tools.py

In this module, we can find assorted functions that help us with creating neuronal models.

This module consists of some helper functions for creating neuronal networks.

neurons.tools.poisson_homogenous(lam, timesteps)

Generate a poisson spike train for a single neuron using a homogenous poisson distribution.

Homogenous Poisson spike train
Example:

The spike train of the image above was generated by following function:

>>> poisson_homogenous(0.4, 200)
Parameters:
  • lam (Float) – lambda value
  • timesteps (Int) – total length of spike train
neurons.tools.poisson_inhomogenous(lambdas, timesteps)

Generate a poisson spike train for a single neuron using an inhomogenous poisson distribution.

Inhomogenous Poisson spike train
Example:

The spike train of the image above was generated by following function:

>>> poisson_inhomogenous((0.5, 0.25, 0, 0, 1, 0.5, 0, 0, 0.25, 0.5), 200)
Parameters:
  • lambdas (List or Tuple) – Lambda values
  • timesteps (Int) – total length of the spike train
neurons.tools.sound(timesteps, midpoint, maximum, variance)

Generates a spike train with a peak at midpoint.

Sound Plot
Example:

The spike train of the image above was generated by following function:

>>> sound(280, 150, 0.4, 50)
Parameters:
  • timesteps –
  • midpoint – central peak
  • maximum – Lambda value at peak
  • variance – Variance around peak
Returns: