dict:
dict() -> new empty dictionary
dict(mapping) -> new dictionary initialized from a mapping object's
(key, value) pairs
dict(iterable) -> new dictionary initialized as if via:
d = {}
for k, v in iterable:
d[k] = v
dict(**kwargs) -> new dictionary initialized with the name=value pairs
in the keyword argument list.
mdp.utils.DelayCovarianceMatrix:
This class stores an empirical covariance matrix between the signal and
time delayed signal that can be updated incrementally.
mdp.Flow:
A 'Flow' is a sequence of nodes that are trained and executed
together to form a more complex algorithm.
mdp.CheckpointFlow:
Subclass of Flow class that allows user-supplied checkpoint functions
to be executed at the end of each phase, for example to
save the internal structures of a node for later analysis.
mdp.nodes.GrowingNeuralGasNode:
Learn the topological structure of the input data by building a
corresponding graph approximation.
mdp.nodes.GrowingNeuralGasExpansionNode:
Perform a trainable radial basis expansion, where the centers and
sizes of the basis functions are learned through a growing neural
gas.
mdp.nodes.NeuralGasNode:
Learn the topological structure of the input data by building a
corresponding graph approximation (original Neural Gas algorithm).
mdp.nodes.ICANode:
ICANode is a general class to handle different batch-mode algorithm for
Independent Component Analysis.
mdp.nodes.CuBICANode:
Perform Independent Component Analysis using the CuBICA algorithm.
mdp.nodes.FastICANode:
Perform Independent Component Analysis using the FastICA algorithm.
mdp.nodes.JADENode:
Perform Independent Component Analysis using the JADE algorithm.
mdp.nodes.ISFANode:
Perform Independent Slow Feature Analysis on the input data.
mdp.nodes.TDSEPNode:
Perform Independent Component Analysis using the TDSEP algorithm.
mdp.hinet.Layer:
Layers are nodes which consist of multiple horizontally parallel nodes.
mdp.hinet.CloneLayer:
Layer with a single node instance that is used multiple times.
mdp.nodes.TimeDelaySlidingWindowNode:
``TimeDelaySlidingWindowNode`` is an alternative to ``TimeDelayNode``
which should be used for online learning/execution.
mdp.nodes.XSFANode:
Perform Non-linear Blind Source Separation using Slow Feature Analysis.
mdp.nodes._OneDimensionalHitParade:
Class to produce hit-parades (i.e., a list of the largest
and smallest values) out of a one-dimensional time-series.
mdp.caching.cache:
Context manager for the 'cache_execute' extension.
mdp.config:
Provide information about optional dependencies.