neuroml

adapters.neuroml

NeuroML/LEMS adapter for SimulationExperiment.

Renders a self-contained LEMS XML simulation file from any TVBO SimulationExperiment using a Mako template. Every Dynamics model is exported as a custom LEMS ComponentType — no hardcoded mappings to built-in NeuroML cell types.

Validation is done via PyLEMS (lems.Model). Simulation can be run via pyNeuroML (jnml).

Classes

Name	Description
NeuroMLAdapter	Adapter for exporting a SimulationExperiment (or bare Dynamics) as LEMS XML.

NeuroMLAdapter

adapters.neuroml.NeuroMLAdapter(source=None)

Adapter for exporting a SimulationExperiment (or bare Dynamics) as LEMS XML.

Supports both a single monolithic file and a canonical three-file split:

render_dynamics() → standalone ComponentType definitions
render_network() → Network component (may include a dynamics file)
render_simulation() → LEMS Simulation block (may include a network file)
render_code() → monolithic all-in-one LEMS file (default)
render_neuroml() → NeuroML v2 document (<neuroml> root)
render_lems_wrapper() → LEMS wrapper for a NeuroML file
export(dir) → write file(s) to disk, optionally validate

render('lems') produces a self-contained <Lems> file. render('neuroml') produces a <neuroml> document with custom ComponentType definitions — no mapping to native NeuroML cell types.

All render_* methods pass a fully pre-computed context via :func:build_lems_context so templates stay logic-free.

Methods

Name	Description
export	Export LEMS or NeuroML XML to a directory.
render_code	Render a complete, self-contained LEMS simulation file (`<Lems>` root).
render_dynamics	Render a standalone LEMS file with only ComponentType definitions.
render_lems_wrapper	Render a LEMS simulation wrapper for a NeuroML file.
render_network	Render a LEMS Network document.
render_neuroml	Render a NeuroML v2 document (`<neuroml>` root).
render_simulation	Render a LEMS Simulation document.
run	Run the LEMS simulation via jNeuroML.
validate	Validate rendered LEMS XML with PyLEMS. Returns True or raises.

export

adapters.neuroml.NeuroMLAdapter.export(
    dir,
    format='lems',
    split=False,
    validate=True,
    **kwargs,
)

Export LEMS or NeuroML XML to a directory.

Parameters

dir : str or Path Output directory (created if needed). format : str 'lems' (default) — LEMS output (monolithic or split). 'neuroml' — NeuroML .nml document + LEMS simulation wrapper. split : bool Only used for format='lems'. False (default) — one monolithic {prefix}_simulation.xml. True — three canonical files:

* ``{prefix}_dynamics.xml``   — ComponentType definitions
* ``{prefix}_network.xml``    — Network (includes dynamics)
* ``{prefix}_simulation.xml`` — Simulation (includes network)

validate : bool Run PyLEMS validation on every written file (default True).

Returns

dict Mapping of role to absolute file paths.

render_code

adapters.neuroml.NeuroMLAdapter.render_code(**kwargs)

Render a complete, self-contained LEMS simulation file (<Lems> root).

If the experiment dynamics uses standard NeuroML types (iri: neuroml:*), emits standard NeuroML components (ionChannelHH, pointCellCondBased, etc.) with <Include file="Cells.xml"/> etc. Otherwise falls through to the flat custom-ComponentType template.

render_dynamics

adapters.neuroml.NeuroMLAdapter.render_dynamics(**kwargs)

Render a standalone LEMS file with only ComponentType definitions.

The output is a valid LEMS document containing dimensions, units, the dynamics ComponentType, the Coupling ComponentType, and the default Component instances. No Network or Simulation elements are included, making it suitable for inclusion in larger LEMS documents via <Include file="..."/>.

render_lems_wrapper

adapters.neuroml.NeuroMLAdapter.render_lems_wrapper(neuroml_file=None, **kwargs)

Render a LEMS simulation wrapper for a NeuroML file.

The wrapper includes standard NeuroML type files and the given NeuroML document, then defines a <Simulation> targeting the network defined in the .nml file.

