Copy

Copy(
    self,
    pre,
    post,
    target,
    psp='pre.r * w',
    operation='sum',
    name=None,
    copied=False,
    net_id=0,
)

Creates a virtual projection reusing the weights and delays of an already-defined projection.

Although the original projection can be learnable, this one can not. Changes in the original weights will be reflected in this projection. The only possible modifications are psp and operation.

The pre- and post-synaptic populations of both projections must have the same geometry.

Example:

import ANNarchy as ann
from ANNarchy.extensions.convolution import Copy

net = ann.Network()

pop1 = net.create(1000, ann.Izhikevich)
pop2 = net.create(1000, ann.Izhikevich)
pop3 = net.create(1000, ann.Izhikevich)

proj = ann.Projection(pop1, pop2, "exc")
proj.fixed_probability(0.1, 0.5)

copy_proj = Copy(pop1, pop3, "exc")
copy_proj.copy(proj)

Parameters

Name	Type	Description	Default
pre		pre-synaptic population (either its name or a Population object).	required
post		post-synaptic population (either its name or a Population object).	required
target		type of the connection	required
psp		continuous influence of a single synapse on the post-synaptic neuron (default for rate-coded: w*pre.r).	'pre.r * w'
operation		operation (sum, max, min, mean) performed by the kernel (default: sum).	'sum'

Methods

Name	Description
copy	Instantiates the projection.
save_connectivity	Not available.
save	Not available.
load	Not available.
receptive_fields	Not available.
connectivity_matrix	Not available.

copy

copy(projection)

Instantiates the projection.

Parameters

Name	Type	Description	Default
projection		Existing projection to copy.	required

save_connectivity

save_connectivity(filename)

Not available.

save

save(filename)

Not available.

load

load(filename)

Not available.

receptive_fields

receptive_fields(variable='w', in_post_geometry=True)

Not available.

connectivity_matrix

connectivity_matrix(fill=0.0)

Not available.