Source code for botmpy.nodes.base_nodes
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# Developed by: Philipp Meier <pmeier82@gmail.com>
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# Philipp Meier <pmeier82@gmail.com>
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"""abstract base classes derived from MDP nodes"""
__docformat__ = "restructuredtext"
__all__ = ["Node", "ResetNode", "TrainingResetMixin", "PCANode"]
## IMPORTS
# MPD environ settings to stop it importing all sorts of packages
import os
os.environ["MDP_DISABLE_PARALLEL_PYTHON"] = "True"
os.environ["MDP_DISABLE_MONKEYPATCH_PP"] = "True"
os.environ["MDP_DISABLE_SHOGUN"] = "True"
os.environ["MDP_DISABLE_LIBSVM"] = "True"
os.environ["MDP_DISABLE_JOBLIB"] = "True"
os.environ['MDP_DISABLE_SKLEARN'] = "True"
# MPD DONE
from mdp import Node
from mdp.nodes import PCANode
## CLASSES
[docs]class TrainingResetMixin(object):
"""allows :py:class:`mdp.Node` to reset to training state
This is a mixin class for subclasses of :py:class:`mdp.Node`. To use it
inherit from :py:class:`mdp.Node` and put this mixin as the first
superclass.
node is a mdp.signal_node.Cumulator that can have its training phase
reinitialised once a batch of cumulated data has been processed on. This
is useful for online algorithms that derive parameters from the batch of
data currently under consideration (Ex.: stochastic thresholding).
"""
## additional interface
[docs] def reset(self):
"""reset handler, calls the reset hook and resets to training phase"""
# reset training capability
self._train_phase = 0
self._train_phase_started = False
self._training = True
self._reset()
def _reset(self):
pass
[docs]class ResetNode(TrainingResetMixin, Node):
pass
## MAIN
if __name__ == "__main__":
pass
## EOF