Package mdp :: Package nodes :: Class TimeFramesNode

Class TimeFramesNode

Copy delayed version of the input signal on the space dimensions.

For example, for ``time_frames=3`` and ``gap=2``::

  [ X(1) Y(1)        [ X(1) Y(1) X(3) Y(3) X(5) Y(5)
    X(2) Y(2)          X(2) Y(2) X(4) Y(4) X(6) Y(6)
    X(3) Y(3)   -->    X(3) Y(3) X(5) Y(5) X(7) Y(7)
    X(4) Y(4)          X(4) Y(4) X(6) Y(6) X(8) Y(8)
    X(5) Y(5)          ...  ...  ...  ...  ...  ... ]
    X(6) Y(6)
    X(7) Y(7)
    X(8) Y(8)
    ...  ...  ]

It is not always possible to invert this transformation (the
transformation is not surjective. However, the ``pseudo_inverse``
method does the correct thing when it is indeed possible.

Instance Methods

[hide private]

__init__(self, time_frames, gap=1, input_dim=None, dtype=None)
Input arguments:...

_execute(self, x)

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

_set_input_dim(self, n)

_set_output_dim(self, n)

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

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

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 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`.

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]

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)


Input arguments:
time_frames -- Number of delayed copies
gap -- Time delay between the copies

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

_set_input_dim(self, n)

Overrides: Node._set_input_dim

_set_output_dim(self, n)

Overrides: Node._set_output_dim

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

is_invertible()
Static Method

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

Overrides: Node.is_invertible: (inherited documentation)

is_trainable()
Static Method

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

Overrides: Node.is_trainable: (inherited documentation)

pseudo_inverse(self, y)

This function returns a pseudo-inverse of the execute frame.
y == execute(x) only if y belongs to the domain of execute and
has been computed with a sufficently large x.
If gap > 1 some of the last rows will be filled with zeros.

Class TimeFramesNode

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

_execute(self, x)

_get_supported_dtypes(self)

_set_input_dim(self, n)

_set_output_dim(self, n)

execute(self, x)

is_invertible() Static Method

is_trainable() Static Method

pseudo_inverse(self, y)

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

is_invertible()
Static Method

is_trainable()
Static Method