment.

static latex_equation(eq_string)

Helper function to convert the right hand side of an equation string eq_string to a LaTeX expression (not a full equation in LaTeX terms) using sympy.

static latex_equations(eqs)

Convert Brian equations (either a – possibly multi-line – string or an Equation object) eqs into a LaTeX equation using amsmath’s align environment.

brian.experimental.model_documentation.document_network(net=None, output='text', **kwargs)

Convenience method for documenting a network without having to construct a DocumentWriter object first.

If no network net is given, a MagicNetwork is automatically created and documented. The output argument should be either text (the default) or latex. Any further keyword arguments are passed on to the respective DocumentWriter.

brian.experimental.model_documentation.labels_from_namespace(namespace)

Creates a labels dictionary that can be handed over to the document_network from a given namespace. Would typically be called like this: net.document_network(labels=labels_from_namespace(locals())) This allows document_network to use the variable names used in the Python code as the short labels, making it easier to link the model description and the actual code.