StepCurrentEncoder

class braintools.StepCurrentEncoder(current_scale=10.0, offset=0.0, normalize=True, min_val=None, max_val=None)

Encode inputs as step current injections for LIF neurons.

Converts input values to constant current levels that can be injected into integrate-and-fire neurons. The current amplitude determines the firing rate of the neuron.

Example:

>>> encoder = StepCurrentEncoder(current_scale=10.0)
>>> currents = encoder(jnp.array([0.1, 0.5, 1.0]), n_time=100)
>>> # Returns current levels [1.0, 5.0, 10.0] nA

Parameters:

• current_scale (float) – float. Scaling factor to convert inputs to current (nA).

• offset (float) – float. Baseline current offset.

• normalize (bool) – bool. Whether to normalize inputs.

• min_val (float) – float. Minimum value for normalization.

• max_val (float) – float. Maximum value for normalization.