Package mdp :: Package nodes :: Class NoiseNode
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Class NoiseNode


Inject multiplicative or additive noise into the input data.

Original code contributed by Mathias Franzius.

Instance Methods [hide private]
 
__init__(self, noise_func=<built-in method normal of mtrand.RandomState object at 0x7fb8..., noise_args=(0, 1), noise_type='additive', input_dim=None, output_dim=None, dtype=None)
Initializes an object of type 'NoiseNode'.
 
_execute(self, x)
list
_get_supported_dtypes(self)
Return the data types supported by this node.
 
execute(self, x)
Process the data contained in x.
 
save(self, filename, protocol=-1)
Save a pickled serialization of the node to 'filename'. If 'filename' is None, return a string.

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 PreserveDimNode
 
_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.
 
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, noise_func=<built-in method normal of mtrand.RandomState object at 0x7fb8..., noise_args=(0, 1), noise_type='additive', input_dim=None, output_dim=None, dtype=None)
(Constructor)

 
Initializes an object of type 'NoiseNode'.
Parameters:
  • noise_func (function) - 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) - Tuple of additional arguments passed to noise_func. Default is (0,1) for (mean, standard deviation) of the normal distribution.
  • noise_type (str) - Either 'additive' or 'multiplicative'.
  • input_dim (int) - The input dimensionality.
  • output_dim (int) - The output dimensionality.
  • dtype (numpy.dtype or str) - The datatype.
Overrides: object.__init__

_execute(self, x)

 
Overrides: Node._execute

_get_supported_dtypes(self)

 
Return the data types supported by this node.
Returns: list
The list of numpy.dtypes that this node supports.
Overrides: Node._get_supported_dtypes

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)

save(self, filename, protocol=-1)

 

Save a pickled serialization of the node to 'filename'. If 'filename' is None, return a string.

Note: the pickled Node is not guaranteed to be upward or backward compatible.

Parameters:
  • filename (str) - The name of the file to save to.
  • protocol - Whether to open the file in binary mode (protocol != 0). Default is -1.
Overrides: Node.save