Jaxley is a Python library for differentiable neuron simulations built on JAX. Current version is 0.13.0, released with monthly cadence. It enables automatic differentiation through neuron models, supporting multi-compartment simulations, channel dynamics, and synaptic connections.
pip install jaxleyNo compatibility data collected yet for this library.
Verified import paths — ran on the pinned version, not inferred.
Quickstart: create a single-compartment neuron, apply a step current, record membrane potential, and run simulation.
Use `jx.Module()` and call `.add('compartment')` instead of `jx.single_compartment()`.Convert with `np.asarray(voltage)` if NumPy operations are required.
Set `jax.config.update('jax_enable_x64', True)` before importing jaxley.Use `jx.Module()` and add compartments via `.add('compartment')`.Rewrite custom channel models using `jx.channels.HHChannel` or other built-in channel classes.
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