Package mdp :: Package utils :: Class CrossCovarianceMatrix
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Class CrossCovarianceMatrix


Instance Methods [hide private]
 
_init_internals(self, x, y)
Init the internal structures.
 
fix(self)
Returns a triple containing the covariance matrix, the average and the number of observations.
 
update(self, x, y)
Update internal structures.

Inherited from unreachable.newobject: __long__, __native__, __nonzero__, __unicode__, next

Inherited from object: __delattr__, __format__, __getattribute__, __hash__, __new__, __reduce__, __reduce_ex__, __repr__, __setattr__, __sizeof__, __str__, __subclasshook__

    Inherited from CovarianceMatrix
 
__init__(self, dtype=None, bias=False)
If dtype is not defined, it will be inherited from the first data bunch received by 'update'.
Properties [hide private]

Inherited from object: __class__

Method Details [hide private]

_init_internals(self, x, y)

 
Init the internal structures.

The reason this is not done in the constructor is that we want to be
able to derive the input dimension and the dtype directly from the
data this class receives.

Overrides: CovarianceMatrix._init_internals
(inherited documentation)

fix(self)

 
Returns a triple containing the covariance matrix, the average and
the number of observations. The covariance matrix is then reset to
a zero-state.

If center is false, the returned matrix is the matrix of the second moments,
i.e. the covariance matrix of the data without subtracting the mean.

Overrides: CovarianceMatrix.fix
(inherited documentation)

update(self, x, y)

 
Update internal structures.

Note that no consistency checks are performed on the data (this is
typically done in the enclosing node).

Overrides: CovarianceMatrix.update
(inherited documentation)