Package mdp :: Package nodes :: Class CutoffNode

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.

Instance Methods

__init__(self, lower_bound=None, upper_bound=None, input_dim=None, output_dim=None, dtype=None)
Initializes an object of type 'CutoffNode'.

numpy.ndarray

_execute(self, x)
Return the clipped data.

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

numpy.ndarray

execute(self, x)
Return the clipped data.

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.

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]

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, lower_bound=None, upper_bound=None, input_dim=None, output_dim=None, dtype=None)
(Constructor)

Initializes an object of type 'CutoffNode'.

Parameters:

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

Return the clipped data.

Parameters:

x (numpy.ndarray) - Data to clip.

Returns: numpy.ndarray

The clipped data.

Overrides: Node._execute

_get_supported_dtypes(self)

Return the list of dtypes supported by this node.

The types can be specified in any format allowed by numpy.dtype.

Overrides: Node._get_supported_dtypes: (inherited documentation)

execute(self, x)

Return the clipped data.

Parameters:

x (numpy.ndarray) - Data to clip.

Returns: numpy.ndarray

The clipped data.

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)

Class CutoffNode

__init__(self, lower_bound=None, upper_bound=None, input_dim=None, output_dim=None, dtype=None) (Constructor)

_execute(self, x)

_get_supported_dtypes(self)

execute(self, x)

is_invertible() Static Method

is_trainable() Static Method

init(self, lower_bound=None, upper_bound=None, input_dim=None, output_dim=None, dtype=None)
(Constructor)

is_invertible()
Static Method

is_trainable()
Static Method