nengolib.Connection¶
-
class
nengolib.
Connection
(pre, post, solver=LstsqL2(reg=0.1, solver=Cholesky(transpose=None), weights=False), **kwargs)[source]¶ Drop-in replacement for
nengo.Connection
.Extends
nengo.Connection
to improve decoding by using a bias. If thepre
object is anengo.Ensemble
, then a bias will be included in its decoders. This automatically improves the decoding of functions with a constant offset when the ensemble has few neurons. This is equivalent to a change in postsynaptic biases (in effect changing the representation to be centered around some constant offset, that is discovered optimally).Parameters: - pre :
nengo.Ensemble
ornengo.ensemble.Neurons
ornengo.Node
Nengo source object for the connection.
- post :
nengo.Ensemble
ornengo.ensemble.Neurons
ornengo.Node
ornengo.Probe
Nengo destination object for the connection.
- solver :
nengo.solvers.Solver
, optional Solver to use for decoded bias and connection. Defaults to
nengo.solvers.LstsqL2
.- **kwargs :
dictionary
, optional Additional keyword arguments passed to
nengo.Connection
.
See also
Attributes: - eval_points
- function
- function_info
Connection-specific validation for functions.
- is_decoded
- label
A parameter where the value is a string.
learning_rule
(LearningRule or iterable) Connectable learning rule object(s).
- learning_rule_type
Connection-specific validation for learning rules.
- modulatory
A parameter that is no longer supported.
params
Returns a list of parameter names that can be set.
- post
- post_obj
- post_slice
- pre
- pre_obj
- pre_slice
- scale_eval_points
A parameter where the value is a boolean.
- seed
A parameter where the value is an integer.
size_in
(int) The number of output dimensions of the pre object.
size_mid
(int) The number of output dimensions of the function, if specified.
size_out
(int) The number of input dimensions of the post object.
- solver
Connection-specific validation for decoder solvers.
- synapse
- transform
The transform additionally validates size_out.
Methods
copy - pre :