Package mdp :: Package nodes :: Class CuBICANode

Class CuBICANode

Perform Independent Component Analysis using the CuBICA algorithm.

Note that CuBICA is a batch-algorithm, which means that it needs all input data before it can start and compute the ICs. The algorithm is here given as a Node for convenience, but it actually accumulates all inputs it receives. Remember that to avoid running out of memory when you have many components and many time samples.

As an alternative to this batch mode you might consider the telescope mode (see the docs of the __init__ method).

Reference

Blaschke, T. and Wiskott, L. (2003). CuBICA: Independent Component Analysis by Simultaneous Third- and Fourth-Order Cumulant Diagonalization. IEEE Transactions on Signal Processing, 52(5), pp. 1250-1256.

Instance Methods

[hide private]

float

core(self, data)
This is the core routine of a node inheriting from ICANode.

Inherited from unreachable.ProjectMatrixMixin: get_projmatrix, get_recmatrix

Inherited from unreachable.newobject: __long__, __native__, __nonzero__, __unicode__, next

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

Inherited from ICANode

__init__(self, limit=0.001, telescope=False, verbose=False, whitened=False, white_comp=None, white_parm=None, input_dim=None, dtype=None)
Initializes an object of type 'ICANode'.

_execute(self, x)

_inverse(self, y)

_set_input_dim(self, n)

_stop_training(self)
Whiten data if needed and call the 'core' routine to perform ICA.

execute(self, x)
Process the data contained in x.

inverse(self, y)
Invert y.

stop_training(self)
Whiten data if needed and call the 'core' routine to perform ICA.

Inherited from Cumulator

_train(self, *args)
Collect all input data in a list.

train(self, *args)
Collect all input data in a list.

Inherited from Node

__add__(self, other)

__call__(self, x, *args, **kwargs)
Calling an instance of Node is equivalent to calling 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_supported_dtypes(self)
Return the list of dtypes supported by this node.

_get_train_seq(self)

_if_training_stop_training(self)

_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_output_dim(self, n)

copy(self, protocol=None)
Return a deep copy of the node.

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.

has_multiple_training_phases(self)
Return True if the node has multiple training phases.

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. If filename is None, return a string.

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

set_input_dim(self, n)
Set input dimensions.

set_output_dim(self, n)
Set output dimensions.

Static Methods

[hide private]

Inherited from Node

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

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

Instance Variables

[hide private]

convergence
The value of the convergence threshold.

filters
The ICA filters matrix (this is the transposed of the projection matrix after whitening).

white
The whitening node used for preprocessing.

Properties

[hide private]

Inherited from object: __class__

Inherited from Node

_train_seq
List of tuples:

dtype
dtype

input_dim
Input dimensions

output_dim
Output dimensions

supported_dtypes
Supported dtypes

Method Details

[hide private]

core(self, data)

This is the core routine of a node inheriting from ICANode.

As a subclass, the CuBICANode define this function to return the achieved convergence value. This function is also responsible for setting the ICA filters matrix self.filters.

Parameters:

data (numpy.ndarray) - The data you want to perform ICA on.

Returns: float

The convergence value, i.e. the maximum angle of rotation.

Overrides: ICANode.core

Instance Variable Details

[hide private]

convergence

The value of the convergence threshold.

filters

The ICA filters matrix (this is the transposed of the projection matrix after whitening).

white

The whitening node used for preprocessing.