Network

class pylgn.core.Network(memory_efficient=False)

Network class

Variables:

• neurons (list) – List with pylgn.Neuron objects
• integrator (pylgn.Integrator) – Integrator object
• stimulus (pylgn.Stimulus) – Stimulus object

__init__(memory_efficient=False)

Network constructor

clear()

Clears the neuron list.

compute_irf(neuron, recompute_ft=False)

Computes the impulse-response function of a neuron.

Parameters:

• neuron (pylgn.Neuron)
• recompute_ft (bool) – If True the Fourier transform is recalculated.

compute_irf_ft(neuron)

Computes the Fourier transform of the impulse-response function of a neuron.

Parameters:neuron (pylgn.Neuron)

compute_response(neuron, recompute_ft=False)

Computes the response of a neuron.

Parameters:

• neuron (pylgn.Neuron)
• recompute_ft (bool) – If True the Fourier transform is recalculated.

compute_response_ft(neuron, recompute_irf_ft=False)

Computes the Fourier transform of the response of a neuron.

Parameters:neuron (pylgn.Neuron)

connect(source, target, kernel, weight=1.0)

Connect neurons.

Parameters:

• source (pylgn.Neuron) – Source neuron
• target (pylgn.Neuron) – Target neuron
• kernel (function) – Connectivity kernel
• weight (float) – Connectivity weight

create_cortical_cell(background_response=array(0.) * 1/s, annotations={})

Create cortical cell

Parameters:

• background_response (quantity scalar) – Background activity.
• annotations (dict) – Dictionary with various annotations.

Returns:

out – Cortical object

Return type:

pylgn.Cortical

create_descriptive_neuron(background_response=array(0.) * 1/s, kernel=None, annotations={})

Create descriptive neuron

Parameters:

• background_response (quantity scalar) – Background activity.
• kernel (function) – Impulse-response function.
• annotations (dict) – Dictionary with various annotations.

Returns:

out – Descriptive neuron object

Return type:

pylgn.DescriptiveNeuron

create_ganglion_cell(background_response=array(0.) * 1/s, kernel=None, annotations={})

Create ganglion cell

Parameters:

• background_response (quantity scalar) – Background activity.
• kernel (function) – Impulse-response function.
• annotations (dict) – Dictionary with various annotations.

Returns:

out – Ganglion object

Return type:

pylgn.Ganglion

create_integrator(nt, nr, dt, dr)

Create and set integrator

Parameters:

• nt (int) – The power to raise 2 to. Number of temporal points is 2**nt.
• nr (int) – The power to raise 2 to. Number of spatial points is 2**nr.
• dt (quantity scalar) – Temporal resolution
• dr (quantity scalar) – Spatial resolution

Returns:

out – Integrator object

Return type:

pylgn.Integrator

create_relay_cell(background_response=array(0.) * 1/s, annotations={})

Create relay cell

Parameters:

• background_response (quantity scalar) – Background activity.
• annotations (dict) – Dictionary with various annotations.

Returns:

out – Relay object

Return type:

pylgn.Relay

set_stimulus(closure, compute_fft=False)

Sets stimulus.

Parameters:

• closure (callable (closure)) – stimulus function. If compute_fft is False the stimulus function should be the Fourier transform of the stimulus.
• compute_fft (bool) – If True numerical integration is used to calculate the Fourier transform of the stimulus.

pylgn.core.closure_params(closure)

Stores closure parameters in a dict

Parameters:closure (function) – A closure function Returns:out – Dictionary Return type:dict