Package mdp :: Package nodes :: Class NoiseNode

Class NoiseNode

Inject multiplicative or additive noise into the input data.

Original code contributed by Mathias Franzius.

Note that due to the noise_func attribute this node cannot be pickled.

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, noise_func=<built-in method normal of mtrand.RandomState object at 0xb7c4..., noise_args=(0, 1), noise_type='additive', input_dim=None, dtype=None)
Add noise to input signals.

_execute(self, x)

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

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, noise_func=<built-in method normal of mtrand.RandomState object at 0xb7c4`...`, noise_args=`(`0`,` 1`)`, noise_type=`'additive'`, input_dim=None, dtype=None)
(Constructor)


Add noise to input signals.

Input signal:
'noise_func' -- A function that generates noise. It must
                take a 'size' keyword argument and return
                a random array of that size. Default is normal noise.
  
'noise_args' -- Tuple of additional arguments passed to noise_func.
                Default is (0,1) for (mean, standard deviation)
                of the normal distribution.

'noise_type' -- Either 'additive' or 'multiplicative':
                 'additive' returns x + noise
                 'multiplicative' returns x * (1 + noise)
                Default is 'additive'.

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

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 NoiseNode

__init__(self, noise_func=<built-in method normal of mtrand.RandomState object at 0xb7c4..., noise_args=(0, 1), noise_type='additive', input_dim=None, dtype=None) (Constructor)

_execute(self, x)

_get_supported_dtypes(self)

is_invertible(self)

is_trainable(self)

init(self, noise_func=<built-in method normal of mtrand.RandomState object at 0xb7c4`...`, noise_args=`(`0`,` 1`)`, noise_type=`'additive'`, input_dim=None, dtype=None)
(Constructor)