Package mdp :: Package nodes :: Class RBFExpansionNode

Class RBFExpansionNode

Expand input space with Gaussian Radial Basis Functions (RBFs).

The input data is filtered through a set of unnormalized Gaussian
filters, i.e.,

   y_j = exp(-0.5/s_j * ||x - c_j||^2)

for isotropic RBFs, or more in general

   y_j = exp(-0.5 * (x-c_j)^T S^-1 (x-c_j))

for anisotropic RBFs.

Nested Classes

[hide private]

Inherited from Node

__metaclass__
This Metaclass is meant to overwrite doc strings of methods like execute, stop_training, inverse with the ones defined in the corresponding private methods _execute, _stop_training, _inverse, etc...

Instance Methods

[hide private]

__init__(self, centers, sizes, dtype=None)
Input arguments: centers -- Centers of the RBFs.

_execute(self, x)

_get_supported_dtypes(self)
Return the list of dtypes supported by this node.

_init_RBF(self, centers, sizes)

is_invertible(self)
Return True if the node can be inverted, False otherwise.

is_trainable(self)
Return True if the node can be trained, False otherwise.

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

Inherited from Node

__add__(self, other)

__call__(self, x, *args, **kargs)
Calling an instance of Node is equivalent to call its 'execute' method.

__repr__(self)
repr(x)

__str__(self)
str(x)

_check_input(self, x)

_check_output(self, y)

_check_train_args(self, x, *args, **kwargs)

_get_train_seq(self)

_if_training_stop_training(self)

_inverse(self, x)

_pre_execution_checks(self, x)
This method contains all pre-execution checks.

_pre_inversion_checks(self, y)
This method contains all pre-inversion checks.

_refcast(self, x)
Helper function to cast arrays to the internal dtype.

_set_dtype(self, t)

_set_input_dim(self, n)

_set_output_dim(self, n)

_stop_training(self, *args, **kwargs)

_train(self, x)

copy(self, protocol=-1)
Return a deep copy of the node.

execute(self, x, *args, **kargs)
Process the data contained in 'x'.

get_current_train_phase(self)
Return the index of the current training phase.

get_dtype(self)
Return dtype.

get_input_dim(self)
Return input dimensions.

get_output_dim(self)
Return output dimensions.

get_remaining_train_phase(self)
Return the number of training phases still to accomplish.

get_supported_dtypes(self)
Return dtypes supported by the node as a list of numpy.dtype objects.

inverse(self, y, *args, **kargs)
Invert 'y'.

is_training(self)
Return True if the node is in the training phase, False otherwise.

save(self, filename, protocol=-1)
Save a pickled serialization of the node to 'filename'.

set_dtype(self, t)
Set internal structures' dtype.

set_input_dim(self, n)
Set input dimensions.

set_output_dim(self, n)
Set output dimensions.

stop_training(self, *args, **kwargs)
Stop the training phase.

train(self, x, *args, **kwargs)
Update the internal structures according to the input data 'x'.

Properties

[hide private]

Inherited from object: __class__

Inherited from Node

_train_seq
List of tuples: [(training-phase1, stop-training-phase1), (training-phase2, stop_training-phase2), ...

dtype
dtype

input_dim
Input dimensions

output_dim
Output dimensions

supported_dtypes
Supported dtypes

Method Details

[hide private]

init(self, centers, sizes, dtype=None)
(Constructor)


Input arguments:
centers -- Centers of the RBFs. The dimensionality
           of the centers determines the input dimensionality;
           the number of centers determines the output
           dimensionalities
sizes -- Radius of the RBFs.
        'sizes' is a list with one element for each RBF, either
        a scalar (the variance of the RBFs for isotropic RBFs)
        or a covariance matrix (for anisotropic RBFs).
        If 'sizes' is not a list, the same variance/covariance
        is used for all RBFs.

Overrides: object.__init__

_execute(self, x)

Overrides: Node._execute

_get_supported_dtypes(self)

Return the list of dtypes supported by this node.

Overrides: Node._get_supported_dtypes

_init_RBF(self, centers, sizes)

is_invertible(self)

Return True if the node can be inverted, False otherwise.

Overrides: Node.is_invertible: (inherited documentation)

is_trainable(self)

Return True if the node can be trained, False otherwise.

Overrides: Node.is_trainable: (inherited documentation)

Class RBFExpansionNode

__init__(self, centers, sizes, dtype=None) (Constructor)

_execute(self, x)

_get_supported_dtypes(self)

_init_RBF(self, centers, sizes)

is_invertible(self)

is_trainable(self)

init(self, centers, sizes, dtype=None)
(Constructor)