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name: units-and-equations description: "Use Brian2 physical units, equation declarations and flags, parser-supported expressions, stochastic terms, namespaces, state updaters, and unit-aware custom functions safely." disable-model-invocation: true metadata: disco-role: operating license: NOASSERTION

Brian2 units and equations

Use this route when a task is about dimensional correctness, equation-string syntax, stochastic symbols, numerical integration method selection, namespaces, or unit-aware custom functions. Load only the reference needed for the current question:

• Equation syntax for declarations, flags, special symbols, parser limits, namespaces, and integrated-form conversion.
• Numerical methods for deterministic and stochastic state-updater choices and restrictions.
• API reference for units, Equations, check_units, Function, and implementation boundaries.
• Troubleshooting for classified failures.

For a quick, read-only probe of unit declarations and unit-aware functions, run python scripts/unit_equation_smoke.py --help, then --all in an environment where the brian2 package imports successfully. The smoke script intentionally checks both passing and failing dimensional cases; it is not a replacement for model or device tests.

Operating procedure

1. Write down the physical dimension of every state variable, parameter, derivative, and external value. In a differential declaration, the unit after : is the variable's unit; the right-hand side must be that unit per second.
2. Use Brian's base unit names in declarations (volt, second, amp, metre, etc.), including compound dimensions. Use scaled units (mV, ms, nA) for assigned values and external namespaces. Use mmolar/mM for molar concentration in equations.
3. Parse a minimal Equations object first. Then instantiate the owning group or call its unit check so unknown names, namespaces, flags, dependency cycles, and dimensional errors are actually validated. Equations construction alone does not perform all context-dependent checks.
4. Resolve external names explicitly with a group namespace or the Network.run(..., namespace=...) argument when reproducibility matters. Avoid relying on implicit locals/globals when a name could be shadowed.
5. Select method only after classifying the ODE (linear, conditionally linear, deterministic nonlinear, additive noise, or multiplicative noise). If a method rejects the equations, change the method or the equation form; do not hide the rejection by disabling unit checks.
6. For a custom function, declare argument and result units with @check_units (or a complete Function). Add target implementations only when the selected code-generation target needs them, and keep the implementation decorator outside the unit decorator. Test the Python/NumPy path separately from C++/Cython compiler integration.

The bundled smoke covers a valid and invalid dimensional operation, equation flags and parser rejection, explicit namespaces, suffixed-noise rules, a unit-checked Function, a NumPy implementation, exact versus Euler decay, and finite additive noise. Treat --all as a bounded contract check, not as a substitute for owner-specific synapse, linked-variable, or device tests.

Route high-level neuron/synapse construction to the modeling or synapses-and-inputs routes. Route device, compiler, standalone build, and backend installation problems to code-generation. Keep this route focused on the contracts above.