Package mdp :: Package nodes :: Class CutoffNode
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Class CutoffNode


Node to cut off values at specified bounds.

Works similar to numpy.clip, but also works when only a lower or upper
bound is specified.

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, lower_bound=None, upper_bound=None, input_dim=None, dtype=None)
Initialize node.
 
_execute(self, x)
Return the clipped data.
 
execute(self, x, *args, **kargs)
Return the clipped data.
 
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_supported_dtypes(self)
Return the list of dtypes supported by this node.
 
_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.
 
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, lower_bound=None, upper_bound=None, input_dim=None, dtype=None)
(Constructor)

 
Initialize node.

lower_bound -- Data values below this are cut to the lower_bound value.
    If lower_bound is None no cutoff is performed.
upper_bound -- Works like lower_bound.

Overrides: object.__init__

_execute(self, x)

 
Return the clipped data.

Overrides: Node._execute

execute(self, x, *args, **kargs)

 
Return the clipped data.

Overrides: Node.execute

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)