jaxsnn.event.solver

Modules

`jaxsnn.event.solver.custom_root_newton`
`jaxsnn.event.solver.custom_root_ttfs`
`jaxsnn.event.solver.lif_analytical`	Analytically find the time of the next spike for a LIF neuron for the special cases of $ au_mem = au_syn$ and $ au_mem = 2 * au_syn$.
`jaxsnn.event.solver.newton`
`jaxsnn.event.solver.next_finder`

Functions

jaxsnn.event.solver.cr_newton_solver(f, initial_guess, state, dt)

jaxsnn.event.solver.cr_ttfs_solver(tau_mem, v_th, y0, initial_guess)

jaxsnn.event.solver.newton_solver(f, initial_guess, state, dt): Newton’s method for root-finding.

jaxsnn.event.solver.ttfs_solver(tau_mem: float, tau_syn: float, v_th: float, state: jaxsnn.event.states.LIFState, t_max: float) → jax.Array

Find the next spike time for special cases $ au_mem = au_syn$ and $ au_mem = 2 * au_syn$

Args:: tau_mem (float): Membrane time constant tau_syn (float): Synaptic time constant v_th (float): Threshold Voltage state (LIFState): State of the neuron (voltage, current) t_max (float): Maximum time which is to be searched
Returns:: float: Time of next threshold crossing or t_max if no crossing