Package mdp :: Package nodes :: Class TimeDelaySlidingWindowNode

Class TimeDelaySlidingWindowNode

TimeDelaySlidingWindowNode is an alternative to TimeDelayNode which should be used for online learning/execution. Whereas the TimeDelayNode works in a batch manner, for online application a sliding window is necessary which yields only one row per call.

Applied to the same data the collection of all returned rows of the TimeDelaySlidingWindowNode is equivalent to the result of the TimeDelayNode.

Original code contributed by Sebastian Hoefer. Dec 31, 2010

Instance Methods

[hide private]

__init__(self, time_frames, gap=1, input_dim=None, dtype=None)
Initializes an object of type 'TimeDelaySlidingWindowNode'.

_execute(self, x)

_init_sliding_window(self)

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

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 TimeDelayNode

numpy.ndarray

pseudo_inverse(self, y)
This function returns a pseudo-inverse of the execute frame.

Inherited from TimeFramesNode

list

_get_supported_dtypes(self)
Return the data types supported by this node.

_set_input_dim(self, n)

_set_output_dim(self, n)

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_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)

_stop_training(self, *args, **kwargs)

_train(self, x)

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.

inverse(self, y, *args, **kwargs)
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. 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.

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

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

Static Methods

[hide private]

Inherited from TimeFramesNode

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

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

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]

init(self, time_frames, gap=1, input_dim=None, dtype=None)
(Constructor)

Initializes an object of type 'TimeDelaySlidingWindowNode'.

Parameters:

time_frames (int) - Number of delayed copies.
gap (int) - Time delay between the copies.
input_dim (int) - The input dimensionality.
dtype (numpy.dtype or str) - The datatype.

Overrides: object.__init__

_execute(self, x)

Overrides: Node._execute

_init_sliding_window(self)

execute(self, x)

Process the data contained in x.

If the object is still in the training phase, the function stop_training will be called. x is a matrix having different variables on different columns and observations on the rows.

By default, subclasses should overwrite _execute to implement their execution phase. The docstring of the _execute method overwrites this docstring.

Overrides: Node.execute

Class TimeDelaySlidingWindowNode

__init__(self, time_frames, gap=1, input_dim=None, dtype=None) (Constructor)

_execute(self, x)

_init_sliding_window(self)

execute(self, x)

init(self, time_frames, gap=1, input_dim=None, dtype=None)
(Constructor)