Parameters

neuroml_file : str or None Filename of the NeuroML document to include.

render_network

adapters.neuroml.NeuroMLAdapter.render_network(dynamics_file=None, **kwargs)

Render a LEMS Network document.

Parameters

dynamics_file : str or None If given, an <Include file="..."/> referencing that filename is prepended so the document can be used standalone.

render_neuroml

adapters.neuroml.NeuroMLAdapter.render_neuroml(**kwargs)

Render a NeuroML v2 document (<neuroml> root).

Uses custom <ComponentType> definitions for the dynamics model rather than mapping to native NeuroML cell types. The output contains ComponentType definitions, Component instances, and a <network> with populations.

To run the output, pair it with a LEMS simulation wrapper generated by :meth:render_lems_wrapper.

render_simulation

adapters.neuroml.NeuroMLAdapter.render_simulation(network_file=None, **kwargs)

Render a LEMS Simulation document.

Parameters

network_file : str or None If given, an <Include file="..."/> referencing that filename is prepended so the document can be used standalone.

run

adapters.neuroml.NeuroMLAdapter.run(**kwargs)

Run the LEMS simulation via jNeuroML.

Uses a fully self-contained monolithic LEMS file with all dimensions, units, and infrastructure types (Simulation, OutputFile, OutputColumn) defined inline. This avoids the jNeuroML double-read bug that occurs when external NeuroML type files are included via <Include>.

Returns

ExperimentResult Simulation results loaded from jNeuroML output files.

validate

adapters.neuroml.NeuroMLAdapter.validate(xml_string=None)

Validate rendered LEMS XML with PyLEMS. Returns True or raises.

Functions

Name	Description
build_lems_context	Build the shared rendering context passed to all LEMS Mako templates.
inline_model_functions	Inline model-defined functions into a SymPy expression.
safe_id	Make a string safe for XML id attribute.
sympy_to_lems	Convert a TVBO equation RHS string (or SymPy expr) to LEMS syntax.
validate_lems_xml	Validate a LEMS XML string using PyLEMS.

build_lems_context

adapters.neuroml.build_lems_context(experiment)

Build the shared rendering context passed to all LEMS Mako templates.

Extracts and pre-computes every variable that LEMS templates need — model objects, name lists for safe SymPy parsing, expression helpers, and integration/network scalars. All templates receive this dict via template.render(**build_lems_context(experiment)).

Parameters

experiment : SimulationExperiment

Returns

dict Keys: dyn, dyn_id, params, svs, dvs, events, coupling_inputs, coupling_meta, coupling_params, coupling_pre_rhs, coupling_post_rhs, coupling_global, sv_names_set, n_nodes, dt, duration, lems_expr (callable), _parse_piecewise (callable), lems_dim (callable), safe_id (callable).

inline_model_functions

adapters.neuroml.inline_model_functions(expr, dynamics, all_names)

Inline model-defined functions into a SymPy expression.

LEMS has no user-defined function mechanism, so calls like Sigm(y1 - y2) must be expanded to their body (e.g. 2*e0/(1 + exp(r*(v0 - (y1-y2))))) before the expression is printed.

Parameters

expr : sympy.Basic Already-parsed SymPy expression that may contain calls to model functions. dynamics : Dynamics The model whose functions dict holds body + formal arguments. all_names : list of str All symbol names in scope (parameters, state variables, …) so the body is parsed with the correct local dict.

safe_id

adapters.neuroml.safe_id(s)

Make a string safe for XML id attribute.

sympy_to_lems

adapters.neuroml.sympy_to_lems(expr_str, parameters=None)

Convert a TVBO equation RHS string (or SymPy expr) to LEMS syntax.

Parameters

expr_str : str or sympy.Basic Equation RHS to convert. parameters : list of str, optional Model symbol names (parameters, state variables, etc.) to inject as SymPy Symbols before parsing, overriding any conflicting built-ins (e.g. I, gamma, lambda).

validate_lems_xml

adapters.neuroml.validate_lems_xml(xml_string)

Validate a LEMS XML string using PyLEMS.

Raises if the XML is not valid LEMS.