Package topo :: Package base :: Module cf :: Class CFPLF_Plugin

Class CFPLF_Plugin

                       object --+        
                                |        
param.parameterized.Parameterized --+    
                                    |    
                        CFPLearningFn --+
                                        |
                                       CFPLF_Plugin

Known Subclasses:

CFPLearningFunction applying the specified single_cf_fn to each CF.

Nested Classes

[hide private]

Inherited from param.parameterized.Parameterized: __metaclass__

Instance Methods

[hide private]

__call__(self, iterator, input_activity, output_activity, learning_rate, **params)
Apply the specified single_cf_fn to every CF.

source code

Inherited from CFPLearningFn: constant_sum_connection_rate

Inherited from param.parameterized.Parameterized: __getstate__, __init__, __repr__, __setstate__, __str__, debug, defaults, force_new_dynamic_value, get_param_values, get_value_generator, inspect_value, message, print_param_values, script_repr, set_dynamic_time_fn, state_pop, state_push, verbose, warning

Inherited from param.parameterized.Parameterized (private): _check_params, _instantiate_param, _set_name, _setup_params

Inherited from object: __delattr__, __getattribute__, __hash__, __new__, __reduce__, __reduce_ex__, __setattr__

Class Methods

[hide private]

Inherited from param.parameterized.Parameterized: params, print_param_defaults

Class Variables

[hide private]

single_cf_fn = param.ClassSelector(LearningFn, default= Hebbia...
Accepts a LearningFn that will be applied to each CF individually.

Inherited from param.parameterized.Parameterized: name, print_level

Properties

[hide private]

Inherited from object: __class__

Method Details

[hide private]

call(self, iterator, input_activity, output_activity, learning_rate, **params)
(Call operator)

source code

Apply the specified single_cf_fn to every CF.

Overrides: CFPLearningFn.__call__

Class Variable Details

[hide private]

single_cf_fn

Accepts a LearningFn that will be applied to each CF individually.

Value:

param.ClassSelector(LearningFn, default= Hebbian(), doc= "Accepts a LearningFn tha
t will be applied to each CF individually.")

Class CFPLF_Plugin

__call__(self, iterator, input_activity, output_activity, learning_rate, **params) (Call operator)

single_cf_fn

call(self, iterator, input_activity, output_activity, learning_rate, **params)
(Call operator)